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WO2025213150A1 - Methods, kits and systems for measuring psa and psma expression and methods for treating cancer based on same - Google Patents

Methods, kits and systems for measuring psa and psma expression and methods for treating cancer based on same

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Publication number
WO2025213150A1
WO2025213150A1 PCT/US2025/023339 US2025023339W WO2025213150A1 WO 2025213150 A1 WO2025213150 A1 WO 2025213150A1 US 2025023339 W US2025023339 W US 2025023339W WO 2025213150 A1 WO2025213150 A1 WO 2025213150A1
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Prior art keywords
psma
subject
expression
psa
modifications
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French (fr)
Inventor
Matthew EATON
Anthony D'IPPOLITO
Jacob E. BERCHUCK
Rehan VERJEE
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Precede Biosciences Inc
Dana Farber Cancer Institute Inc
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Precede Biosciences Inc
Dana Farber Cancer Institute Inc
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Publication of WO2025213150A1 publication Critical patent/WO2025213150A1/en
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/112—Disease subtyping, staging or classification
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/118—Prognosis of disease development
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/154—Methylation markers
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers

Definitions

  • PCa Prostate cancer
  • PSMA Prostate-Specific Membrane Antigen
  • PSMA-targeting therapeutics e.g., antibody-drug conjugates and radioimmune conjugates
  • PSMA expression level is commonly used as a criteria for determining patient eligibility for treatment.
  • PSA Prostate-specific antigen
  • KLK3 gamma-seminoprotein or kallikrein-3
  • PSA is a glycoprotein enzyme encoded in humans by the KLK3 gene.
  • PSA is present in small quantities in the serum of men with healthy prostates, but is often elevated in the presence of prostate cancer or other prostate disorders. As such, PSA can be used to screen for prostate cancer.
  • the present disclosure is based, at least in part, on the demonstration that PSMA expression level in a subject can be measured by detecting and quantifying the presence of histone modifications and/or DNA methylation at one or more genomic loci in cell-free DNA (cfDNA) from a liquid biopsy sample, e.g., a plasma sample obtained or derived from a subject.
  • cfDNA cell-free DNA
  • the present disclosure demonstrates that PSMA expression level can be determined in cancer cells in a subject, including, e g., PSMA expression level in prostate cancer (e.g., mCRPC).
  • PSMA expression level determined by detecting histone modifications and/or DNA methylation at one or more genomic loci in cfDNA from a liquid biopsy sample can be used as a proxy for established biomarkers for, e.g., monitoring, characterizing, diagnosing, and prognosing disease and/or determining patient eligibility for certain therapeutics.
  • biomarkers e.g., monitoring, characterizing, diagnosing, and prognosing disease and/or determining patient eligibility for certain therapeutics.
  • technologies described herein can be used to predict PSMA PET measurements (e.g., PSMA PET SUVmean).
  • PSMA PET measurements predicted by technologies described herein have been shown to closely match actual PSMA PET measurements and also to be predictive of response to PSMA-targeted agents in patients.
  • PSA expression level in a subject can be measured or predicted by detecting and quantifying the presence of histone modifications and/or DNA methylation at one or more genomic loci in cell-free DNA (cfDNA) from a liquid biopsy sample, e.g., a plasma sample obtained or derived from a subject.
  • cfDNA cell-free DNA
  • Technologies described herein for measuring or predicting PSA expression can provide certain advantages as compared to assays that measure PSA protein concentrations directly (e.g., via ELISA or an enzymatic assay).
  • technologies described herein can be combined with one or more additional technologies that comprise measuring epigenome modifications (e.g., technologies described herein that comprise measuring PSMA expressing or predicting PSMA PET signal), allowing for multiple epigenome measurements to obtained using a single sample (which, in some embodiments, can comprise a small volume of sample (e.g., 5 mb or less, or about 1 mL of plasma).
  • a single sample which, in some embodiments, can comprise a small volume of sample (e.g., 5 mb or less, or about 1 mL of plasma).
  • Use of single sample is advantageous as it allows for, e.g., a reduced number of sample processing steps (i.e., epigenome measurements only have to be collected once, and can be used to perform multiple analytes), and improved patient convenience.
  • the present disclosure encompasses methods that quantify the presence of histone modifications and/or DNA methylation, as well as methods that assess chromatin accessibility and/or binding of one or more transcription factors at one or more genomic loci instead of (or in addition to) histone modifications and/or DNA methylation.
  • Liquid biopsies are now widely utilized in clinical oncology to detect cancer recurrence and inform therapeutic decisions.
  • most commercially available cfDNA assays only detect genetic mutations and not all disease states have a characteristic mutation that can be used for detection.
  • Technologies that detect epigenetic modifications offer numerous benefits over assays that detect genetic mutations, including, e.g., allowing the detection of disease states that a characteristic mutation has not been identified for, and/or providing measurements that are more directly relevant to a biological characteristic of interest (e.g., detecting increased transcription activation of a gene, rather than a mutation that has been previously shown to be correlated with activation for some subjects).
  • the present disclosure provides tools to analyze multiple epigenomic features from patient plasma, including DNA methylation, chromatin accessibility, and histone modifications.
  • the present disclosure demonstrates that epigenomic cfDNA profiling can be used to detect PSMA and/or expression levels as well as characterize disease severity, prognose patients, evaluate patient eligibility for certain therapeutics, and inform methods of treatment.
  • prostate cancer e.g., mCRPC
  • cfDNA profiling would be immediately clinically actionable, as guidelines currently recommend that prostate cancer be monitored using imaging methods that assess PSMA expression in tumors and administering certain therapeutics to patients on the basis of PSMA expression level.
  • the present disclosure includes, among other things, technologies for determining PSMA expression level and for the detection, monitoring, and/or treatment of prostate cancer based on PSMA expression level.
  • the present disclosure relates to the measurement of histone modifications in a sample obtained or derived from a subject to detect and/or treat prostate cancer based on PSMA expression level.
  • the present disclosure includes, among other things, histone modification measurements in cell-free DNA (cfDNA) that are associated with PSMA expression level, and which in various embodiments are useful, e.g., for detecting, monitoring, selecting treatment for, and/or treating prostate cancer.
  • cfDNA cell-free DNA
  • the present disclosure includes, among other things, histone modification measurements in cfDNA that are associated with increased PSMA expression, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating prostate cancer (e.g., mCRPC).
  • histone modification measurements in cfDNA can be used to detect or determine responsiveness of prostate cancer (e.g., mCRPC) to a therapy.
  • histone modification measurements in cfDNA can be used to monitor or predict progression of prostate cancer (e.g., mCRPC).
  • histone modification measurements in cfDNA can be used to inform therapeutic selection for a subject with prostate cancer (e.g., determine an initial therapy, predict patients that are likely to respond to a given therapy, and/or determine when therapy should be changed for a subject).
  • histone modification measurements in cfDNA can be used as a complement to other diagnostic methods (e.g., imaging methods, histology methods, and/or symptom-based methods) for monitoring and/or treating prostate cancer (e g., performed concurrently and/or subsequent to other methods).
  • a method of described herein can be performed in combination with one or more diagnostic assays that do not comprise measuring one or more epigenome features.
  • a method described herein can be performed in combination with one or more diagnostic assays for prostate cancer that use PSA level, biopsy measurements, histology measurements, and/or medical imaging tests.
  • technologies described herein can be used to screen patients (e.g., identify patients for treatment, diagnosis, etc.) to identify patients that may benefit from being tested using one or more additional diagnostic assays.
  • technologies described herein can be performed in conjunction with one or more diagnostic assays that do not comprise measuring one or more epigenome features.
  • technologies described herein can be used for subjects that have been previously screened using one or more diagnostic assays that do not comprise measuring one or more epigenome features.
  • a method can be performed on a subject who has already been screened using one or more diagnostic assays for prostate cancer, e.g., one or more diagnostic assays described herein).
  • the present disclosure includes exemplary genomic loci whose epigenetic modification status is associated with PSMA expression level.
  • these genomic loci are or include one or more enhancers regions.
  • these genomic loci are or include one or more promoter regions.
  • the present disclosure includes, among other things, technologies for determining PSA expression level and for the detection, monitoring, and/or treatment of prostate cancer and/or the selection of subjects for further screening for prostate cancer based on PSA expression level.
  • the present disclosure relates to the measurement of histone modifications in a sample obtained or derived from a subject to detect and/or treat prostate cancer based on PSA expression level.
  • the present disclosure includes, among other things, histone modification measurements in cell-free DNA (cfDNA) that are associated with PSA expression level, and which in various embodiments are useful, e.g., for detecting, monitoring, selecting treatment for, and/or treating prostate cancer.
  • cfDNA cell-free DNA
  • histone modification measurements in cfDNA that are associated with increased PSA expression, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating prostate cancer (e.g., mCRPC) or for identifying subjects for further screening for prostate cancer.
  • histone modification measurements in cfDNA can be used to detect or determine responsiveness of prostate cancer (e.g., mCRPC) to a therapy.
  • histone modification measurements in cfDNA can be used to monitor or predict progression of prostate cancer (e.g., mCRPC).
  • histone modification measurements in cfDNA can be used to inform therapeutic selection for a subject with prostate cancer (e.g., determine an initial therapy, predict patients that are likely to respond to a given therapy, and/or determine when therapy should be changed for a subject).
  • histone modification measurements in cfDNA can be used as a complement to other diagnostic methods (e.g., imaging methods and/or symptom-based methods) for detecting, monitoring, and/or treating prostate cancer (e.g., performed concurrently and/or subsequent to other methods).
  • the present disclosure includes exemplary genomic loci whose epigenetic modification status is associated with PSA expression level.
  • these genomic loci are or include one or more enhancer regions.
  • these genomic loci are or include one or more promoter regions.
  • a genomic locus is differentially modified if it is characterized by increased or decreased histone modification as compared to a reference (e.g., a sample from a healthy subject).
  • Increased or decreased histone modification can be or include, e.g., increased or decreased histone methylation (hypermethylation or hypomethylation, respectively) of one or more particular methylation marks, or a combination thereof; increased or decreased pan-methylation; increased or decreased histone acetylation (hyperacetylation or hypoacetylation, respectively) of one or more particular acetylation marks, or a combination thereof; and/or increased or decreased pan-acetylation (e.g., pan-H3 acetylation).
  • the present disclosure further relates, in various embodiments, to the measurement of chromatin accessibility in cell-free DNA (cfDNA) to determine PSMA expression level.
  • cfDNA cell-free DNA
  • the present disclosure includes, among other things, chromatin accessibility measurements in cfDNA that are characteristic of increased PSMA expression in a tumor, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating prostate cancer.
  • chromatin accessibility measurements in cfDNA that are characteristic of increased PSMA expression, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating prostate cancer.
  • the present disclosure further relates, in various embodiments, to the measurement of chromatin accessibility in cell-free DNA (cfDNA) to determine PSA expression level.
  • cfDNA cell-free DNA
  • the present disclosure includes, among other things, chromatin accessibility measurements in cfDNA that are characteristic of increased PSA expression in a tumor, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, treating, and/or screening for prostate cancer.
  • chromatin accessibility measurements in cfDNA that are characteristic of increased PSA expression, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, treating, and/or screening for prostate cancer.
  • chromatin accessibility measurements in cfDNA can be used to detect or determine resistance of prostate cancer to a therapy.
  • the present disclosure includes genomic loci that are differentially accessible when PSA expression is increased.
  • genomic loci differentially accessible in cfDNA are or include one or more enhancers.
  • genomic loci differentially accessible in cfDNA are or include one or more promoters.
  • histone methylation e.g., H3K4me3 corresponds and/or is correlated with chromatin accessibility.
  • histone acetylation corresponds and/or is correlated with chromatin accessibility.
  • DNA methylation corresponds and/or is correlated with chromatin accessibility.
  • the present disclosure further relates, in various embodiments, to the measurement of transcription factor binding in cell-free DNA (cfDNA) to determine PSMA expression level.
  • the present disclosure includes, among other things, transcription factor binding measurements in cfDNA that are characteristic of increased PSMA expression, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating prostate cancer.
  • transcription factor binding measurements in cfDNA can be used to detect or determine resistance of prostate cancer to a therapy.
  • the present disclosure includes genomic loci that are differentially bound by transcription factors when PSMA expression is increased.
  • genomic loci that are differentially bound by transcription factors in cfDNA are or include one or more enhancers.
  • genomic loci that are differentially bound by transcription factors in cfDNA are or include one or more promoters.
  • the present disclosure further relates, in various embodiments, to the measurement of transcription factor binding in cell-free DNA (cfDNA) to determine PSA expression level.
  • the present disclosure includes, among other things, transcription factor binding measurements in cfDNA that are characteristic of increased PSA expression, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, screening for, and/or treating prostate cancer.
  • transcription factor binding measurements in cfDNA can be used to detect or determine resistance of prostate cancer to a therapy.
  • the present disclosure includes genomic loci that are differentially bound by transcription factors when PSA expression is increased.
  • genomic loci that are differentially bound by transcription factors in cfDNA are or include one or more enhancers.
  • genomic loci that are differentially bound by transcription factors in cfDNA are or include one or more promoters.
  • histone methylation corresponds and/or is correlated with transcription factor binding.
  • histone acetylation corresponds and/or is correlated with transcription factor binding.
  • DNA methylation corresponds and/or is correlated with transcription factor binding.
  • a genomic locus is differentially bound by transcription factors if it is characterized by increased or decreased transcription factor binding as compared to a reference (e.g., a sample from a healthy subject).
  • Increased or decreased transcription factor binding can be or include, e.g., increased or decreased transcription factor binding as determined by various transcription factor binding assays known in the art.
  • the present disclosure provides a method of determining PSMA expression level in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject: (i) one or more histone modifications, (ii) chromatin accessibility, (iii) binding of one or more transcription factors, and/or (iv) DNA methylation.
  • cfDNA cell-free DNA
  • the one or more histone modifications are quantified using a histone modification assay that measures one or more of H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, H3K4me3, and pan-acetylation.
  • the histone modification assay detects H3K4me3 modifications.
  • the histone modification assay detects H3K27ac modifications.
  • the histone modification assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
  • chromatin accessibility is quantified using a chromatin accessibility assay selected from ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde- Assisted Isolation of Regulatory Elements sequencing), MNase-seq (Micrococcal Nuclease digestion with sequencing), a Dnase hypersensitivity assay, and a fragmentomics assay.
  • ATAC-seq Assay of Transpose Accessible Chromatin sequencing
  • NOMe-seq Nucleosome Occupancy and Methylome sequencing
  • FAIRE-seq Formmaldehyde- Assisted Isolation of Regulatory Elements sequencing
  • MNase-seq Merococcal Nuclease digestion with sequencing
  • Dnase hypersensitivity assay and a fragmentomics assay.
  • binding of one or more transcription factors is quantified using a transcription factor binding assay.
  • the transcription factor binding assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
  • DNA methylation is quantified using Bisulfite sequencing (BS-Seq), Whole Genome Bisulfite Sequencing (WGBS), Methylated DNA ImmunoPrecipitation sequencing (MeDIP-seq), or Methyl-CpG-Binding Domain sequencing (MBD-seq).
  • BS-Seq Bisulfite sequencing
  • WGBS Whole Genome Bisulfite Sequencing
  • MBD-seq Methyl-CpG-Binding Domain sequencing
  • a method comprises quantifying two or more of the following, each at one or more genomic loci in cell-free DNA (cfDNA) from a liquid biopsy sample obtained or derived from the subject: (i) one or more histone modifications, (ii) chromatin accessibility, (iii) transcription factor binding, and/or (iv) DNA methylation.
  • the method comprises quantifying two or more histone modifications, e.g., quantifying H3K4me3 and H3K27ac modifications.
  • a method comprises quantifying one or more histone modifications and DNA methylation, e.g., quantifying H3K4me3 and/or H3K27ac modifications and DNA methylation.
  • a method comprises quantifying H3K4me3 modifications, H3K27ac modifications and DNA methylation.
  • a biological sample is a liquid biopsy sample, e.g., a plasma sample, serum sample, or urine sample.
  • quantification of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at the one or more genomic loci as compared to a reference indicates that the subject has increased PSMA expression.
  • the reference is a predetermined threshold, a measurement from a liquid biopsy sample, and/or a normalized value, optionally wherein the reference is a measurement from a liquid biopsy sample obtained from a cohort of healthy subjects.
  • technologies described herein comprise or can be used to measure PSMA expression and/or predict medical imaging results (e.g., PSMA PET imaging results).
  • a method for measuring PSMA expression measures PSMA expression specific to one or more tumors in a subject.
  • PSMA expression comprises cell surface expression.
  • PSMA expression comprises tumor cell specific expression.
  • PSMA expression comprises tumor specific, cell surface expression of PSMA.
  • one or more histone modifications are quantified using a histone modification assay that measures H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, H3K4me3, or pan-acetylation, or any combination thereof.
  • a histone modification assay detects H3K4me3 modifications.
  • a histone modification assay detects H3K27ac modifications.
  • chromatin accessibility is quantified using a chromatin accessibility assay selected from ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde-Assisted Isolation of Regulatory Elements sequencing), Mnase-seq (Micrococcal Nuclease digestion with sequencing), a Dnase hypersensitivity assay, and a fragmentomics assay.
  • ATAC-seq Assay of Transpose Accessible Chromatin sequencing
  • NOMe-seq Nucleosome Occupancy and Methylome sequencing
  • FAIRE-seq Formmaldehyde-Assisted Isolation of Regulatory Elements sequencing
  • Mnase-seq Merococcal Nuclease digestion with sequencing
  • Dnase hypersensitivity assay and a fragmentomics assay.
  • binding of one or more transcription factors
  • a transcription factor binding assay is selected from ChlP- seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
  • a method described herein comprises quantifying two or more histone modifications. In some embodiments, a method described herein comprises quantifying H3K4me3 and H3K27ac modifications. In some embodiments, a method described herein comprises quantifying one or more histone modifications and DNA methylation. In some embodiments, a method described herein comprises quantifying H3K4me3 and/or H3K27ac modifications and DNA methylation. In some embodiments, a method described herein comprises quantifying H3K4me3 modifications, H3K27ac modifications, and DNA methylation. [0050] In some embodiments, a liquid biopsy sample is a plasma sample, serum sample, or urine sample.
  • an increase of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci as compared to a reference indicates that a subject has increased PSMA expression (e.g., increased as compared to a healthy subject).
  • a method described herein comprises measuring one or more prostate cancer specific markers.
  • one or more prostate cancer specific markers comprise PSA expression (e.g., PSA serum level).
  • PSA expression is measured by measuring PSA protein concentrations (e.g., via an ELISA assay and/or an enzymatic assay).
  • PSA expression is measured by quantifying histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci (e.g., using technologies described in the present disclosure).
  • a method comprises measuring PSMA expression or predicting PSMA expression (e.g., predicting a PSMA PET measurement) and measuring one or more prostate cancer specific markers.
  • a method described herein comprises quantifying one or more histone modifications and/or DNA methylation at one or more prostate cancer specific marker genes or regulatory regions thereof (e.g., one or more promoters and/or enhancers of one or more prostate cancer specific marker genes).
  • one or more prostate cancer specific marker genes comprise HXBI3, KLK2, KLK3, SPDEF, or FOLH1, or any combination thereof.
  • a method described herein comprises quantifying one or more histone modifications and/or DNA methylation for one or more of AMN, ARHGEF37, Clorf 36, CADM1, CCDC175, CDC7, CLSTN1, COL5A1, EDNRA, FOLH1, GALR3, MED13L, MICB, NDRG3, NEDD1, NPAS2, NPVF, OLFM1, PCBP4, PROZ, PRRG3, RREB1, SCUBE3, SERPINA5, SNRPF, SORCS3, ST8SIA5, TEX19, TMEM132B, or TTC29 or any combination thereof, or one or more regulatory regions of any one of the foregoing (e.g., one or more promoter and/or enhancer regions oiAMN, ARHGEF37, C4orf36, CADM1, CCDC175, CDC7, CLSTNI, COL5A1, EDNRA, FOLH1, GALR3, MED13L, MICB, NDRG3,
  • genomic loci that are associated with PSMA expression and can be used to measure PSMA expression (e.g., tumor specific PSMA expression).
  • Exemplary genomic loci include those provided in Tables 1 and 2.
  • a method described herein comprises quantifying:
  • promoter signal e.g., H3K4me3
  • H3K4me3 promoter signal
  • CADM1 CDC7
  • COL5A1 promoter region of C4orf36
  • EDNRA e.g., CDC7
  • COL5A1 e.g., EDNRA
  • MED13L e.g., ED13L
  • PROZ e.g., SNRPF, TEX19, or any combination thereof
  • enhancer signal e.g., H3K27ac signal
  • enhancer signal at one or more enhancer regions of ARHGEF37, CLSTNI, FOLH1, NDRG3, NPAS2, NPVF, 0LFM1, RREBl, SCUBE3, or TTC29, or any combination thereof;
  • a method described herein comprises:
  • a method described herein comprises:
  • promoter signal e.g., H3K4me3 modifications
  • a method described herein comprises quantifying:
  • promoter signal e.g., H3K4me3 modifications
  • H3K4me3 modifications for 1 or 2 H3K4me3 analyte genomic loci in Table 4;
  • enhancer signal e.g., H3K27ac modifications
  • H3K27ac modifications for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 4;
  • a method described herein comprises quantifying (a) promoter signal (e.g., H3K4me3 modifications) at chrl 1 :49,228,902-49,230,855; and/or (b) enhancer signal (e.g., H3K27ac modifications) at chrl 1 :49, 229, 019-49, 230, 275.
  • promoter signal e.g., H3K4me3 modifications
  • enhancer signal e.g., H3K27ac modifications
  • promoter signal and enhancer signal are normalized prior to aggregating (e.g., normalized based on sequence read depth or ctDNA fraction).
  • aggregating comprises summing epigenetic modification signal (e.g., H3K4me3 and/or H3K27ac signal) at two or more loci.
  • signal is corrected prior to summing.
  • correcting comprises adjusting for (i) sequencing depth, (ii) background signal (e.g., signal in healthy subjects), (iii) the length of a genomic locus, or any combination of (i)-(iii).
  • signal (optionally corrected signal) at each locus is weighted when aggregated.
  • weighting entails multiplying by a coefficient that has been determined using a model trained to predict PSA or PSMA expression.
  • promoter signal and enhancer signal are separately aggregated, and then the aggregated promoter signal and enhancer signal are aggregated in a second aggregation step. In some embodiments, promoter signal and enhancer signal are aggregated together (i.e., without an intervening aggregation step).
  • a biological sample e.g., a plasma sample
  • a subject has previously been diagnosed with a disease or condition that is associated with increased PSMA expression.
  • a disease or condition that is associated with increased PSMA expression is cancer.
  • a disease or indication associated with PSMA expression is prostate cancer.
  • prostate cancer is mCRPC (metastatic castration resistant prostate cancer).
  • prostate cancer is prostate adenocarcinoma (PRAD).
  • prostate cancer is neuroendocrine prostate cancer (NEPC).
  • a subject has previously been diagnosed with a disease or condition that is associated with increased PSA expression.
  • a disease or condition that is associated with increased PSA expression is cancer.
  • a disease or indication associated with PSA expression is prostate cancer.
  • prostate cancer is mCRPC (metastatic castration resistant prostate cancer).
  • prostate cancer is prostate adenocarcinoma (PRAD).
  • prostate cancer is neuroendocrine prostate cancer (NEPC).
  • one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and DNA/or DNA methylation is quantified in a subject before the subject is administered a PSMA-targeted agent.
  • the present disclosure describes a method of predicting PSA expression in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) or circulating tumor DNA (ctDNA) from a liquid biopsy sample, obtained or derived from the subject:
  • cfDNA cell-free DNA
  • ctDNA circulating tumor DNA
  • PSA expression is or comprises serum PSA concentration.
  • a method measures or predicts PSA expressed by one or more cancer cells in the subject.
  • a method measures or predicts serum concentration of total PSA. [0076] In some embodiments, a method predicts PSA expression as determined using an assay that (a) utilizes one or more antibodies that bind PSA (e.g., an ELISA assay) and/or (b) measures PSA enzymatic activity.
  • an assay that (a) utilizes one or more antibodies that bind PSA (e.g., an ELISA assay) and/or (b) measures PSA enzymatic activity.
  • a method of predicting a likelihood that a subject having a disease or disorder associated with increased PSA expression will respond to a therapeutic comprises measuring PSA expression or predicting PSA expression in a subject using a method described herein, and comparing the measured PSA expression level or predicted PSA expression to a reference, wherein
  • a method of treating a subject having a disease or disorder associated with increased PSA expression comprises measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total serum PSA) in a subject using a method described herein.
  • a method of treating a subject having a disease or disorder associated with increased PSA expression comprises measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total serum PSA) in a subject using a method described herein, and comparing the measured PSA or predicted PSA expression to a reference, and
  • a reference is the median, lower bound of the top tertile, or lower bound of the top quartile value of a PSMA expression level measured, tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) predicted, or tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) measured in a cohort of subjects having a disease or disorder associated with increased PSMA expression (e.g., prostate cancer, including, e g., mCRPC); and if the PSMA expression level or predicted tumor specific PSMA expression level in the subject is equal to or greater than the reference, administering a PSMA targeted therapeutic (e.g., 177Lu-PSMA-617); and if the PSMA expression level or predicted tumor specific PSMA expression level in the subject is less than the reference, not administering the PSMA targeted therapeutic.
  • a PSMA targeted therapeutic e.g., 177Lu-PSMA-617
  • the PSMA PET SUVmean median is about 4 to about 8, about 5 to about 8, 5 to about 7, about 6 to about 9, about 5, about 6, about 7, or about 8 in a reference population.
  • the lower bound of the top tertile of PSMA PET SUVmean is about 6 to about 12, about 6 to about 10, about 8 to about 12, about 6, about 7, about 8, about 9, about 10, about 11, or about 12 in a reference population.
  • the lower bound of the top quartile of PSMA PET SUVmean is about 6 to about 14, about 6 to about 12, about 8 to about 14, about 8, about 9, about 10, about 11, about 12, about 13, or about 14 in a reference population.
  • a disease or indication associated with increased PSMA expression is a cancer.
  • the cancer is prostate cancer, including, e.g., mCRPC.
  • a therapeutic is administered via one or more intravenous, subcutaneous, intraperitoneal, or intramuscular injections.
  • a subject has previously been diagnosed as having a disease or indication associated with increased PSMA or PSA expression (e.g., a cancer, prostate cancer, mCRPC, PRAD and/or NEPC).
  • a disease or indication associated with increased PSMA or PSA expression e.g., a cancer, prostate cancer, mCRPC, PRAD and/or NEPC.
  • a prostate cancer is localized or metastatic.
  • a prostate cancer has metastasized to one or more site(s) that include lymph node, bone, lung, and/or liver tissue.
  • a subject has previously been administered one or more
  • promoter signal e.g., H3K4me3 modifications
  • H3K4me3 modifications for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K4me3 analyte genomic loci in Table 1;
  • enhancer signal e.g., H3K27ac modifications
  • H3K27ac modifications for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 1;
  • promoter signal e.g., H3K4me3 modifications
  • kits comprises one or more antibodies for use in ChlP- seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac- modified histones.
  • a kit comprises one or more methyl-binding domains for use in MBD-seq or wherein the kit comprises one or more antibodies that bind methylated DNA for use in MeDIP.
  • a kit comprises reagents for isolation of cell-free DNA (cfDNA) from a liquid biopsy sample.
  • a kit comprises reagents for library preparation for sequencing.
  • a kit comprises reagents for sequencing.
  • described herein is a non-transitory computer readable storage medium encoded with a computer program, wherein the program comprises instructions that when executed by one or more processors cause the one or more processors to perform operations to perform a method described herein.
  • a computer system comprising a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform operations to perform a method described herein.
  • a sequencer is configured to generate a Whole Genome Sequencing (WGS) data set from the sample.
  • WGS Whole Genome Sequencing
  • a system comprises a sample preparation device configured to prepare a sample for sequencing from a biological sample, optionally a liquid biopsy sample.
  • promoter signal e.g., H3K4me3 modifications
  • H3K4me3 modifications for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K4me3 analyte genomic loci in Table 1;
  • enhancer signal e.g., H3K27ac modifications
  • H3K27ac modifications for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 1;
  • enhancer signal e.g., H3K27ac modifications
  • promoter signal e.g., H3K4me3 modifications
  • enhancer signal e.g., H3K27ac modifications
  • promoter signal e.g., H3K4me3 modifications
  • promoter signal e.g., H3K4me3 modifications
  • enhancer signal e.g., H3K27ac modifications
  • a system described herein comprises reagents that comprise one or more antibodies for use in ChlP-seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac-modified histones.
  • a device comprises reagents for isolation of cell-free DNA (cfDNA) from a biological sample, optionally a liquid biopsy sample.
  • cfDNA cell-free DNA
  • a system comprises a device that comprises reagents for library preparation for sequencing.
  • a sequencer comprises reagents for sequencing.
  • the present disclosure is based, at least in part, on the demonstration that certain genomic loci associated with an ADC target antigen (FOLH1, encoding the ADC target antigen PSMA) have different histone modification levels (e.g., histone methylation marks such as H3K4me3 and histone acetylation marks such as H3K27ac) in plasma samples from cancer patients (e.g., prostate cancer) as compared to plasma samples from healthy volunteers.
  • FOLH1 histone methylation marks
  • H3K27ac histone acetylation marks
  • the present disclosure encompasses methods, kits and systems that use epigenomic differences (alone or in combination with each other and/or with other biomarkers) to select subjects for treatment with an agent that is directed to FOLH1 (e.g., an ADC therapy or radioligand directed to PSMA), to identify subpopulations of subjects that respond to treatment with an agent that is directed to FOLH1, to monitor subjects during treatment with an agent that is directed to FOLHl (e.g., an ADC therapy or radioligand directed to PSMA), etc. by detecting and quantifying the presence of histone modifications at these one or more genomic loci in cell- free DNA (cfDNA) from a liquid biopsy sample, e.g., a plasma sample obtained or derived from a subject.
  • cfDNA cell- free DNA
  • the present disclosure also encompasses methods where chromatin accessibility and/or binding of one or more transcription factors are detected at the one or more genomic loci instead of (or in addition to) histone modifications.
  • the present disclosure also encompasses methods, kits and systems where the genomic loci that are differentially modified based on different types of histone modifications (e.g, histone methylation marks such as H3K4me3 and histone acetylation marks such as H3K27ac) are combined into multimodal classifiers to select subjects for treatment with an agent that is directed to F0LH1 (e.g., an ADC therapy or radioligand directed to PSMA), etc.
  • F0LH1 e.g., an ADC therapy or radioligand directed to PSMA
  • These monomodal and multimodal classifiers can provide minimally invasive ways of selecting subjects for treatment with an agent that is directed to F0LH1 (e.g., an ADC therapy or radioligand directed to PSMA), etc. that are more accurate, objective, and comprehensive than the current tissue-based approaches.
  • an agent that is directed to F0LH1 e.g., an ADC therapy or radioligand directed to PSMA
  • the present disclosure includes, among other things, technologies for the determination of the activation status of F0LH1 and for the detection, monitoring, and/or treatment of cancer (including, e.g., prostate cancer, breast cancer, SCLC, NSCLC, etc.) based on the activation status of these genes.
  • cancer including, e.g., prostate cancer, breast cancer, SCLC, NSCLC, etc.
  • the present disclosure relates to the measurement of histone modifications in a sample obtained or derived from a subject to detect and/or treat cancer (including, e.g., prostate cancer, breast cancer, SCLC, NSCLC, etc.) based on the activation status of these genes.
  • the present disclosure includes, among other things, histone modification measurements in cell-free DNA (cfDNA) that are characteristic of the activation status of genes for F0LH1, and which in various embodiments are useful, e.g., for detecting, monitoring, selecting treatment for, and/or treating cancer (including, e.g., prostate cancer, breast cancer, SCLC, NSCLC, etc.) based on the activation status of these genes.
  • cfDNA cell-free DNA
  • histone modification measurements in cfDNA can be used to detect or determine resistance of a cancer (e.g., prostate cancer, breast cancer, SCLC, NSCLC, etc.) to treatment with an agent that is directed to FOLH1 (e.g., an ADC therapy or radioligand directed to PSMA) or transformation of a cancer from one subtype to another.
  • the present disclosure includes exemplary genomic loci that are differentially modified in different cancer patients (including, e.g., prostate cancer, breast cancer, SCLC, NSCLC, etc. patients) and/or between cancer patients and healthy volunteers.
  • genomic loci differentially modified in cfDNA are or include one or more enhancers.
  • genomic loci differentially modified in cfDNA are or include one or more promoters.
  • a genomic locus is differentially modified if it is characterized by increased or decreased histone modification as compared to a reference (e.g., a sample from a PSMA-negative or healthy subject).
  • Increased or decreased histone modification can be or include, e.g., increased or decreased histone methylation (hypermethylation or hypomethylation, respectively) of one or more particular methylation marks, or a combination thereof; increased or decreased pan-methylation; increased or decreased histone acetylation (hyperacetylation or hypoacetylation, respectively) of one or more particular acetylation marks, or a combination thereof; and/or increased or decreased pan-acetylation (e.g., pan-H3 acetylation).
  • histone methylation can be or include histone methylation marks selected from H3K4mel, H3K4me2, H3K4me3, or a combination thereof. In various embodiments, histone methylation can be or include H3K4me3. In various embodiments, histone acetylation can be or include histone acetylation marks selected from H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, or a combination thereof. In various embodiments, histone acetylation can be or include H3K27ac.
  • the present disclosure further relates, in various embodiments, to the measurement of chromatin accessibility in cell-free DNA (cfDNA) to determine the activation status of FOLH1.
  • cfDNA cell-free DNA
  • the present disclosure includes, among other things, chromatin accessibility measurements in cfDNA that are characteristic of PSMA-positive cancers, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating a PSMA-positive cancer.
  • histone acetylation corresponds and/or is correlated with chromatin accessibility.
  • histone methylation corresponds and/or is correlated with chromatin accessibility.
  • a genomic locus is differentially accessible if it is characterized by increased or decreased chromatin accessibility as compared to a reference (e.g, a sample from an ADC target-negative or healthy subject).
  • Increased or decreased histone modification can be or include, e.g., increased or decreased accessibility as determined by various chromatin accessibility assays known in the art.
  • the present disclosure includes genomic loci that are differentially bound by transcription factors in PSMA-positive vs. PSMA- negative cancers.
  • genomic loci that are differentially bound by transcription factors in cfDNA are or include one or more enhancers.
  • genomic loci that are differentially bound by transcription factors in cfDNA are or include one or more promoters.
  • the present disclosure provides a method comprising quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from a subject: (i) one or more histone modifications, (ii) DNA methylation, (iii) chromatin accessibility, and/or (iv) binding of one or more transcription factors, wherein the one or more genomic loci are (a) within a gene encoding PSMA.
  • cfDNA cell-free DNA
  • a method comprises quantifying enhancer signal (e.g., H3K27ac modifications) at one or more loci within a certain distance of KLK3 (e.g., within 500 kb, 400 kb, 300 kb, 200 kb, 150 kb, 100 kb, or 50 kB of KLK3).
  • enhancer signal e.g., H3K27ac modifications
  • a method comprises quantifying promoter signal (e.g., H3K4me3) at one or more loci within a certain distance of KLK3 (e g., 500 kb, 400 kb, 300 kb, 200 kb, 150 kb, 100 kb, 50 kB, 20 kB, 10 kB, 5, kB, 4 kB, 3 kB, 2 kB, or 1 kB of KLK3).
  • promoter signal e.g., H3K4me3
  • KLK3 e.g., 500 kb, 400 kb, 300 kb, 200 kb, 150 kb, 100 kb, 50 kB, 20 kB, 10 kB, 5, kB, 4 kB, 3 kB, 2 kB, or 1 kB of KLK3
  • a method comprises quantifying DNA methylation at one or more loci within the transcript encoding portion of KLK3 and/or at one or more loci within a certain distance of KLK3 (e.g., within 500 kb, 400 kb, 300 kb, 200 kb, 150 kb, 100 kb, or 50 kB of KLK3).
  • one or more loci within a certain distance of KLK3 include one or more loci with differential H3K4me3, H3K27ac, and/or DNA methylation signal (e.g., as compared to a healthy subject).
  • one or more loci within a certain distance of KLK3 include one or more loci at which levels of H3K4me3, H3K27ac, and/or DNA methylation signal is correlated with PSA expression (e.g., as determined by quantifying RNA transcript (e.g., as determined using an RNA-seq assay using tumor samples, PDX samples, and/or one or more cell lines).
  • a method comprises quantifying enhancer signal (e.g., H3K27ac modifications) at one or more loci within a certain distance of FOLH1 (e.g., within 500 kb, 400 kb, 300 kb, 200 kb, 150 kb, 100 kb, or 50 kB o FOLHl .
  • enhancer signal e.g., H3K27ac modifications
  • a method comprises quantifying promoter signal (e.g., H3K4me3) at one or more loci within a certain distance oiFOLHl (e.g., 500 kb, 400 kb, 300 kb, 200 kb, 150 kb, 100 kb, 50 kB, 20 kB, 10 kB, 5, kB, 4 kB, 3 kB, 2 kB, or 1 kB oiFOLHl .
  • promoter signal e.g., H3K4me3
  • oiFOLHl e.g., 500 kb, 400 kb, 300 kb, 200 kb, 150 kb, 100 kb, 50 kB, 20 kB, 10 kB, 5, kB, 4 kB, 3 kB, 2 kB, or 1 kB oiFOLHl .
  • one or more loci within a certain distance of FOLH1 include one or more loci with differential H3K4me3, H3K27ac, and/or DNA methylation signal (e g., as compared to a healthy subject).
  • one or more loci within a certain distance of FOLH1 include one or more loci at which levels of H3K4me3, H3K27ac, and/or DNA methylation signal is correlated with PSMA expression (e.g., as determined by quantifying RNA transcript (e.g., as determined using an RNA-seq assay using tumor samples, PDX samples, and/or one or more cell lines).
  • Fig. 1 is a schematic showing a summary of an exemplary comprehensive epigenomic platform offering dynamic resolution into target and pathway biology from plasma.
  • A Cell free DNA derived from tumors exists in circulation as chromatin fragments that faithfully maintain tumor-associated epigenetic modifications on histones and DNA. Antibodies against H3K27ac (marking active enhancers), H3K4me3 (marking active promoters), and DNA methylation can be used to enrich for associated DNA fragments from plasma, which can then be sequenced to provide genome-wide epigenomic maps that capture the underlying transcriptional state of tumor cells.
  • B Clinical study overview of mCRPC patient plasma samples evaluated in the study described in Example 2.
  • Fig. 2 shows volcano plots demonstrating identification of plasma epigenomic features that associate with mCRPC and PSMA-PET signal.
  • “Up’7 “Down” labels indicate the number of statistically-significant loci for enhancers, promoters, and DNA methylation that are upregulated (Up) or downregulated (Down) in mCRPC patients vs healthy volunteers. Labels represent the nearest TSS to statistically significant peaks of interest.
  • the x-axis values represent the slope of the association between the z-score of the epigenomic feature and the z-score of PSMA PET SUVmean, and the y-axis is the statistical significance of that association.
  • the top three features for each analyte are labeled with their closest gene (TSS).
  • Fig. 3 shows exemplary enrichment tracks demonstrating that the F0LH1 locus has robust enhancer and promoter signal in mCRPC patients compared to healthy volunteers.
  • Enhancer, promoter, and DNA methylation signal in mCRPC patients with either high or low PSMA PET SUV mean WHS normalized, smoothed, and averaged together (within analyte) with the mean signal from a cohort of male healthy volunteers.
  • Fig. 4 shows exemplary enrichment tracks demonstrating that the FOLH1 locus has higher enhancer and promoter signal in patients with higher PSMA PET SUVmean.
  • Enhancer, promoter, and DNA methylation signal in mCRPC patients with either high or low PSMA PET SUV mean W3S normalized, smoothed, and averaged together (within analyte) with the mean signal from a cohort of male healthy volunteers.
  • FIG. 5 shows scatter plots demonstrating that enhancer and promoter signal at the FOLH1 locus predicts PSMA PET SUVmean in both cross-validation and in validation cohort.
  • Enhancer and promoter signal at the FOLH1 locus were used to train a machine learning (ML) model to predict PSMA PET SUVmean.
  • Samples were first split into training and validation cohorts, which were matched for ctDNA% and PSMA PET SUVmean distributions.
  • training cohort samples (ctDNA% >3) were used to identify robust, mCRPC-specific enhancer/promoter regions at the FOLH1 locus. Signal at these regions were then used train a model to predict the corresponding PSMA PET SUVmean quantifications. Performance was assessed via Pearson correlation in both a leave-one-out (LOO) cross-validation (CV) setting within the training cohort, as well as the held-out validation cohort using a final model trained on all data from the training cohort.
  • LEO leave-one-out
  • CV cross-validation
  • FIG. 6 shows survival graphs demonstrating association with clinical outcomes with PSMA PET scores predicted using a model described herein. Shown are clinical outcomes (as measured by 4 clinical trial metrics) for mCRPC subjects having different PSMA PETtreated with lutetium-177 (177Lu)-PSMA-617, having different PSMA scores as determined using methods provided herein.
  • A Shows progression free survival as determined by whether there is an increase in serum PSA (PSA-PFS).
  • B Shows “crPFS” values, referring to progression free survival based on clinical or radiological evidence of progression.
  • C Shows Time to Next Treatment.
  • D Shows overall survival. In each of (A)-(D), lines represent patients with a PSMA score, from left to right, in the bottom tertile of patients, in the middle tertile of patients, in the top tertile of patients.
  • FIG. 7 shows survival graphs for comparison of hazard ratios based on PSMA PET SUVmean predictions vs. PSMA PET measured values. Shown is a comparison of clinical trial outcomes for a cohort of mCRPC patients administered lutetium-177 (177Lu)-PSMA-617, and having different measured PSMA PET SUVmean values (PSMA PET SUVmean (Measured)) vs. predicted PSMA PET SUVmean values (PSMA PET SUVmean (Predicted)), which were predicted using technologies described herein.
  • (A) and (B) show progression free survival as determined by whether an increase in serum PSA was observed (PSA-PFS), in subjects having different measured PSMA PET SUVmean or predicted PSMA PET SUVmean values, respectively.
  • (C) and (D) show Time to Next Treatment (TTNT), in subjects having different measured PSMA PET SUVmean or predicted PSMA PET SUVmean values, respectively.
  • (E) and (F) show “crPFS” values, referring to progression free survival based on clinical or radiological evidence of progression, in subjects having different measured PSMA PET SUVmean or predicted PSMA PET SUVmean values, respectively.
  • (G) and (H) show Overall Survival (OS), in subjects having different measured PSMA PET SUV mean or predicted PSMA PET SUVmean values, respectively.
  • black lines represent patients with a measured or predicted PSMA PET SUVmean in the top tertile of patients and grey lines represent patients with a measured or predicted PSMA PET SUVmean in the middle and bottom tertiles of patients.
  • HR refers to Hazard Ratio.
  • Fig. 8 shows a scatterplot with comparison of predicted and measured PSA expression in plasma samples from prostate cancer patients. Shown is predicted PSA expression (“Predicted KLK3 RNA-seq expression,” y-axis), determined using epigenetic modification measurements collected in plasma samples obtained from prostate cancer patients, and serum PSA (“PSA plasma concentration,” x-axis) measured in matched plasma samples, p refers to Pearson’s coefficient. Shading indicates 95% confidence interval.
  • FIG. 9 shows a scatterplot demonstrating prediction of PSMA PET SUVmean using patient plasma samples.
  • A Shows PSMA expression predicted using a biopsy model, using epigenetic modification measurements from plasma samples obtained from prostate cancer patients (y-axis) vs. PSMA PET SUVmean measured in matched patients (x-axis).
  • B Shows PSMA PET SUVmean predicted using a model generated using patient plasma data and PMSA PET SUVmean values vs. PSMA PET SUVmean measured in matched patients (x-axis).
  • Fig. 11 shows clinicoradiographic Progression Free Survival (CR PFS) for mCRPC patients with a predicted PSMA PET SUVmean value in the top tertile (top, black line) and middle and bottom tertiles (red, bottom line).
  • HR refers to Hazard Ratio.
  • Figs. 12(A)-(D) show prostate specific antigen (PSA), time to next treatment (TTNT), clinicoradiographic Progression Free Survival (CR PFS), and overall survival (OS) metrics for patients with mCRPC with ctDNA% in the top tertile (bottom, black line) and middle and bottom tertiles (red, top line).
  • HR refers to Hazard Ratio.
  • PSMA expression level e.g., PSMA expression level
  • a subject can be determined by detecting and quantifying the presence of histone modifications and/or DNA methylation at one or more genomic loci in cell-free DNA (cfDNA) from a liquid biopsy sample, e.g., a plasma sample obtained or derived from a subject.
  • cfDNA cell-free DNA
  • the present disclosure demonstrates that PSMA expression level can be determined in cancer cells in a subject, including, e.g., PSMA expression level in prostate cancer (e.g., mCRPC).
  • Determining PSMA expression level can be used for, e.g., diagnosing, prognosing, or monitoring a disease in a subject, and methods of treatment (e.g., for identifying subject more likely to respond to treatment with a PSMA-targeted therapeutic).
  • Prostate cancer is a disease characterized by the uncontrolled growth of cells in the prostate, a gland in the male reproductive system below the bladder.
  • Risk factors for prostate cancer include age (especially after the age of 50; risk increases further after the age of 65, with -60% of prostate cancers found in men older than 65), ethnicity (prostate cancer is more common in African American men and in Caribbean men of African ancestry), family history (having a father or brother with prostate cancer more than doubles a man’s risk of developing the disease), and certain genetic variants or mutations (including variants of the BRCA1 and BRCA2 genes, and men with Lynch syndrome, a condition caused by inherited gene changes).
  • PSA prostate-specific antigen
  • prostate tumors remain small and cause no health problems. These are managed with active surveillance and monitoring tumor(s) with regular tests to ensure that have not grown. Tumors more likely to be dangerous can be targeted with radiation therapy or surgically removed by radical prostatectomy. Subjects whose cancer spreads beyond the prostate can be treated with hormone therapy, which reduces levels of the androgens (male sex hormones) that prostate cells need to survive. Cancer cells can eventually grow resistant to this treatment. This most-advanced stage of the disease, called castration-resistant prostate cancer (CRPC), can be treated with continued hormone therapy alongside with a chemotherapy drug (e g., docetaxel). Some tumors metastasize to other areas of the body, particularly the bones and lymph nodes.
  • a chemotherapy drug e g., docetaxel
  • Prostate cancer prognosis depends on how far the cancer has spread at diagnosis. Most men diagnosed have tumors confined to the prostate; 99% survive more than 10 years from their diagnoses. Tumors that have metastasized to distant body sites are most dangerous, with five- year survival rates of 30-40%.
  • PSA protein prostate-specific antigen
  • a typical man's blood has around 1 nanogram (ng) of PSA per milliliter (mb) of blood tested.
  • ng nanogram
  • mb milliliter
  • PSA levels below average are very unlikely to develop dangerous prostate cancer over the next 8 to 10 years.
  • Men with PSA levels above 4 ng/mL are at increased risk - around 1 in 4 will develop prostate cancer - and are often referred for a prostate biopsy. PSA levels over 10 ng/mL indicate an even higher risk: over half of men in this group develop prostate cancer.
  • Those with elevated PSA may undergo secondary screening blood tests that measure subtypes of PSA and other molecules to better predict the likelihood that a person will develop aggressive prostate cancer.
  • Many tests measure “free PSA” - the fraction of PSA unbound to other blood proteins, which is usually around 10% to 30%. Men who have a lower percentage of free PSA are more likely to have prostate cancer.
  • Several common tests more accurately detect prostate cancer cases by also measuring subtypes of free PSA, including the Prostate Health Index (measures a fragment called -2proPSA) and 4K score (measures intact free PSA).
  • Other tests measure blood levels of additional prostate-related proteins such as kallikrein-2 (also measured by 4K score), or urine levels of mRNA molecules common to prostate tumors like PC A3 and TMPRSS2 fused to ERG.
  • MRI magnetic resonance imaging
  • Prostate biopsies are typically taken by a needle passing through the rectum or perineum, guided by transrectal ultrasonography, MRI, or a combination of the two. Ten to twelve samples are taken from several regions of the prostate to improve the chances of finding any tumors. Biopsies are sent for a histopathologic diagnosis of prostate cancer, wherein they are examined under a microscope by a pathologist, who determines the type and extent of cancerous cells present. Cancers are first classified based on their appearance under a microscope.
  • adenocarcinomas (resembling gland tissue), with the rest largely squamous-cell carcinoma (resembling squamous cells, a type of epithelial cell) and transitional cell carcinoma (resembling transitional cells).
  • tumor samples are graded based on how much the tumor tissue differs from normal prostate tissue; the more different the tumor appears, the faster the tumor is likely to grow.
  • the Gleason grading system is commonly used, where the pathologist assigns numbers ranging from 3 (most similar to healthy prostate tissue) to 5 (least similar) to different regions of the biopsied tissue. They then calculate a “Gleason score” by adding the two numbers that represent the largest areas of the biopsy sample. The lowest possible Gleason score of 6 represents a biopsy most similar to healthy prostate; the highest Gleason score of 10 represents the most severely cancerous.
  • Gleason scores are commonly grouped into “Gleason grade groups”, which predict disease prognosis: a Gleason score of 6 is Gleason grade group 1 (best prognosis). A score of 7 (with Gleason scores 4 + 3, or Gleason scores 3 + 4, with the most prominent listed first) can be grade group 2 or 3; it is grade group 2 if the less severe Gleason score (3) covered more area; grade group 3 if the more severe Gleason score (4) covered more area. A score of 8 is grade group 4. A score of 9 or 10 is grade group 5 (worst prognosis).
  • the extent of cancer spread can be assessed by MRI or PSMA scan - a positron emission tomography (PET) imaging technique where a radioactive label that binds the prostate protein prostate-specific membrane antigen is used to detect metastases distant from the prostate.
  • PET positron emission tomography
  • CT scans may also be used but are less able to detect spread outside the prostate.
  • Bone scintigraphy can be used to test for spread of cancer to bones.
  • Prostate-specific membrane antigen is encoded by folate hydrolase 1 (FOLHI), and is a transmembrane glutamate carboxypeptidase that is highly expressed on prostate cancer cells. It consists of a large extracellular domain, a small transmembrane domain, and a cytoplasmic tail. High PSMA expression is a biomarker of poor prognosis throughout the course of prostate cancer and across anatomical sites. Metastatic lesions are PSMA-positive in most patients that have metastatic castration-resistant prostate cancer, and high PSMA expression has been independently associated with reduced survival.
  • FOLHI folate hydrolase 1
  • a PSMA PET scan is a nuclear medicine imaging technique that can be used in the diagnosis and staging of prostate cancer. It is carried out by injecting a radiopharmaceutical with a positron or gamma emitting radionuclide and a prostate-specific membrane antigen (PSMA) targeting ligand. After injection, imaging of positron emitters such as gallium-68 (68Ga), copper-64 (64Cu), and fluorine-18 (18F) is carried out with a positron emission tomography (PET) scanner. For gamma emitters such as technetium-99m (99mTc) and indium- 111 (11 Un) single-photon emission computed tomography (SPECT) imaging is performed with a gamma camera.
  • positron emitters such as gallium-68 (68Ga), copper-64 (64Cu), and fluorine-18 (18F) is carried out with a positron emission tomography (PET) scanner.
  • gamma emitters such as technetium-99
  • PSMA imaging can also be used to assess suitability for and plan treatment with external beam radiotherapy and PSMA- targeted therapeutics (e.g., PSMA-targeted radionuclides).
  • PSMA- targeted therapeutics e.g., PSMA-targeted radionuclides.
  • PSMA targeting therapies such as radionuclide therapies (e.g., lutetium- 177 (177Lu)-PSMA-617) can target prostate cancer cells while sparing most normal tissues in patients who have been selected with the use of imaging to confirm radionuclide binding.
  • radionuclide therapies e.g., lutetium- 177 (177Lu)-PSMA-617
  • PSMA expression in tumors is commonly assessed using PSMA- targeted positron emission tomography (PET), which has gained increased acceptance in diagnosing prostate cancer due to its superior accuracy in identifying metastases as compared to CT and MRI methods.
  • PET positron emission tomography
  • Patient eligibility for lutetium- 177 (177Lu)-PSMA-617 currently requires PSMA PET imaging.
  • MEDI3726 an engineered version of an anti-PSMA IgGlK antibody (J591), site- specifically conjugated with pyrrolobenzodiazepine (PBD) dimers (SG3199). Described, e.g., in de Bono et al. “Phase I study of MEDI3726: a prostate-specific membrane antigen-targeted antibody-drug conjugate, in patients with mCRPC after failure of abiraterone or enzalutamide.” Clinical Cancer Research 27.13 (2021): 3602-3609.
  • PSA Prostate-specific antigen
  • KLK3 kallikrein- 3
  • P-30 antigen is a glycoprotein enzyme encoded in humans by the KLK3 gene.
  • PSA is a member of the kallikrein-related peptidase family and is secreted by the epithelial cells of the prostate gland in men and the paraurethral glands in women.
  • PSA levels can also be monitored (e.g., measured periodically (e.g., every 6-36 months)).
  • patients with high-risk disease are monitored at an increased frequency as compared to patients with lower-risk disease.
  • surgical therapy i.e., radical prostatectomy
  • PSA can become undetectable within a few weeks.
  • a subsequent rise in PSA level above 0.2 ng/mL is generally regarded as evidence of recurrent prostate cancer after a radical prostatectomy; less commonly, it may simply indicate residual benign prostate tissue.
  • Recurrent prostate cancer detected by a rise in PSA levels after curative treatment is referred to as a “biochemical reoccurrence.”
  • the likelihood of developing recurrent prostate cancer after curative treatment is related to the pre-operative variables described in the preceding section (PSA level and grade/stage of cancer).
  • Low-risk cancers are the least likely to recur, but they are also the least likely to have required treatment in the first place.
  • a sample analyzed using methods, kits and systems provided herein can be any biological sample including any processed sample that includes cell free DNA (cfDNA) derived from a biological sample.
  • a sample analyzed using methods, kits and systems provided herein can be a sample obtained from a mammalian subject.
  • a sample analyzed using methods, kits and systems provided herein can be a sample obtained from a human subject.
  • a sample from a subject can be obtained from a liquid biopsy.
  • a sample and/or reference is obtained from serum, plasma, or urine.
  • the sample is serum.
  • a sample comprises cell free DNA (cfDNA).
  • cfDNA cell free DNA
  • a sample is derived from about 1 mL of blood obtained from the subject.
  • a sample is derived from about 0.5-2 mL of blood obtained from the subject, e.g., about 0.5 to 1 .75 mL, about 0.5 to 1.5 mb, about 0.75 to 1.25 mL or about 0.9 to 1.1 mL of blood.
  • a sample comprises circulating tumor DNA (ctDNA).
  • a sample is derived from about 1 mL of blood obtained from the subject.
  • a sample is a sample of cell-free DNA (cfDNA).
  • cfDNA is typically found in human biofluids (e.g., plasma, serum, or urine) in short, double-stranded fragments.
  • the concentration of cfDNA is typically low, but can significantly increase under particular conditions, including without limitation pregnancy, autoimmune disorders, myocardial infarction, and cancer.
  • Circulating tumor DNA is a component of cell-free DNA specifically derived from cancer cells.
  • ctDNA can be present in human biofluids bound to leukocytes and erythrocytes or not bound to leukocytes and erythrocytes.
  • ctDNA comprises less than 30%, less than 20%, or less than 10% of the cfDNA in the liquid biopsy sample obtained from the subject, e.g., less than 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2% or less than 1% of the cfDNA in the sample.
  • the percentage of ctDNA in the liquid biopsy sample is assessed using ichorCNA which estimates the percentage of ctDNA in a sample probabilistically (see Adalsteinsson et al., Nat Commun (2017) 8(1): 1324 the entire contents of which are incorporated herein by reference).
  • cfDNA and ctDNA can provide a real-time or nearly real time metric of status of a source tissue.
  • cfDNA and ctDNA demonstrate a half-life in blood of about 2 hours, such that a sample taken at a given time provides a relatively timely reflection of the status of a source tissue.
  • Samples include materials prepared by processes including, without limitation, steps such as concentration, dilution, adjustment of pH, removal of high abundance polypeptides (e.g., albumin, gamma globulin, and transferrin, etc.), addition of preservatives, addition of calibrants, addition of protease inhibitors, addition of denaturants, desalting, concentration and/or extraction of sample nucleic acids, and/or amplification of sample nucleic acids (e.g., by PCR or other nucleic acid amplification techniques). Samples also include materials prepared by techniques that isolate, e.g., nucleosomes or transcription factors and/or nucleic acids associated with nucleosomes or transcription factors.
  • steps such as concentration, dilution, adjustment of pH, removal of high abundance polypeptides (e.g., albumin, gamma globulin, and transferrin, etc.), addition of preservatives, addition of calibrants, addition of protease inhibitors, addition of denaturants
  • Removal from a sample of proteins that are not desirable for a relevant purpose or context can be achieved using high affinity reagents, high molecular weight filters, ultracentrifugation and/or electrodialysis.
  • High affinity reagents include antibodies or other reagents (e.g., aptamers) that selectively bind to high abundance proteins.
  • Sample preparation can also include ion exchange chromatography, metal ion affinity chromatography, gel filtration, hydrophobic chromatography, chromatofocusing, adsorption chromatography, isoelectric focusing and related techniques.
  • the membranes used in electrodialysis may have the ability to selectively transport ions having positive or negative charge, reject ions of the opposite charge, or to allow species to migrate through a semipermeable membrane based on size and charge, it renders electrodialysis useful for concentration, removal, or separation of electrolytes.
  • Separation and purification in the present disclosure may include any procedure known in the art, such as capillary electrophoresis (e.g., in capillary or on-chip) or chromatography (e.g., in capillary, column or on a chip).
  • Electrophoresis is a method that can be used to separate ionic molecules under the influence of an electric field. Electrophoresis can be conducted in a gel, capillary, or in a microchannel on a chip. Examples of gels used for electrophoresis include starch, acrylamide, polyethylene oxides, agarose, or combinations thereof.
  • a gel can be modified by its cross-linking, addition of detergents, or denaturants, immobilization of enzymes or antibodies (affinity electrophoresis) or substrates (zymography) and incorporation of a pH gradient.
  • capillaries used for electrophoresis include capillaries that interface with an electrospray.
  • CE Capillary electrophoresis
  • CZE capillary zone electrophoresis
  • CIEF capillary isoelectric focusing
  • CITP capillary isotachophoresis
  • CEC capillary electrochromatography
  • An embodiment to couple CE techniques to electrospray ionization involves the use of volatile solutions, for example, aqueous mixtures containing a volatile acid and/or base and an organic such as an alcohol or acetonitrile.
  • Capillary isotachophoresis is a technique in which the analytes move through the capillary at a constant speed but are nevertheless separated by their respective mobilities.
  • Capillary zone electrophoresis also known as free-solution CE (FSCE)
  • FSCE free-solution CE
  • Capillary isoelectric focusing allows weakly-ionizable amphoteric molecules, to be separated by electrophoresis in a pH gradient.
  • CEC is a hybrid technique between traditional high performance liquid chromatography (HPLC) and CE.
  • Separation and purification techniques used in the present disclosure can include any chromatography procedures known in the art. Chromatography can be based on the differential adsorption and elution of certain analytes or partitioning of analytes between mobile and stationary phases. Different examples of chromatography include, but not limited to, liquid chromatography (LC), gas chromatography (GC), high performance liquid chromatography (HPLC), etc.
  • LC liquid chromatography
  • GC gas chromatography
  • HPLC high performance liquid chromatography
  • whole blood is collected from a subject, and a plasma layer is separated by centrifugation.
  • cfDNA may be then extracted from the plasma using methods known in the art.
  • Histone methylation is understood to increase or decrease expression of associated coding sequences, depending on which histone residue is methylated.
  • Histone methylation is an essential modification that can cause monomethylation (mel), dimethylation (me2), and trimethylation (me3) of several amino acids, thus directly affecting heterochromatin formation, gene imprinting, X chromosome inactivation, and gene transcriptional regulation.
  • Histone methyltransferases promote monomethylation, dimethylation, or trimethylation of histones while histone demethylases promote demethylation of histones.
  • Histone methylation In general, lysine (Lys or K), arginine (Arg or R), and rarely histidine (His or H) are the most common histone methyl acceptors. Histone methylation only occurs at specific lysine and arginine sites of histone H3 and H4. In histone H3, lysine 4, 9, 26, 27, 36, 56, and 79 and arginine 2, 8, and 17 can be methylated. By comparison, histone H4 has fewer methylation sites, in which only lysine 5, 12, and 20 and arginine 3 can be methylated. Histone methylation is often associated with transcriptional activation or inhibition of downstream genes.
  • H3K4, R8, R17, K26, K36, K79, H4R3, and K12 can activate gene transcription.
  • the methylation of histone H3K9, K27, K56, H4K5, and K20 can inhibit gene transcription.
  • H3K4 methylation generally activates gene expression
  • H3K27 methylation generally represses gene expression.
  • Histone acetylation occurs predominantly at lysine residues and is generally understood to increase expression of associated coding sequences. Without wishing to be bound by any theory, acetylation of lysine residues is thought to neutralize lysine’s positive charge and thereby cause histones to drift away from DNA, which has a negative charge. The released structure facilitates access to transcriptional machinery such as transcription factors and RNA polymerase II. Histone acetylation and deacetylation are generally catalyzed by histone acetyltransferases (HATs) and HDACs, respectively. Acetyl-CoA can be a source and co-factor of acetylation.
  • HATs histone acetyltransferases
  • HDACs histone acetyltransferases
  • HATs can acetylate histones and recruit HAT-containing complexes to activate the transcriptional process.
  • H3K9ac and H3K27ac levels can be associated with promoter and enhancer activities.
  • H3K27ac enhances not only the kinetics of transcriptional activation, but also accelerates the transition of RNA polymerase II from the initiation state to the elongation state.
  • Differential modification of a genomic locus can refer to, or be determined by or detected as, a comparative difference or change in modification status of one or more genomic loci between a first sample, condition, disease, or state and a second or reference sample, condition, disease, or state.
  • a reference is typically produced by measurement using a methodology identical, similar, or comparable to that by which a compared non-reference measurement was taken.
  • Chromatin accessibility can refer to the degree to which nuclear macromolecules are able to physically contact DNA and is determined in part by the occupancy and modification status of nucleosomes.
  • Modified histones can regulate chromatin accessibility through a variety of mechanisms, such as altering transcription factor (TF) binding through steric hindrance and modulating nucleosome affinity for active chromatin remodelers.
  • TF transcription factor
  • the topological organization of nucleosomes across the genome is non-uniform: while histones can be densely arranged within facultative and constitutive heterochromatin, histones can be depleted at regulatory loci, including within enhancers, insulators and transcribed gene bodies. Active regulatory elements of the genome are generally accessible.
  • Differential accessibility of a genomic locus can refer to, or be determined by or detected as, a comparative difference or change in modification status of one or more genomic loci between a first sample, condition, disease, or state and a second or reference sample, condition, disease, or state.
  • a reference is typically produced by measurement using a methodology identical, similar, or comparable to that by which a compared non-reference measurement was taken.
  • a reference can be a value or set of values that are predetermined or derived from a sample or set of samples.
  • a reference can be a sample or set of samples.
  • a reference value can be a predetermined threshold value, a value that varies in accordance with circumstances (e.g., according to patient subpopulation, age, weight, or other variables), or a ratio.
  • Reference ratios can be ratios relating to the modification and/or accessibility of multiple loci within individual samples and/or references, or across or between samples and/or references.
  • a reference can have or represent a normal, non-diseased state.
  • a reference can have or represent a diseased state, e.g., prostate cancer.
  • a reference can represent prostate cancer by being obtained from a subject diagnosed as having prostate cancer (e.g., based on imaging, symptoms, and/or biomarker analysis).
  • a reference is a non-contemporaneous sample from the same source, e.g., a prior sample from the same source, e.g., from the same subject.
  • a reference for the modification status of one or more genomic loci can be the modification status of the one or more genomic loci (e.g., one or more differentially modified genomic loci) in a sample (e.g., a sample from a subject), or a plurality of samples, known to represent a particular state (e.g., mCRPC with elevated PSMA expression or prostate cancer with elevated serum PSA).
  • a reference for the accessibility status of one or more genomic loci can be the accessibility status of the one or more genomic loci (e.g., one or more differentially accessible genomic loci) in a sample (e.g., a sample from a subject), or a plurality of samples, known to represent a particular state (e.g., mCRPC with elevated PSMA expression or prostate cancer with elevated serum PSA).
  • differential modification or differential accessibility can refer to a differential (e.g., between a sample and a reference) with an absolute log2(fold-change) that is greater than or equal to 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0 or more, or any range in between, inclusive, e.g., as measured according to an assay provided herein.
  • Enhancers are genomic loci that can be differentially modified or differentially accessible in and/or between conditions, diseases, and other states. Enhancers are cis-acting DNA regulatory regions that are thought to bind trans-acting proteins that contribute to expression patterns of associated genes. Chromatin ImmunoPrecipitation sequencing (ChlP-seq) of histone modifications (e.g., acetylation) have identified millions of enhancers in mammalian genomes. The number of active enhancers in any given cell type is estimated to be in the tens of thousands. Certain transcription factors (TFs), sometimes referred to as “master” transcription factors, associate with active enhancers with important impacts on gene expression and cell function.
  • TFs transcription factors
  • transcription factors preferentially associate with enhancers that regulate genes required for establishing cell identity and function, including enhancer domains known as “super-enhancers”.
  • master TFs can participate in inter-connected auto-regulatory circuitries or “cliques” that are self-reinforcing, show marked cell selectivity, and function to maintain cell state and/or cell survival.
  • Chromatin ImmunoPrecipitation is one technique of molecular biology useful in detecting and quantifying histone modifications and transcription factor binding in samples.
  • CUT&RUN or CUT&Tag are other more recent techniques that can also be used to detect and quantify histone modifications and transcription factor binding sites.
  • ChIP -chip, ChlP-exo, ChIP Re-ChIP, and ChlPmentation are other alternative techniques that could be used.
  • ChIP can involve various steps including one or more of fixation, sonication, immunoprecipitation, and analysis of the immunoprecipitated DNA.
  • ChIP has become a very widely used tissue-based technique for determining the in vivo location of binding sites of various transcription factors and histones. Because the proteins are captured at the sites of their binding with DNA, ChIP helps to detect DNA-protein interactions that take place in living cells. More importantly, ChIP can be coupled to many commonly used molecular biology techniques such as PCR and real-time PCR, PCR with single-stranded conformational polymorphism, Southern blot analysis, Western blot analysis, cloning, and microarray. The resulting versatility has increased the potential of this technique.
  • ChIP of tissue samples usually involves cross-linking of the chromatin-bound proteins by formaldehyde, followed by sonication or nuclease treatment to obtain small DNA fragments. Immunoprecipitation can be then carried out using specific antibodies to the DNA- binding protein of interest. The DNA can be then released from the proteins and analyzed using various methods. ChIP has also been used to study RNA-protein interactions. X-ChIP methods utilize fixed chromatin fragmented by sonication, while the N-ChIP methods utilize native chromatin, which can be unfixed and nuclease digested.
  • the first step of the technique can be the cross-linking of DNA and proteins.
  • Formaldehyde is one of the most used cross-linking agents.
  • One advantage of using formaldehyde can be the ease of reversibility of the cross-links and its ability to form bonds that span approximately 2 angstroms. This means that formaldehyde can bind molecules in close association with each other.
  • formaldehyde can be added to the medium in the cell culture flask or plate. It enters the cells through the cell membrane and cross-links the proteins to the chromatin. Formaldehyde fixation of tumor tissues has also been done.
  • Other cross-linking agents that have been used include chemicals such as methylene blue and acridine orange, cisplatin, dimethylarsinic acid, potassium chromate, and ultraviolet (UV) light and lasers.
  • Harvested chromatin can be sonicated in one or more sonication cycles.
  • DNA can be typically broken into to 100-500 bp fragments to pinpoint the location of the DNA sequence of interest.
  • An alternative to sonication can be nuclease digestion of the chromatin, e.g., in N- ChlP methods.
  • Purification of chromatin can be achieved using a cesium chloride (CsCl) gradient centrifugation.
  • CsCl cesium chloride
  • Chromatin can be immunoprecipitated using one or more antibodies that bind a target epitope.
  • an antibody used in ChIP can selectively bind a particular transcription factor or one or more particular histone modifications, such as one or more particular histone acetylation modifications or histone methylation modifications.
  • an antibody used to bind a target epitope can be a “pan” antibody (e.g., a panacetylation antibody, a pan-methylation antibody, an antibody that binds a group of histone modifications associated with increased transcription activation, and/or an antibody that binds a group of histone modifications associated with increased transcription repression).
  • the antibody against the protein of interest is allowed to bind to the protein-DNA complex, and the complex can be then precipitated.
  • Immunosorbants commonly used to separate the antigen-antibody complex from the lysate include salmon sperm DNA-protein A-Sepharose®, protein G, magnetic beads, and other engineered immunoprecipitation systems known to those of skill in the art.
  • Immunoprecipitated DNA can be eluted. Once the DNA of interest is isolated, many detection and quantification methods can be used to study the isolated gene fragments. Commonly utilized methods include PCR, real-time PCR, slot blot hybridization, microarray techniques, and deep or next-generation sequencing. ChlP-seq combines chromatin immunoprecipitation (ChIP) with massively parallel DNA sequencing to identify the binding sites of DNA-associated proteins. ChlP-seq can be used to map DNA-binding proteins, e.g., transcription factor binding sites and histone modifications in a genome-wide manner.
  • ChIP chromatin immunoprecipitation
  • Cell-free Chromatin ImmunoPrecipitation sequencing involves applying ChlP-seq to samples that include cell-free DNA, e.g., liquid biopsy samples including cfDNA such as plasma samples including cfDNA (e.g., see Sadeh et al., Nat Biotechnol (2021) 39: 586-598 and Jang et al., Life Sci Alliance (2023) 6(12):e202302003 the entire contents of each of which are incorporated herein by reference).
  • cfChlP-seq uses antibodies or antibody fragments that bind specific histone modifications (e.g., H3K4me3 and/or H3K27ac) and/or transcription factors that are coupled (covalently or non-covalently) to beads, e g., magnetic beads such as Dynabeads® magnetic beads and incubated with a volume, e.g., about 1 mL of thawed plasma obtained from a subject.
  • specific histone modifications e.g., H3K4me3 and/or H3K27ac
  • transcription factors that are coupled (covalently or non-covalently) to beads, e g., magnetic beads such as Dynabeads® magnetic beads and incubated with a volume, e.g., about 1 mL of thawed plasma obtained from a subject.
  • exemplary antibodies that bind H3K4me3 include PA5-27029 (available from Thermo Fisher Scientific in Waltham, MA) and C15410003 (available from Diagenode in Denville, NJ) and exemplary antibodies that bind H3K27ac include ab21623 or ab4729 (both available from Abeam in Cambridge, UK) and Cl 5210016 (available from Diagenode in Denville, NJ).
  • the antibodies or antibody fragments can be covalently coupled to beads, e.g., epoxy beads.
  • the antibodies or antibody fragments can be non-covalently coupled to beads, e.g., Protein A or Protein G beads such as Dynabeads® Protein A or Dynabeads® Protein G beads.
  • a cfDNA library is then typically prepared from the captured cfDNA. Library preparation can be done on-bead or after releasing the captured cfDNA by digestion of bound histones, e g., using proteinase K.
  • the cfDNA library is then sequenced to generate reads of captured cfDNA sequences, e.g., by next-generation sequencing (NGS) as is known in the art.
  • NGS next-generation sequencing
  • the reads are then analyzed, e.g., aligned and counted using standard bioinformatic techniques as is known in the art.
  • a cfChlP-seq bioinformatic pipeline can include, e.g., alignment of sequence reads to a reference genome with BWA or Bowtie2. Aligned reads can be used to call and quantify peaks as compared to a reference.
  • CUT&Tag involves antibody-based binding of a target protein, e.g., transcription factor or histone modification of interest, where antibody incubation is directly followed by the shearing of the chromatin and library preparation (see Kaya-Okur et al., Nat Comm (2019) 10: 1930).
  • CUT&Tag assays take advantage of a Tn5 transposase that is fused with Protein A to direct the enzyme to the antibody bound to its target on chromatin.
  • Tn5 transposase is pre-loaded with sequencing adapters (generating the assembled pA-Tn5 adapter transposome) to carry out antibody-targeted tagmentation.
  • samples are incubated with an antibody immobilized on Concanavalin A-coated magnetic beads to facilitate subsequent washing steps.
  • Cells can be incubated with a primary antibody specific for the target protein of interest followed by incubation with a secondary antibody.
  • Samples can then be incubated with assembled transposomes, which consist of Protein A fused to the Tn5 transposase enzyme that is conjugated to NGS adapters. After incubation, unbound transposome can be washed away using stringent conditions.
  • Tn5 is a Mg 2+ -dependent enzyme so Mg 2+ can be added to activate the reaction, which results in the chromatin being cut close to the protein binding site and simultaneous addition of the NGS adapter DNA sequences. Chromatin cleavage and library preparation can be achieved in one single step.
  • CUT&RUN is an epigenomic profiling strategy in which antibody-targeted controlled cleavage by micrococcal nuclease releases specific protein-DNA complexes into the supernatant for paired-end DNA sequencing (see Skene and Henikoff, Elife (2017) 6:1-35, Skene et al., Nat Protoc (2016) 13:1006-1019). As only targeted fragments enter into solution, and the vast majority of DNA is left behind, CUT&RUN has low background levels.
  • a sample is incubated with an antibody or antibody fragment that binds the target protein, e.g., transcription factor or histone modification of interest.
  • the sample is then incubated with Protein-A-MNase after which CaCh can be added to initiate the calcium dependent nuclease activity of MNase to cleave the DNA around the target protein.
  • the protein- A-MNase reaction can be quenched by adding chelating agents (EDTA and EGTA). Cleaved DNA fragments are then liberated, extracted, and used to construct a sequencing library.
  • kits and systems of the present disclosure involve the detection and quantification of chromatin accessibility in samples, e.g., in liquid biopsy samples including cfDNA such as plasma samples including cfDNA.
  • ATAC-seq Assay of Transpose Accessible Chromatin sequencing
  • NOMe-seq Nucleosome Occupancy and Methylome sequencing
  • FAIRE-seq Formmaldehyde-Assisted Isolation of Regulatory Elements sequencing
  • MNase-seq Merococcal Nuclease digestion with sequencing
  • DNase hypersensitivity assays are exemplary techniques of molecular biology useful in detecting and quantifying chromatin accessibility in samples.
  • Sono-Seq is another alternative method that could be used (see Auerbach et al., Proc Natl Acad USA (2009) 106(35): 14926-14931).
  • Fragmentomics-based methods are yet another method that can be used to assess chromatin accessibility (see Ding, Spencer C., and YM Dennis Lo. "Cell-free DNA fragmentomics in liquid biopsy.” Diagnostics 12.4 (2022): 978).
  • DNase hypersensitivity assays can use the non-specific DNA endonuclease Deoxyribonuclease I (DNase I), which selectively digests accessible DNA regions.
  • DNase I hypersensitivity sites (DHS) identified by DNase-seq include open chromatin regulatory regions.
  • a typical DNase hypersensitivity assay can include a first step in which nuclei are isolated from cells using lysis buffer, and nuclei are digested using DNase I. DNA fragment sizes are measured to identify optimal digestion using gel electrophoresis. Biotinylated linkers can be ligated to the ends of digested DNA after polishing to make blunt ends, and the DNA can then be isolated.
  • DNA with biotinylated linker can be digested by restriction endonuclease Mmel and captured by streptavidin coated Dynabeads® to generate short tags to which a second sequencing adaptor can be ligated.
  • a second linker can be ligated and amplified to generate a library for sequencing.
  • a DNase-seq bioinformatic pipeline can include, e.g., alignment of sequence reads to a reference genome with BWA or Bowtie2. Aligned reads can be used to call and quantify peaks as compared to a reference.
  • MNase-seq determines chromatin accessibility with micrococcal nuclease (MNase) that preferentially digests nucleosome-free, protein-unbound DNA.
  • MNase- seq assay can include a first step in which nuclei are isolated from either native or crosslinked chromatin and digested using MNase with titration. In vivo formaldehyde crosslinking step that is designed to capture the interaction between proteins and DNA. This crosslinking allows bound proteins to shield their associated DNA from digestion by MNase. Following crosslinking, samples are digested with MNase, which can be specifically activated by addition of Ca2+ to the buffer.
  • Digestion can be halted by chelating the reaction, at which point the samples are RNase treated, crosslinks are reversed, and proteins are digested away from the chromatin. DNA can then be isolated via a phenol-chloroform extraction. Uncut DNA is purified and mononucleosome bands are isolated and excised through gel electrophoresis. Isolated DNA can be amplified by adding adapters to generate a library, and sequenced. MNase-seq primarily sequences regions of DNA bound by histones or other proteins. Therefore, it indirectly determines which regions of DNA are accessible by directly determining which regions are bound to nucleosomes or proteins.
  • FAIRE-seq is a method in which nucleosome-depleted regions of DNA (NDRs) are isolated from chromatin.
  • a typical FAIRE-seq assay can include a first step in which cells are fixed using formaldehyde so that histones are crosslinked to interacting DNA. Crosslinked chromatin can then be sheared by sonication that generates protein-free DNA and protein- crosslinked DNA fragments. Protein-free DNA can be isolated using a phenol-chloroform extraction: DNA crosslinked with protein stays in organic phase, while protein-free DNA stays in aqueous phase. Highly crosslinked DNA remains in the organic phase and the non-crosslinked DNA is pulled to the aqueous phase.
  • Non-crosslinked DNA from the aqueous phase can then be amplified and sequenced. Reads enriched in the sequencing pool tend to have lower nucleosome and transcription factor binding and are therefore inferred to come from accessible regions.
  • NOMe-seq is a method to identify nucleosome-depleted regions of DNA (NDRs) with M.CviPI methyltransferase that methylates cytosine in GpC dinucleotides not protected by nucleosomes or other proteins.
  • NDRs nucleosome-depleted regions of DNA
  • M.CviPI methyltransferase M.CviPI methyltransferase that methylates cytosine in GpC dinucleotides not protected by nucleosomes or other proteins.
  • GpC m in the human genome does not occur naturally in most cell types. GpC in levels at open chromatin regions can be compared to background signals and used to detect and quantify NDRs.
  • a typical NOMe-seq protocol can include a step in which samples are treated with M.CviPI and S-adenosylhomocysteine (SAM) to methylate accessible GpC sites.
  • M.CviPI treated DNA can be sheared using a sonicator, so that DNA fragments can be sequenced.
  • DNA is treated with bisulfite, which converts unmethylated cytosine to uracil using sodium bisulfite, while methylated cytosine is unaffected.
  • a library is generated using adapters and sequenced. Accessible chromatin is expected to have high levels of GpC m but low levels of C m pG. Therefore, NOMe-seq identifies NDRs using the two separate methylation analyses that serve as independent (but opposite) measures, providing matched chromatin designations for each regulatory element.
  • RRBS Reduced representation bisulfite sequencing
  • DNA methylation typically refers to the methylation of the 5’ position of cytosine (mC) by DNA methyltransferases (DNMT). It is a major epigenetic modification in humans and many other species. In mammals, most DNA methylations occur within the context of CpG dinucleotides. DNA methylation is thought to be a repressive chromatin modification. Aberrant methylation can lead to many diseases including cancers (Robertson, Nat Rev Genet (2005) 6:597-610 and Bergman and Cedar, Nat Struct Mol Biol (2013) 20:274-281).
  • MeDIP-seq was first reported by Weber et al., Nat Genet (2005) 37:853-862.
  • antibody or antibody-fragment that binds 5-methylcytidine (5mC) is used to enrich methylated DNA fragments, then these fragments are sequenced and analyzed. If using 5mC-specific antibodies or antibody fragments, methylated DNA is isolated from genomic DNA via immunoprecipitation. Anti-5mC antibodies are incubated with fragmented genomic DNA and precipitated, followed by DNA purification and sequencing.
  • Methyl-CpG-Binding Domain sequencing is similar to MeDIP-seq except that it uses methyl binding domain (MBD) proteins instead of antibodies or antibody fragments to bind methylated DNA.
  • MBD methyl binding domain
  • genomic DNA is first sonicated and incubated with tagged MBD proteins that can bind methylated cytosines.
  • the protein-DNA complex is then precipitated with antibody -conjugated beads that are specific to the MBD protein tag, followed by DNA purification and sequencing.
  • a subject is determined to have an epigenetic profile indicative of a cancer associated with elevated serum PSA levels based on analysis of a biological sample, optionally of cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject.
  • cfDNA cell-free DNA
  • a cancer is determined to be PSMA-positive if PSMA expression is detected that is above a threshold value.
  • the threshold value is a predetermined threshold and/or a normalized value.
  • the threshold value is a PSMA expression level determined in a reference population.
  • the reference population comprises subjects having prostate cancer and previously found to respond to treatment with a PSMA-targeted therapeutic.
  • the reference population comprises subjects having cancer and previously found to not respond to treatment with a PSMA-targeted therapy.
  • the reference population comprises subjects having a PSMA-positive cancer (e.g., as determined by PSMA PET imaging).
  • the reference population comprises subjects having a low PMSA expressing cancer (e.g., as determined by PSMA PET imaging) or subjects with a cancer having a level of PSMA expression that is associated with poor response to a PSMA-targeted therapeutic. In some embodiments, the reference population comprises subjects determined to be cancer free.
  • PSA expression is determined or predicted to be elevated if the determined or predicted value is above a threshold value.
  • the threshold value is a predetermined threshold and/or a normalized value.
  • the threshold value is a PSA expression level determined in a reference population.
  • the reference population comprises subjects having prostate cancer.
  • the reference population comprises subjects that have not been diagnosed with cancer.
  • the present disclosure is not limited to methods that use the exact same chromosomal coordinates that are recited in Tables 1-5.
  • the present disclosure encompasses methods that use any of the genomic loci in Tables 1-5 and also subregions thereof, i.e., references herein to methods that involve detecting and/or quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci of Tables 1-5 encompasses methods that detect these marks anywhere within these genomic loci including within any subregions.
  • a classifier is generated using a set of differentially modified and/or differentially accessible genomic loci that are correlated with increased PSA or PSMA expression (e.g., increased PSMA PET SUVmean or increased PSA concentrations). Sequence reads that fall into each selected genomic locus are analyzed and counted, e.g., as described herein including the Examples. In some embodiments, counts from genomic loci that are correlated with increased PSMA or PSA expression (e.g., increased PSMA PET SUVmean or increased serum PSA) are aggregated.
  • exemplary genomic loci from one or more of Tables 1-5 are used in a monomodal PSMA PET Score Model Predictor, e.g., a PSMA PET Score Model Predictor that uses a single histone modification (e.g., H3K4me3 or H3K27ac) or DNA methylation at one or more genomic loci for purposes of determining PSMA expression level.
  • a monomodal PSMA PET Score Model Predictor e.g., a PSMA PET Score Model Predictor that uses a single histone modification (e.g., H3K4me3 or H3K27ac) or DNA methylation at one or more genomic loci for purposes of determining PSMA expression level.
  • exemplary genomic loci from any one of Table 1-5, or any combination thereof are used in combination in a multimodal classifier, e.g., a PSMA PET Score Model Predictor that uses more than one histone modification (e.g., H3K4me3 and H3K27ac) or one or more histone modifications (e.g., H3K4me3 and/or H3K27ac) and DNA methylation at one or more genomic loci for purposes of measuring PSMA expression.
  • a multimodal classifier e.g., a PSMA PET Score Model Predictor that uses more than one histone modification (e.g., H3K4me3 and H3K27ac) or one or more histone modifications (e.g., H3K4me3 and/or H3K27ac) and DNA methylation at one or more genomic loci for purposes of measuring PSMA expression.
  • a method described herein comprises quantifying one or more of a histone modification, DNA methylation, chromatic accessibility and/or binding of a transcription factor at one or more loci provided in one or more of Tables 1-5. In some embodiments, a method described herein comprises quantifying one or more of a histone modification, DNA methylation, chromatic accessibility and/or binding of a transcription factor at 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, or 30 loci listed in one or more of Tables 1-5.
  • a method described herein comprises quantifying one or more of a histone modification, DNA methylation, chromatic accessibility and/or binding of a transcription factor at each of the loci provided in Table 1, Table 2, Table 3, Table 4, and/or Table 5. In some embodiments, a method described herein comprises quantifying one or more of a histone modification, DNA methylation, chromatic accessibility and/or binding of a transcription factor for at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of loci identified in Tables 1-5, or any combination thereof.
  • a method described herein comprises quantifying one or more of a histone modification, DNA methylation, chromatic accessibility and/or binding of a transcription factor for at least a percent of loci identified in Table 1, Table 2, Table 3, Table 4, and/or Table 5 having a lower bound selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10%, and an upper bound selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100%.
  • Exemplary genomic loci whose H3K4 methylation state (in particular H3K4 trimethylation, H3K4me3) is associated with PSMA expression level are provided in Tables 1, 2, 4 and 5 (see H3K4me3 analyte loci).
  • Exemplary genomic loci whose H3K4 methylation state (in particular H3K4 trimethylation, H3K4me3) is associated with PSA expression level are provided in Tables 3.
  • Subsets of the H3K4me3 analyte genomic loci of Tables 1-5 can be selected (e.g., for use in determining PSMA expression level or PSA expression level) based on various performance criteria, e.g., to select genomic loci that demonstrate differential modification with a particular level of statistical significance and/or a particular threshold of differential between relevant states (e.g., a measured log2(fold-change)). Subsets of the genomic loci may also be selected based on an algorithm, e.g., during the process of obtaining a classifier.
  • a sample or subject from which the sample is obtained or derived is determined to have a particular PSMA expression level if one or both H3K4me3 analyte loci identified in Table 4 are differentially H3K4me3 modified as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
  • a reference e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
  • a sample or subject from which the sample is obtained or derived is determined to have a particular PSMA expression level if the H3K4me3 analyte loci identified in Table 5 is differentially H3K4me3 modified as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUV mean signal)).
  • a reference e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUV mean signal).
  • a sample or subject from which the sample is derived is determined to have a particular PSMA expression level if one or more promoter regions of one or more H3K4me3 analyte genes (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10) in Table 1 are differentially H3K4me3 modified as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
  • a reference e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
  • a promoter region refers to a region a certain number of nucleotides upstream of a gene (e.g., 10,000, 9,000, 8,000, 7,000, 6,000, 5,000, 4,000, 3,000, 2,000, or 1,000 nucleotides upstream of a gene). In some embodiments, a promoter region refers to a region identified in any one of Tables 1-5.
  • a sample or subject from which the sample is obtained or derived is determined to have a particular PSMA expression level if H3K4me3 modifications for 1, 2, 3, 4, 5, 6, or 7 of the H3K4me3 analyte loci that are identified in Table 1 as having a positive association with PSMA expression are increased relative to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
  • a reference e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
  • differentially H3K4me3 modified refers to a methylation status characterized by an increase or decrease in a value measuring methylation (e.g., of read counts and/or normalized read counts for a given genomic locus), and/or a mean, median and/or mode thereof, and/or a log thereof e.g., log base 2 (log2)), of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4- fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40- fold, 45-fold, 50-fold, or greater, or any range in between, inclusive, such as 1% to 50%, 50% to 2-fold, 25% to 50-fold, 25% to 30-fold, 25% to 20-fold
  • an increase or decrease in a value measuring methylation can be, or is expressed as, a log2(fold-change), e.g., a log2(fold-change) of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, or greater, or any range in between, inclusive, such as an increase or decrease of 0.1 -fold to 10- fold, 0.2-fold to 5-fold, 0.2-fold to 4.0-fold, 0.4-4.0-fold, 0.4-fold to 4.0-fold, 0.6-fold to 4.0- fold, 0.8-fold to 4.0-fold, 1.0-fold to 4.0-fold.
  • a log2(fold-change) e.g., a log2(fold-change
  • H3K27ac analyte genomic locus listed in Tables 1-5 be assessed for H3K27ac modifications. Instead, a subset of H3K27ac analyte loci may be assessed for H3K27ac modification. Subsets of the H3K27ac analyte genomic loci of Tables 1-5 can be selected (e.g., for use in determining PSMA expression level) based on various performance criteria, e.g., to select genomic loci that demonstrate differential modification with a particular level of statistical significance and/or a particular threshold of differential between relevant states (e.g., a measured log2(fold-change)).
  • Subsets of the genomic loci may also be selected based on an algorithm, e.g., during the process of obtaining a classifier.
  • an algorithm e.g., during the process of obtaining a classifier.
  • loci of Tables 1-5, and loci included in such subsets are together, individually, and/or in randomly selected subsets, at least as informative (e.g., as statistically significant and/or reliable) for uses disclosed herein, e.g., for determining PSMA expression level.
  • a sample or subject from which the sample is obtained or derived is determined to have a particular PSMA expression level if 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more H3K27ac analyte loci identified in Table 4 are differentially H3K27ac modified as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
  • a reference e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
  • a sample or subject from which the sample is obtained or derived is determined to have a particular PSMA expression level if the H3K27ac analyte locus identified in Table 5 is differentially H3K27ac modified as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
  • a reference e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
  • a sample or subject from which the sample is derived is determined to have a particular PSMA expression level if one or more enhancer regions of one or more H3K27ac analyte genes (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10) in Table 1 are differentially H3K27ac modified as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
  • a reference e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
  • differentially H3K27ac modified refers to an acetylation status characterized by an increase or decrease in a value measuring acetylation (e.g., of read counts and/or normalized read counts for a given genomic locus), and/or a mean, median and/or mode thereof, and/or a log thereof (e.g., log base 2 (log2)), of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4- fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40- fold, 45-fold, 50-fold, or greater, or any range in between, inclusive, such as 1% to 50%, 50% to 2-fold, 25% to 50-fold, 25% to 30-fold, 25% to
  • an increase or decrease in a value measuring acetylation can be, or is expressed as, a log2(fold-change), e.g., a log2(fold-change) of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, or greater, or any range in between, inclusive, such as an increase or decrease of 0.1-fold to 10- fold, 0.2-fold to 5-fold, 0.2-fold to 4.0-fold, 0.4-4.0-fold, 0.4-fold to 4.0-fold, 0.6-fold to 4.0- fold, 0.8-fold to 4.0-fold, 1.0-fold to 4.0-fold.
  • a log2(fold-change) e.g., a log2(fold-
  • one or more enhancer regions of a recited gene are provided in Tables 1 and 2.
  • one or more enhancer regions of a recited gene corresponds to: (i) one or more loci with increased or decreased H3K27ac modifications as compared to a reference (e.g., a sample from a healthy subject) within a certain number of nucleotides (e.g., 50,000 nucleotides) of the recited gene; and/or (ii) one or more loci with increased or decreased H3K27ac modifications as compared to a reference (e.g., a sample from a healthy subject) that are closest to the recited gene in the genome.
  • a reference e.g., a sample from a healthy subject
  • Exemplary genomic loci whose DNA methylated state is associated with PSMA expression level are provided in Table 1 (see MBD analyte loci).
  • a person of skill in the art will recognize that the methods disclosed herein do not require that every MBD analyte genomic locus listed in Table 1 be assessed for DNA methylation. Instead, a subset of MBD loci may be assessed for DNA methylation. Subsets of the MBD genomic loci of Table 1 can be selected (e.g., for use in determining PSMA expression level) based on various performance criteria, e.g., to select genomic loci that demonstrate differential modification with a particular level of statistical significance and/or a particular threshold of differential between relevant states (e.g., a measured log2(fold-change)). Subsets of the genomic loci may also be selected based on an algorithm, e.g., during the process of obtaining a classifier.
  • subsets of loci of Table 1 are together, individually, and/or in randomly selected subsets, at least as informative (e.g., as statistically significant and/or reliable) for uses disclosed herein, e.g., for determining PSMA expression level.
  • a sample or subject from which the sample is derived is determined to have a particular PSMA expression level if one or more MBD analyte loci (e g., 1,
  • a sample or subject from which the sample is obtained or derived is determined to have a particular PSMA expression level if DNA methylation for 1, 2,
  • 3, 4, 5, 6, 7, or 8 of the MBD analyte loci that are identified in Table 1 as having a positive association with PSMA expression are increased relative to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
  • a reference e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
  • Genomic loci provided in Tables 1-2 can also demonstrate differential chromatin accessibility or transcription factor binding in different PSMA expression states.
  • histone methylation corresponds and/or is correlated with chromatin accessibility.
  • histone acetylation corresponds and/or is correlated with chromatin accessibility.
  • DNA methylation corresponds and/or is correlated with chromatin accessibility.
  • chromatin accessibility corresponds and/or is correlated with H3K4me3 modifications.
  • PSMA expression level may be determined by detecting and quantifying chromatin accessibility at one or more genomic loci in Tables 1 and 2 in accordance with the section above discussing exemplary genomic loci with differential H3K4me3 modifications.
  • chromatin accessibility corresponds and/or is correlated with H3K27ac modifications.
  • PSMA expression level may be determined by detecting and quantifying chromatin accessibility at one or more genomic loci in Tables 1 and 2 in accordance with the section above discussing exemplary genomic loci with differential H3K27ac modifications.
  • chromatin accessibility corresponds and/or is correlated with DNA methylation.
  • PSMA expression can be measured by detecting and quantifying chromatin accessibility at one or more genomic loci in Tables 1 and 2 in accordance with the section above discussing exemplary genomic loci with differential DNA methylation.
  • histone methylation corresponds and/or is correlated with transcription factor binding.
  • histone acetylation corresponds and/or is correlated with transcription factor binding.
  • DNA methylation corresponds and/or is correlated with transcription factor binding.
  • Methods, kits and systems of the present disclosure include analysis of differentially modified and/or differentially accessible genomic loci to measure disease-specific PSMA expression. Methods, kits and systems of the present disclosure can be used in any of a variety of applications. For example, methods, kits and systems of the present disclosure can be used in detecting and/or treating a disease or indication that can be associated with increased disease-specific PSMA expression (e.g., mCRPC). Methods, kits and systems of the present disclosure can also be used to detect or determine resistance of a disease or condition to a certain therapeutic (e.g., a PSMA-targeted therapeutic).
  • a disease or indication e.g., mCRPC
  • Methods, kits and systems of the present disclosure can also be used to detect or determine resistance of a disease or condition to a certain therapeutic (e.g., a PSMA-targeted therapeutic).
  • methods, kits and systems of the present disclosure can be applied to an asymptomatic human subject.
  • a subject can be referred to as “asymptomatic” if the subject does not report, and/or demonstrate by non-invasively observable indicia (e.g., without one, several, or all of device-based probing, tissue sample analysis, bodily fluid analysis, surgery, or autoimmune screening), sufficient characteristics of a disease or condition that can be associated with increased PSMA expression to support a medically reasonable suspicion that the subject is likely suffering from a disease or condition that can be associated with increased PSMA expression. Detection of early-stage diseases or conditions that can be associated with increased PSMA expression can be achieved using methods, kits and systems of the present disclosure, with attendant medical benefits including potential for early treatment and attendant improvement in therapeutic outcomes.
  • a subject can be referred to as “symptomatic” if the subject report, and/or demonstrates by non-invasively observable indicia (e.g., without one, several, or all of device-based probing, tissue sample analysis, bodily fluid analysis, surgery, or prostate cancer screening), sufficient characteristics of a disease or condition that can be associated with increased PSMA expression (including, e.g., prostate cancer (e.g., CRPC)) to support a medically reasonable suspicion that the subject is likely suffering from a disease or condition that can be associated with increased PSMA expression.
  • non-invasively observable indicia e.g., without one, several, or all of device-based probing, tissue sample analysis, bodily fluid analysis, surgery, or prostate cancer screening
  • sufficient characteristics of a disease or condition that can be associated with increased PSMA expression including, e.g., prostate cancer (e.g., CRPC)
  • methods, kits and systems of the present disclosure can be applied to a human subject previously determined to have a disease or condition that can be associated with increased PSMA expression.
  • methods, kits and systems of the present disclosure can be applied to a human subject previously determined to have prostate cancer (e.g., mCRPC)).
  • methods, kits and systems of the present disclosure can be used to determine that a subject has a PSMA expression level that correlates with a prior determination of PSMA expression level (e.g., based on imaging and/or one or more biomarkers). In some embodiments, methods, kits and systems of the present disclosure can be used to validate or confirm a prior determination that a subject has a certain PSMA expression level.
  • PSMA expression level improves diagnosis, prognosis, and treatment of a disease or indication that can be associated with increased PSMA expression, including and/or particularly an early stage disease or indication that can be associated with increased PSMA expression (e.g., mCRPC).
  • a disease or indication that can be associated with increased PSMA expression
  • an early stage disease or indication that can be associated with increased PSMA expression
  • the present disclosure provides, among other things, methods, kits and systems particularly useful for the diagnosis and treatment of early- stage diseases that can be associated with increased PSMA expression (e.g., mCRPC).
  • PSMA expression level determination in accordance with the present disclosure is performed once for a given subject or multiple times for a given subject.
  • PSMA expression level determination in accordance with the present disclosure is performed on a regular basis, e.g., every six months, annually, every two years, every three years, every four years, every five years, or every ten years.
  • methods, kits and systems disclosed herein provide a determination of PSMA expression level. In other instances, methods, kits and systems disclosed herein will be indicative of PSMA expression level but not definitive for PSMA expression level. In various instances in which methods, kits and systems of the present disclosure are used to determine PSMA expression level, the same can be followed by a further confirmatory assay, which further assay can confirm, support, undermine, or reject a determination resulting from a prior determination, e.g., a determination in accordance with the present disclosure. As used herein, a confirmatory assay can be a test that is currently recognized by medical practitioners, e.g., based on imaging or other testing.
  • PSMA expression level determination is followed by treatment with a PSMA- targeted therapeutic (e.g., 177Lu-PSMA-617).
  • a PSMA- targeted therapeutic e.g., 177Lu-PSMA-617.
  • treatment with a PSMA- targeted therapeutic includes administration of one or more therapies provided herein, including without limitation a radioligand conjugate and/or an ADC.
  • treatment of a disease or indication associated with increased PSMA expression includes administration of a therapeutic regimen including one or more treatments provided herein as available, appropriate, and/or preferred for a particular PSMA expression level.
  • methods, kits and systems can be used to determine whether a particular subject is likely to be and/or is characterized as responsive to a PSMA- targeted agent. In some such embodiments, methods, kits and systems can be followed by treatment of the subject with a PSMA-targeted agent.
  • methods, kits and systems can be used to determine whether a particular subject is likely to be and/or is characterized as resistant to, non-responsive to, or not recommended treatment with a PSMA-targeted agent. In some such embodiments, methods, kits and systems can be followed by treatment with a therapeutic agent to a different target.
  • Responsiveness can refer to the ability or likelihood of a therapy to cause a reduction in the number and/or size of tumor lesions, an increase in the time to next treatment, slowing of disease progression (e.g., as measured by plasma PSA levels for prostate cancer, and/or clinical or radiological evidence of progression), reduced disease activity, and/or increased survival.
  • Responsiveness can refer to improvement in prognosis.
  • Responsiveness can refer to achievement of a treatment benefit, including e.g., improvement in one or more symptoms of a disease or indication associated with increased PSMA expression.
  • Responsiveness can be measured quantitatively (e.g., as in the case of tumor size and/or number, PSA concentration, histone modification, chromatin accessibility, transcription factor binding, or DNA methylation at one or more genomic loci; or as in the calculation of clinical benefit (CBR)), or qualitatively (e.g., by measures such as “pathological complete response” (pCR), “clinical stable disease” (cSD), “clinical progressive disease” (cPD), or other qualitative criteria).
  • CBR clinical benefit
  • Methods of the present disclosure can also be programmed or modeled in mathematical software packages that allow symbolic entry of equations and high-level specification of processing, including specific algorithms to be used, thereby freeing a user of the need to procedurally program individual equations and algorithms.
  • Such packages include, e.g., Matlab from Mathworks (Natick, MA), Mathematica from Wolfram Research (Champaign, IL), S-Plus from MathSoft (Seattle, WA), R from R Foundation for Statistical Computing (Vienna, Austria), Python from Python Software Foundation (Wilmington, DE), or Perl from Perl Foundation (Holland, MI).
  • a computer system comprises a database for storage of genomic locus modification status and/or accessibility status data.
  • a single learning statistical classifier system such as a classification tree (e. ., random forest) is used. In other embodiments, a combination of 2, 3, 4, 5, 6, 7, 8, 9, 10, or more learning statistical classifier systems are used, preferably in tandem.
  • Examples of learning statistical classifier systems include, but are not limited to, those described in the Examples and also those using inductive learning (e.g., decision/classification trees such as random forests, classification and regression trees (C&RT), boosted trees, etc.), Probably Approximately Correct (PAC) learning, connectionist learning (e.g, neural networks (NN), artificial neural networks (ANN), neuro fuzzy networks (NFN), network structures, perceptrons such as multi-layer perceptrons, multilayer feed-forward networks, applications of neural networks, Bayesian learning in belief networks, etc.), reinforcement learning (e.g, passive learning in a known environment such as naive learning, adaptive dynamic learning, and temporal difference learning, passive learning in an unknown environment, active learning in an unknown environment, learning action-value functions, applications of reinforcement learning, etc ), and genetic algorithms and evolutionary programming.
  • inductive learning e.g., decision/classification trees such as random forests, classification and regression trees (C&RT), boosted trees, etc.
  • PAC Probably Approximately Correct
  • connectionist learning e.g
  • methods of the present disclosure can include sending classification results to a medical practitioner, e.g., an oncologist.
  • a medical practitioner e.g., an oncologist.
  • the present disclosure includes methods where a therapeutic agent or regimen is administered to a subject based on PSMA expression level (e.g., disease specific PSMA expression level).
  • PSMA expression level e.g., disease specific PSMA expression level
  • the therapeutic agent or regimen provided herein will be available, appropriate, and/or preferred for a certain PSMA expression level.
  • those of skill in the art will be aware of recommended and/or governmentally approved formulations and/or dosages for various therapeutic agents provided herein.
  • compositions for delivery of one or more therapeutic agents to a subject include pharmaceutical compositions for delivery of one or more therapeutic agents to a subject.
  • a pharmaceutical composition may be in any form known in the art, including formulations for administration according to any route known in the art.
  • a suitable means of administration can be selected based on the age and condition of a subject.
  • composition forms of the present disclosure can include, e.g., liquid, semi-solid and solid dosage forms.
  • Pharmaceutical composition forms of the present disclosure can include, e.g., liquid solutions (e.g., injectable and infusible solutions), dispersions or suspensions, tablets, pills, powders, and liposomes. Selection or use of any particular form may depend, in part, on the intended mode of administration and therapeutic application.
  • compositions can be formulated for administration by a parenteral mode (e.g., intravenous, subcutaneous, intraperitoneal, or intramuscular injection) or a non-parenteral mode.
  • parenteral administration refers to modes of administration other than enteral and topical administration, usually by injection or infusion.
  • a pharmaceutical composition of the present disclosure can be in an injectable or infusible form.
  • the present disclosure includes sterile formulations for injection or infusion, which can be formulated in accordance with conventional pharmaceutical practices.
  • sterile powders for the preparation of sterile injectable solutions methods for preparation include vacuum drying and freeze-drying that yield a powder of a composition described herein plus any additional desired ingredient (see below) from a previously sterile-fdtered solution thereof.
  • the proper fluidity of a solution can be maintained, for example, by the use of a coating such as lecithin, by the maintenance of the required particle size in the case of dispersion and by the use of surfactants.
  • Prolonged absorption of injectable compositions can be brought about by including in the composition a reagent that delays absorption, for example, monostearate salts, and gelatin.
  • Route of administration can be parenteral, for example, administration by injection.
  • Administration by injection can be by intravenous injection, intramuscular injection, intraperitoneal injection, subcutaneous injection.
  • Administration can be systemic or local.
  • a composition described herein can be therapeutically delivered to a subject by way of local administration.
  • local administration or “local delivery,” can refer to delivery that does not rely upon transport of the composition or therapeutic agent to its intended target tissue or site via the vascular system.
  • the composition may be delivered by injection or implantation of the composition or therapeutic agent or by injection or implantation of a device containing the composition or therapeutic agent.
  • the composition or therapeutic agent, or one or more components thereof may diffuse to an intended target tissue or site that is not the site of administration.
  • a pharmaceutical composition can be administered parenterally in the form of an injectable formulation comprising a sterile solution or suspension in water or another pharmaceutically acceptable liquid.
  • a pharmaceutical composition can be formulated by suitably combining the therapeutic molecule with pharmaceutically acceptable vehicles or media, such as sterile water and physiological saline, vegetable oil, emulsifier, suspension agent, surfactant, stabilizer, flavoring excipient, diluent, vehicle, preservative, binder, followed by mixing in a unit dose form required for generally accepted pharmaceutical practices.
  • pharmaceutically acceptable vehicles or media such as sterile water and physiological saline, vegetable oil, emulsifier, suspension agent, surfactant, stabilizer, flavoring excipient, diluent, vehicle, preservative, binder, followed by mixing in a unit dose form required for generally accepted pharmaceutical practices.
  • examples of oily liquid include sesame oil and soybean oil, and it may be combined with benzyl benzoate or benzyl alcohol as a solubilizing agent.
  • administration of a therapeutic agent as described herein is achieved by administering to a subject a nucleic acid encoding a therapeutic agent described herein.
  • Nucleic acids encoding a therapeutic agent described herein can be incorporated into a gene construct to be used as a part of a gene therapy protocol to deliver nucleic acids that can be used to express and produce therapeutic agent within cells.
  • Expression constructs of such components may be administered in any therapeutically effective carrier, e.g., any formulation or composition capable of effectively delivering the component gene to cells in vivo.
  • a pharmaceutical composition can include a therapeutically effective amount of a therapeutic agent described herein. Such effective amounts can be readily determined by one of ordinary skill in the art. A therapeutically effective amount can be an amount at which any toxic or detrimental effects of the composition are outweighed by therapeutically beneficial effects. In some embodiments, a dose can also be chosen to reduce or avoid production of antibodies or other host immune responses against a therapeutic agent. Those of skill in the art will appreciate that data obtained from cell culture assays and animal studies can be used in formulating a range of dosage for use in humans. In various embodiments, the amount of active ingredient included in a pharmaceutical composition is such that a suitable dose within the designated range can be administered to subjects. The dose and method of administration can vary depending on weight, age, condition, and other characteristics of a patient, and can be suitably selected as needed by those skilled in the art.
  • compositions including certain therapeutic agents can be administered as a fixed dose, or in a milligram per kilogram (mg/kg) dose.
  • an exemplary single dose of certain pharmaceutical compositions described herein can include certain therapeutic agents as described herein in an amount equal to, e.g., 0.001 to 1000 mg/kg, 1-1000 mg/kg, 1-100 mg/kg, 0.5-50 mg/kg, 0.1-100 mg/kg, 0.5-25 mg/kg, 1-20 mg/kg, and 1-10 mg/kg body weight.
  • Exemplary dosages of a composition described herein include, without limitation, 0.1 mg/kg, 0.5 mg/kg, 1 mg/kg, 2 mg/kg, 4 mg/kg, 8 mg/kg, or 20 mg/kg. The present disclosure is not limited to such ranges or dosages.
  • the present disclosure further includes methods of preparing pharmaceutical compositions of the present disclosure and kits including pharmaceutical compositions of the present disclosure.
  • therapeutic agents of the present disclosure can be administered to a subject in a course of treatment that further includes administration of one or more additional therapeutic agents or therapies that are not therapeutic agents (e.g., surgery or radiation).
  • Combination therapies of the present disclosure can include simultaneous exposure of a subject to therapeutic agents of two or more therapeutic regimens.
  • an additional therapeutic agent or therapy administered in combination with a therapeutic agent as described herein can be administered such that administration of the therapeutic agent and the additional therapeutic agent or therapy are separated by one or more hours before or after, one or more days before or after, one or more weeks before or after, or one or more months before or after administration of the therapeutic agent.
  • the administration frequency and/or dosage of one or more additional therapeutic agents can be the same as, similar to, or different from the administration frequency of a therapeutic agent.
  • administration of a therapeutic agent can be to a subject having previously received, scheduled to receive, or in the course of a treatment regimen including an additional cancer therapy (e.g., prostate cancer therapy).
  • Administration of a therapeutic agent can, in some instances, improve delivery or efficacy of another therapeutic agent or therapy with which it is administered in combination.
  • therapeutic agent combination therapies can demonstrate synergy and/or greater-than-additive effects between a therapeutic agent and one or more additional therapeutic agents with which it is administered in combination.
  • a therapeutic agent can be administered in any effective amount as determined independently or as determined by the joint action of therapeutic agent and any of one or more additional therapeutic agents or therapies administered.
  • Administration of the therapeutic agent may, in some embodiments, reduce the therapeutically effective dosage, required dosage, or administered dosage of the additional therapeutic agent or therapy relative to a reference regimen for administration of additional therapeutic agent or therapy or therapy absent the therapeutic agent.
  • a composition described herein can replace or augment other previously or currently administered therapy. For example, upon treating with therapeutic agent, administration of one or more additional therapeutic agents or therapies can cease or diminish, e.g., be administered at lower levels.
  • kits for detecting modification and/or accessibility of one or more genomic loci include kits for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci.
  • Kits of the present disclosure can include, e g., reagents such as buffers and/or antibodies useful in the detection and quantification of histone modifications.
  • a kit of the present disclosure can include at least one antibody that selective binds a histone modification selected from H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, or H3K4me3, or pan acetylation.
  • a kit of the present disclosure can include at least one antibody that selective binds H3K4me3 modifications.
  • a kit of the present disclosure can include at least one antibody that selective binds H3K27ac modifications.
  • a kit of the present disclosure can include instructional materials disclosing or describing the use of the kit in a method of measuring PSMA expression and/or treatment disclosed herein.
  • the kit comprises reagents for measuring chromatin accessibility via an ATAC-seq assay.
  • the system comprises reagents for quantifying H3K4me3 modifications for 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or 11 of the H3K4me3 analyte genomic loci in Table 1 and 2.
  • the system comprises reagents for quantifying H3K27ac modifications for 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 H3K27ac analyte loci in Tables 1 and 2.
  • the system comprises reagents for quantifying H3K27ac modifications for 1, 2, 3, 4, 5, 6, 7, or 8 H3K27ac genomic loci in Table 2 and/or H3K4me3 modifications for the H3K4me3 genomic loci in Table 2.
  • the system comprises one or more antibodies for use in ChlP-seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac-modified histones.
  • the system comprises reagents for quantifying H3K4me3 modifications for 1, 2, 3, or 4 of the H3K4me3 analyte genomic loci in Table 3.
  • the system comprises reagents for quantifying H3K4me3 modifications for one or both of the H3K4me3 analyte genomic loci in Table 4.
  • the system comprises reagents for quantifying H3K4me3 modifications for the H3K4me3 analyte genomic locus in Table 4.
  • the system comprises reagents for quantifying H3K27ac modifications for 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, or 23 of the H3K27ac analyte genomic loci in Table 4. In some embodiments, the system comprises reagents for quantifying H3K27ac modifications for the H3K27ac analyte genomic locus in Table 4.
  • the system comprises reagents for quantifying DNA methylation for 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 of the MBD analyte genomic loci in Table 1.
  • the system comprises one or more methyl-binding domains (e.g., for use in MBD-seq).
  • the system comprises one or more antibodies that can bind methylated DNA (e.g., for use in MeDIP).
  • the system comprises reagents for isolation of cell-free DNA (cfDNA) from a liquid biopsy sample.
  • the sequencer comprises reagents for library preparation for sequencing.
  • the sequencer comprises reagents for sequencing.
  • the system comprises instructions for determining PSMA expression level.
  • the system comprises reagents for measuring chromatin accessibility via an ATAC-seq assay.
  • Accessibility Status or “Chromatin Accessibility Status”: As used herein, “accessibility status” or “chromatin accessibility status” of a genomic locus refers to the frequency with which DNA sequences corresponding to the genomic locus are identified in an assay for detection of accessible chromatin. Accessibility status can be determined by various assays known in the art, including without limitation ChlP-seq as one example. Where two samples are separately analyzed by the same assay or comparable assays for detection of accessible DNA sequences, differences in chromatin accessibility status of genomic loci can be detected. Accessibility status can be compared to a standard or reference. A sample that has an accessibility status that differs in accessibility status from a standard or reference can be referred to as differentially modified.
  • Suitable assays for determining chromatin accessibility are known in the art.
  • Exemplary assays include ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde-Assisted Isolation of Regulatory Elements sequencing), Mnase-seq (Micrococcal Nuclease digestion with sequencing), Dnase hypersensitivity assay, and/or a fragmentomics assay.
  • ATAC-seq Assay of Transpose Accessible Chromatin sequencing
  • NOMe-seq Nucleosome Occupancy and Methylome sequencing
  • FAIRE-seq Formmaldehyde-Assisted Isolation of Regulatory Elements sequencing
  • Mnase-seq Merococcal Nuclease digestion with sequencing
  • Dnase hypersensitivity assay and/or a fragmentomics assay
  • the term “administration” typically refers to the administration of a disease appropriate (e.g., prostate cancer appropriate) treatment.
  • the disease appropriate treatment may comprise administering a composition to a subject, for example to achieve delivery of an agent that is, is included in, or is otherwise delivered by, the composition.
  • the disease appropriate treatment may comprise administering an appropriate surgical procedure or radiological procedure, optionally in combination with administration of a composition.
  • agent may refer to any chemical or physical entity, including without limitation any of one or more of an atom, e.g., a radioactive atom, molecule, compound, conjugate, polypeptide, polynucleotide, polysaccharide, lipid, cell, or combination or complex thereof.
  • an atom e.g., a radioactive atom, molecule, compound, conjugate, polypeptide, polynucleotide, polysaccharide, lipid, cell, or combination or complex thereof.
  • each heavy chain includes a heavy chain variable domain (VH) and a heavy chain constant domain (CH).
  • VH heavy chain variable domain
  • CH heavy chain constant domain
  • the heavy chain constant domain includes three CH domains: CHI, CH2 and CH3.
  • the “hinge” connects CH2 and CH3 domains to the rest of the immunoglobulin.
  • Each light chain includes a light chain variable domain (VL) and a light chain constant domain (CL), separated from one another by another “switch.”
  • Each variable domain contains three hypervariable loops known as “complement determining regions” (CDR1, CDR2, and CDR3) and four somewhat invariant “framework” regions (FR1, FR2, FR3, and FR4).
  • CDR1, CDR2, and CDR3 Complement determining regions
  • FR1, FR2, FR3, and FR4 four somewhat invariant “framework” regions
  • the three CDRs and four FRs are arranged from amino-terminus to carboxy -terminus in the following order: FR1, CDR1, FR2, CDR2, FR3, CDR3, and FR4.
  • the variable regions of a heavy and/or a light chain are typically understood to provide a binding moiety that can interact with an antigen.
  • an antibody is a polyclonal, monoclonal, monospecific, or multispecific antibody (e.g., a bispecific antibody).
  • an antibody includes at least one light chain monomer or dimer, at least one heavy chain monomer or dimer, at least one heavy chain-light chain dimer, or a tetramer that includes two heavy chain monomers and two light chain monomers.
  • antibody can include (unless otherwise stated or clear from context) any art-known constructs or formats utilizing antibody structural and/or functional features including without limitation intrabodies, domain antibodies, antibody mimetics, Zybodies®, Fab fragments, Fab’ fragments, F(ab’)2 fragments, Fd’ fragments, Fd fragments, isolated CDRs or sets thereof, single chain antibodies, single-chain Fvs (scFvs), disulfide-linked Fvs (sdFv), polypeptide-Fc fusions, single domain antibodies (e.g., shark single domain antibodies such as IgNAR or fragments thereof), cameloid antibodies, camelized antibodies, masked antibodies (e.g., Probodies®), affybodies, anti -idiotypic (anti-Id) antibodies (including, e.g., anti-anti-Id antibodies), Small Modular ImmunoPharmaceuticals (SMIPs), single chain or Tandem diabodies (TandAb®), VHH
  • an antibody includes one or more structural elements recognized by those skilled in the art as a complementarity determining region (CDR) or variable domain.
  • an antibody can be a covalently modified (“conjugated”) antibody (e.g., an antibody that includes a polypeptide including one or more canonical immunoglobulin sequence elements sufficient to confer specific binding to a particular antigen, where the polypeptide is covalently linked with one or more of a therapeutic agent, a detectable moiety, another polypeptide, a glycan, or a polyethylene glycol molecule).
  • conjugated antibody e.g., an antibody that includes a polypeptide including one or more canonical immunoglobulin sequence elements sufficient to confer specific binding to a particular antigen, where the polypeptide is covalently linked with one or more of a therapeutic agent, a detectable moiety, another polypeptide, a glycan, or a polyethylene glycol molecule.
  • antibody sequence elements are humanized, primatized, chimeric, etc.,
  • An antibody including a heavy chain constant domain can be, without limitation, an antibody of any known class, including but not limited to, IgA, secretory IgA, IgG, IgE and IgM, based on heavy chain constant domain amino acid sequence (e.g., alpha (a), delta (8), epsilon (s), gamma (y) and mu (p)).
  • IgG subclasses are also well known to those in the art and include but are not limited to human IgGl, IgG2, IgG3 and IgG4.
  • “Isotype” refers to the Ab class or subclass (e.g., IgM or IgGl) that is encoded by the heavy chain constant region genes.
  • a “light chain” can be of a distinct type, e.g., kappa (K) or lambda (X), based on the amino acid sequence of the light chain constant domain.
  • an antibody has constant region sequences that are characteristic of mouse, rabbit, primate, or human immunoglobulins. Naturally produced immunoglobulins are glycosylated, typically on the CH2 domain. As is known in the art, affinity and/or other binding attributes of Fc regions for Fc receptors can be modulated through glycosylation or other modification. In some embodiments, an antibody may lack a covalent modification (e.g., attachment of a glycan) that it would have if produced naturally. In some embodiments, antibodies produced and/or utilized in accordance with the present disclosure include glycosylated Fc domains, including Fc domains with modified or engineered glycosylation.
  • an antibody can be specific for a particular histone modification (e.g., an antibody can bind one histone modification, e.g., H3K27ac with a higher affinity than other histone modifications, under conditions that are commonly used in ChlP-seq experiments).
  • an antibody is specific for an H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, or H3K4me3 modification.
  • an antibody is specific for an H3K27ac modification.
  • an antibody is specific for an H3K4me3 modification.
  • an antibody is a “pan” antibody.
  • the term pan antibody refers to an antibody that can bind a group of histone modifications having one or more features that are similar.
  • a pan antibody is a pan-methylation antibody (e.g., an antibody that can bind a histone, e.g., H3 that comprises at least one methylated lysine, wherein the at least one methylated lysine can be at any one of a plurality of amino acid positions, e.g., in some embodiments, a pan-methylation antibody can bind an H3 protein comprising a methylated lysine at any position).
  • a pan antibody is a pan-acetylation antibody (e.g., an antibody that can bind a histone, e.g., H3 that comprises at least one acetylated lysine, wherein the at least one acetylated lysine can be at any one of a plurality of amino acid positions, e.g., a pan-acetylation antibody can bind an H3 protein comprising an acetylated lysine at any position).
  • a pan antibody can bind one or more histone modifications that are associated with transcription activation.
  • a pan antibody can bind one or more histone modifications that are associated with transcription silencing.
  • an “antibody fragment” refers to a portion of an antibody or antibody agent as described herein, and typically refers to a portion that includes an antigen-binding portion or variable region thereof.
  • An antibody fragment can be produced by any means. For example, in some embodiments, an antibody fragment can be enzymatically or chemically produced by fragmentation of an intact antibody or antibody agent. Alternatively, in some embodiments, an antibody fragment can be recombinantly produced, i.e., by expression of an engineered nucleic acid sequence. In some embodiments, an antibody fragment can be wholly or partially synthetically produced.
  • an antibody fragment (particularly an antigen-binding antibody fragment) can have a length of at least about 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190 amino acids or more, in some embodiments at least about 200 amino acids.
  • Two events or entities are “associated” with one another, as that term is used herein, if the presence, level and/or form of one is correlated with that of the other.
  • a particular entity e.g., an epigenetic profile comprising one or more histone modifications at a set of genomic loci, etc.
  • two or more entities are physically “associated” with one another if they interact, directly or indirectly, so that they are and/or remain in physical proximity with one another.
  • two or more entities that are physically associated with one another are covalently linked to one another; in some embodiments, two or more entities that are physically associated with one another are not covalently linked to one another but are non- covalently associated, for example by means of hydrogen bonds, van der Waals interaction, hydrophobic interactions, magnetism, or a combination thereof.
  • biological sample typically refers to a sample obtained or derived from a biological source (e.g., a tissue or organism or cell) of interest, as described herein.
  • a biological source is or includes an organism, such as a human subject.
  • a biological sample is or includes a biological tissue or fluid.
  • a biological sample can be or include cells, tissue, or bodily fluid.
  • Bodily fluids refer to fluids that are excreted or secreted from the body as well as fluids that are normally not (e.g., blood, serum, plasma, Cowper’s fluid or preejaculate fluid, chyle, chyme, stool, interstitial fluid, intracellular fluid, lymph, menses, saliva, sebum, semen, serum, sweat, synovial fluid, tears, urine, vitreous humor, vomit).
  • a biological sample can be or include blood, blood components, cell-free DNA (cfDNA), circulating-tumor DNA (ctDNA), ascites, biopsy samples, surgical specimens, cellcontaining body fluids, sputum, saliva, feces, urine, cerebrospinal fluid, peritoneal fluid, pleural fluid, lymph, gynecological fluids, secretions, excretions, skin swabs, vaginal swabs, oral swabs, nasal swabs, washings or lavages such as a ductal lavages or bronchoalveolar lavages, aspirates, scrapings, or bone marrow.
  • cfDNA cell-free DNA
  • ctDNA circulating-tumor DNA
  • a biological sample is a liquid biopsy sample obtained from a bodily fluid.
  • a biological sample is or includes DNA obtained from a single subject or from a plurality of subjects.
  • a biological sample can be a “primary sample” obtained directly from a biological source or can be a “processed sample”, i.e., a sample that was derived from a primary sample, e.g., via dilution, purification, mixing with one or more reagents, or any other processing step(s) as described herein.
  • a biological sample can also be referred to as a “sample.”
  • Combination therapy refers to administration to a subject of two or more therapeutic agents or therapeutic regimens such that the two or more therapeutic agents or therapeutic regimens together treat a disease, condition, or disorder of the subject.
  • the two or more therapeutic agents or therapeutic regimens can be administered simultaneously, sequentially, or in overlapping dosing regimens.
  • combination therapy includes but does not require that the two therapeutic agents or therapeutic regimens be administered together in a single composition, nor at the same time.
  • corresponding to may be used to designate the position/identity of a structural element in a compound or composition through comparison with an appropriate reference compound or composition.
  • a monomeric residue in a polymer e.g., an amino acid residue in a polypeptide or a nucleic acid residue in a polynucleotide
  • corresponding to a residue in an appropriate reference polymer.
  • Two sequences can be identified as corresponding if they are identical or if they share substantial identity, e.g., at least 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% identity, e.g., over a length of at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500 or more residues.
  • a nucleic acid sequence can correspond to a sequence that is identical or substantially identical (e.g., at least 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% identical) to the complement of the nucleic acid sequence, e.g., over a length of at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500 or more nucleic acid residues.
  • diagnosis includes the act, process, and/or outcome of determining whether, and/or the qualitative of quantitative probability that, a subject has or will develop the condition, disease, or related state.
  • diagnosing can include a determination relating to prognosis and/or likely response to one or more general or particular therapeutic agents or regimens.
  • Expression level, amount, or level As used herein, the terms “expression level,” “amount,” or “level,” or used herein interchangeably, of a biomarker is a detectable level in a biological sample. “Expression” generally refers to the process by which information (e.g., gene-encoded and/or epigenetic) is converted into the structures present and operating in the cell. Therefore, as used herein, “expression” may refer to transcription into a polynucleotide, translation into a polypeptide, or even polynucleotide and/or polypeptide modifications (e.g., posttranslational modification of a polypeptide).
  • Expression level, amount, or level of a given polypeptide is a measure of the expression process for that polypeptide.
  • Fragments of the transcribed polynucleotide, the translated polypeptide, or polynucleotide and/or polypeptide modifications shall also be regarded as expressed whether they originate from a transcript generated by alternative splicing or a degraded transcript, or from a post-translational processing of the polypeptide, e.g., by proteolysis.
  • “Expressed genes” include those that are transcribed into a polynucleotide as mRNA and then translated into a polypeptide, and also those that are transcribed into RNA but not translated into a polypeptide (for example, transfer and ribosomal RNAs). Expression levels can be measured by methods known to one skilled in the art and also disclosed herein.
  • the expression level or amount of a biomarker can be used to identify/characterize a subject having a prostate cancer (e.g., mCRPC) who may be likely to respond to, or benefit from, a particular therapy (e.g., a PSMA-targeted therapy).
  • the expression level or amount of a biomarker provided herein in a subject having a prostate cancer described herein can also be used to determine and/or track the benefit of an administered therapy over time.
  • Identity refers to the overall relatedness between polymeric molecules, e.g., between nucleic acid molecules (e.g., DNA molecules) and/or between polypeptide molecules. Methods for the calculation of a percent identity as between two provided sequences are known in the art. The term “% sequence identity” refers to a relationship between two or more sequences, as determined by comparing the sequences. In the art, “identity” also means the degree of sequence relatedness between protein and nucleic acid sequences as determined by the match between strings of such sequences. “Identity” (often referred to as “similarity”) can be readily calculated by known methods, including those described in: Computational Molecular Biology (Lesk, A. M.
  • Methods to determine identity and similarity are codified in publicly available computer programs. For example, calculation of the percent identity of two nucleic acid or polypeptide sequences can be performed by aligning the two sequences (or the complement of one or both sequences) for optimal comparison purposes (e g., gaps can be introduced in one or both of a first and a second sequences for optimal alignment and nonidentical sequences can be disregarded for comparison purposes). The nucleotides or amino acids at corresponding positions are then compared. When a position in the first sequence is occupied by the same residue (e.g., nucleotide or amino acid) as the corresponding position in the second sequence, then the molecules are identical at that position.
  • residue e.g., nucleotide or amino acid
  • the percent identity between the two sequences is a function of the number of identical positions shared by the sequences, optionally accounting for the number of gaps, and the length of each gap, which may need to be introduced for optimal alignment of the two sequences.
  • the comparison of sequences and determination of percent identity between two sequences can be accomplished using a computational algorithm, such as BLAST (basic local alignment search tool). Sequence alignments and percent identity calculations may be performed using the Megalign program of the LASERGENE bioinformatics computing suite (DNASTAR, Inc., Madison, Wisconsin).
  • GCG Genetics Computer Group
  • BLASTP BLASTN
  • BLASTX Altschul et al., J Mol Biol (1990) 215:403-410
  • DNASTAR DNASTAR, Inc., Madison, Wisconsin
  • FASTA program incorporating the Smith-Waterman algorithm (Pearson, Comput Methods Genome Res [Proc Int Symp] (1994), Meeting Date 1992, 111-120. Eds. Suhai, Sandor. Plenum, New York, NY (the contents of each of which is separately incorporated herein by reference in its entirety).
  • Modification Status or “Histone Modification Status” : As used herein, “modification status” or “histone modification status” of a genomic locus refers to the frequency with which DNA sequences corresponding to the genomic locus are identified in an assay for detection of DNA sequences associated with histones bearing one or more histone modifications (e g., one or more particular histone modifications) and/or the density (e g., the measured density) of histone modifications (e.g., one or more particular histone modifications) corresponding to the genomic locus. Modification status can be determined by various assays known in the art, including without limitation ChlP-seq as one example.
  • CUT&RUN Cleavage Under Targets and Release Using Nuclease
  • CUT&Tag Cleavage Under Targets and Tagmentation
  • Modification status can be compared to a standard or reference.
  • a sample that has a modification status that differs in modification status or histone modification status from a standard or reference can be referred to as differentially modified.
  • PSMA expression refers to the amount of PSMA produced in a subject and/or the amount of PSMA produced in a subset of cells within a subject.
  • the subset of cells includes or consists of cells from a particular organ or tissue type (e.g., prostate tissue) of interest.
  • the subset of cells includes or consists of diseased cells.
  • the subset of cells includes or consists of cancer cells.
  • the subset of cells includes or consists of prostate cancer cells.
  • the subset of cells includes or consists of mCRPC cells.
  • “disease specific PSMA expression” refers to PSMA produced by diseased cells.
  • PSMA expression refers to cell surface and/or extracellular expression.
  • PSMA expression measured using technologies described herein can be associated with estimates of PSMA expression determined using other methods.
  • technologies provided herein for measuring PSMA expression level can be used to predict values that would be provided by other technologies, including, e.g., measurements provided by other approaches that have been shown to be associated with clinical outcomes and/or be suitable for determining patient eligibility for a certain therapeutic.
  • technologies provided herein can be used to predict a PSMA expression level determined using an imaging method, including, e.g., a PSMA PET imaging method.
  • technologies provided herein can be used to predict a PSMA PET SUVmean measurement.
  • PSMA Targeted Therapeutic refers to a therapeutic or administration of a therapeutic that can bind to or associate with PSMA (e.g., bind to or associate with PSMA in a subject).
  • a PSMA targeted therapeutic comprises a moiety that can bind to or associate with PSMA in a subject.
  • a PSMA targeted therapeutic comprises an antibody moiety that can bind to or associate with PSMA in a subject.
  • a PSMA targeted therapeutic comprises a small molecule moiety that can bind to or associate with PSMA in a subject.
  • a PSMA targeted therapeutic is an ADC comprising an antibody moiety that can bind PSMA (e.g., an antibody moiety of an ADC described herein).
  • a PSMA targeted therapeutic is a radiolabeled conjugate.
  • promoter signal refers to an epigenetic modification in a promoter region that is associated with increased expression of a gene regulated by the promoter region.
  • promoter signals include, e.g., histone methylation (e.g., H3K4me3).
  • promoter signal can be measured by quantifying histone methylation (e.g., H3K4me3), chromatin accessibility, and/or transcription factor binding.
  • a regulatory sequence is a nucleic acid sequence that controls expression of a coding sequence, e.g., a promoter sequence or an enhancer sequence.
  • a regulatory sequence can control or impact one or more aspects of gene expression (e.g., celltype-specific expression, inducible expression, etc.).
  • Subject refers to an organism, typically a mammal (e.g., a human).
  • a subject is suffering from a disease, disorder or condition (e.g., mCRPC).
  • a subject is susceptible to a disease, disorder, or condition.
  • a subject displays one or more symptoms or characteristics of a disease, disorder or condition.
  • a subject is not suffering from a disease, disorder or condition.
  • a subject does not display any symptom or characteristic of a disease, disorder, or condition.
  • a subject has one or more features characteristic of susceptibility to or risk of a disease, disorder, or condition.
  • a subject is a subject that has been tested for a disease, disorder, or condition, and/or to whom therapy has been administered.
  • a human subject can be interchangeably referred to as a “patient” or “individual”.
  • therapeutic agent refers to any agent that elicits a desired pharmacological effect when administered to a subject.
  • an agent is considered to be a therapeutic agent if it demonstrates a statistically significant effect across an appropriate population.
  • the appropriate population can be a population of model organisms or a human population.
  • an appropriate population can be defined by various criteria, such as a certain age group, gender, genetic background, preexisting clinical conditions, etc.
  • a therapeutic agent is a substance that can be used for treatment of a disease, disorder, or condition (e.g., mCRPC).
  • a therapeutic agent is an agent that has been or is required to be approved by a government agency before it can be marketed for administration to humans.
  • a therapeutic agent is an agent for which a medical prescription is required for administration to humans.
  • therapeutically effective amount refers to an amount that produces the desired effect for which it is administered. In some embodiments, the term refers to an amount that is sufficient, when administered to a population suffering from or susceptible to a disease, disorder, and/or condition (e.g., mCRPC) in accordance with a therapeutic dosing regimen, to treat the disease, disorder, and/or condition. In some embodiments, a therapeutically effective amount is one that reduces the incidence and/or severity of, and/or delays onset of, one or more symptoms of the disease, disorder, and/or condition. Those of ordinary skill in the art will appreciate that the term “therapeutically effective amount” does not in fact require successful treatment be achieved in a particular individual.
  • treatment refers to administration of a therapy that partially or completely alleviates, ameliorates, relieves, inhibits, delays onset of, reduces severity of, and/or reduces incidence of one or more symptoms, features, and/or causes of a particular disease, disorder, or condition, or is administered for the purpose of achieving any such result.
  • a therapy that partially or completely alleviates, ameliorates, relieves, inhibits, delays onset of, reduces severity of, and/or reduces incidence of one or more symptoms, features, and/or causes of a particular disease, disorder, or condition, or is administered for the purpose of achieving any such result.
  • such treatment can be of a subject who does not exhibit signs of the relevant disease, disorder, or condition and/or of a subject who exhibits only early signs of the disease, disorder, or condition (e g., mCRPC).
  • such treatment can be of a subject who exhibits one or more established signs of the relevant disease, disorder and/or condition.
  • treatment can be of a subject who has been diagnosed as suffering from the relevant disease, disorder, and/or condition.
  • treatment can be of a subject known to have one or more susceptibility factors that are statistically correlated with increased risk of development of the relevant disease, disorder, or condition.
  • a “prophylactic treatment” includes a treatment administered to a subject who does not display signs or symptoms of a condition to be treated or displays only early signs or symptoms of the condition to be treated such that treatment is administered for the purpose of diminishing, preventing, or decreasing the risk of developing the condition.
  • a prophylactic treatment functions as a preventive treatment against a condition.
  • a “therapeutic treatment” includes a treatment administered to a subject who displays symptoms or signs of a condition and is administered to the subject for the purpose of reducing the severity or progression of the condition.
  • a method of predicting tumor specific PSMA expression e.g., predicting PSMA expression measurements determined using (i) an imaging procedure, (ii) a radioligand, and/or (iii) PSMA PET imaging (e.g., PSMA PET SUVmax or PSMA PET SUVmean)) in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) or ctDNA from a liquid biopsy sample, obtained or derived from the subject:
  • any one of embodiments 1-23, comprising quantifying one or more histone modifications and/or DNA methylation for one or more of AMN, ARHGEF37, C4orf36, CADM1, CCDC175, CDC7, CLSTN1, COL5A1, EDNRA, FOLH1, GALR3, MED13L, MICB, NDRG3, NEDD1, NPAS2, NPVF, OLFM1, PCBP4, PROZ, PRRG3, RREB1, SCUBE3, SERPINA5, SNRPF, SORCS3, ST8SIA5, TEX19, TMEM132B, or TTC29 or any combination thereof, or one or more regulatory regions of any one of the foregoing (e.g., one or more promoter and/or enhancer regions o AMN, ARHGEF37, C4orf36, CADM1, CCDC175, CDC7, CLSTN1, COL5A1, EDNRA, FOLH1, GALR3, MEDI3L, MICB, NDRG3,
  • promoter signal e.g., H3K4me3 modifications
  • H3K4me3 modifications for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K4me3 analyte genomic loci in Table 1;
  • promoter signal e.g., H3K4me3 modifications
  • H3K4me3 modifications for 1 or 2 H3K4me3 analyte genomic loci in Table 4;
  • enhancer signal e.g., H3K27ac modifications
  • H3K27ac modifications for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 4;
  • promoter signal e.g., H3K4me3 modifications
  • enhancer signal e.g., H3K27ac modifications
  • promoter signal e g., H3K4me3 modifications
  • the subject has previously been diagnosed with a disease or condition that is associated with increased PSMA expression, optionally wherein the disease or condition that is associated with increased PSMA expression is prostate cancer; and/or
  • a method of measuring PSA expression in a subject comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free
  • cfDNA circulating tumor DNA
  • ctDNA circulating tumor DNA
  • a method of predicting PSA expression in a subject comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) or circulating tumor DNA (ctDNA) from a liquid biopsy sample, obtained or derived from the subject:
  • chromatin accessibility is quantified using a chromatin accessibility assay selected from ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde- Assisted Isolation of Regulatory Elements sequencing), MNase-seq (Micrococcal Nuclease digestion with sequencing), a DNase hypersensitivity assay, and a fragmentomics assay.
  • ATAC-seq Assay of Transpose Accessible Chromatin sequencing
  • NOMe-seq Nucleosome Occupancy and Methylome sequencing
  • FAIRE-seq Formmaldehyde- Assisted Isolation of Regulatory Elements sequencing
  • MNase-seq Merococcal Nuclease digestion with sequencing
  • DNase hypersensitivity assay a fragmentomics assay.
  • the transcription factor binding assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
  • promoter signal e.g., H3K4me3 modifications
  • liquid biopsy sample is a plasma sample, serum sample, or urine sample.
  • the prostate cancer is metastatic castration resistant prostate cancer (mCRPC);
  • prostate cancer is prostate adenocarcinoma (PRAD) or neuroendocrine prostate cancer (NEPC).
  • PRAD prostate adenocarcinoma
  • NEPC neuroendocrine prostate cancer
  • a method of identifying a subject with elevated PSMA expression comprising:
  • a method of identifying a subject with elevated PSA expression comprising:
  • PSA expression e.g., serum PSA, including, e.g., total PSA
  • a method of diagnosing a subject as having a disease or disorder associated with elevated PSMA expression comprising:
  • a method of diagnosing a subject as having a disease or disorder associated with elevated PSA expression comprising:
  • PSA expression e.g., serum PSA, including, e.g., total PSA
  • the reference is a predetermined threshold, a measurement from a liquid biopsy sample, a measurement from an imaging test, and/or a normalized value, optionally wherein the reference is a measurement from an imaging test (e.g., PSMA PET SUVmean) or sample obtained from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with a disease or disorder associated with increased PSMA and/or PSA expression.
  • an imaging test e.g., PSMA PET SUVmean
  • a method of prognosing a subject having a disease or disorder associated with increased PSMA expression comprising:
  • a method of prognosing a subject having a disease or disorder associated with increased PSA expression comprising:
  • PSA expression e.g., serum PSA
  • the reference is a predetermined threshold, a measurement from a liquid biopsy sample, a measurement from an imaging test (e.g., PSMA PET SUVmean), and/or a normalized value, optionally wherein the reference is a measurement from a liquid biopsy sample or imaging test (e.g., PSMA PET SUVmean) obtained from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with the disease or disorder associated with increased PSMA and/or PSA expression.
  • an imaging test e.g., PSMA PET SUVmean
  • a normalized value optionally wherein the reference is a measurement from a liquid biopsy sample or imaging test (e.g., PSMA PET SUVmean) obtained from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with the disease or disorder associated with increased PSMA and/or PSA expression.
  • the reference is the median, lower bound of the top tertile, or lower bound of the top quartile value of the PSMA expression level measured, tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) predicted, or tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) measured in the cohort of subjects having the disease or disorder associated with increased PSMA expression; and if the PSMA expression level or predicted tumor specific PSMA expression level in the subject is equal to or greater than the reference, the subject is predicted to have a higher-than- normal risk of experiencing worse than normal disease progression as measured by one or more clinical outcomes.
  • tumor specific PSMA expression level e.g., PSMA PET SUVmean value
  • tumor specific PSMA expression level e.g., PSMA PET SUVmean value
  • the PSMA PET SUVmean median is about 4 to about 8, about 5 to about 8, 5 to about 7, about 6 to about 9, about 5, about 6, about 7, or about 8;
  • the lower bound of the top tertile of PSMA PET SUVmean is about 6 to about 12, about 6 to about 10, about 8 to about 12, about 6, about 7, about 8, about 9, about 10, about 11, or about 12; or
  • the lower bound of the top quartile of PSMA PET SUVmean is about 6 to about 14, about 6 to about 12, about 8 to about 14, about 8, about 9, about 10, about 11, about 12, about 13, or about 14.
  • a measurement from an imaging test e.g., PSMA PET SUVmean
  • the measurement is a serum PSA measurement.
  • any one of embodiments 77-79, wherein the one or more clinical outcomes include (i) overall survival, (ii) time to next treatment, or (iii) progression free survival (e.g., as determined by PSA-PFS (plasma PSA levels) and/or crPFS (clinical or radiological evidence of progression).
  • the one or more clinical outcomes include (i) overall survival, (ii) time to next treatment, or (iii) progression free survival (e.g., as determined by PSA-PFS (plasma PSA levels) and/or crPFS (clinical or radiological evidence of progression).
  • a method of monitoring progression of a disease associated with elevated PSMA expression in a subject comprising, at a first and second point in time:
  • a method of monitoring progression of a disease associated with elevated PSA expression in a subject comprising, at a first and second point in time:
  • a method of treating a subject having a disease or disorder associated with increased PSMA expression comprising measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) in the subject using the method of any one of embodiments 1-33 or 63-67, and comparing the measured PSMA expression level or predicted tumor specific PSMA expression to a reference, and
  • PSMA expression or predicting tumor specific PSMA expression e.g., PSMA PET SUVmean
  • a method of identifying a subject having a disease or disorder associated with increased PSMA expression that is likely to respond to a therapeutic comprising measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) in the subject using the method of any one of embodiments 1-33 or 63-67, and comparing the measured PSMA expression level or predicted tumor specific PSMA expression to a reference, and
  • PSMA expression or predicting tumor specific PSMA expression e.g., PSMA PET SUVmean
  • a method of predicting the likelihood that a subject having a disease or disorder associated with increased PSMA expression will respond to a therapeutic comprising measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) in the subject using the method of any one of embodiments 1-33 or 63-67, and comparing the measured PSMA expression level or predicted tumor specific PSMA expression to a reference, wherein
  • tumor specific PSMA expression e.g., PSMA PET SUVmean
  • any one of embodiments 86-88 wherein the reference is a predetermined threshold, a measurement from a liquid biopsy sample, a measurement from an imaging test, and/or a normalized value, optionally wherein the reference is a measurement from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with the disease or disorder associated with increased PSMA expression.
  • any one of embodiments 86-89, wherein the reference is a PSMA expression level measured, a tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) predicted, or a tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) measured in a cohort of subjects having the disease or disorder associated with increased PSMA expression.
  • a tumor specific PSMA expression level e.g., PSMA PET SUVmean value
  • a tumor specific PSMA expression level e.g., PSMA PET SUVmean value
  • tumor specific PSMA expression level e.g., PSMA PET SUVmean value
  • tumor specific PSMA expression level e.g., PSMA PET SUVmean value
  • the PSMA PET SUVmean median is about 4 to about 8, about 5 to about 8, 5 to about 7, about 6 to about 9, about 5, about 6, about 7, or about 8;
  • the lower bound of the top tertile of PSMA PET SUVmean is about 6 to about 12, about 6 to about 10, about 8 to about 12, about 6, about 7, about 8, about 9, about 10, about 11, or about 12; or
  • the lower bound of the top quartile of PSMA PET SUVmean is about 6 to about 14, about 6 to about 12, about 8 to about 14, about 8, about 9, about 10, about 11, about 12, about 13, or about 14.
  • a method of treating a subject having a disease or disorder associated with increased PSA expression comprising measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total serum PSA) in the subject using the method of any one of embodiments 34-67, and comparing the measured PSA or predicted PSA expression to a reference, and
  • PSA expression e.g., serum PSA, including, e.g., total serum PSA
  • a method of identifying a subject having a disease or disorder associated with increased PSA expression that is likely to respond to a therapeutic comprising measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total PSA) in the subject using the method of any one of embodiments 33-67, and comparing the measured or predicted PSA expression to a reference, and
  • PSA expression e.g., serum PSA, including, e.g., total PSA
  • a method of predicting the likelihood that a subject having a disease or disorder associated with increased PSA expression will respond to a therapeutic comprising measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total PSA) in the subject using the method of any one of embodiments 33-67, and comparing the measured or predicted PSA expression to a reference, wherein
  • PSA expression e.g., serum PSA, including, e.g., total PSA
  • the reference is a predetermined threshold, a measurement from a liquid biopsy sample, and/or a normalized value, optionally wherein the reference is a measurement from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with the disease or disorder associated with increased PSA expression.
  • the therapeutic is an ADC (e.g., PSMA- MMAE, MLN2704, ARX517), and/or wherein the therapeutic is a PSMA-targeted radionuclide (e.g., 177Lu-PSMA-617).
  • the therapeutic is 177Lu-PSMA-617.
  • 111 The method of any one of embodiments 68-110, wherein the subject has a plasma PSA concentration of 0-2000 ng/mL (e.g., at least about 4 ng/mL, at least about 10 ng/mL, 10-2000 ng/mL, 25-2000 ng/mL, 50-2000 ng/mL, 75-2000 ng/ML, 100-2000 ng/mL, 150-1000 ng/mL, 100-500 ng/mL, or 100-200 ng/mL), optionally wherein the plasma PSA concentration has been determined using the method of any one of embodiments 33-67.
  • 0-2000 ng/mL e.g., at least about 4 ng/mL, at least about 10 ng/mL, 10-2000 ng/mL, 25-2000 ng/mL, 50-2000 ng/mL, 75-2000 ng/ML, 100-2000 ng/mL, 150-1000 ng/mL, 100-500 ng/mL,
  • a kit comprising reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci, wherein the one or more genomic loci are selected from Tables 1-5.
  • kit of embodiment 112 wherein the kit comprises reagents for quantifying:
  • promoter signal e.g., H3K4me3 modifications
  • H3K4me3 modifications for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K4me3 analyte genomic loci in Table 1;
  • enhancer signal e.g., H3K27ac modifications
  • H3K27ac modifications for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 1;
  • enhancer signal e.g., H3K27ac modifications
  • promoter signal e.g., H3K4me3 modifications
  • enhancer signal e.g., H3K27ac modifications
  • promoter signal e.g., H3K4me3 modifications
  • H3K4me3 modifications for 1 or 2 H3K4me3 analyte genomic loci in Table 4;
  • enhancer signal e.g., H3K27ac modifications
  • H3K27ac modifications for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 4;
  • promoter signal e.g., H3K4me3 modifications
  • enhancer signal e.g., H3K27ac modifications
  • kit of embodiment 112 or 113 wherein the kit comprises one or more antibodies for use in ChlP-seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac-modified histones.
  • cfDNA cell-free DNA
  • ctDNA cell-free DNA
  • a disease or disorder associated with increased PSMA e.g., a cancer, prostate cancer, or mCRPC.
  • a computer system comprising a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform operations to perform the method of any one of embodiments 1-111.
  • a system for determining the disease or disorder status of a subject comprising a sequencer configured to generate a sequencing data set from a sample; and a non- transitory computer readable storage medium of embodiment 120 and/or a computer system of embodiment 121.
  • invention 122 or 123 further comprising a sample preparation device configured to prepare the sample for sequencing from a biological sample, optionally a liquid biopsy sample.
  • sample preparation device comprises reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci in cell- free DNA (cfDNA) or ctDNA from the biological sample, optionally the liquid biopsy sample.
  • promoter signal e.g., H3K4me3 modifications
  • H3K4me3 modifications for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K4me3 analyte genomic loci in Table 1;
  • enhancer signal e.g., H3K27ac modifications
  • H3K27ac modifications for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 1;
  • enhancer signal e.g., H3K27ac modifications
  • promoter signal e.g., H3K4me3 modifications
  • enhancer signal e.g., H3K27ac modifications
  • promoter signal e.g., H3K4me3 modifications 1 or 2 H3K4me3 analyte genomic loci in Table 4;
  • enhancer signal e.g., H3K27ac modifications
  • H3K27ac modifications for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 4;
  • promoter signal e.g., H3K4me3 modifications
  • enhancer signal e.g., H3K27ac modifications
  • reagents comprise one or more antibodies for use in ChlP-seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac-modified histones.
  • the device comprises reagents for isolation of cell-free DNA (cfDNA) or ctDNA from the biological sample, optionally the liquid biopsy sample.
  • cfDNA cell-free DNA
  • ctDNA cell-free DNA
  • the present Examples demonstrate the identification and use of differentially modified and/or differentially accessible genomic loci in cfDNA in plasma samples obtained from subjects with mCRPC. Loci identified in the present example can be useful, e.g., for detecting mCRPC, characterizing mCRPC disease severity, monitoring mCRPC, prognosing subjects with mCRPC, and informing patient treatment decisions.
  • Example 1 Materials and Methods
  • the present Example describes the materials and methods that were used to generate sequencing data that was then used in Examples 2 and 3 to identify differentially modified genomic loci and create models to predict PSMA PET SUVmean.
  • Plasma samples were prepared from whole blood collected in EDTA blood collection tubes or Streck cell-free DNA BCT with 4-6 hours of collection and plasma was stored at -80°C until use.
  • Whole blood was obtained from metastatic Castration-Resistant Prostate Cancer (mCRPC) patients under a protocol approved by an IRB. Patients had previously been determined to have mCRPC. Informed content was obtained in each case and samples were de-identified.
  • mCRPC metastatic Castration-Resistant Prostate Cancer
  • Chromatin immunoprecipitation (ChIP)
  • Chromatin immunoprecipitation (ChIP) for histone marks (H3K4me3 and H3K27ac) in plasma samples can be performed using methods similar to those previously described in Baca et al. “Liquid biopsy epigenomic profiling for cancer subtyping.” Nature medicine 29.11 (2023): 2737-2741, which is incorporated by reference herein in its entirety. Briefly, about 1 mL frozen plasma was thawed and then prepared for ChIP. The thawed plasma was incubated with antibodies that bind H3K4me3 modifications or H3K27ac modifications that were previously conjugated to magnetic epoxy beads (Invitrogen) with constant mild shaking overnight. The beads were then washed and rinsed. Sequencing libraries were generated from purified immunoprecipitated sample DNA and then sequenced.
  • Enrichment of DNA methylation was performed on DNA extracted from human plasma samples using the EpiMark® Methylated DNA Enrichment Kit (E2600S, available from New England Biolabs) following the manufacturer’s protocol. Briefly, cfDNA libraries were prepared and adaptors ligated. Then, the EpiMark® capture reagent was applied to each library sample following the manufacturer’s protocol. Enriched DNA libraries were amplified and sequenced.
  • ChlP-sequencing reads and MBD-sequencing reads were aligned to the human genome build hgl9 using the Burrows-Wheeler Aligner (BWA) version 0.7.15. Non-uniquely mapping and redundant reads were discarded.
  • BWA Burrows-Wheeler Aligner
  • FDR q- value
  • Example 2 Determination of Tumor PSMA Expression in Prostate Cancer From Blood Using a Novel Epigenomic Liquid Biopsy Platform
  • PSMA Prostate-Specific Membrane Antigen
  • Pluvicto 177Lu-PSMA-617
  • mCRPC metastatic castration-resistant prostate cancer
  • Treatment eligibility currently requires collecting a PSMA PET SUVmean measurement, a PET scan quantification of the level of PSMA positivity in tumor lesions throughout the body.
  • a PET scan quantification of the level of PSMA positivity in tumor lesions throughout the body.
  • therapeutic strategies in development targeting an array of cell surface proteins there is an emerging unmet need to quantify tumor drug target expression minimally invasively.
  • the present Example provides data demonstrating that technologies described herein can be used as an accurate, minimally invasive readout of tumor PSMA expression in mCRPC.
  • the present Example also demonstrates that technologies provided herein can be used to monitor the transcription state of tumor cells in a patient, and can also accurately predict PSMA PET SUVmean, which can be useful, e.g., for prognostic prediction and as a companion diagnostic for PSMA radioimmune conjugates (RICs) (e.g., RICs approved or in development).
  • RICs radioimmune conjugates
  • FIGs. 1(A) and 1(B) Schematics summarizing the method used to characterize the epigenome of patients in the present Example are provided in Figs. 1(A) and 1(B).
  • Plasma samples were collected for 50 men previously diagnosed with mCRPC.
  • PET images were collected for 29 of the 50 men at the time of plasma collection, and the PET images were analyzed to quantify PSMA PET SUVmean.
  • MACS2 (—nolambda) was used to determine regions of the genome enriched for epigenomic signal. Consensus peak maps were then created for each analyte by merging maps across all patients (requiring a region to be covered by at least 3 patients’ peak maps) and removing regions known to be artifactual/technical (ENCODE blacklist). For each analyte’s consensus peak map, tiling across their regions was then performed using a 500 bp window, with a 100 bp step. Tiles were then analyzed to identify tiles having high-confidence mCRPC signal. Finally, high-confidence tiles were merged based on genomic coordinate overlaps.
  • This set of merged tiles are hereafter referred to as the “peaks”. Fragments within the peak regions (above local background) were quantified, normalized for read-depth, log2 -transformed (with a pseudo count of 0.01, and quantile normalized). For model validation this process was performed in a leave-one-out cross-validation schema.
  • differential analysis identified a number of regions having changes in epigenetic modifications in mCRPC subjects as compared to healthy subjects, including 15,174 loci with increased enhancer signal, 10,121 loci with decreased enhancer signal, 10,804 loci with increased promoter signal, 9,518 loci with decreased promoter signal, 41,198 loci with increased DNA methylation, and 9,238 loci with decreased DNA methylation.
  • genes associated with differential modifications were multiple prostate-cancer specific signals, including H0XB13, KLK2, KLK3, and SPDEF.
  • the detection of epigenetic modifications associated with multiple prostate-cancer specific signals demonstrates that technologies provided herein can be used to identify biologically relevant changes in the epigenome, that are reflective of transcription activity in tumor cells in a subject.
  • Table 1 Genomic Loci With Highest Association to PSMA PET SUVmean for H3K27ac, H3K4me3, and DNAme.
  • enhancer signal at the FOLH1 locus was identified as being most highly associated with PSMA PET SUVmean.
  • Fig. 4 provides exemplary epigenomic maps for H3K4me3 (promoter), H3K27ac (enhancers), and methylated DNA (DNAme) at the FOLH1 locus in subjects with low PSMA PET signal (defined as being below the median SUVmean of subjects tested), high PSMA PET signal (defined as being above the median SUVmean of subjects tested), and healthy subjects.
  • Epigenetic signal at the loci listed in the Table 2 (below) were found to provide particularly robust mCRPC-specific signal.
  • Table 2 Loci with particularly robust mCRPC-specific signal.
  • Table C Characteristics of Training and Validation Cohorts: [0441] All prostate cancer specific regions of the genome were normalized, allowing for per-experiment normalization of tumor specific regions and aggregated (aggregation can be performed, e.g., using a weighted sum product).
  • Performance was assessed via Pearson correlation in both a leave-one-out (LOO) cross-validation (CV) setting within the training cohort, as well as the held-out validation cohort using a final model trained on all data from the training cohort.
  • LEO leave-one-out
  • CV cross-validation
  • Results from the training cohort LOOCV and validation cohort analysis are shown in Fig. 5.
  • a positive correlation was observed between predicted PSMA PET SUVmean values and observed PSMA PET SUVmean values, demonstrating that epigenomic cfDNA profiling can provide an accurate surrogate of tumor PSMA expression in men with mCRPC, and can be useful for, e.g., detecting prostate cancer, characterizing prostate cancer in a subject, monitoring progression of prostate cancer, informing treatment selection, and optimizing patient selection.
  • the present Example provides a set of loci and analytes that are particularly useful for predicting PSMA expression levels. Surprisingly, it was found that monitoring epigenetic modifications at one or more of the small set of loci identified in Table 2 provided superior PSMA PET SUVmean predictive ability as compared to use of genome-wide epigenetic signal. Moreover, the ability of an ML model with loci identified in the present Example to predict PSMA PET SUVmean is a significant advancement in the field, as loci previously identified in the region were not found to be PRAD-specific/robust (data not provided).
  • the present Example provides results from a study testing the correlation between a PSMA scoring algorithm described herein and patient health outcomes.
  • PSMA PET SUVmean values were predicted for 84 samples, include 72 samples from subjects administered Pluvicto. Samples were then screened for a ctDNA fraction of > 0.03, resulting in 45 samples. The 45 samples were then split into tertiles based on PSMA PET SUVmean prediction scores and a logrank test was performed for 5 time-to-event clinical outcomes: PSA-PFS, crPFS, Time to Next Treatment, and Overall Survival.
  • the present Example provides data showing that technologies described herein can be used to measure PSA serum levels using epigenetic modifications measured in plasma samples.
  • a model for predicting PSA expression was generated using prostate cancer tumor biopsies. For each biopsy, genome wide maps of H3K4me3 and H3K27ac modifications were obtained using ChlP-seq. PSA expression was also determined for each biopsy using RNA- seq data. Simulated plasma samples were then generated by serially diluting the tumor biopsy sequencing data in silico with sequencing data from healthy plasma samples to create samples with a range of ctDNA%. Regions proximal to KLK3 (i.e., within KLK3 and +/- 200 kB of the transcript encoding portion of KI.K3) JVCQ identified that had epigenetic modification signal that correlated with PSA expression. These regions were then used to build a model for predicting PSA expression. The loci used in the present Example to measure PSA expression are provided in Table 3, below.
  • the model for predicting PSA expression was then applied to plasma samples obtained from subjects with prostate cancer to predict PSA expression level, and these predicted expression values were compared to serum PSA measurements in matched samples. Results of this comparison are shown in Fig. 8. As shown, predicted PSA expression was shown to correlate with measured serum PSA, demonstrating that technologies described herein can be used to measure serum PSA.
  • Example 5 Further PSMA PET SUV mea n Predictions in Prostate Cancer Patients [0454] The present Example provides further data demonstrating that technologies provided herein can be used predict PSMA PET SUVmean.
  • a model for measuring PSMA expression was generated using publicly available prostate tumor biopsy H3K4me3, H3K27Ac, and RNA-seq data. For each biopsy, genome wide maps of H3K4me3 and H3K27ac, and DNAme modifications were obtained. PSMA expression was also measured for each biopsy using RNA-seq.
  • the biopsy generated model was then applied to plasma samples obtained from patients with prostate cancer to obtain predicted PSMA expression values. These predicted values were compared to measured PSMA PET SUVmean in the same patients. Results are shown in Fig. 9(A). As shown, PSMA expression predicted using a biopsy model was shown to correlate with PSMA PET SUVmean signal, demonstrating that technologies described herein can be used to predict PSMA PET SUV mean signal.
  • Fig. 9(B) provides another characterization of the model constructed using the approach described in Examples 2 and 3.
  • the model generated in Example 3 (trained using PSMA PET SUVmean and epigenetic modifications from patient plasma samples) provided a model with improved accuracy as compared to a model generated using biopsy data.
  • sequencing data from plasma samples of patients with prostate cancer were diluted in silica with sequencing data from healthy subjects to generate in silico plasma samples having a range of ctDNA% values.
  • PSMA PET SUVmean was then predicted for each in silico sample using the biopsy model and the model trained using PSMA PET SUVmean (described in Example 3) and Pearson’s coefficients were determined. Results are shown in Fig. 9(C).
  • both models showed a strong Spearman correlation with PSMA PET SUVmean signal at clinically relevant concentrations, with the PSMA PET SUVmean trained model providing higher Spearman correlation at ctDNA% higher than ⁇ 2%.
  • the present Example provides further regions proximal to FOLH1 with H3K4me3 and H3K27ac signal that correlate with PSMA expression.
  • promoter and enhancer signal were identified in plasma samples from patients with lung cancer (SCLC).
  • SCLC lung cancer
  • the loci identified in the present Example can be used to measure or predict PSMA expression in prostate cancer.
  • Plasma samples from cancer patients and healthy volunteers were collected from commercial biobanks and stored at -80°C until use. The percentage of ctDNA in the plasma samples from cancer patients was assessed using ichorCNA, which estimates the percentage of ctDNA in a sample probabilistically (see Adalsteinsson et al., Nat Commun (2017) 8(1): 1324, the entire contents of which are incorporated herein by reference). Plasma samples from cancer patients with at least 5.5% ctDNA were used in the present Example.
  • H3K4me3 To identify promoter (H3K4me3) epigenomic activation signals a. FOLHl, we defined a peak within +/- Ikb of the transcription site (TSS) of FOLH1. To identify enhancer (H3K27ac) epigenomic activation signals at FOLH1, we defined a peak within +/- lOkb of the transcription site (TSS) of FOLHl. As a control, H3K4me3 and H3K27ac epigenomic activation signals were measured at housekeeping genes using a similar approach.
  • a consensus map of all peaks was created by taking the union of all base pairs covered by any peak in any of the cancer patient or healthy volunteer plasma samples. This set of regions was then combined with the set of “regions of interest” defined above to produce a set of “enriched regions”. The number of sequencing fragments (reads) overlapping each enriched region (by at least 1 bp) were quantified for each analyte. Counts of reads in all enriched regions between experiments (any region called a peak in at least one sample) were quantile normalized together. Quantile normalized counts of reads in the regions of interest were corrected for local ChlP-seq background to improve signal-to-noise.
  • Promoter and enhancer epigenomic activation signals were ctDNA corrected independently.
  • ichorCNA estimated values for each sample and regressed the log of the normalized, corrected counts against logit-transformed estimated ctDNA% with standard linear regression, and then subtracted the estimated percent of each count due to ctDNA% based on its regression weight. Corrected enhancer and promoter counts were summed for F0LH1 to produce an integrated activation score. The mean and standard-deviation of the summed enhancer and promoter counts within the healthy volunteers were used to calculate a z- score for each patient sample, which was then logged and 0-1 scaled for the final activation score.
  • Genomic coordinates of an exemplary H3K4me3 peak and an exemplary H3K27ac peak are provided in Table 5.
  • Table 5 Exemplary genomic coordinates of H3K4me3 and H3K27ac peaks for FOLH1.
  • Figs. 10(A) and (B) shows a trend line and confidence intervals for promoter signal (H3K4me3) and enhancer signal (H3K27ac), respectively, based on ctDNA% for PSMA.
  • the present Example provides further clinical trial data demonstrating that technologies described herein can predict responsiveness to treatment with a PSMA-targeted therapy (Pluvicto in the present Example).
  • the present Example provides data demonstrating that technologies provided herein can predict clinicoradiographic (CR) PFS, which provides a holistic assessment of progression by a clinician based on the totality of clinical data (including radiographic results).
  • this metric may more accurately reflect response to treatment with a PSMA-targeted agent (compared to PSA- PFS, time to next treatment (TTNT), and/or overall survival (OS).
  • Fig. 11 shows a comparison of CR PFS outcomes for subjects in (i) the bottom and middle tertiles of PSMA PET SUVmean values as compared to (ii) subjects in the top tertile.
  • technologies described herein were shown to be strong predictors of responsiveness of a PSMA-targeted therapy.
  • ctDNA% was measured for each patient, and patients were split into tertiles on the basis of ctDNA%.
  • Outcomes for four clinical trial metrics (PSA, time to next treatment, CR PFS, and overall survival) were compared for patients having a ctDNA% in the top tertile vs. patients having a ctDNA% in the middle and bottom tertiles. Results are shown in Figs. 12(A)-(D). As shown, ctDNA% was predictive of each of the clinical trial outcomes tested.
  • Predicted PSMA PET SUVmean was also shown to predict patient response to treatment, (see, e.g., Fig. 11, showing an HR of 0.27 for predicted PSMA PET SUVmean). This data demonstrates that technologies described herein, which use epigenetic modifications to predict PSMA PET SUVmean, can provide a predictor of responsiveness to a PSMA-targeted agent.

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Abstract

The present disclosure includes, among other things, methods, kits, and systems for measuring PSMA and PSA expression in a subject. In various embodiments, the present disclosure relates to the use of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation that are associated with PSA and PSMA expression levels. In some embodiments, differential modifications and/or differential accessibility are detected and quantified at one or more genomic loci of a biological sample, e.g., in cell-free DNA (cfDNA) or circulating tumor DNA (ctDNA) from a liquid biopsy sample obtained or derived from a subject with prostate cancer (e.g., mCRPC). In various embodiments a determined status is useful, e.g., in selecting treatment for and/or treating prostate cancer (e.g., mCRPC).

Description

METHODS, KITS AND SYSTEMS FOR MEASURING PSA AND PSMA EXPRESSION AND METHODS FOR TREATING CANCER BASED ON SAME
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. Provisional Application No. 63/575,697, filed on 06 April 2024; and U.S. Provisional Application No. 63/692,119, filed on 08 September 2024; the entire contents of each of which is incorporated by reference herein in its entirety.
BACKGROUND
[0002] Prostate cancer (PCa) is currently the second most commonly diagnosed solid tumor and the fifth leading cause of cancer-related death in men worldwide, with 268,490 estimated new cases in the year 2022. Moreover, in the last decade, the incidence of metastatic PCa diagnosis has been rising, increasing from 3.9% in 2007 to 8.2% in 2018.
[0003] PSMA (Prostate-Specific Membrane Antigen), is a cell surface protein that is highly expressed in prostate cancer. PSMA has emerged as a key biomarker for diagnosis and prognosis of patients with prostate cancer. PSMA-targeting therapeutics (e.g., antibody-drug conjugates and radioimmune conjugates) have also been developed as one modality for treating patients having a prostate cancer. For such therapeutics, PSMA expression level is commonly used as a criteria for determining patient eligibility for treatment.
[0004] Current methods for assessing PSMA expression level in tumors rely on PET imaging using radiolabeled ligands. No blood-based marker has been developed to date that can be used to determine tumor specific expression of PSMA.
[0005] Prostate-specific antigen (PSA), also known as gamma-seminoprotein or kallikrein-3 (KLK3), P-30 antigen, is a glycoprotein enzyme encoded in humans by the KLK3 gene. PSA is present in small quantities in the serum of men with healthy prostates, but is often elevated in the presence of prostate cancer or other prostate disorders. As such, PSA can be used to screen for prostate cancer. SUMMARY
[0006] The present disclosure is based, at least in part, on the demonstration that PSMA expression level in a subject can be measured by detecting and quantifying the presence of histone modifications and/or DNA methylation at one or more genomic loci in cell-free DNA (cfDNA) from a liquid biopsy sample, e.g., a plasma sample obtained or derived from a subject. Among other things, the present disclosure demonstrates that PSMA expression level can be determined in cancer cells in a subject, including, e g., PSMA expression level in prostate cancer (e.g., mCRPC).
[0007] The present disclosure also demonstrates that PSMA expression level determined by detecting histone modifications and/or DNA methylation at one or more genomic loci in cfDNA from a liquid biopsy sample (e.g., a plasma sample) can be used as a proxy for established biomarkers for, e.g., monitoring, characterizing, diagnosing, and prognosing disease and/or determining patient eligibility for certain therapeutics. Among other biomarkers, technologies described herein can be used to predict PSMA PET measurements (e.g., PSMA PET SUVmean). As demonstrated in the Examples of the present disclosure, PSMA PET measurements predicted by technologies described herein have been shown to closely match actual PSMA PET measurements and also to be predictive of response to PSMA-targeted agents in patients.
[0008] The present disclosure also demonstrates that PSA expression level in a subject can be measured or predicted by detecting and quantifying the presence of histone modifications and/or DNA methylation at one or more genomic loci in cell-free DNA (cfDNA) from a liquid biopsy sample, e.g., a plasma sample obtained or derived from a subject. Technologies described herein for measuring or predicting PSA expression can provide certain advantages as compared to assays that measure PSA protein concentrations directly (e.g., via ELISA or an enzymatic assay). Among other things, technologies described herein can be combined with one or more additional technologies that comprise measuring epigenome modifications (e.g., technologies described herein that comprise measuring PSMA expressing or predicting PSMA PET signal), allowing for multiple epigenome measurements to obtained using a single sample (which, in some embodiments, can comprise a small volume of sample (e.g., 5 mb or less, or about 1 mL of plasma). Use of single sample is advantageous as it allows for, e.g., a reduced number of sample processing steps (i.e., epigenome measurements only have to be collected once, and can be used to perform multiple analytes), and improved patient convenience.
[0009] The present disclosure encompasses methods that quantify the presence of histone modifications and/or DNA methylation, as well as methods that assess chromatin accessibility and/or binding of one or more transcription factors at one or more genomic loci instead of (or in addition to) histone modifications and/or DNA methylation.
[0010] Liquid biopsies are now widely utilized in clinical oncology to detect cancer recurrence and inform therapeutic decisions. However, most commercially available cfDNA assays only detect genetic mutations and not all disease states have a characteristic mutation that can be used for detection. Technologies that detect epigenetic modifications offer numerous benefits over assays that detect genetic mutations, including, e.g., allowing the detection of disease states that a characteristic mutation has not been identified for, and/or providing measurements that are more directly relevant to a biological characteristic of interest (e.g., detecting increased transcription activation of a gene, rather than a mutation that has been previously shown to be correlated with activation for some subjects).
[0011] Among other things, the present disclosure provides tools to analyze multiple epigenomic features from patient plasma, including DNA methylation, chromatin accessibility, and histone modifications. Among other things, the present disclosure demonstrates that epigenomic cfDNA profiling can be used to detect PSMA and/or expression levels as well as characterize disease severity, prognose patients, evaluate patient eligibility for certain therapeutics, and inform methods of treatment.
[0012] Diagnosing and monitoring of prostate cancer (e.g., mCRPC) by cfDNA profiling would be immediately clinically actionable, as guidelines currently recommend that prostate cancer be monitored using imaging methods that assess PSMA expression in tumors and administering certain therapeutics to patients on the basis of PSMA expression level.
[0013] The present disclosure includes, among other things, technologies for determining PSMA expression level and for the detection, monitoring, and/or treatment of prostate cancer based on PSMA expression level. In various embodiments, the present disclosure relates to the measurement of histone modifications in a sample obtained or derived from a subject to detect and/or treat prostate cancer based on PSMA expression level. The present disclosure includes, among other things, histone modification measurements in cell-free DNA (cfDNA) that are associated with PSMA expression level, and which in various embodiments are useful, e.g., for detecting, monitoring, selecting treatment for, and/or treating prostate cancer. The present disclosure includes, among other things, histone modification measurements in cfDNA that are associated with increased PSMA expression, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating prostate cancer (e.g., mCRPC). In some embodiments, histone modification measurements in cfDNA can be used to detect or determine responsiveness of prostate cancer (e.g., mCRPC) to a therapy. In some embodiments, histone modification measurements in cfDNA can be used to monitor or predict progression of prostate cancer (e.g., mCRPC). In some embodiments, histone modification measurements in cfDNA can be used to inform therapeutic selection for a subject with prostate cancer (e.g., determine an initial therapy, predict patients that are likely to respond to a given therapy, and/or determine when therapy should be changed for a subject). In some embodiments, histone modification measurements in cfDNA can be used as a complement to other diagnostic methods (e.g., imaging methods, histology methods, and/or symptom-based methods) for monitoring and/or treating prostate cancer (e g., performed concurrently and/or subsequent to other methods).
[0014] In some embodiments, a method of described herein can be performed in combination with one or more diagnostic assays that do not comprise measuring one or more epigenome features. In some embodiments, a method described herein can be performed in combination with one or more diagnostic assays for prostate cancer that use PSA level, biopsy measurements, histology measurements, and/or medical imaging tests. In some embodiments, technologies described herein can be used to screen patients (e.g., identify patients for treatment, diagnosis, etc.) to identify patients that may benefit from being tested using one or more additional diagnostic assays. In some embodiments, technologies described herein can be performed in conjunction with one or more diagnostic assays that do not comprise measuring one or more epigenome features. In some embodiments, technologies described herein can be used for subjects that have been previously screened using one or more diagnostic assays that do not comprise measuring one or more epigenome features. In some embodiments, wherein a disease or disorder associated with elevated PSA or PSMA expression is prostate cancer, a method can be performed on a subject who has already been screened using one or more diagnostic assays for prostate cancer, e.g., one or more diagnostic assays described herein).
[0015] In various embodiments, the present disclosure includes exemplary genomic loci whose epigenetic modification status is associated with PSMA expression level. In various embodiments, these genomic loci are or include one or more enhancers regions. In various embodiments, these genomic loci are or include one or more promoter regions.
[0016] The present disclosure includes, among other things, technologies for determining PSA expression level and for the detection, monitoring, and/or treatment of prostate cancer and/or the selection of subjects for further screening for prostate cancer based on PSA expression level. In various embodiments, the present disclosure relates to the measurement of histone modifications in a sample obtained or derived from a subject to detect and/or treat prostate cancer based on PSA expression level. The present disclosure includes, among other things, histone modification measurements in cell-free DNA (cfDNA) that are associated with PSA expression level, and which in various embodiments are useful, e.g., for detecting, monitoring, selecting treatment for, and/or treating prostate cancer. The present disclosure includes, among other things, histone modification measurements in cfDNA that are associated with increased PSA expression, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating prostate cancer (e.g., mCRPC) or for identifying subjects for further screening for prostate cancer. In some embodiments, histone modification measurements in cfDNA can be used to detect or determine responsiveness of prostate cancer (e.g., mCRPC) to a therapy. In some embodiments, histone modification measurements in cfDNA can be used to monitor or predict progression of prostate cancer (e.g., mCRPC). In some embodiments, histone modification measurements in cfDNA can be used to inform therapeutic selection for a subject with prostate cancer (e.g., determine an initial therapy, predict patients that are likely to respond to a given therapy, and/or determine when therapy should be changed for a subject). In some embodiments, histone modification measurements in cfDNA can be used as a complement to other diagnostic methods (e.g., imaging methods and/or symptom-based methods) for detecting, monitoring, and/or treating prostate cancer (e.g., performed concurrently and/or subsequent to other methods). [0017] In various embodiments, the present disclosure includes exemplary genomic loci whose epigenetic modification status is associated with PSA expression level. In various embodiments, these genomic loci are or include one or more enhancer regions. In various embodiments, these genomic loci are or include one or more promoter regions.
[0018] In various embodiments, a genomic locus is differentially modified if it is characterized by increased or decreased histone modification as compared to a reference (e.g., a sample from a healthy subject). Increased or decreased histone modification can be or include, e.g., increased or decreased histone methylation (hypermethylation or hypomethylation, respectively) of one or more particular methylation marks, or a combination thereof; increased or decreased pan-methylation; increased or decreased histone acetylation (hyperacetylation or hypoacetylation, respectively) of one or more particular acetylation marks, or a combination thereof; and/or increased or decreased pan-acetylation (e.g., pan-H3 acetylation). In various embodiments, histone methylation can be or include histone methylation marks selected from H3K4mel, H3K4me2, H3K4me3, or a combination thereof. In various embodiments, histone methylation can be or include H3K4me3. In various embodiments, histone acetylation can be or include histone acetylation marks selected from H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, or a combination thereof. In various embodiments, histone acetylation can be or include H3K27ac. In some embodiments, a healthy subject is a subject who has not been diagnosed with an indication or disease. In some embodiments, a healthy subject is a subject who has not been diagnosed with a cancer, who has not previously been diagnosed with cancer, and/or who has not been found to exhibit one or more symptoms associated with cancer (e.g., not been found to exhibit one or more symptoms associated with cancer within the last 10 years, 5 years, 4 years, 3, years, 2 years, or 1 year).
[0019] In various embodiments, the present disclosure relates to the measurement of DNA methylation in a sample obtained or derived from a subject to detect PSMA expression level and/or treat prostate cancer. The present disclosure includes, among other things, DNA methylation measurements in cell-free DNA (cfDNA) that are characteristic of PSMA expression level, and which in various embodiments are useful, e.g., for detecting, monitoring, selecting treatment for, and/or treating prostate cancer. The present disclosure includes, among other things, DNA methylation measurements in cfDNA that are associated with PSMA expression levels, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating prostate cancer. The present disclosure includes, among other things, DNA methylation measurements in cfDNA that are characteristic of increased PSMA expression in a tumor, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating prostate cancer. In some embodiments, DNA methylation measurements in cfDNA can be used to predict or determine responsiveness of prostate cancer to a therapy. In various embodiments, the present disclosure includes exemplary genomic loci that are differentially DNA methylated when PSMA expression is increased. In various embodiments, a genomic locus is differentially modified if it is characterized by increased or decreased DNA methylation as compared to a reference (e.g., a sample from a healthy subject). In various embodiments, genomic loci differentially modified in cfDNA are or include one or more enhancers. In various embodiments, genomic loci differentially modified in cfDNA are or include one or more promoters.
[0020] In various embodiments, the present disclosure relates to the measurement of DNA methylation in a sample obtained or derived from a subject to detect PSA expression level and/or treat prostate cancer. The present disclosure includes, among other things, DNA methylation measurements in cell-free DNA (cfDNA) that are characteristic of PSA expression level, and which in various embodiments are useful, e.g., for detecting, monitoring, selecting treatment for, treating, and/or screening for prostate cancer. The present disclosure includes, among other things, DNA methylation measurements in cfDNA that are associated with PSA expression levels, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, treating, and/or screening for prostate cancer. In some embodiments, DNA methylation measurements in cfDNA can be used to predict or determine responsiveness of prostate cancer to a therapy. In various embodiments, the present disclosure includes exemplary genomic loci that are differentially DNA methylated when PSA expression is increased. In various embodiments, a genomic locus is differentially modified if it is characterized by increased or decreased DNA methylation as compared to a reference (e.g., a sample from a healthy subject). In various embodiments, genomic loci differentially modified in cfDNA are or include one or more enhancers. In various embodiments, genomic loci differentially modified in cfDNA are or include one or more promoters. [0021] The present disclosure further relates, in various embodiments, to the measurement of chromatin accessibility in cell-free DNA (cfDNA) to determine PSMA expression level. The present disclosure includes, among other things, chromatin accessibility measurements in cfDNA that are characteristic of increased PSMA expression in a tumor, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating prostate cancer. The present disclosure includes, among other things, chromatin accessibility measurements in cfDNA that are characteristic of increased PSMA expression, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating prostate cancer. In some embodiments, chromatin accessibility measurements in cfDNA can be used to detect or determine resistance of prostate cancer to a therapy. In various embodiments, the present disclosure includes genomic loci that are differentially accessible when PSMA expression is increased. In various embodiments, genomic loci differentially accessible in cfDNA are or include one or more enhancers. In various embodiments, genomic loci differentially accessible in cfDNA are or include one or more promoters.
[0022] The present disclosure further relates, in various embodiments, to the measurement of chromatin accessibility in cell-free DNA (cfDNA) to determine PSA expression level. The present disclosure includes, among other things, chromatin accessibility measurements in cfDNA that are characteristic of increased PSA expression in a tumor, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, treating, and/or screening for prostate cancer. The present disclosure includes, among other things, chromatin accessibility measurements in cfDNA that are characteristic of increased PSA expression, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, treating, and/or screening for prostate cancer. In some embodiments, chromatin accessibility measurements in cfDNA can be used to detect or determine resistance of prostate cancer to a therapy. In various embodiments, the present disclosure includes genomic loci that are differentially accessible when PSA expression is increased. In various embodiments, genomic loci differentially accessible in cfDNA are or include one or more enhancers. In various embodiments, genomic loci differentially accessible in cfDNA are or include one or more promoters. [0023] In various embodiments, without wishing to be bound by any particular scientific theory, histone methylation (e.g., H3K4me3) corresponds and/or is correlated with chromatin accessibility. In various embodiments, without wishing to be bound by any particular scientific theory, histone acetylation (e.g., H3K27ac) corresponds and/or is correlated with chromatin accessibility. In various embodiments, without wishing to be bound by any particular scientific theory, DNA methylation corresponds and/or is correlated with chromatin accessibility.
[0024] In various embodiments, a genomic locus is differentially accessible if it is characterized by increased or decreased chromatin accessibility as compared to a reference (e.g., a sample from a healthy subject). Increased or decreased chromatin accessibility can be or include, e.g., increased or decreased accessibility as determined by various chromatin accessibility assays known in the art.
[0025] The present disclosure further relates, in various embodiments, to the measurement of transcription factor binding in cell-free DNA (cfDNA) to determine PSMA expression level. The present disclosure includes, among other things, transcription factor binding measurements in cfDNA that are characteristic of increased PSMA expression, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating prostate cancer. In some embodiments, transcription factor binding measurements in cfDNA can be used to detect or determine resistance of prostate cancer to a therapy. In various embodiments, the present disclosure includes genomic loci that are differentially bound by transcription factors when PSMA expression is increased. In various embodiments, genomic loci that are differentially bound by transcription factors in cfDNA are or include one or more enhancers. In various embodiments, genomic loci that are differentially bound by transcription factors in cfDNA are or include one or more promoters.
[0026] The present disclosure further relates, in various embodiments, to the measurement of transcription factor binding in cell-free DNA (cfDNA) to determine PSA expression level. The present disclosure includes, among other things, transcription factor binding measurements in cfDNA that are characteristic of increased PSA expression, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, screening for, and/or treating prostate cancer. In some embodiments, transcription factor binding measurements in cfDNA can be used to detect or determine resistance of prostate cancer to a therapy. In various embodiments, the present disclosure includes genomic loci that are differentially bound by transcription factors when PSA expression is increased. In various embodiments, genomic loci that are differentially bound by transcription factors in cfDNA are or include one or more enhancers. In various embodiments, genomic loci that are differentially bound by transcription factors in cfDNA are or include one or more promoters.
[0027] In various embodiments, without wishing to be bound by any particular scientific theory, histone methylation (e.g., H3K4me3) corresponds and/or is correlated with transcription factor binding. In various embodiments, without wishing to be bound by any particular scientific theory, histone acetylation (e.g., H3K27ac) corresponds and/or is correlated with transcription factor binding. In various embodiments, without wishing to be bound by any particular scientific theory, DNA methylation corresponds and/or is correlated with transcription factor binding.
[0028] In various embodiments, a genomic locus is differentially bound by transcription factors if it is characterized by increased or decreased transcription factor binding as compared to a reference (e.g., a sample from a healthy subject). Increased or decreased transcription factor binding can be or include, e.g., increased or decreased transcription factor binding as determined by various transcription factor binding assays known in the art.
[0029] In one aspect, the present disclosure provides a method of determining PSMA expression level in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject: (i) one or more histone modifications, (ii) chromatin accessibility, (iii) binding of one or more transcription factors, and/or (iv) DNA methylation.
[0030] In some embodiments, the one or more histone modifications are quantified using a histone modification assay that measures one or more of H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, H3K4me3, and pan-acetylation. In some embodiments, the histone modification assay detects H3K4me3 modifications. In some embodiments, the histone modification assay detects H3K27ac modifications. In some embodiments, the histone modification assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing. [0031] In some embodiments, chromatin accessibility is quantified using a chromatin accessibility assay selected from ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde- Assisted Isolation of Regulatory Elements sequencing), MNase-seq (Micrococcal Nuclease digestion with sequencing), a Dnase hypersensitivity assay, and a fragmentomics assay.
[0032] In some embodiments, binding of one or more transcription factors is quantified using a transcription factor binding assay. In some embodiments, the transcription factor binding assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
[0033] In some embodiments, DNA methylation is quantified using Bisulfite sequencing (BS-Seq), Whole Genome Bisulfite Sequencing (WGBS), Methylated DNA ImmunoPrecipitation sequencing (MeDIP-seq), or Methyl-CpG-Binding Domain sequencing (MBD-seq).
[0034] In some embodiments, a method comprises quantifying two or more of the following, each at one or more genomic loci in cell-free DNA (cfDNA) from a liquid biopsy sample obtained or derived from the subject: (i) one or more histone modifications, (ii) chromatin accessibility, (iii) transcription factor binding, and/or (iv) DNA methylation. In some embodiments, the method comprises quantifying two or more histone modifications, e.g., quantifying H3K4me3 and H3K27ac modifications. In some embodiments, a method comprises quantifying one or more histone modifications and DNA methylation, e.g., quantifying H3K4me3 and/or H3K27ac modifications and DNA methylation. In some embodiments, a method comprises quantifying H3K4me3 modifications, H3K27ac modifications and DNA methylation.
[0035] In some embodiment, a biological sample is a liquid biopsy sample, e.g., a plasma sample, serum sample, or urine sample.
[0036] In some embodiments, quantification of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at the one or more genomic loci as compared to a reference indicates that the subject has increased PSMA expression. Tn some embodiments, the reference is a predetermined threshold, a measurement from a liquid biopsy sample, and/or a normalized value, optionally wherein the reference is a measurement from a liquid biopsy sample obtained from a cohort of healthy subjects.
[0037] Among other things, the present disclosure describes a method of measuring PSMA expression in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility,
(iii) binding of one or more transcription factors, and/or
(iv) DNA methylation.
[0038] In some embodiments, technologies described herein comprise or can be used to measure PSMA expression and/or predict medical imaging results (e.g., PSMA PET imaging results). In some embodiments, a method for measuring PSMA expression measures PSMA expression specific to one or more tumors in a subject. In some embodiments, PSMA expression comprises cell surface expression. In some embodiments, PSMA expression comprises tumor cell specific expression. In some embodiments, PSMA expression comprises tumor specific, cell surface expression of PSMA.
[0039] Among other things, the present disclosure describes a method of predicting tumor specific PSMA expression as determined using (i) an imaging procedure, (ii) a radioligand, and/or (iii) PSMA PET imaging (e.g., PSMA PET SUVmean)) in a subject. In some embodiments, the method of predicting comprises measuring PSMA expression using a method described herein. In some embodiments, the method of predicting comprises: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility, (iii) binding of one or more transcription factors, and/or
(iv) DNA methylation.
[0040] In some embodiments, one or more histone modifications are quantified using a histone modification assay that measures H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, H3K4me3, or pan-acetylation, or any combination thereof.
[0041] In some embodiments, a histone modification assay detects H3K4me3 modifications.
[0042] In some embodiments, a histone modification assay detects H3K27ac modifications.
[0043] In some embodiments, a histone modification assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
[0044] In some embodiments, chromatin accessibility is quantified using a chromatin accessibility assay selected from ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde-Assisted Isolation of Regulatory Elements sequencing), Mnase-seq (Micrococcal Nuclease digestion with sequencing), a Dnase hypersensitivity assay, and a fragmentomics assay. [0045] In some embodiments, binding of one or more transcription factors is quantified using a transcription factor binding assay.
[0046] In some embodiments, a transcription factor binding assay is selected from ChlP- seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
[0047] In some embodiments, DNA methylation is quantified using Bisulfite sequencing (BS-Seq), Whole Genome Bisulfite Sequencing (WGBS), Methylated DNA ImmunoPrecipitation sequencing (MeDIP-seq), or Methyl-CpG-Binding Domain sequencing (MBD-seq). [0048] In some embodiments, a method described herein comprises quantifying two or more of the following, each at one or more genomic loci in cell-free DNA (cfDNA) from a liquid biopsy sample obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility,
(iii) transcription factor binding, and/or
(iv) DNA methylation.
[0049] In some embodiments, a method described herein comprises quantifying two or more histone modifications. In some embodiments, a method described herein comprises quantifying H3K4me3 and H3K27ac modifications. In some embodiments, a method described herein comprises quantifying one or more histone modifications and DNA methylation. In some embodiments, a method described herein comprises quantifying H3K4me3 and/or H3K27ac modifications and DNA methylation. In some embodiments, a method described herein comprises quantifying H3K4me3 modifications, H3K27ac modifications, and DNA methylation. [0050] In some embodiments, a liquid biopsy sample is a plasma sample, serum sample, or urine sample.
[0051] In some embodiments, an increase of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci as compared to a reference indicates that a subject has increased PSMA expression (e.g., increased as compared to a healthy subject).
[0052] In some embodiments, a method described herein comprises measuring one or more prostate cancer specific markers. In some embodiments, one or more prostate cancer specific markers comprise PSA expression (e.g., PSA serum level). In some embodiments, PSA expression is measured by measuring PSA protein concentrations (e.g., via an ELISA assay and/or an enzymatic assay). In some embodiments, PSA expression is measured by quantifying histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci (e.g., using technologies described in the present disclosure). In some embodiments, a method comprises measuring PSMA expression or predicting PSMA expression (e.g., predicting a PSMA PET measurement) and measuring one or more prostate cancer specific markers. [0053] In some embodiments, a method described herein comprises quantifying one or more histone modifications and/or DNA methylation at one or more prostate cancer specific marker genes or regulatory regions thereof (e.g., one or more promoters and/or enhancers of one or more prostate cancer specific marker genes).
[0054] In some embodiments, one or more prostate cancer specific marker genes comprise HXBI3, KLK2, KLK3, SPDEF, or FOLH1, or any combination thereof.
[0055] In some embodiments, a method described herein comprises quantifying one or more histone modifications and/or DNA methylation for one or more of AMN, ARHGEF37, Clorf 36, CADM1, CCDC175, CDC7, CLSTN1, COL5A1, EDNRA, FOLH1, GALR3, MED13L, MICB, NDRG3, NEDD1, NPAS2, NPVF, OLFM1, PCBP4, PROZ, PRRG3, RREB1, SCUBE3, SERPINA5, SNRPF, SORCS3, ST8SIA5, TEX19, TMEM132B, or TTC29 or any combination thereof, or one or more regulatory regions of any one of the foregoing (e.g., one or more promoter and/or enhancer regions oiAMN, ARHGEF37, C4orf36, CADM1, CCDC175, CDC7, CLSTNI, COL5A1, EDNRA, FOLH1, GALR3, MED13L, MICB, NDRG3, NEDD1, NPAS2, NPVF, 0LFM1, PCBP4, PROZ, PRRG3, RREBl, SCUBE3, SERPINA5, SNRPF, SORCS3, ST8SIA5, TEX19, TMEM I32B, or TIC 29, or any combination thereof).
[0056] Among other things, the present disclosure provides exemplary genomic loci that are associated with PSMA expression and can be used to measure PSMA expression (e.g., tumor specific PSMA expression). Exemplary genomic loci include those provided in Tables 1 and 2.
[0057] In some embodiments, a method described herein comprises quantifying:
(a) promoter signal (e.g., H3K4me3) at one or more promoter regions of C4orf36, CADM1, CDC7, COL5A1, EDNRA, MED13L, NEDD1, PROZ, SNRPF, TEX19, or any combination thereof,
(b) enhancer signal (e.g., H3K27ac signal) at one or more enhancer regions of ARHGEF37, CLSTNI, FOLH1, NDRG3, NPAS2, NPVF, 0LFM1, RREBl, SCUBE3, or TTC29, or any combination thereof;
I DNA methylation of AMN, CCDCI75, GALR3, MICB, PCBP4, PRRG3, SERP1NA5, SORCS3, SI8SIA5, TMEM132B, or any combination thereof; or d) any combination of (a)-(c).
[0058] In some embodiments, a method described herein comprises quantifying: (a) promoter signal (e.g., H3K4me3 modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K4me3 analyte genomic loci in Table 1;
(b) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 1;
(c) DNA methylation for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 MBD analyte genomic loci in Table 1; or
(d) or any combination of (a)-(c).
[0059] In some embodiments, a method described herein comprises:
(a) quantifying enhancer signal (e.g., H3K27ac modifications) at one or more (e.g., all) of genomic loci 1-8 in Table 2;
(b) quantifying promoter signal (e.g., H3K4me3 modifications) at genomic locus 9 in Table 2; or
(c) a combination of (a) and (b).
[0060] In some embodiments, a method described herein comprises:
(a) aggregating promoter signal (e.g., H3K4me3 modifications) for one or more genomic loci;
(b) aggregating enhancer signal (e.g., H3K27ac modifications) for one or more genomic loclor
(c) a combination of (a) and (b).
[0061] In some embodiments, a method described herein comprises quantifying:
(a) promoter signal (e.g., H3K4me3 modifications) for 1 or 2 H3K4me3 analyte genomic loci in Table 4;
(b) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 4;
(c) or a combination of (a) and (b).
[0062] In some embodiments, a method described herein comprises quantifying (a) promoter signal (e.g., H3K4me3 modifications) at chrl 1 :49,228,902-49,230,855; and/or (b) enhancer signal (e.g., H3K27ac modifications) at chrl 1 :49, 229, 019-49, 230, 275.
[0063] In some embodiments, promoter signal and enhancer signal at each genomic locus are aggregated. In some embodiments, promoter signal and enhancer signal are separately aggregated. In some embodiments, promoter signal and enhancer signal are separately aggregated, and the aggregated promoter signal and aggregated enhancer signal are aggregated in an additional step. In some embodiments, promoter signal and enhancer signal are aggregated in a single step.
[0064] In some embodiments, promoter signal and enhancer signal are normalized prior to aggregating (e.g., normalized based on sequence read depth or ctDNA fraction).
[0065] In some embodiments, aggregating comprises summing epigenetic modification signal (e.g., H3K4me3 and/or H3K27ac signal) at two or more loci. In some embodiments, signal is corrected prior to summing. In some embodiments, correcting comprises adjusting for (i) sequencing depth, (ii) background signal (e.g., signal in healthy subjects), (iii) the length of a genomic locus, or any combination of (i)-(iii). In some embodiments signal (optionally corrected signal) at each locus is weighted when aggregated. In some embodiments, weighting entails multiplying by a coefficient that has been determined using a model trained to predict PSA or PSMA expression.
[0066] In some embodiments, promoter signal and enhancer signal are separately aggregated, and then the aggregated promoter signal and enhancer signal are aggregated in a second aggregation step. In some embodiments, promoter signal and enhancer signal are aggregated together (i.e., without an intervening aggregation step).
[0067] In some embodiments, a biological sample (e.g., a plasma sample) comprises a ctDNA fraction of at least 0.03.
[0068] In some embodiments, a subject has previously been diagnosed with a disease or condition that is associated with increased PSMA expression. In some embodiments, a disease or condition that is associated with increased PSMA expression is cancer. In some embodiments, a disease or indication associated with PSMA expression is prostate cancer. In some embodiments, prostate cancer is mCRPC (metastatic castration resistant prostate cancer). In some embodiments, prostate cancer is prostate adenocarcinoma (PRAD). In some embodiments prostate cancer is neuroendocrine prostate cancer (NEPC).
[0069] In some embodiments, a subject has previously been diagnosed with a disease or condition that is associated with increased PSA expression. In some embodiments, a disease or condition that is associated with increased PSA expression is cancer. In some embodiments, a disease or indication associated with PSA expression is prostate cancer. In some embodiments, prostate cancer is mCRPC (metastatic castration resistant prostate cancer). In some embodiments, prostate cancer is prostate adenocarcinoma (PRAD). In some embodiments prostate cancer is neuroendocrine prostate cancer (NEPC).
[0070] In some embodiments, one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and DNA/or DNA methylation is quantified in a subject before the subject is administered a PSMA-targeted agent.
[0071] Among other things, the present disclosure describes a method of measuring PSA expression in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) or circulating tumor DNA (ctDNA) from a liquid biopsy sample, obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility, iii) binding of one or more transcription factors, and/or
(iv) DNA methylation.
[0072] Among other things, the present disclosure describes a method of predicting PSA expression in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) or circulating tumor DNA (ctDNA) from a liquid biopsy sample, obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility,
(iii) binding of one or more transcription factors, and/or
(iv) DNA methylation.
[0073] In some embodiments, PSA expression is or comprises serum PSA concentration.
[0074] In some embodiments, a method measures or predicts PSA expressed by one or more cancer cells in the subject.
[0075] In some embodiments, a method measures or predicts serum concentration of total PSA. [0076] In some embodiments, a method predicts PSA expression as determined using an assay that (a) utilizes one or more antibodies that bind PSA (e.g., an ELISA assay) and/or (b) measures PSA enzymatic activity.
[0077] In some embodiments, a method comprises
(i) quantifying enhancer signal (e.g., H3K27ac modifications) at one or more loci within 200 kB of a KLK3 gene;
(ii) quantifying enhancer signal (e.g., H3K27ac modifications) at one or more loci within 200 kB of a KLK3 gene;
(iii) quantifying DNA methylation at one or more loci within 200 kB of a KLK3 gene; or
(iv) any combination of (i)-(iii).
[0078] In some embodiments, a method comprises quantifying enhancer signal (e.g., H3K27ac modifications) at one or more (e.g., all) genomic loci in Table 3.
[0079] In some embodiments, a method comprises (i) measuring PSMA expression or predicting PSMA expression (e.g., predicting PSMA PET imaging measurements), e.g., using technologies described herein, and (ii) measuring PSA expression or predicting PSA expression, e.g., using a technology described herein and/or by measuring protein expression directly (e.g., using an ELISA assay or an enzymatic assay).
[0080] In some embodiments, a subject has previously been diagnosed with a disease or condition that is associated with increased PSA expression.
[0081] In some embodiments, a biological sample (e.g., a liquid biopsy sample) comprises a ctDNA fraction of at least 0.03%, at least 0.05%, or at least 0.10%.
[0082] In some embodiments, a liquid biopsy sample is a plasma sample, serum sample, or urine sample.
[0083] In some embodiments, a subject has previously been diagnosed with cancer. In some embodiments, a subject has previously been diagnosed with breast cancer. In some embodiments, a subject has previously been diagnosed with prostate cancer. In some embodiments, a subject has previously been diagnosed with lung cancer. In some embodiments, a subject has previously been diagnosed with small cell lung cancer (SCLC). [0084] In some embodiments, a prostate cancer is metastatic castration resistant prostate cancer (mCRPC). In some embodiments, a subject has previously been administered an androgen receptor pathway inhibitor (ARPI) therapy. In some embodiments, it has been determined to be appropriate to delay administering a taxane-based chemotherapy to a subject. In some embodiments, a subject has not previously received taxane-based chemotherapy.
[0085] In some embodiments,
(i) a prostate cancer is metastatic castration resistant prostate cancer (mCRPC);
(ii) a subject has previously been administered an androgen receptor pathway inhibitor (ARPI) therapy;
(iii) it has been determined to be appropriate to delay administering a taxane-based chemotherapy to a subject or a subject has previously received taxane-based chemotherapy; or
(iv) any combination of (i)-(iii).
[0086] In some embodiments, a prostate cancer is prostate adenocarcinoma (PRAD) or neuroendocrine prostate cancer (NEPC).
[0087] Among other things, the present disclosure describes a method of identifying a subject with elevated PSMA expression. In some embodiments, a method of identifying a subject with elevated PSMA expression comprises use of a technology described herein for measuring PSMA expression and/or predicting PSMA expression. In some embodiments a method of identifying a subject with elevated PSMA expression comprises:
(a) measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) using a method described herein, and
(b) comparing the measured PSMA expression or predicted tumor specific PSMA expression to a reference.
[0088] Among other things, the present disclosure describes a method of identifying a subject with elevated PSA expression. In some embodiments, a method of identifying a subject with elevated PSA expression comprises use of a technology described herein for measuring PSA expression and/or predicting PSA expression. In some embodiments, a method of identifying a subject with elevated PSA expression, comprising:
(a) measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total PSA) using a method described herein, and (b) comparing the measured or predicted PSA expression to a reference.
[0089] Among other things, described herein is a method of diagnosing a subject as having a disease or disorder associated with elevated PSMA expression. In some embodiments, a method of diagnosing a subject as having a disease or disorder associated with elevated PSMA expression comprises use of a technology described herein to measure PSMA expression or predict PSMA expression. In some embodiments, a method of diagnosing a subject as having a disease or disorder associated with elevated PSMA expression comprises identifying a subject with elevated PSMA expression. In some embodiments, a method of diagnosing a subject as having a disease or disorder associated with elevated PSMA expression comprises:
(a) measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) using a method described herein, and
(b) comparing the measured PSMA expression or predicted tumor specific PSMA expression to a reference.
[0090] Among other things, described herein is a method of diagnosing a subject as having a disease or disorder associated with elevated PSA expression. In some embodiments, a method of diagnosing a subject as having a disease or disorder associated with elevated PSA expression comprises use of a technology described herein to measure PSA expression or predict PSA expression. In some embodiments, a method of diagnosing a subject as having a disease or disorder associated with elevated PSA expression comprises identifying a subject with elevated PSA expression. In some embodiments, a method of diagnosing a subject as having a disease or disorder associated with elevated PSA expression comprises:
(a) measuring PSA expression or predicting PSA expression using a method described herein, and
(b) comparing the measured PSA expression or predicted PSA expression to a reference.
[0091] In some embodiments, a reference is a predetermined threshold, a measurement from a liquid biopsy sample, a measurement from an imaging test, and/or a normalized value, optionally wherein the reference is a measurement from an imaging test (e.g., PSMA PET SUVmean) or sample obtained from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with a disease or disorder associated with increased PSMA expression.
[0092] In some embodiments, a reference is a predetermined threshold, a measurement from a liquid biopsy sample, a measurement from an imaging test, and/or a normalized value, optionally wherein the reference is a measurement from a test that directly measures the expression of PSA (e.g., using an ELISA assay or an enzymatic assay) obtained from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with a disease or disorder associated with increased PSA expression (e.g., prostate cancer).
[0093] Among other things, described herein is a method of prognosing a subject having a disease or disorder associated with increased PSMA expression (e.g., prostate cancer, including, e g., mCRPC). In some embodiments, a method of prognosing comprises measuring PSMA expression or predicting PSMA expression at two or more time points. In some embodiments, a method of prognosing a subject having a disease or disorder associated with increased PSMA expression comprises:
(a) measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) using a method described herein, and
(b) comparing the measured PSMA expression or predicted tumor specific PSMA expression to a reference.
[0094] Among other things, described herein is a method of prognosing a subject having a disease or disorder associated with increased PSA expression (e.g., prostate cancer, including, e.g., mCRPC). In some embodiments, a method of prognosing comprises measuring PSA expression or predicting PSA expression at two or more time points. In some embodiments, a method of prognosing a subject having a disease or disorder associated with increased PSA expression comprises:
(a) measuring PSA expression or predicting PSA expression using a method described herein, and
(b) comparing the measured PSA expression or predicted PSA expression to a reference. [0095] In some embodiments, a reference is a measurement from a sample taken from a subject at an earlier point in time. In some embodiments, a measurement from a sample taken from a subject at an earlier point in time is from a liquid biopsy sample (e.g., a measurement or prediction obtained using a method described herein). In some embodiments, a measurement from a sample taken from a subject at an earlier point in time is a measurement from an imaging test (e.g., PSMA PET SUVmean). In some embodiments, a measurement from a sample taken from a subject at an earlier point in time is a serum PSA measurement.
[0096] In some embodiments, a reference is a predetermined threshold, a measurement from a liquid biopsy sample, a measurement from an imaging test (e.g., PSMA PET SUVmean), and/or a normalized value, optionally wherein the reference is a measurement from a liquid biopsy sample or imaging test (e.g., PSMA PET SUVmean) obtained from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with the disease or disorder associated with increased PSMA expression.
[0097] In some embodiments, a reference is a PSMA expression level measured, a tumor specific PSMA expression level (e.g., PSMA PET SUVmean) predicted, or a tumor specific PSMA expression level (e.g., PSMA PET SUVmean) measured in a cohort of subjects having the disease or disorder associated with increased PSMA expression.
[0098] In some embodiments, a reference is the median, lower bound of the top tertile, or lower bound of the top quartile value of the PSMA expression level measured, tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) predicted, or tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) measured in a cohort of subjects having a disease or disorder associated with increased PSMA expression; and if the PSMA expression level or predicted tumor specific PSMA expression level determined using a method described herein is equal to or greater than the reference, a subject is predicted to have a higher than normal risk of experiencing worse than normal disease progression as measured by one or more clinical outcomes.
[0099] In some embodiments, a higher-than-normal risk of experiencing a worse than normal disease progression comprises (a) an increased chance (e.g., an increased likelihood, as compared to the mean or median of a relevant patient population) of a disease progressing at a more rapid rate than the mean or median of the relevant patient population (e.g., as measured using one or more clinical trial metrics), (b) an increased chance (e.g., an increased likelihood, as compared to the mean or median of a relevant patient population) of disease regression (e g., recurrence of cancer.
[0100] In some embodiments, technologies described herein can be used to identify a patient that is unlikely to respond to treatment with a therapy (e.g., a PSMA targeted therapy). In some embodiments, a method comprises not administering a PSMA-targeted therapy to a patient that is unlikely to respond to treatment with a PSMA-targeted therapy.
[0101] In some embodiments, a PSMA PET SUVmean median in a cohort of subjects used as a reference is about 4 to about 8, about 5 to about 8, 5 to about 7, about 6 to about 9, about 5, about 6, about 7, or about 8. In some embodiments, the lower bound of the top tertile of PSMA PET SUVmean is about 6 to about 12, about 6 to about 10, about 8 to about 12, about 6, about 7, about 8, about 9, about 10, about 11, or about 12 in a cohort of subjects used as a reference. In some embodiments, the lower bound of the top quartile of PSMA PET SUVmean is about 6 to about 14, about 6 to about 12, about 8 to about 14, about 8, about 9, about 10, about 11, about 12, about 13, or about 14 in a cohort of subjects used as a reference.
[0102] In some embodiments, one or more clinical outcomes include (i) overall survival, (ii) time to next treatment, and/or (iii) progression free survival (e.g., as determined by PSA-PFS (plasma PSA levels) and/or crPFS (clinical or radiological evidence of progression)).
[0103] In some embodiments, a disease or indication associated with increased PSMA expression is cancer. Exemplary cancers include prostate cancer, including, e.g., mCRPC.
[0104] Among other things, the present disclosure describes a method of monitoring progression of a disease (e.g., prostate cancer). In some embodiments, a method of monitoring progression of a disease comprises measuring PSMA expression or predicting PSMA expression at two or more time points. In some embodiments, a method of monitoring progression of a disease associated with elevated PSMA expression comprises, at a first and second point in time:
(a) measuring PSMA expression or predicting tumor specific PSMA expression using a method described herein;
(b) testing whether the subject has elevated PSMA expression or diagnosing the subject using a method described heln; or
(c) prognosing the subject using a method described herein; and (d) comparing PSMA expression, predicted tumor specific PSMA expression, PSMA expression status, diagnosis, or prognosis for the first and the second time point.
[0105] Among other things, the present disclosure describes a method of monitoring progression of a disease (e.g., prostate cancer). In some embodiments, a method of monitoring progression of a disease comprises measuring PSA expression or predicting PSA expression at two or more time points. In some embodiments, a method of monitoring progression of a disease associated with elevated PSA expression in a subject, comprises, at a first and second point in time:
(a) measuring or predicting PSA expression using a method described hereiin;
(b) testing whether the subject has elevated PSA expression or diagnosing the subject using a method described herein; or
(c) prognosing the subject using a method described herein; and
(d) comparing the measured or predicted PSA expression, PSA expression status, diagnosis, or prognosis at the first and the second time point.
[0106] Among other things, described herein is a method of treating a subject having a disease or disorder associated with increased PSMA expression (e.g., prostate cancer, including, e.g., mCRPC), the method comprising measuring PSMA expression or predicting tumor specific PSMA expression determined using an imaging technique (e.g., PSMA PET SUVmean) in the subject using a method described herein, and comparing the measured PSMA expression level or predicted tumor specific PSMA expression to a reference, and
(a) if the measured PSMA expression level or predicted tumor specific PSMA expression is equal to or greater than the reference, administering a PSMA targeted therapeutic (e.g., e.g., I77Lu-PSMA-6I7), and
(b) if the measured PSMA expression level or predicted tumor specific PSMA expression is less than the reference, not administering the PSMA targeted therapeutic.
[0107] Among other things, described herein is a method of predicting a likelihood that a subject having a disease or disorder associated with increased PSA expression will respond to a therapeutic. In some embodiments, a method of predicting a likelihood that a subject having a disease or disorder associated with increased PSA expression will respond to a therapeutic comprises measuring PSA expression or predicting PSA expression in a subject using a method described herein, and comparing the measured PSA expression level or predicted PSA expression to a reference, wherein
(a) if the measured PSA expression level or predicted tumor specific PSA expression is equal to or greater than the reference, the subject is likely to respond to the therapeutic, and
(b) if the measured PSA expression level or predicted tumor specific PSA expression is less than the reference, the subject is not likely to respond to the therapeutic.
[0108] Among other things, described herein is a method of identifying a subject having a disease or disorder associated with increased PSMA expression that is likely to respond or that has an increased likelihood of responding as compared to a reference to a PSMA-targeted therapeutic (e.g., 177Lu-PSMA-617). In some embodiments, a method of identifying a subject having a disease or disorder associated with increased PSMA expression that is likely to respond or that has an increased likelihood of responding as compared to a reference to a PSMA-targeted therapeutic (e.g., 177Lu-PSMA-617) comprises measuring PSMA expression or predicting tumor specific PSMA expression determined using an imaging technique (e.g., PSMA PET SUVmean) in the subject using a method described herein. In some embodiments, a method of identifying a subject having a disease or disorder associated with increased PSMA expression that is likely to respond or that has an increased likelihood of responding as compared to a reference to a PSMA-targeted therapeutic (e.g., 177Lu-PSMA-617) comprises measuring PSMA expression or predicting tumor specific PSMA expression determined using an imaging technique (e g., PSMA PET SUVmean) in the subject using a method described herein and comparing the measured PSMA expression level or predicted tumor specific PSMA expression to a reference, and
(a) if the measured PSMA expression level or predicted tumor specific PSMA expression is equal to or greater than the reference, identifying the subject as likely to respond to the PSMA targeted therapeutic, and
(b) if the measured PSMA expression level or predicted tumor specific PSMA expression is less than the reference, identifying the subject as not likely to respond to the PSMA targeted therapeutic.
[0109] In some embodiments, a reference is a predetermined threshold, a measurement from a liquid biopsy sample, a measurement from an imaging test, and/or a normalized value, optionally wherein the reference is a measurement from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with the disease or disorder associated with increased PSMA expression.
[0110] Among other things, the present disclosure describes a method of treating a subject having a disease or disorder associated with increased PSA expression. In some embodiments, a method of treating a subject having a disease or disorder associated with increased PSA expression comprises measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total serum PSA) in a subject using a method described herein. In some embodiments, a method of treating a subject having a disease or disorder associated with increased PSA expression comprises measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total serum PSA) in a subject using a method described herein, and comparing the measured PSA or predicted PSA expression to a reference, and
(a) if the measured PSA or predicted PSA expression is equal to or greater than the reference, administering a therapeutic, and
(b) if the measured or predicted PSA expression is less than the reference, not administering the therapeutic.
[0111] Among other things, the present disclosure describes a method of identifying a subject having a disease or disorder associated with increased PSA expression that is likely to respond to a therapeutic. In some embodiments, a method of identifying a subject having a disease or disorder associated with increased PSA expression that is likely to respond to a therapeutic, comprises measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total PSA) in a subject using a method described herein. In some embodiments, a method of identifying a subject having a disease or disorder associated with increased PSA expression that is likely to respond to a therapeutic, comprises measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total PSA) in a subject using a method described herein, and comparing the measured or predicted PSA expression to a reference, and
(a) if the measured or predicted PSA expression is equal to or greater than the reference, identifying the subject as likely to respond to the therapeutic, and
(b) if the measured or predicted PSA expression is less than the reference, identifying the subject as not likely to respond to the therapeutic. [0112] Among other things, the present disclosure describes a method of predicting the likelihood that a subject having a disease or disorder associated with increased PSA expression will respond to a therapeutic. In some embodiments, the method of predicting the likelihood that a subject having a disease or disorder associated with increased PSA expression will respond to a therapeutic, comprises measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total PSA) using a method described in the present disclosure. In some embodiments, a method of predicting the likelihood that a subject having a disease or disorder associated with increased PSA expression will respond to a therapeutic, comprises measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total PSA) using a method described in the present disclosure, and comparing the measured or predicted PSA expression to a reference, wherein
(a) if the measured or predicted PSA expression is equal to or greater than the reference, the subject is likely to respond to the therapeutic, and
(b) if the measured or predicted PSA expression is less than the reference, the subject is not likely to respond to the therapeutic.
[0113] In some embodiments, a reference is a predetermined threshold, a measurement from a liquid biopsy sample, and/or a normalized value, optionally wherein the reference is a measurement from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with the disease or disorder associated with increased PSA expression.
[0114] In some embodiments, a reference is a PSA expression that has previously been shown to be predictive of response to the therapeutic and/or previously been shown to be predictive of the presence of a disease that has been shown to respond to the therapeutic.
[0115] In some embodiments, a measured or predicted PSA expression is at least about 4 ng/mL, or at least about 10 ng/mL. In some embodiments, a measured or predicted PSA expression is an aberrant PSA level (e.g., relative to a general population).
[0116] In some embodiments, a reference is a PSMA expression level measured, a tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) predicted, or a tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) measured in a cohort of subjects having the disease or disorder associated with increased PSMA expression. [0117] In some embodiments, a reference is the median, lower bound of the top tertile, or lower bound of the top quartile value of the PSMA expression level measured, tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) predicted, or tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) measured in a cohort of subjects having a disease or disorder associated with increased PSMA expression (e.g., prostate cancer, including, e g., mCRPC).
[0118] In some embodiments, a reference is the median, lower bound of the top tertile, or lower bound of the top quartile value of a PSMA expression level measured, tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) predicted, or tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) measured in a cohort of subjects having a disease or disorder associated with increased PSMA expression (e.g., prostate cancer, including, e g., mCRPC); and if the PSMA expression level or predicted tumor specific PSMA expression level in the subject is equal to or greater than the reference, administering a PSMA targeted therapeutic (e.g., 177Lu-PSMA-617); and if the PSMA expression level or predicted tumor specific PSMA expression level in the subject is less than the reference, not administering the PSMA targeted therapeutic.
[0119] In some embodiments, the PSMA PET SUVmean median is about 4 to about 8, about 5 to about 8, 5 to about 7, about 6 to about 9, about 5, about 6, about 7, or about 8 in a reference population. In some embodiments, the lower bound of the top tertile of PSMA PET SUVmean is about 6 to about 12, about 6 to about 10, about 8 to about 12, about 6, about 7, about 8, about 9, about 10, about 11, or about 12 in a reference population. In some embodiments, the lower bound of the top quartile of PSMA PET SUVmean is about 6 to about 14, about 6 to about 12, about 8 to about 14, about 8, about 9, about 10, about 11, about 12, about 13, or about 14 in a reference population.
[0120] In some embodiments, a disease or indication associated with increased PSMA expression is a cancer. In some embodiments, the cancer is prostate cancer, including, e.g., mCRPC.
[0121] In some embodiments, a therapeutic is a PSMA-targeted therapeutic (e.g., a PSMA-targeted therapeutic described herein). [0122] In some embodiments, a therapeutic is an ADC (e.g., PSMA-MMAE, MLN2704, ARX517). In some embodiments, a PSMA-targeted therapeutic is a PSMA-targeted radionuclide (e.g., 177Lu-PSMA-617). In some embodiments, a therapeutic is 177Lu-PSMA-617.
[0123] In some embodiments, a therapeutic is administered via one or more intravenous, subcutaneous, intraperitoneal, or intramuscular injections.
[0124] In some embodiments, a subject has previously been diagnosed as having a disease or indication associated with increased PSMA or PSA expression (e.g., a cancer, prostate cancer, mCRPC, PRAD and/or NEPC).
[0125] In some embodiments, a prostate cancer is localized or metastatic.
[0126] In some embodiments, a prostate cancer has metastasized to one or more site(s) that include lymph node, bone, lung, and/or liver tissue.
[0127] In some embodiments, a subject has previously been administered one or more
(e g., 2-7, 2-5, 3-4, 1, 2, 3, 4, 5, 6, or 7) systemic therapies for metastatic prostate cancer.
[0128] In some embodiments, a subject has previously been determined to have a plasma PSA concentration of 0-2000 ng/mL. In some embodiments, a subject has previously been determined to have a plasma PSA concentration of at least about 4 ng/mL, at least about 10 ng/mL, 10-2000 ng/mL, 25-2000 ng/mL, 50-2000 ng/mL, 75-2000 ng/ML, 100-2000 ng/mL, 150-1000 ng/mL, 100-500 ng/mL, or 100-200 ng/mL. In some embodiments, a plasma PSA concentration has previously been determined in a subject using a method described herein.
[0129] Among other things, described herein is a kit comprising reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci, wherein the one or more genomic loci are selected from Tables 1-2.
[0130] In some embodiments, a kit comprises reagents for quantifying:
(a) promoter signal (e.g., H3K4me3 modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K4me3 analyte genomic loci in Table 1;
(b) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 1;
(c) DNA methylation for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 MBD analyte genomic loci in Table 1; (d) enhancer signal (e.g., H3K27ac modifications) at one or more (e g., all) of genomic loci 1-8 in Table 2;
(e) promoter signal (e.g., H3K4me3 modifications) at genomic locus 9 in Table 2;
(f) enhancer signal (e.g., H3K27ac modifications) for 1, 2, 3, or 4 H3K27ac analyte genomic loci in Table 3;
(g) promoter signal (e.g., H3K4me3 modifications) for 1 or 2 H3K4me3 analyte genomic loci in Table 4;
(h) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 4;
(i) promoter signal (e.g., H3K4me3 modifications) at chrl 1 : 49, 228, 902-49, 230, 855;
(j) enhancer signal (e.g., H3K27ac modifications) at chrl 1 :49, 229, 019-49, 230, 275;
(k) a combination of any one of (a)-(j).
[0131] In some embodiments, a kit comprises one or more antibodies for use in ChlP- seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac- modified histones.
[0132] In some embodiments, a kit comprises one or more methyl-binding domains for use in MBD-seq or wherein the kit comprises one or more antibodies that bind methylated DNA for use in MeDIP.
[0133] In some embodiments, a kit comprises reagents for isolation of cell-free DNA (cfDNA) from a liquid biopsy sample.
[0134] In some embodiments, a kit comprises reagents for library preparation for sequencing.
[0135] In some embodiments, a kit comprises reagents for sequencing.
[0136] In some embodiments, a kit comprises instructions for determining if a subject has a disease or disorder associated with increased PSMA (e.g., a cancer, prostate cancer, or mCRPC).
[0137] Among other things, described herein is a non-transitory computer readable storage medium encoded with a computer program, wherein the program comprises instructions that when executed by one or more processors cause the one or more processors to perform operations to perform a method described herein. [0138] Among other things, described herein is a computer system comprising a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform operations to perform a method described herein.
[0139] Among other things, described herein is a system for determining the disease or disorder status of a subject, the system comprising a sequencer configured to generate a sequencing data set from a sample; and a non-transitory computer readable storage medium described herein.
[0140] In some embodiments, a sequencer is configured to generate a Whole Genome Sequencing (WGS) data set from the sample.
[0141] In some embodiments, a system comprises a sample preparation device configured to prepare a sample for sequencing from a biological sample, optionally a liquid biopsy sample.
[0142] In some embodiments, a sample preparation device comprises reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci in cell-free DNA (cfDNA) from the biological sample, optionally the liquid biopsy sample.
[0143] In some embodiments, one or more genomic loci are selected from Tables 1-2.
[0144] In some embodiments, a device comprises reagents for quantifying:
(a) promoter signal (e.g., H3K4me3 modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K4me3 analyte genomic loci in Table 1;
(b) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 1;
(c) DNA methylation for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 MBD analyte genomic loci in Table 1;
(d) enhancer signal (e.g., H3K27ac modifications) at one or more (e.g., all) of genomic loci 1-8 in Table 2;
(e) promoter signal (e.g., H3K4me3 modifications) at genomic locus 9 in Table 2;
(f) enhancer signal (e.g., H3K27ac modifications) for 1, 2, 3, or 4 H3K27ac analyte genomic loci in Table 3; (g) promoter signal (e.g., H3K4me3 modifications) for 1 or 2 H3K4me3 analyte genomic loci in Table 4;
(h) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 4;
(i) promoter signal (e.g., H3K4me3 modifications) at chrl 1:49,228,902-49,230,855;
(j) enhancer signal (e.g., H3K27ac modifications) at chrl 1 :49, 229, 019-49, 230, 275; or
(k) any combination of (a)-(j).
[0145] In some embodiments, a system described herein comprises reagents that comprise one or more antibodies for use in ChlP-seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac-modified histones.
[0146] In some embodiments, a system comprises reagents that comprise one or more methyl-binding domains for use in MBD-seq.
[0147] In some embodiments, a device comprises reagents for isolation of cell-free DNA (cfDNA) from a biological sample, optionally a liquid biopsy sample.
[0148] In some embodiments, a system comprises a device that comprises reagents for library preparation for sequencing.
[0149] In some embodiments, a sequencer comprises reagents for sequencing.
[0150] The present disclosure is based, at least in part, on the demonstration that certain genomic loci associated with an ADC target antigen (FOLH1, encoding the ADC target antigen PSMA) have different histone modification levels (e.g., histone methylation marks such as H3K4me3 and histone acetylation marks such as H3K27ac) in plasma samples from cancer patients (e.g., prostate cancer) as compared to plasma samples from healthy volunteers.
[0151] The present disclosure encompasses methods, kits and systems that use epigenomic differences (alone or in combination with each other and/or with other biomarkers) to select subjects for treatment with an agent that is directed to FOLH1 (e.g., an ADC therapy or radioligand directed to PSMA), to identify subpopulations of subjects that respond to treatment with an agent that is directed to FOLH1, to monitor subjects during treatment with an agent that is directed to FOLHl (e.g., an ADC therapy or radioligand directed to PSMA), etc. by detecting and quantifying the presence of histone modifications at these one or more genomic loci in cell- free DNA (cfDNA) from a liquid biopsy sample, e.g., a plasma sample obtained or derived from a subject. The present disclosure also encompasses methods where chromatin accessibility and/or binding of one or more transcription factors are detected at the one or more genomic loci instead of (or in addition to) histone modifications. The present disclosure also encompasses methods, kits and systems where the genomic loci that are differentially modified based on different types of histone modifications (e.g, histone methylation marks such as H3K4me3 and histone acetylation marks such as H3K27ac) are combined into multimodal classifiers to select subjects for treatment with an agent that is directed to F0LH1 (e.g., an ADC therapy or radioligand directed to PSMA), etc. These monomodal and multimodal classifiers can provide minimally invasive ways of selecting subjects for treatment with an agent that is directed to F0LH1 (e.g., an ADC therapy or radioligand directed to PSMA), etc. that are more accurate, objective, and comprehensive than the current tissue-based approaches.
[0152] The present disclosure includes, among other things, technologies for the determination of the activation status of F0LH1 and for the detection, monitoring, and/or treatment of cancer (including, e.g., prostate cancer, breast cancer, SCLC, NSCLC, etc.) based on the activation status of these genes. In various embodiments, the present disclosure relates to the measurement of histone modifications in a sample obtained or derived from a subject to detect and/or treat cancer (including, e.g., prostate cancer, breast cancer, SCLC, NSCLC, etc.) based on the activation status of these genes. The present disclosure includes, among other things, histone modification measurements in cell-free DNA (cfDNA) that are characteristic of the activation status of genes for F0LH1, and which in various embodiments are useful, e.g., for detecting, monitoring, selecting treatment for, and/or treating cancer (including, e.g., prostate cancer, breast cancer, SCLC, NSCLC, etc.) based on the activation status of these genes. In some embodiments, histone modification measurements in cfDNA can be used to detect or determine resistance of a cancer (e.g., prostate cancer, breast cancer, SCLC, NSCLC, etc.) to treatment with an agent that is directed to FOLH1 (e.g., an ADC therapy or radioligand directed to PSMA) or transformation of a cancer from one subtype to another. In various embodiments, the present disclosure includes exemplary genomic loci that are differentially modified in different cancer patients (including, e.g., prostate cancer, breast cancer, SCLC, NSCLC, etc. patients) and/or between cancer patients and healthy volunteers. In various embodiments, genomic loci differentially modified in cfDNA are or include one or more enhancers. Tn various embodiments, genomic loci differentially modified in cfDNA are or include one or more promoters.
[0153] In various embodiments, a genomic locus is differentially modified if it is characterized by increased or decreased histone modification as compared to a reference (e.g., a sample from a PSMA-negative or healthy subject). Increased or decreased histone modification can be or include, e.g., increased or decreased histone methylation (hypermethylation or hypomethylation, respectively) of one or more particular methylation marks, or a combination thereof; increased or decreased pan-methylation; increased or decreased histone acetylation (hyperacetylation or hypoacetylation, respectively) of one or more particular acetylation marks, or a combination thereof; and/or increased or decreased pan-acetylation (e.g., pan-H3 acetylation). In various embodiments, histone methylation can be or include histone methylation marks selected from H3K4mel, H3K4me2, H3K4me3, or a combination thereof. In various embodiments, histone methylation can be or include H3K4me3. In various embodiments, histone acetylation can be or include histone acetylation marks selected from H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, or a combination thereof. In various embodiments, histone acetylation can be or include H3K27ac.
[0154] The present disclosure further relates, in various embodiments, to the measurement of chromatin accessibility in cell-free DNA (cfDNA) to determine the activation status of FOLH1. The present disclosure includes, among other things, chromatin accessibility measurements in cfDNA that are characteristic of PSMA-positive cancers, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating a PSMA-positive cancer. In some embodiments, chromatin accessibility measurements in cfDNA can be used to detect or determine resistance of a cancer e.g., prostate cancer, breast cancer, SCLC, NSCLC, etc.) to treatment with an agent that is directed to PSMA (e.g., an ADC therapy or radioligand) or transformation of a cancer from one subtype to another. In various embodiments, the present disclosure includes genomic loci that are differentially accessible in PSMA-positive vs. PSMA-negative cancers. In various embodiments, genomic loci differentially accessible in cfDNA are or include one or more enhancers. In various embodiments, genomic loci differentially accessible in cfDNA are or include one or more promoters. [0155] In various embodiments, without wishing to be bound by any particular scientific theory, histone acetylation (e.g, H3K27ac) corresponds and/or is correlated with chromatin accessibility. In various embodiments, without wishing to be bound by any particular scientific theory, histone methylation (e.g, H3K4me3) corresponds and/or is correlated with chromatin accessibility.
[0156] In various embodiments, a genomic locus is differentially accessible if it is characterized by increased or decreased chromatin accessibility as compared to a reference (e.g, a sample from an ADC target-negative or healthy subject). Increased or decreased histone modification can be or include, e.g., increased or decreased accessibility as determined by various chromatin accessibility assays known in the art.
[0157] The present disclosure further relates, in various embodiments, to the measurement of transcription factor binding in cell-free DNA (cfDNA) to determine the activation status of genes for PSMA. The present disclosure includes, among other things, transcription factor binding measurements in cfDNA that are characteristic of PSMA-positive cancers, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating a PSMA-positive cancer. In some embodiments, transcription factor binding measurements in cfDNA can be used to detect or determine resistance of a cancer (e.g, prostate cancer, breast cancer, SCLC, NSCLC, etc.) to a therapy or transformation of a cancer from one subtype to another. In various embodiments, the present disclosure includes genomic loci that are differentially bound by transcription factors in PSMA-positive vs. PSMA- negative cancers. In various embodiments, genomic loci that are differentially bound by transcription factors in cfDNA are or include one or more enhancers. In various embodiments, genomic loci that are differentially bound by transcription factors in cfDNA are or include one or more promoters.
[0158] In various embodiments, without wishing to be bound by any particular scientific theory, histone acetylation (e.g, H3K27ac) corresponds and/or is correlated with transcription factor binding. In various embodiments, without wishing to be bound by any particular scientific theory, histone methylation (e.g, H3K4me3) corresponds and/or is correlated with transcription factor binding. [0159] In various embodiments, a genomic locus is differentially bound by transcription factors if it is characterized by increased or decreased transcription factor binding as compared to a reference (e.g., a sample from a PSMA-negative or healthy subject). Increased or decreased transcription factor binding can be or include, e.g., increased or decreased transcription factor binding as determined by various transcription factor binding assays known in the art.
[0160] In one aspect the present disclosure provides a method comprising quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from a subject: (i) one or more histone modifications, (ii) DNA methylation, (iii) chromatin accessibility, and/or (iv) binding of one or more transcription factors, wherein the one or more genomic loci are (a) within a gene encoding PSMA.
[0161] In some embodiments, a method comprises quantifying enhancer signal (e.g., H3K27ac modifications) at one or more loci within a certain distance of KLK3 (e.g., within 500 kb, 400 kb, 300 kb, 200 kb, 150 kb, 100 kb, or 50 kB of KLK3).
[0162] In some embodiments, a method comprises quantifying promoter signal (e.g., H3K4me3) at one or more loci within a certain distance of KLK3 (e g., 500 kb, 400 kb, 300 kb, 200 kb, 150 kb, 100 kb, 50 kB, 20 kB, 10 kB, 5, kB, 4 kB, 3 kB, 2 kB, or 1 kB of KLK3).
[0163] In some embodiments, a method comprises quantifying DNA methylation at one or more loci within the transcript encoding portion of KLK3 and/or at one or more loci within a certain distance of KLK3 (e.g., within 500 kb, 400 kb, 300 kb, 200 kb, 150 kb, 100 kb, or 50 kB of KLK3).
[0164] In some embodiments, one or more loci within a certain distance of KLK3 include one or more loci with differential H3K4me3, H3K27ac, and/or DNA methylation signal (e.g., as compared to a healthy subject). In some embodiments, one or more loci within a certain distance of KLK3 include one or more loci at which levels of H3K4me3, H3K27ac, and/or DNA methylation signal is correlated with PSA expression (e.g., as determined by quantifying RNA transcript (e.g., as determined using an RNA-seq assay using tumor samples, PDX samples, and/or one or more cell lines). [0165] In some embodiments, a method comprises quantifying enhancer signal (e.g., H3K27ac modifications) at one or more loci within a certain distance of FOLH1 (e.g., within 500 kb, 400 kb, 300 kb, 200 kb, 150 kb, 100 kb, or 50 kB o FOLHl .
[0166] In some embodiments, a method comprises quantifying promoter signal (e.g., H3K4me3) at one or more loci within a certain distance oiFOLHl (e.g., 500 kb, 400 kb, 300 kb, 200 kb, 150 kb, 100 kb, 50 kB, 20 kB, 10 kB, 5, kB, 4 kB, 3 kB, 2 kB, or 1 kB oiFOLHl .
[0167] In some embodiments, a method comprises quantifying DNA methylation at one or more loci within the transcript encoding portion of FOLH1 and/or at one or more loci within a certain distance of FOLH1 (e.g., within 500 kb, 400 kb, 300 kb, 200 kb, 150 kb, 100 kb, or 50 kB ofFOLHi
[0168] In some embodiments, one or more loci within a certain distance of FOLH1 include one or more loci with differential H3K4me3, H3K27ac, and/or DNA methylation signal (e g., as compared to a healthy subject). In some embodiments, one or more loci within a certain distance of FOLH1 include one or more loci at which levels of H3K4me3, H3K27ac, and/or DNA methylation signal is correlated with PSMA expression (e.g., as determined by quantifying RNA transcript (e.g., as determined using an RNA-seq assay using tumor samples, PDX samples, and/or one or more cell lines).
BRIEF DESCRIPTION OF THE DRAWING
[0169] Fig. 1 is a schematic showing a summary of an exemplary comprehensive epigenomic platform offering dynamic resolution into target and pathway biology from plasma. (A) Cell free DNA derived from tumors exists in circulation as chromatin fragments that faithfully maintain tumor-associated epigenetic modifications on histones and DNA. Antibodies against H3K27ac (marking active enhancers), H3K4me3 (marking active promoters), and DNA methylation can be used to enrich for associated DNA fragments from plasma, which can then be sequenced to provide genome-wide epigenomic maps that capture the underlying transcriptional state of tumor cells. (B) Clinical study overview of mCRPC patient plasma samples evaluated in the study described in Example 2.
[0170] Fig. 2 shows volcano plots demonstrating identification of plasma epigenomic features that associate with mCRPC and PSMA-PET signal. (A) Differential analysis of normalized epigenomic signal between mCRPC patients (N=29) and healthy male volunteers (N=51) revealed enrichment of multiple prostate-cancer specific signals including H0XB13, KLK2, KLK3, and SPDEF in mCRPC patient plasma. Fold enrichment and significance was calculated using DESeq with Benjamini-Hochberg p-value correction. Points represent individual peaks and are colored by significance (light to dark grey=FDR<0.05, black=FDR>0.05). “Up’7 “Down” labels indicate the number of statistically-significant loci for enhancers, promoters, and DNA methylation that are upregulated (Up) or downregulated (Down) in mCRPC patients vs healthy volunteers. Labels represent the nearest TSS to statistically significant peaks of interest. (B) A genome wide analysis correlating epigenomic signal to PSMA PET SUVmean quantifications in mCRPC patients (ctDNA% >3, N=29) identified enhancer signal at the F0LH1 locus as the top association. For each analyte, robust mCRPC- specific epigenomic features were identified and normalized to reduce technical variability and dependence on ctDNA fraction. Each feature was then tested for its association with PSMA PET SUVmean via linear regression. The x-axis values represent the slope of the association between the z-score of the epigenomic feature and the z-score of PSMA PET SUVmean, and the y-axis is the statistical significance of that association. The top three features for each analyte are labeled with their closest gene (TSS).
[0171] Fig. 3 shows exemplary enrichment tracks demonstrating that the F0LH1 locus has robust enhancer and promoter signal in mCRPC patients compared to healthy volunteers. Epigenomic signal at the FOLH1 locus showed increased active promoter and active enhancer marks in mCRPC patients with high PSMA PET SUVmean (>median, N=15) compared to mCRPC patients with low PSMA PET SUVmean (<median, N=14). Enhancer, promoter, and DNA methylation signal in mCRPC patients with either high or low PSMA PET SUV mean WHS normalized, smoothed, and averaged together (within analyte) with the mean signal from a cohort of male healthy volunteers.
[0172] Fig. 4 shows exemplary enrichment tracks demonstrating that the FOLH1 locus has higher enhancer and promoter signal in patients with higher PSMA PET SUVmean. Epigenomic signal at the FOLH1 locus shows increased active promoter and active enhancer marks in mCRPC patients with high PSMA PET SUVmean (>median, N=15) compared to mCRPC patients with low PSMA PET SUVmean (<median, N=14). Enhancer, promoter, and DNA methylation signal in mCRPC patients with either high or low PSMA PET SUV mean W3S normalized, smoothed, and averaged together (within analyte) with the mean signal from a cohort of male healthy volunteers.
[0173] Fig. 5 shows scatter plots demonstrating that enhancer and promoter signal at the FOLH1 locus predicts PSMA PET SUVmean in both cross-validation and in validation cohort. Enhancer and promoter signal at the FOLH1 locus were used to train a machine learning (ML) model to predict PSMA PET SUVmean. Samples were first split into training and validation cohorts, which were matched for ctDNA% and PSMA PET SUVmean distributions. For model training, training cohort samples (ctDNA% >3) were used to identify robust, mCRPC-specific enhancer/promoter regions at the FOLH1 locus. Signal at these regions were then used train a model to predict the corresponding PSMA PET SUVmean quantifications. Performance was assessed via Pearson correlation in both a leave-one-out (LOO) cross-validation (CV) setting within the training cohort, as well as the held-out validation cohort using a final model trained on all data from the training cohort.
[0174] Fig. 6 shows survival graphs demonstrating association with clinical outcomes with PSMA PET scores predicted using a model described herein. Shown are clinical outcomes (as measured by 4 clinical trial metrics) for mCRPC subjects having different PSMA PETtreated with lutetium-177 (177Lu)-PSMA-617, having different PSMA scores as determined using methods provided herein. (A) Shows progression free survival as determined by whether there is an increase in serum PSA (PSA-PFS). (B) Shows “crPFS” values, referring to progression free survival based on clinical or radiological evidence of progression. (C) Shows Time to Next Treatment. (D) Shows overall survival. In each of (A)-(D), lines represent patients with a PSMA score, from left to right, in the bottom tertile of patients, in the middle tertile of patients, in the top tertile of patients.
[0175] Fig. 7 shows survival graphs for comparison of hazard ratios based on PSMA PET SUVmean predictions vs. PSMA PET measured values. Shown is a comparison of clinical trial outcomes for a cohort of mCRPC patients administered lutetium-177 (177Lu)-PSMA-617, and having different measured PSMA PET SUVmean values (PSMA PET SUVmean (Measured)) vs. predicted PSMA PET SUVmean values (PSMA PET SUVmean (Predicted)), which were predicted using technologies described herein. (A) and (B) show progression free survival as determined by whether an increase in serum PSA was observed (PSA-PFS), in subjects having different measured PSMA PET SUVmean or predicted PSMA PET SUVmean values, respectively. (C) and (D) show Time to Next Treatment (TTNT), in subjects having different measured PSMA PET SUVmean or predicted PSMA PET SUVmean values, respectively. (E) and (F) show “crPFS” values, referring to progression free survival based on clinical or radiological evidence of progression, in subjects having different measured PSMA PET SUVmean or predicted PSMA PET SUVmean values, respectively. (G) and (H) show Overall Survival (OS), in subjects having different measured PSMA PET SUV mean or predicted PSMA PET SUVmean values, respectively. In each of (A)-(H), black lines represent patients with a measured or predicted PSMA PET SUVmean in the top tertile of patients and grey lines represent patients with a measured or predicted PSMA PET SUVmean in the middle and bottom tertiles of patients. HR refers to Hazard Ratio.
[0176] Fig. 8 shows a scatterplot with comparison of predicted and measured PSA expression in plasma samples from prostate cancer patients. Shown is predicted PSA expression (“Predicted KLK3 RNA-seq expression,” y-axis), determined using epigenetic modification measurements collected in plasma samples obtained from prostate cancer patients, and serum PSA (“PSA plasma concentration,” x-axis) measured in matched plasma samples, p refers to Pearson’s coefficient. Shading indicates 95% confidence interval.
[0177] Fig. 9 shows a scatterplot demonstrating prediction of PSMA PET SUVmean using patient plasma samples. (A) Shows PSMA expression predicted using a biopsy model, using epigenetic modification measurements from plasma samples obtained from prostate cancer patients (y-axis) vs. PSMA PET SUVmean measured in matched patients (x-axis). (B) Shows PSMA PET SUVmean predicted using a model generated using patient plasma data and PMSA PET SUVmean values vs. PSMA PET SUVmean measured in matched patients (x-axis). (C) Shows Spearman correlation values between predicted PSMA expression or PSMA PET SUVmean and measured PSMA PET SUVmean (y-axis) at different ctDNA% (x-axis) for the PSMA PET SUVmean trained model (top line at higher ctDNA%) and biopsy trained model (bottom line at higher ctDNA%). ISP refers to In Silico Plasma, p refers to Pearson’s coefficient. Shading indicates 95% confidence interval. [0178] Fig. 10 shows trend lines and confidence intervals for (A) promoter signal (H3K4me3) and (B) enhancer signal (H3K27ac) based on ctDNA% for FOLH1.
[0179] Fig. 11 shows clinicoradiographic Progression Free Survival (CR PFS) for mCRPC patients with a predicted PSMA PET SUVmean value in the top tertile (top, black line) and middle and bottom tertiles (red, bottom line). HR refers to Hazard Ratio.
[0180] Figs. 12(A)-(D) show prostate specific antigen (PSA), time to next treatment (TTNT), clinicoradiographic Progression Free Survival (CR PFS), and overall survival (OS) metrics for patients with mCRPC with ctDNA% in the top tertile (bottom, black line) and middle and bottom tertiles (red, top line). HR refers to Hazard Ratio.
DETAILED DESCRIPTION
[0181] The present disclosure is based, at least in part, on the demonstration that PSMA expression level (e.g., PSMA expression level) in a subject can be determined by detecting and quantifying the presence of histone modifications and/or DNA methylation at one or more genomic loci in cell-free DNA (cfDNA) from a liquid biopsy sample, e.g., a plasma sample obtained or derived from a subject. Among other things, the present disclosure demonstrates that PSMA expression level can be determined in cancer cells in a subject, including, e.g., PSMA expression level in prostate cancer (e.g., mCRPC). Determining PSMA expression level can be used for, e.g., diagnosing, prognosing, or monitoring a disease in a subject, and methods of treatment (e.g., for identifying subject more likely to respond to treatment with a PSMA-targeted therapeutic).
Prostate Cancer
[0182] Prostate cancer is a disease characterized by the uncontrolled growth of cells in the prostate, a gland in the male reproductive system below the bladder. Risk factors for prostate cancer include age (especially after the age of 50; risk increases further after the age of 65, with -60% of prostate cancers found in men older than 65), ethnicity (prostate cancer is more common in African American men and in Caribbean men of African ancestry), family history (having a father or brother with prostate cancer more than doubles a man’s risk of developing the disease), and certain genetic variants or mutations (including variants of the BRCA1 and BRCA2 genes, and men with Lynch syndrome, a condition caused by inherited gene changes).
[0183] Abnormal growth of prostate tissue is usually detected through screening tests, typically blood tests that check for prostate-specific antigen (PSA) levels. High blood levels of PSA indicates an increased risk of developing prostate cancer. Diagnosis can be performed using a biopsy of the prostate. If cancer is present, a pathologist assigns a Gleason score, where a higher score represents a more dangerous tumor. Medical imaging can be used to look for cancer that has spread outside the prostate. Based on the Gleason score, PSA levels, and imaging results, a cancer can be assigned a stage 1 to 4, where a higher stage signifies a more advanced, more dangerous disease.
[0184] Most prostate tumors remain small and cause no health problems. These are managed with active surveillance and monitoring tumor(s) with regular tests to ensure that have not grown. Tumors more likely to be dangerous can be targeted with radiation therapy or surgically removed by radical prostatectomy. Subjects whose cancer spreads beyond the prostate can be treated with hormone therapy, which reduces levels of the androgens (male sex hormones) that prostate cells need to survive. Cancer cells can eventually grow resistant to this treatment. This most-advanced stage of the disease, called castration-resistant prostate cancer (CRPC), can be treated with continued hormone therapy alongside with a chemotherapy drug (e g., docetaxel). Some tumors metastasize to other areas of the body, particularly the bones and lymph nodes. There, tumors cause severe bone pain, leg weakness or paralysis, and eventually death. Prostate cancer prognosis depends on how far the cancer has spread at diagnosis. Most men diagnosed have tumors confined to the prostate; 99% survive more than 10 years from their diagnoses. Tumors that have metastasized to distant body sites are most dangerous, with five- year survival rates of 30-40%.
[0185] Most cases of prostate cancer are diagnosed through screening tests, when tumors are too small to cause any symptoms. This can be done through blood tests to measure levels of the protein prostate-specific antigen (PSA), which are elevated in those with enlarged prostates, whether due to prostate cancer or benign prostatic hyperplasia. A typical man's blood has around 1 nanogram (ng) of PSA per milliliter (mb) of blood tested. Those with PSA levels below average are very unlikely to develop dangerous prostate cancer over the next 8 to 10 years. Men with PSA levels above 4 ng/mL are at increased risk - around 1 in 4 will develop prostate cancer - and are often referred for a prostate biopsy. PSA levels over 10 ng/mL indicate an even higher risk: over half of men in this group develop prostate cancer.
[0186] Those with elevated PSA may undergo secondary screening blood tests that measure subtypes of PSA and other molecules to better predict the likelihood that a person will develop aggressive prostate cancer. Many tests measure “free PSA” - the fraction of PSA unbound to other blood proteins, which is usually around 10% to 30%. Men who have a lower percentage of free PSA are more likely to have prostate cancer. Several common tests more accurately detect prostate cancer cases by also measuring subtypes of free PSA, including the Prostate Health Index (measures a fragment called -2proPSA) and 4K score (measures intact free PSA). Other tests measure blood levels of additional prostate-related proteins such as kallikrein-2 (also measured by 4K score), or urine levels of mRNA molecules common to prostate tumors like PC A3 and TMPRSS2 fused to ERG.
[0187] Men suspected of having prostate cancer may undergo several tests to assess the prostate. One common procedure is the digital rectal examination, in which a doctor inserts a lubricated finger into the rectum to feel the nearby prostate. Tumors feel like stiff, irregularly shaped lumps against the rest of the prostate. Hardening of the prostate can also be due to benign prostatic hyperplasia; around 20-25% of those with abnormal findings on their rectal exams have prostate cancer. Several urological societies’ guidelines recommend magnetic resonance imaging (MRI) to evaluate the prostate for potential tumors in men with high PSA levels. MRI results can help distinguish those who have potentially dangerous tumors from those who do not.
[0188] A definitive diagnosis of prostate cancer currently requires a biopsy of the prostate. Prostate biopsies are typically taken by a needle passing through the rectum or perineum, guided by transrectal ultrasonography, MRI, or a combination of the two. Ten to twelve samples are taken from several regions of the prostate to improve the chances of finding any tumors. Biopsies are sent for a histopathologic diagnosis of prostate cancer, wherein they are examined under a microscope by a pathologist, who determines the type and extent of cancerous cells present. Cancers are first classified based on their appearance under a microscope. Over 95% of prostate cancers are classified as adenocarcinomas (resembling gland tissue), with the rest largely squamous-cell carcinoma (resembling squamous cells, a type of epithelial cell) and transitional cell carcinoma (resembling transitional cells).
[0189] Next, tumor samples are graded based on how much the tumor tissue differs from normal prostate tissue; the more different the tumor appears, the faster the tumor is likely to grow. The Gleason grading system is commonly used, where the pathologist assigns numbers ranging from 3 (most similar to healthy prostate tissue) to 5 (least similar) to different regions of the biopsied tissue. They then calculate a “Gleason score” by adding the two numbers that represent the largest areas of the biopsy sample. The lowest possible Gleason score of 6 represents a biopsy most similar to healthy prostate; the highest Gleason score of 10 represents the most severely cancerous. Gleason scores are commonly grouped into “Gleason grade groups”, which predict disease prognosis: a Gleason score of 6 is Gleason grade group 1 (best prognosis). A score of 7 (with Gleason scores 4 + 3, or Gleason scores 3 + 4, with the most prominent listed first) can be grade group 2 or 3; it is grade group 2 if the less severe Gleason score (3) covered more area; grade group 3 if the more severe Gleason score (4) covered more area. A score of 8 is grade group 4. A score of 9 or 10 is grade group 5 (worst prognosis).
[0190] The extent of cancer spread can be assessed by MRI or PSMA scan - a positron emission tomography (PET) imaging technique where a radioactive label that binds the prostate protein prostate-specific membrane antigen is used to detect metastases distant from the prostate. CT scans may also be used but are less able to detect spread outside the prostate. Bone scintigraphy can be used to test for spread of cancer to bones.
PSMA Expression Level and Disease
[0191] Prostate-specific membrane antigen (PSMA), is encoded by folate hydrolase 1 (FOLHI), and is a transmembrane glutamate carboxypeptidase that is highly expressed on prostate cancer cells. It consists of a large extracellular domain, a small transmembrane domain, and a cytoplasmic tail. High PSMA expression is a biomarker of poor prognosis throughout the course of prostate cancer and across anatomical sites. Metastatic lesions are PSMA-positive in most patients that have metastatic castration-resistant prostate cancer, and high PSMA expression has been independently associated with reduced survival.
[0192] A PSMA PET scan is a nuclear medicine imaging technique that can be used in the diagnosis and staging of prostate cancer. It is carried out by injecting a radiopharmaceutical with a positron or gamma emitting radionuclide and a prostate-specific membrane antigen (PSMA) targeting ligand. After injection, imaging of positron emitters such as gallium-68 (68Ga), copper-64 (64Cu), and fluorine-18 (18F) is carried out with a positron emission tomography (PET) scanner. For gamma emitters such as technetium-99m (99mTc) and indium- 111 (11 Un) single-photon emission computed tomography (SPECT) imaging is performed with a gamma camera.
[0193] As well as the diagnosis and staging of prostate cancer, PSMA imaging can also be used to assess suitability for and plan treatment with external beam radiotherapy and PSMA- targeted therapeutics (e.g., PSMA-targeted radionuclides).
PSMA Targeted Therapeutics
[0194] PSMA can be highly expressed on the surface of prostate cancer cells but has low normal -tissue expression. As such, PSMA offers a useful target for selectively targeting prostate cancer cells. A common approach in designing therapeutics for use in treating prostate cancer (including, e.g., mCRPC) has been to link moieties that can bind to or associate with PSMA in a subject to moieties that can kill cells.
[0195] PSMA targeting therapies such as radionuclide therapies (e.g., lutetium- 177 (177Lu)-PSMA-617) can target prostate cancer cells while sparing most normal tissues in patients who have been selected with the use of imaging to confirm radionuclide binding.
[0196] 177Lu-PSMA-617 delivers beta-particle radiation selectively to PSMA-positive cells and the surrounding microenvironment. This radioligand therapy has been associated with encouraging biochemical and radiographic response rates, reduced pain, and low toxicity in multiple early-phase studies involving patients with progression of metastatic castration-resistant prostate cancer after standard therapy.
[0197] Currently, PSMA expression in tumors is commonly assessed using PSMA- targeted positron emission tomography (PET), which has gained increased acceptance in diagnosing prostate cancer due to its superior accuracy in identifying metastases as compared to CT and MRI methods. Patient eligibility for lutetium- 177 (177Lu)-PSMA-617 currently requires PSMA PET imaging.
PSMA Targeted Radionuclide Therapeutics [0198] Moi eties that can bind to or associate with PSMA in a subject can be labeled with different radionuclides for therapeutic purposes. PSMA targeted radionuclides typically consist of a PSMA-binding domain, a linker, and a chelator labeled with various radionuclides. A PSMA-binding domain can be, e.g., a small molecule domain or an antibody moiety.
[0199] PSMA- targeting small molecule domains are divided into 3 types — urea-based, phosphorus-based, and thiol-based — with urea-based compounds commonly used due to their superior PSMA binding affinity. Changing linker or chelator structure can influence PSMA binding efficacy and pharmacokinetics. In addition, adding an albumin-binding domain, which effectively increases the agent’s size, has been explored to increase circulation time within the tumor vasculature and reduce healthy-organ circulation time, with the goal of mitigating on- target, off-tumor toxicities.
[0200] On accumulation of a PSMA-targeted radionuclide at a tumor site, radioactive decay of a- or fl-emitting radionuclides induces DNA strand breaks and causes cell death, a- radiation reaches a shorter range (40-100 pm) than P-particles (50-12,000 pm) but has a linear energy transfer significantly higher than that of P-particles (5-9 vs. 0.1-2.2 MeV), a-emitting radionuclides therefore lead to several ionizing events, resulting in DNA double-strand breaks (DSBs) in a short range. Both PSMA-targeted a-emitting and PSMA-targeted P-emitting radionuclides are currently in clinical development.
[0201] A summary of exemplary PSMA targeted radionuclides currently in development is provided, e.g., in Sandhu et al. “Radionuclide therapy in prostate cancer: from standalone to combination PSMA theranostics.” Journal of Nuclear Medicine 62.12 (2021): 1660-1668, the contents of which are incorporated by reference herein in their entirety. Provided below is a short list of exemplary PSMA targeted radionuclides.
[0202] 177Lu-PSMA-617 is a 177Lu-conjugated small-molecule peptide that delivers beta-particle radiation to PSMA-positive cells and surrounding microenvironment. This radioligand therapy has been associated with encouraging biochemical and radiographic response rates, reduced pain, and low toxicity in multiple early-phase studies involving patients with progression of metastatic castration-resistant prostate cancer after standard therapy. 177Lu- PSMA-617 is currently the most developed PSMA-targeted radioligand therapy, with Phase 3 outcome data. [0203] The chemical name for lutetium-177 (177Lu)-PSMA-617 is 2-[4-[2-[[4-[[(2S)-l- [[(5S)-5-carboxy-5-[[(lS)-l,3-dicarboxy propyl]carbamoylamino]pentyl]amino]-3-naphthalen-2- yl-l-oxopropan-2-yl]carbamoyl]cyclohexyl]methylamino]-2-oxoethyl]-4,7, 10- tris(carboxylatomethyl)-l,4,7,10-tetrazacyclododec-l-yl]acetate; lutetium-177(3+). The molecular mass is 1216.06 g/mol and the molecular formula is C49H68177LuN9Oi6. The chemical structure for lutetium Lu 177 vipivotide tetraxetan is shown below:
[0204] The antitumor activity of a-emitting radioligand was first demonstrated by 223Ra- dichloride, an a-emitting radionuclide therapy (RNT) that binds areas of increased bone turnover. 223Ra-di chloride showed an overall survival (OS) benefit and a reduced time to the first symptomatic skeletal event in patients with mCRPC involving bone. Several a-emitting PSMA- targeted radioligands, including an antibody -based RNT, 225Ac-J591, and the small molecules 225Ac-PSMA-617 and PSMA-targeted 227Th conjugate (BAY2315497) are currently in clinical development. The high-energy, short-range a-emissions enable pinpoint tumor targeting, which has advantages in patients with marrow infiltration due to the limited crossfire effect on surrounding bone marrow reserve but also has limitations in the setting of heterogeneous cellular PSMA expression within tumor deposits.
[0205] Antibody-based radioligands have pharmacokinetics different from those of small molecules and have been shown to have less uptake in glandular tissue and kidneys but may also have less tumor uptake. In a Phase 1 clinical trial, 22 men (55% had previously received 177Lu- PSMA) received a single dose of 225AC-J591 across 7 dose levels (13.3-93.3 kBq/kg). One patient receiving 80 kBq/kg had dose-limiting toxicities, with grade 4 thrombocytopenia and anemia in the context of prior treatment with 177Lu-PSMA. Thirty-five percent of patients to date have had a PSA decline of more than 50%, and although PSMA uptake was not a selection criterion, most patients had PSMA uptake with an SUVmax greater than that seen in the liver. This trial has recently begun the Phase 2a expansion.
[0206] Retrospective case series of patients treated with 225Ac-PSMA-617 showed antitumor activity in 60-70%, including in some patients who had progressed on 177Lu-PSMA. Xerostomia and weight loss were clinically significant. A recent study evaluating 225Ac-PSMA- 617 in mCRPC patients who had progressed on abiraterone or enzalutamide, taxane-based chemotherapy, and 177Lu-PSMA and demonstrated PSMA-ligand uptake on imaging reported a PSA decline of at least 50% in 17 of 26 (65%) patients. Median OS was 7.7 months. Grade 3 or 4 myelosuppression was seen in 35% of patients, grade 1 or 2 renal impairment in 19%, and grade 1 or 2 xerostomia in 100%. The clinical context in which a-emitting RNT will be used is yet to be defined.
[0207] Given their distinct properties and emerging evidence of antitumor activity when a- and P-emitting PSMA-targeted therapies are given sequentially, rational combination of these radioisotopes may serve a complementary role when delivered concurrently or sequentially. [0208] Combination therapies: Purported acquired resistance mechanisms to PSMA- targeted radionuclides include heterogeneity or loss of PSMA expression or a failure to deliver a sustained lethal dose to the target. Potential strategies to improve PSMA-targeted therapies include combining PSMA-targeted therapies with agents that upregulate PSMA expression, increase tumor radiosensitivity, target different PSMA-binding sites, or exhibit complementary antitumor effects. To this end, several potential combinations are being explored in ongoing clinical studies. These include the combination of PSMA-targeting RNT with AR-targeted agents, DNA repair inhibitors, immunotherapies, chemotherapy, or a combination of different PSMA-targeting RNTs.
PSMA-Targeting Antibody Drug Conjugates (ADC)
[0209] PSMA is a well-established target in the therapeutic field of prostate cancer, with a number of PSMA-directed ADC treatments in development.
[0210] Exemplary PSMA-direct ADCs include: • 225Ac-J591 : anti-PSMA monoclonal antibody J591 radiolabeled with the alpha emitter actinium-225. 225Ac-J591 is described, e.g., in Tagawa et al. “Prostate-Specific Membrane Antigen-Targeting Alpha Emitter via Antibody Delivery for Metastatic Castration-Resistant Prostate Cancer: A Phase I Dose-Escalation Study of 225Ac-J591.” Journal of Clinical Oncology 42.7 (2024): 842-851.
• PSMA ADC: a fully human immunoglobulin G1 anti-PSMA monoclonal antibody conjugated to monomethylauristatin E, and which is described in, e.g., Petrylak et al. “PSMA ADC monotherapy in patients with progressive metastatic castration-resistant prostate cancer following abiraterone and/or enzalutamide: Efficacy and safety in openlabel single-arm phase 2 study.” The Prostate 80.1 (2020): 99-108.
• MLN2704: the PSMA-targeted monoclonal antibody MLN591 conjugated to maytansinoid-1 (an antimicrotubule agent drug). Described, e.g., in Gaisky et al. “Phase I trial of the prostate-specific membrane antigen-directed immunoconjugate MLN2704 in patients with progressive metastatic castration-resistant prostate cancer.” Journal of clinical oncology 26.13 (2008): 2147-2154.
• MEDI3726: an engineered version of an anti-PSMA IgGlK antibody (J591), site- specifically conjugated with pyrrolobenzodiazepine (PBD) dimers (SG3199). Described, e.g., in de Bono et al. “Phase I study of MEDI3726: a prostate-specific membrane antigen-targeted antibody-drug conjugate, in patients with mCRPC after failure of abiraterone or enzalutamide.” Clinical Cancer Research 27.13 (2021): 3602-3609.
• MLN2704: humanized monoclonal antibody MLN591 linked to the maytansinoid DM1. Described, e.g., in Milowsky et al. “Phase 1/2 multiple ascending dose trial of the prostate-specific membrane antigen-targeted antibody drug conjugate MLN2704 in metastatic castration -resistant prostate cancer.” Urologic Oncology: Seminars and Original Investigations. Vol. 34. No. 12. Elsevier, 2016.
• ARX517: a humanized immunoglobulin G1 kappa (IgGlk) monoclonal antibody site- specifically conjugated to two of the microtubule-disrupting toxin amberstatin (AS269). Described, e.g., in Skidmore et al. “Preclinical characterization of ARX517, a nextgeneration anti-PSMA antibody drug conjugate for the treatment of metastatic castrationresistant prostate cancer.” Cancer Research 83.7_Supplement (2023): 3997-3997. • MLN2704: a humanized monoclonal antibody MLN591 targeting prostate-specific membrane antigen, linked to the maytansinoid DM1. Described, e.g., in Milowsky et al. “Phase 1/2 multiple ascending dose trial of the prostate-specific membrane antigen- targeted antibody drug conjugate MLN2704 in metastatic castration-resistant prostate cancer.” Urologic Oncology: Seminars and Original Investigations. Vol. 34. No. 12. Elsevier, 2016.
PSMA-Targeting CAR-T Cell Therapy
[0211] CAR-T cell therapies have also been investigated for treatment of prostate cancer. A first-in-human Phase I study of PSMA CAR-T (NCT03089203) enrolled mCRPC patients and treated them with a PSMA-directed armored CAR-T cell. See Narayan et al., “PSMA- targeting TGFP-insensitive armored CAR T cells in metastatic castration-resistant prostate cancer: a phase 1 trial.” Nature Medicine 28.4 (2022): 724-734.
Bi-Specific T-Cell Engagers (BiTEs)
[0212] PSMA targeted BiTEs can also be used to treat prostate cancer. One example is pasotuxizumab, which engages CD3 on T-cells and PSMA on prostate cancer cells. A Phase I trial enrolled 47 patients with mCRPC post >1 taxane and either abiraterone or enzalutamide, and escalated doses of pasotuxizumab in subcutaneous (SC) and continuous intravenous infusion (cIV) routes. See Hummel, Horst-Dieter, et al. “Pasotuxizumab, a BiTE® immune therapy for castration-resistant prostate cancer: Phase I, dose-escalation study findings.” Immunotherapy 13.2 (2021): 125-141.
PSA Expression Level and Disease
[0213] Prostate-specific antigen (PSA), also known as gamma-seminoprotein, kallikrein- 3 (KLK3), or P-30 antigen, is a glycoprotein enzyme encoded in humans by the KLK3 gene. PSA is a member of the kallikrein-related peptidase family and is secreted by the epithelial cells of the prostate gland in men and the paraurethral glands in women.
[0214] PSA is present in small quantities in the serum of men with healthy prostates, but is often elevated in the presence of prostate cancer or other prostate disorders. PSA is not uniquely an indicator of prostate cancer, but may also detect prostatitis or benign prostatic hyperplasia. [0215] PSA levels between 4 and 10 ng/mL (nanograms per milliliter) and higher are considered to be suspicious, and consideration should be given to confirming the abnormal PSA with a repeat test. That said, the "normal" reference ranges for prostate-specific antigen increase with age, as do the usual ranges in cancer (see Table A, below). See, e.g., Connolly, D., et al. "798 Population Based Age-Specific Reference Ranges for PSA." European Urology Supplements 6.2 (2007): 222, and Luboldt, Hans-Joachim, Joachim F. Schindler, and Herbert Riibben. "Age-specific reference ranges for prostate-specific antigen as a marker for prostate cancer." EAU-EBU update series 5.1 (2007): 38-48, the contents of each of which are incorporated by reference herein in their entirety.
Table A: PSA Levels in Subjects with Prostate Cancer.
[0216] Per the current U.S. Preventive Services Task Force (USPSTF) recommendation statement (dated May 8, 2018), screening for prostate cancer begins with a test that measures the amount of PSA protein in the blood. Elevated PSA may be caused by prostate cancer but can also be caused by other conditions, including an enlarged prostate (benign prostatic hyperplasia) and inflammation of the prostate (prostatitis). As such, men with elevated PSA, who have not yet been screened for using other diagnostic tests for prostate cancer often go through additional diagnostic tests.
[0217] Men with prostate cancer may be characterized as having a low, intermediate, or high risk for having/developing metastatic disease or dying of prostate cancer. PSA level is one of three variables on which the risk stratification is based; the others are the grade of prostate cancer (e.g., as determined using the Gleason grading system) and the stage of cancer based on physical examination and imaging studies. The D'Amico criteria for each risk category are: [0218] Low risk: PSA < 10, Gleason score < 6, AND clinical stage < T2a
[0219] Intermediate risk: PSA 10-20, Gleason score 7, OR clinical stage T2b/c
[0220] High risk: PSA > 20, Gleason score > 8, OR clinical stage > T3
[0221] Given the relative simplicity of the 1998 D'Amico criteria (above), other predictive models of risk stratification based on mathematical probability constructs exist or have been proposed to allow for better matching of treatment decisions with disease features (see, e.g., Rodrigues, George, et al. "Pre-treatment risk stratification of prostate cancer patients: A critical review." Canadian Urological Association Journal 6.2 (2012): 121). Studies are also being conducted into the incorporation of multiparametric MRI imaging results into nomograms that rely on PSA, Gleason grade, and tumor stage.
[0222] Following administration of a prostate cancer treatment, PSA levels can also be monitored (e.g., measured periodically (e.g., every 6-36 months)). In some embodiments, patients with high-risk disease are monitored at an increased frequency as compared to patients with lower-risk disease. If surgical therapy (i.e., radical prostatectomy) is successful at removing all prostate tissue (and prostate cancer), PSA can become undetectable within a few weeks. A subsequent rise in PSA level above 0.2 ng/mLis generally regarded as evidence of recurrent prostate cancer after a radical prostatectomy; less commonly, it may simply indicate residual benign prostate tissue.
[0223] Following radiation therapy of any type for prostate cancer, some PSA levels might be detected, even when the treatment ultimately proves to be successful. This can make interpreting the relationship between PSA levels and recurrence/persistence of prostate cancer after radiation therapy more difficult. PSA levels may continue to decrease for several years after radiation therapy. The lowest level is referred to as the PSA nadir. A subsequent increase in PSA levels by 2.0 ng/mL above the nadir is the currently accepted definition of prostate cancer recurrence after radiation therapy.
[0224] Recurrent prostate cancer detected by a rise in PSA levels after curative treatment is referred to as a “biochemical reoccurrence.” The likelihood of developing recurrent prostate cancer after curative treatment is related to the pre-operative variables described in the preceding section (PSA level and grade/stage of cancer). Low-risk cancers are the least likely to recur, but they are also the least likely to have required treatment in the first place.
[0225] PSA velocity, or the rate at which PSA levels change over a given period of time, may have value in prostate cancer prognosis. For example, men with prostate cancer whose PSA level increased by more than 2.0 ng/mL in the year before diagnosis of prostate cancer have previously been shown to have a higher risk of death from prostate cancer despite undergoing radical prostatectomy. See, e.g., D'Amico, Anthony V., et al. "Preoperative PSA velocity and the risk of death from prostate cancer after radical prostatectomy." New England Journal of Medicine 351.2 (2004): 125-135. PSA has also been found to be more useful than the PSA doubling time (PSA DT) in identifying men with life-threatening disease before start of treatment. See, e.g., Loeb, Stacy, et al. "PSA doubling time versus PSA velocity to predict high- risk prostate cancer: data from the Baltimore Longitudinal Study of Aging." European urology 54.5 (2008): 1073-1080.
[0226] Free PSA: Most PSA in the blood is bound to serum proteins. A small amount is not protein-bound and is called 'free PSA'. In men with prostate cancer, the ratio of free (unbound) PSA to total PSA is decreased. The risk of cancer increases if the free to total ratio is less than 25%. The lower the ratio is, the greater the probability of prostate cancer.
[0227] Complexed PSA: PSA exists in serum in the free (unbound) form and in a complex with alpha 1 -anti chymotrypsin; research has been conducted to see if measurements of complexed PSA are more specific and sensitive biomarkers for prostate cancer than other approaches. See, e g., Mikolajczyk, Stephen D., et al. "Free prostate-specific antigen in serum is becoming more complex." Urology 59.6 (2002): 797-802; and Naya, Yoshio, and Koji Okihara. "Role of complexed PSA in the early detection of prostate cancer." Journal of the National Comprehensive Cancer Network 2.3 (2004): 209-212. Subjects and Samples
[0228] A sample analyzed using methods, kits and systems provided herein can be any biological sample including any processed sample that includes cell free DNA (cfDNA) derived from a biological sample. In various embodiments, a sample analyzed using methods, kits and systems provided herein can be a sample obtained from a mammalian subject. In various embodiments, a sample analyzed using methods, kits and systems provided herein can be a sample obtained from a human subject.
[0229] In various instances, a human subject is a subject diagnosed or seeking diagnosis as having, diagnosed as, or seeking diagnosis as at risk of having, and/or diagnosed as or seeking diagnosis as at immediate risk of having a disease or indication associated with increased PSMA or PSA expression (e.g., prostate cancer, optionally wherein the prostate cancer is mCRPC). In various instances, a human subject is a subject identified as needing PSA or PSMA expression level screening. In certain instances, a human subject is a subject identified as needing PSA or PSMA expression level screening by a medical practitioner.
[0230] The subject may not have undergone previous treatments for prostate cancer, such as the treatments recited in this disclosure (including, e.g., PSMA- targeting therapies or other treatments for prostate cancer). In other embodiments, the subject has undergone previous treatments for prostate cancer, such as the treatments recited in this disclosure (including, e.g., PSMA-targeting therapies).
[0231] In various embodiments a subject has one or more biomarkers and/or risk factors for increased PSA or PSMA expression. In certain embodiments, a human subject is identified as in need of PSA or PSMA expression level screening based on an initial prostate cancer diagnosis. In various instances, a human subject is a subject not yet diagnosed as having, not at risk of having, not at immediate risk of having, not diagnosed as having, and/or not seeking diagnosis for prostate cancer.
[0232] In various embodiments, a sample from a subject, e.g., a human can be obtained from a liquid biopsy. In certain embodiments, a sample and/or reference is obtained from serum, plasma, or urine. In certain embodiments, the sample is serum. In certain embodiments, a sample comprises cell free DNA (cfDNA). In certain embodiments, a sample is derived from about 1 mL of blood obtained from the subject. In certain embodiments, a sample is derived from about 0.5-2 mL of blood obtained from the subject, e.g., about 0.5 to 1 .75 mL, about 0.5 to 1.5 mb, about 0.75 to 1.25 mL or about 0.9 to 1.1 mL of blood. In certain embodiments, a sample comprises circulating tumor DNA (ctDNA). In certain embodiments, a sample is derived from about 1 mL of blood obtained from the subject.
[0233] In various embodiments, a sample is a sample of cell-free DNA (cfDNA). cfDNA is typically found in human biofluids (e.g., plasma, serum, or urine) in short, double-stranded fragments. The concentration of cfDNA is typically low, but can significantly increase under particular conditions, including without limitation pregnancy, autoimmune disorders, myocardial infarction, and cancer. Circulating tumor DNA (ctDNA) is a component of cell-free DNA specifically derived from cancer cells. ctDNA can be present in human biofluids bound to leukocytes and erythrocytes or not bound to leukocytes and erythrocytes. Various tests for detection of tumor-derived ctDNA are based on detection of genetic or epigenetic modifications that are characteristic of cancer (e.g., of a relevant cancer). Genetic or epigenetic factors characteristic of cancer can include, without limitation, oncogenic or cancer-associated mutations in tumor-suppressor genes, activated oncogenes, chromosomal disorders, histone modifications (e.g., histone methylation and/or histone acetylation), chromatin accessibility, binding of one or more transcription factors and/or DNA methylation.
[0234] In various embodiments, ctDNA comprises less than 30%, less than 20%, or less than 10% of the cfDNA in the liquid biopsy sample obtained from the subject, e.g., less than 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2% or less than 1% of the cfDNA in the sample. In some embodiments, the percentage of ctDNA in the liquid biopsy sample is assessed using ichorCNA which estimates the percentage of ctDNA in a sample probabilistically (see Adalsteinsson et al., Nat Commun (2017) 8(1): 1324 the entire contents of which are incorporated herein by reference).
[0235] cfDNA and ctDNA can provide a real-time or nearly real time metric of status of a source tissue. cfDNA and ctDNA demonstrate a half-life in blood of about 2 hours, such that a sample taken at a given time provides a relatively timely reflection of the status of a source tissue.
[0236] In various embodiments, a sample is a sample of cell-free DNA (cfDNA). cfDNA is typically found in human biofluids (e.g., plasma, serum, or urine) in short, double-stranded fragments. The concentration of cfDNA is typically low, but can significantly increase under particular conditions, including without limitation pregnancy, autoimmune disorders, myocardial infarction, and cancer.
[0237] cfDNA can provide a real-time or nearly real time metric of status of a source tissue. cfDNA demonstrates a half-life in blood of about 2 hours, such that a sample taken at a given time provides a relatively timely reflection of the status of a source tissue.
[0238] Various methods of isolating nucleic acids from a sample (e.g., of isolating cfDNA from blood or plasma) are known in the art. Nucleic acids can be isolated using, without limitation, standard DNA purification techniques, by direct gene capture (e.g., by clarification of a sample to remove assay-inhibiting agents and capturing a target nucleic acid, if present, from the clarified sample with a capture agent to produce a capture complex and isolating the capture complex to recover the target nucleic acid).
[0239] Reagents and protocols for obtaining and analyzing cfDNA and ctDNA, such as circulating in blood or other tissue, are commercially available as described in the Examples and well-known in the art (see, for example, Anker et al., Cancer and Metastasis Rev (1999) 18:65- 73; Wua et al., Clin Chim Acta (2002) 321 :77-87; Fiegl et al., Cancer Res (2005) 15:1141-1145; Pathak et al., Clin Chem (2006) 52: 1833-1842; Schwarzenbach et al., Clin Cancer Res (2009) 15: 1032-1038; Schwarzenbach et al., Nat Rev Cancer (2011) 11:426-437) the contents of each of which is separately incorporated herein by reference in their entirety).
[0240] In various embodiments, samples can be collected from individuals repeatedly over a period of time (e.g., once daily, weekly, monthly, annually, biannually, etc.). In various embodiments, such samples can be used to verify results from earlier detections and/or to identify an alteration in biological pattern because of, for example, disease progression, resistance to therapy, treatment, remission, and the like. For example, subject samples can be taken and monitored every month, every two months, or combinations of one, two, or three- month intervals according to the present disclosure. In various embodiments, samples can be collected for monitoring over time beginning at or at certain clinically determined stages, such as at resistance to a therapy, before radiographic progression, after radiographic progression, and/or at tissue biopsy. In addition, the PSMA expression measured at different points in time can be conveniently compared with each other, as well as with those of normal controls during the monitoring period, thereby providing the subject’s own values, as an internal, or personal, control for long-term monitoring.
[0241] Samples include materials prepared by processes including, without limitation, steps such as concentration, dilution, adjustment of pH, removal of high abundance polypeptides (e.g., albumin, gamma globulin, and transferrin, etc.), addition of preservatives, addition of calibrants, addition of protease inhibitors, addition of denaturants, desalting, concentration and/or extraction of sample nucleic acids, and/or amplification of sample nucleic acids (e.g., by PCR or other nucleic acid amplification techniques). Samples also include materials prepared by techniques that isolate, e.g., nucleosomes or transcription factors and/or nucleic acids associated with nucleosomes or transcription factors.
[0242] Removal from a sample of proteins that are not desirable for a relevant purpose or context (e g., high abundance, uninformative, or undetectable proteins) can be achieved using high affinity reagents, high molecular weight filters, ultracentrifugation and/or electrodialysis. High affinity reagents include antibodies or other reagents (e.g., aptamers) that selectively bind to high abundance proteins. Sample preparation can also include ion exchange chromatography, metal ion affinity chromatography, gel filtration, hydrophobic chromatography, chromatofocusing, adsorption chromatography, isoelectric focusing and related techniques.
Molecular weight filters include membranes that separate molecules based on size and molecular weight. Such filters may further employ reverse osmosis, nanofiltration, ultrafiltration and microfiltration. Ultracentrifugation is the centrifugation of a sample at about 15,000-60,000 rpm while monitoring with an optical system the sedimentation (or lack thereof) of particles. Electrodialysis is a procedure which uses an electromembrane or semipermeable membrane in a process in which ions are transported through semi-permeable membranes from one solution to another under the influence of a potential gradient. Since the membranes used in electrodialysis may have the ability to selectively transport ions having positive or negative charge, reject ions of the opposite charge, or to allow species to migrate through a semipermeable membrane based on size and charge, it renders electrodialysis useful for concentration, removal, or separation of electrolytes.
[0243] Separation and purification in the present disclosure may include any procedure known in the art, such as capillary electrophoresis (e.g., in capillary or on-chip) or chromatography (e.g., in capillary, column or on a chip). Electrophoresis is a method that can be used to separate ionic molecules under the influence of an electric field. Electrophoresis can be conducted in a gel, capillary, or in a microchannel on a chip. Examples of gels used for electrophoresis include starch, acrylamide, polyethylene oxides, agarose, or combinations thereof. A gel can be modified by its cross-linking, addition of detergents, or denaturants, immobilization of enzymes or antibodies (affinity electrophoresis) or substrates (zymography) and incorporation of a pH gradient. Examples of capillaries used for electrophoresis include capillaries that interface with an electrospray.
[0244] Capillary electrophoresis (CE) is preferred for separating complex hydrophilic molecules and highly charged solutes. CE technology can also be implemented on microfluidic chips. Depending on the types of capillary and buffers used, CE can be further segmented into separation techniques such as capillary zone electrophoresis (CZE), capillary isoelectric focusing (CIEF), capillary isotachophoresis (CITP) and capillary electrochromatography (CEC). An embodiment to couple CE techniques to electrospray ionization involves the use of volatile solutions, for example, aqueous mixtures containing a volatile acid and/or base and an organic such as an alcohol or acetonitrile.
[0245] Capillary isotachophoresis (CITP) is a technique in which the analytes move through the capillary at a constant speed but are nevertheless separated by their respective mobilities. Capillary zone electrophoresis (CZE), also known as free-solution CE (FSCE), is based on differences in the electrophoretic mobility of the analytes, determined by the charge on the analytes, and the frictional resistance the analytes encounter during migration, which is often directly proportional to the size of the analytes. Capillary isoelectric focusing (CIEF) allows weakly-ionizable amphoteric molecules, to be separated by electrophoresis in a pH gradient.
CEC is a hybrid technique between traditional high performance liquid chromatography (HPLC) and CE.
[0246] Separation and purification techniques used in the present disclosure can include any chromatography procedures known in the art. Chromatography can be based on the differential adsorption and elution of certain analytes or partitioning of analytes between mobile and stationary phases. Different examples of chromatography include, but not limited to, liquid chromatography (LC), gas chromatography (GC), high performance liquid chromatography (HPLC), etc.
[0247] In some embodiments, whole blood is collected from a subject, and a plasma layer is separated by centrifugation. cfDNA may be then extracted from the plasma using methods known in the art.
Histone Modifications, Chromatin Accessibility and Transcription Factor Binding [0248] Histone methylation is understood to increase or decrease expression of associated coding sequences, depending on which histone residue is methylated. Histone methylation is an essential modification that can cause monomethylation (mel), dimethylation (me2), and trimethylation (me3) of several amino acids, thus directly affecting heterochromatin formation, gene imprinting, X chromosome inactivation, and gene transcriptional regulation. Histone methyltransferases promote monomethylation, dimethylation, or trimethylation of histones while histone demethylases promote demethylation of histones. In general, lysine (Lys or K), arginine (Arg or R), and rarely histidine (His or H) are the most common histone methyl acceptors. Histone methylation only occurs at specific lysine and arginine sites of histone H3 and H4. In histone H3, lysine 4, 9, 26, 27, 36, 56, and 79 and arginine 2, 8, and 17 can be methylated. By comparison, histone H4 has fewer methylation sites, in which only lysine 5, 12, and 20 and arginine 3 can be methylated. Histone methylation is often associated with transcriptional activation or inhibition of downstream genes. The methylation of histone H3K4, R8, R17, K26, K36, K79, H4R3, and K12 can activate gene transcription. However, the methylation of histone H3K9, K27, K56, H4K5, and K20 can inhibit gene transcription. Thus, for example, H3K4 methylation generally activates gene expression, while H3K27 methylation generally represses gene expression.
[0249] Histone acetylation occurs predominantly at lysine residues and is generally understood to increase expression of associated coding sequences. Without wishing to be bound by any theory, acetylation of lysine residues is thought to neutralize lysine’s positive charge and thereby cause histones to drift away from DNA, which has a negative charge. The released structure facilitates access to transcriptional machinery such as transcription factors and RNA polymerase II. Histone acetylation and deacetylation are generally catalyzed by histone acetyltransferases (HATs) and HDACs, respectively. Acetyl-CoA can be a source and co-factor of acetylation. In regulatory regions, HATs can acetylate histones and recruit HAT-containing complexes to activate the transcriptional process. For instance, H3K9ac and H3K27ac levels can be associated with promoter and enhancer activities. Furthermore, H3K27ac enhances not only the kinetics of transcriptional activation, but also accelerates the transition of RNA polymerase II from the initiation state to the elongation state.
[0250] Differential modification of a genomic locus (e.g., differential histone methylation and/or differential histone acetylation) can refer to, or be determined by or detected as, a comparative difference or change in modification status of one or more genomic loci between a first sample, condition, disease, or state and a second or reference sample, condition, disease, or state. Those of skill in the art will appreciate that a reference is typically produced by measurement using a methodology identical, similar, or comparable to that by which a compared non-reference measurement was taken.
[0251] Chromatin accessibility can refer to the degree to which nuclear macromolecules are able to physically contact DNA and is determined in part by the occupancy and modification status of nucleosomes. Modified histones can regulate chromatin accessibility through a variety of mechanisms, such as altering transcription factor (TF) binding through steric hindrance and modulating nucleosome affinity for active chromatin remodelers. The topological organization of nucleosomes across the genome is non-uniform: while histones can be densely arranged within facultative and constitutive heterochromatin, histones can be depleted at regulatory loci, including within enhancers, insulators and transcribed gene bodies. Active regulatory elements of the genome are generally accessible.
[0252] Differential accessibility of a genomic locus can refer to, or be determined by or detected as, a comparative difference or change in modification status of one or more genomic loci between a first sample, condition, disease, or state and a second or reference sample, condition, disease, or state. Those of skill in the art will appreciate that a reference is typically produced by measurement using a methodology identical, similar, or comparable to that by which a compared non-reference measurement was taken.
[0253] A reference can be a value or set of values that are predetermined or derived from a sample or set of samples. A reference can be a sample or set of samples. A reference value can be a predetermined threshold value, a value that varies in accordance with circumstances (e.g., according to patient subpopulation, age, weight, or other variables), or a ratio. Reference ratios can be ratios relating to the modification and/or accessibility of multiple loci within individual samples and/or references, or across or between samples and/or references. In various embodiments, a reference can have or represent a normal, non-diseased state. In some embodiments, such as for staging of disease or for evaluating the efficacy of treatment, a reference can have or represent a diseased state, e.g., prostate cancer. In some embodiments, a reference can represent prostate cancer by being obtained from a subject diagnosed as having prostate cancer (e.g., based on imaging, symptoms, and/or biomarker analysis).
[0254] In certain instances, a reference is a non-contemporaneous sample from the same source, e.g., a prior sample from the same source, e.g., from the same subject. In certain instances, a reference for the modification status of one or more genomic loci (e.g., one or more differentially modified genomic loci) can be the modification status of the one or more genomic loci (e.g., one or more differentially modified genomic loci) in a sample (e.g., a sample from a subject), or a plurality of samples, known to represent a particular state (e.g., mCRPC with elevated PSMA expression or prostate cancer with elevated serum PSA). In certain instances, a reference for the accessibility status of one or more genomic loci (e.g., one or more differentially accessible genomic loci) can be the accessibility status of the one or more genomic loci (e.g., one or more differentially accessible genomic loci) in a sample (e.g., a sample from a subject), or a plurality of samples, known to represent a particular state (e.g., mCRPC with elevated PSMA expression or prostate cancer with elevated serum PSA).
[0255] In some illustrative but non-limiting embodiments of the present disclosure differential modification or differential accessibility can refer to a differential (e.g., between a sample and a reference) with an absolute log2(fold-change) that is greater than or equal to 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0 or more, or any range in between, inclusive, e.g., as measured according to an assay provided herein.
[0256] Enhancers are genomic loci that can be differentially modified or differentially accessible in and/or between conditions, diseases, and other states. Enhancers are cis-acting DNA regulatory regions that are thought to bind trans-acting proteins that contribute to expression patterns of associated genes. Chromatin ImmunoPrecipitation sequencing (ChlP-seq) of histone modifications (e.g., acetylation) have identified millions of enhancers in mammalian genomes. The number of active enhancers in any given cell type is estimated to be in the tens of thousands. Certain transcription factors (TFs), sometimes referred to as “master” transcription factors, associate with active enhancers with important impacts on gene expression and cell function. Certain such transcription factors preferentially associate with enhancers that regulate genes required for establishing cell identity and function, including enhancer domains known as “super-enhancers”. Moreover, master TFs can participate in inter-connected auto-regulatory circuitries or “cliques” that are self-reinforcing, show marked cell selectivity, and function to maintain cell state and/or cell survival.
Techniques for Detecting and Quantifying Histone Modifications and Transcription Factor Binding
[0257] Various techniques of molecular biology are well known in the art and/or disclosed in the present application for detecting and quantifying histone modifications and/or transcription factor binding. In some embodiments, the methods, kits and systems of present disclosure involve the detection and quantification of histone modifications and/or transcription factor binding in samples, e.g., in liquid biopsy samples including cfDNA such as plasma samples including cfDNA. Chromatin ImmunoPrecipitation (ChIP) is one technique of molecular biology useful in detecting and quantifying histone modifications and transcription factor binding in samples. CUT&RUN or CUT&Tag are other more recent techniques that can also be used to detect and quantify histone modifications and transcription factor binding sites. ChIP -chip, ChlP-exo, ChIP Re-ChIP, and ChlPmentation are other alternative techniques that could be used.
[0258] ChIP can involve various steps including one or more of fixation, sonication, immunoprecipitation, and analysis of the immunoprecipitated DNA. ChIP has become a very widely used tissue-based technique for determining the in vivo location of binding sites of various transcription factors and histones. Because the proteins are captured at the sites of their binding with DNA, ChIP helps to detect DNA-protein interactions that take place in living cells. More importantly, ChIP can be coupled to many commonly used molecular biology techniques such as PCR and real-time PCR, PCR with single-stranded conformational polymorphism, Southern blot analysis, Western blot analysis, cloning, and microarray. The resulting versatility has increased the potential of this technique.
[0259] ChIP of tissue samples usually involves cross-linking of the chromatin-bound proteins by formaldehyde, followed by sonication or nuclease treatment to obtain small DNA fragments. Immunoprecipitation can be then carried out using specific antibodies to the DNA- binding protein of interest. The DNA can be then released from the proteins and analyzed using various methods. ChIP has also been used to study RNA-protein interactions. X-ChIP methods utilize fixed chromatin fragmented by sonication, while the N-ChIP methods utilize native chromatin, which can be unfixed and nuclease digested.
[0260] The first step of the technique can be the cross-linking of DNA and proteins. Formaldehyde is one of the most used cross-linking agents. One advantage of using formaldehyde can be the ease of reversibility of the cross-links and its ability to form bonds that span approximately 2 angstroms. This means that formaldehyde can bind molecules in close association with each other. Generally, formaldehyde can be added to the medium in the cell culture flask or plate. It enters the cells through the cell membrane and cross-links the proteins to the chromatin. Formaldehyde fixation of tumor tissues has also been done. Other cross-linking agents that have been used include chemicals such as methylene blue and acridine orange, cisplatin, dimethylarsinic acid, potassium chromate, and ultraviolet (UV) light and lasers.
[0261] Harvested chromatin can be sonicated in one or more sonication cycles. DNA can be typically broken into to 100-500 bp fragments to pinpoint the location of the DNA sequence of interest. An alternative to sonication can be nuclease digestion of the chromatin, e.g., in N- ChlP methods. Purification of chromatin can be achieved using a cesium chloride (CsCl) gradient centrifugation.
[0262] Chromatin can be immunoprecipitated using one or more antibodies that bind a target epitope. For example, an antibody used in ChIP can selectively bind a particular transcription factor or one or more particular histone modifications, such as one or more particular histone acetylation modifications or histone methylation modifications. In some embodiments, an antibody used to bind a target epitope can be a “pan” antibody (e.g., a panacetylation antibody, a pan-methylation antibody, an antibody that binds a group of histone modifications associated with increased transcription activation, and/or an antibody that binds a group of histone modifications associated with increased transcription repression). The antibody against the protein of interest is allowed to bind to the protein-DNA complex, and the complex can be then precipitated. Immunosorbants commonly used to separate the antigen-antibody complex from the lysate include salmon sperm DNA-protein A-Sepharose®, protein G, magnetic beads, and other engineered immunoprecipitation systems known to those of skill in the art.
[0263] Immunoprecipitated DNA can be eluted. Once the DNA of interest is isolated, many detection and quantification methods can be used to study the isolated gene fragments. Commonly utilized methods include PCR, real-time PCR, slot blot hybridization, microarray techniques, and deep or next-generation sequencing. ChlP-seq combines chromatin immunoprecipitation (ChIP) with massively parallel DNA sequencing to identify the binding sites of DNA-associated proteins. ChlP-seq can be used to map DNA-binding proteins, e.g., transcription factor binding sites and histone modifications in a genome-wide manner.
[0264] Cell-free Chromatin ImmunoPrecipitation sequencing (cfChlP-seq) involves applying ChlP-seq to samples that include cell-free DNA, e.g., liquid biopsy samples including cfDNA such as plasma samples including cfDNA (e.g., see Sadeh et al., Nat Biotechnol (2021) 39: 586-598 and Jang et al., Life Sci Alliance (2023) 6(12):e202302003 the entire contents of each of which are incorporated herein by reference). In some embodiments, cfChlP-seq uses antibodies or antibody fragments that bind specific histone modifications (e.g., H3K4me3 and/or H3K27ac) and/or transcription factors that are coupled (covalently or non-covalently) to beads, e g., magnetic beads such as Dynabeads® magnetic beads and incubated with a volume, e.g., about 1 mL of thawed plasma obtained from a subject. Without limitation, exemplary antibodies that bind H3K4me3 include PA5-27029 (available from Thermo Fisher Scientific in Waltham, MA) and C15410003 (available from Diagenode in Denville, NJ) and exemplary antibodies that bind H3K27ac include ab21623 or ab4729 (both available from Abeam in Cambridge, UK) and Cl 5210016 (available from Diagenode in Denville, NJ).
[0265] In some embodiments, the antibodies or antibody fragments can be covalently coupled to beads, e.g., epoxy beads. In some embodiments, the antibodies or antibody fragments can be non-covalently coupled to beads, e.g., Protein A or Protein G beads such as Dynabeads® Protein A or Dynabeads® Protein G beads. After washing, a cfDNA library is then typically prepared from the captured cfDNA. Library preparation can be done on-bead or after releasing the captured cfDNA by digestion of bound histones, e g., using proteinase K. The cfDNA library is then sequenced to generate reads of captured cfDNA sequences, e.g., by next-generation sequencing (NGS) as is known in the art. The reads are then analyzed, e.g., aligned and counted using standard bioinformatic techniques as is known in the art. A cfChlP-seq bioinformatic pipeline can include, e.g., alignment of sequence reads to a reference genome with BWA or Bowtie2. Aligned reads can be used to call and quantify peaks as compared to a reference.
[0266] CUT&Tag involves antibody-based binding of a target protein, e.g., transcription factor or histone modification of interest, where antibody incubation is directly followed by the shearing of the chromatin and library preparation (see Kaya-Okur et al., Nat Comm (2019) 10: 1930). CUT&Tag assays take advantage of a Tn5 transposase that is fused with Protein A to direct the enzyme to the antibody bound to its target on chromatin. Tn5 transposase is pre-loaded with sequencing adapters (generating the assembled pA-Tn5 adapter transposome) to carry out antibody-targeted tagmentation. In a typical CUT&Tag assay samples are incubated with an antibody immobilized on Concanavalin A-coated magnetic beads to facilitate subsequent washing steps. Cells can be incubated with a primary antibody specific for the target protein of interest followed by incubation with a secondary antibody. Samples can then be incubated with assembled transposomes, which consist of Protein A fused to the Tn5 transposase enzyme that is conjugated to NGS adapters. After incubation, unbound transposome can be washed away using stringent conditions. Tn5 is a Mg2+-dependent enzyme so Mg2+ can be added to activate the reaction, which results in the chromatin being cut close to the protein binding site and simultaneous addition of the NGS adapter DNA sequences. Chromatin cleavage and library preparation can be achieved in one single step.
[0267] CUT&RUN is an epigenomic profiling strategy in which antibody-targeted controlled cleavage by micrococcal nuclease releases specific protein-DNA complexes into the supernatant for paired-end DNA sequencing (see Skene and Henikoff, Elife (2017) 6:1-35, Skene et al., Nat Protoc (2018) 13:1006-1019). As only targeted fragments enter into solution, and the vast majority of DNA is left behind, CUT&RUN has low background levels. In an example CUT&RUN assay, a sample is incubated with an antibody or antibody fragment that binds the target protein, e.g., transcription factor or histone modification of interest. The sample is then incubated with Protein-A-MNase after which CaCh can be added to initiate the calcium dependent nuclease activity of MNase to cleave the DNA around the target protein. The protein- A-MNase reaction can be quenched by adding chelating agents (EDTA and EGTA). Cleaved DNA fragments are then liberated, extracted, and used to construct a sequencing library.
Techniques for Detecting and Quantifying Chromatin Accessibility
[0268] Various techniques of molecular biology are well known in the art and/or disclosed in the present application for detecting and quantifying chromatin accessibility. In some embodiments, the methods, kits and systems of the present disclosure involve the detection and quantification of chromatin accessibility in samples, e.g., in liquid biopsy samples including cfDNA such as plasma samples including cfDNA. ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde-Assisted Isolation of Regulatory Elements sequencing), MNase-seq (Micrococcal Nuclease digestion with sequencing), and DNase hypersensitivity assays are exemplary techniques of molecular biology useful in detecting and quantifying chromatin accessibility in samples. Sono-Seq is another alternative method that could be used (see Auerbach et al., Proc Natl Acad USA (2009) 106(35): 14926-14931). Fragmentomics-based methods are yet another method that can be used to assess chromatin accessibility (see Ding, Spencer C., and YM Dennis Lo. "Cell-free DNA fragmentomics in liquid biopsy." Diagnostics 12.4 (2022): 978).
[0269] DNase hypersensitivity assays can use the non-specific DNA endonuclease Deoxyribonuclease I (DNase I), which selectively digests accessible DNA regions. DNase I hypersensitivity sites (DHS) identified by DNase-seq include open chromatin regulatory regions. A typical DNase hypersensitivity assay can include a first step in which nuclei are isolated from cells using lysis buffer, and nuclei are digested using DNase I. DNA fragment sizes are measured to identify optimal digestion using gel electrophoresis. Biotinylated linkers can be ligated to the ends of digested DNA after polishing to make blunt ends, and the DNA can then be isolated. DNA with biotinylated linker can be digested by restriction endonuclease Mmel and captured by streptavidin coated Dynabeads® to generate short tags to which a second sequencing adaptor can be ligated. A second linker can be ligated and amplified to generate a library for sequencing. A DNase-seq bioinformatic pipeline can include, e.g., alignment of sequence reads to a reference genome with BWA or Bowtie2. Aligned reads can be used to call and quantify peaks as compared to a reference.
[0270] MNase-seq determines chromatin accessibility with micrococcal nuclease (MNase) that preferentially digests nucleosome-free, protein-unbound DNA. A typical MNase- seq assay can include a first step in which nuclei are isolated from either native or crosslinked chromatin and digested using MNase with titration. In vivo formaldehyde crosslinking step that is designed to capture the interaction between proteins and DNA. This crosslinking allows bound proteins to shield their associated DNA from digestion by MNase. Following crosslinking, samples are digested with MNase, which can be specifically activated by addition of Ca2+ to the buffer. Digestion can be halted by chelating the reaction, at which point the samples are RNase treated, crosslinks are reversed, and proteins are digested away from the chromatin. DNA can then be isolated via a phenol-chloroform extraction. Uncut DNA is purified and mononucleosome bands are isolated and excised through gel electrophoresis. Isolated DNA can be amplified by adding adapters to generate a library, and sequenced. MNase-seq primarily sequences regions of DNA bound by histones or other proteins. Therefore, it indirectly determines which regions of DNA are accessible by directly determining which regions are bound to nucleosomes or proteins.
[0271] FAIRE-seq is a method in which nucleosome-depleted regions of DNA (NDRs) are isolated from chromatin. A typical FAIRE-seq assay can include a first step in which cells are fixed using formaldehyde so that histones are crosslinked to interacting DNA. Crosslinked chromatin can then be sheared by sonication that generates protein-free DNA and protein- crosslinked DNA fragments. Protein-free DNA can be isolated using a phenol-chloroform extraction: DNA crosslinked with protein stays in organic phase, while protein-free DNA stays in aqueous phase. Highly crosslinked DNA remains in the organic phase and the non-crosslinked DNA is pulled to the aqueous phase. Non-crosslinked DNA from the aqueous phase can then be amplified and sequenced. Reads enriched in the sequencing pool tend to have lower nucleosome and transcription factor binding and are therefore inferred to come from accessible regions. [0272] NOMe-seq is a method to identify nucleosome-depleted regions of DNA (NDRs) with M.CviPI methyltransferase that methylates cytosine in GpC dinucleotides not protected by nucleosomes or other proteins. Unlike CrapG, GpCm in the human genome does not occur naturally in most cell types. GpCin levels at open chromatin regions can be compared to background signals and used to detect and quantify NDRs. A typical NOMe-seq protocol can include a step in which samples are treated with M.CviPI and S-adenosylhomocysteine (SAM) to methylate accessible GpC sites. M.CviPI treated DNA can be sheared using a sonicator, so that DNA fragments can be sequenced. DNA is treated with bisulfite, which converts unmethylated cytosine to uracil using sodium bisulfite, while methylated cytosine is unaffected. A library is generated using adapters and sequenced. Accessible chromatin is expected to have high levels of GpCm but low levels of CmpG. Therefore, NOMe-seq identifies NDRs using the two separate methylation analyses that serve as independent (but opposite) measures, providing matched chromatin designations for each regulatory element.
[0273] ATAC-seq uses hyperactive Tn5 transposase that preferentially cuts accessible chromatin regions and simultaneously inserts adapters to the fragmented region (Buenrostro et al., Nat Methods (2013) 10(12): 1213-1218 the entirety of which is incorporated herein by reference). A typical ATAC-seq assay can include a first step in which samples are incubated with Tn5 transposase. DNA can then be isolated and purified. DNA fragmented and tagged by Tn5 transposase can be purified and then amplified to generate a library and sequenced for analysis.
[0274] “Fragmentomics” or a “fragmentomics assay” refers to methods that use certain size and sequence characteristics of cfDNA to gain insight into the epigenetic state of cells at the time their genomic DNA was released into the extracellular environment. Without wishing to be bound by theory, upon release of genomic DNA from a cell into the extracellular environment, nucleases rapidly cleave the genomic DNA into short fragments. The cleavage pattern and sequences of the fragments reflect the positioning of nucleosomes genome-wide at the point of cell death, and by finding nucleosomes that are consistently genomically positioned across cancer cells (i.e. many of the circulating tumor DNA fragments that map to that small region of the genome have the same start and end positions or similar fragment length characteristics) fragmentomics attempts to infer the location of stably positioned nucleosomes at regulatory sites, and thus to infer where the active regulatory sites are in a given cell type. Accordingly, analysis of cfDNA fragmentation patterns can be used to infer characteristics of the cells at the time they released genomic DNA. Examples of metrics commonly measured in fragmentomics include fragment size, preferred ends, end motifs, single-stranded jagged ends, and nucleosomal footprints. Approaches for measuring fragmentomics metrics include, e.g., qPCR, electron microscopy, single molecule sequencing, and next-generation sequencing. A relationship between fragmentomic metrics and histone modifications (h3K4me3 and H3K27ac) has been established. See Bai, Jinyue, et al. "Histone modifications of circulating nucleosomes are associated with changes in cell-free DNA fragmentation patterns." Proceedings of the National Academy of Sciences 121.42 (2024): e2404058121.
Techniques for Detecting and Quantifying DNA Methylation
[0275] Various techniques of molecular biology are well known in the art and/or disclosed in the present application for detecting and quantifying DNA methylation. In some embodiments, the methods, kits and systems of the present disclosure involve the detection and quantification of chromatin accessibility in samples, e.g., in liquid biopsy samples including cfDNA such as plasma samples including cfDNA. Bisulfite sequencing (BS-Seq), Whole Genome Bisulfite Sequencing (WGBS), Methylated DNA ImmunoPrecipitation sequencing (MeDIP-seq), or Methyl-CpG-Binding Domain sequencing (MBD-seq) are exemplary techniques of molecular biology useful in detecting and quantifying chromatin accessibility in samples. Reduced representation bisulfite sequencing (RRBS) is another alternative method that could be used (see Meissner et al., Nucleic Acids Res (2005) 33( 18): 5868-5877). Illumina Infinium arrays could also be used to detect and quantify DNA methylation.
[0276] DNA methylation typically refers to the methylation of the 5’ position of cytosine (mC) by DNA methyltransferases (DNMT). It is a major epigenetic modification in humans and many other species. In mammals, most DNA methylations occur within the context of CpG dinucleotides. DNA methylation is thought to be a repressive chromatin modification. Aberrant methylation can lead to many diseases including cancers (Robertson, Nat Rev Genet (2005) 6:597-610 and Bergman and Cedar, Nat Struct Mol Biol (2013) 20:274-281).
[0277] Bisulfite sequencing (BS-Seq) or Whole-Genome Bisulfite Sequencing (WGBS) is a well-established protocol to detect methylated cytosines in genomic DNA. In this method, genomic DNA is treated with sodium bisulfite and then sequenced, providing single-base resolution of methylated cytosines in the genome. Upon bisulfite treatment, unmethylated cytosines are deaminated to uracils which, upon sequencing, are converted to thymidines. Simultaneously, methylated cytosines resist deamination and are read as cytosines. The location of the methylated cytosines can then be determined by comparing treated and untreated sequences.
[0278] MeDIP-seq was first reported by Weber et al., Nat Genet (2005) 37:853-862. In a typical MeDIP-seq protocol, antibody or antibody-fragment that binds 5-methylcytidine (5mC) is used to enrich methylated DNA fragments, then these fragments are sequenced and analyzed. If using 5mC-specific antibodies or antibody fragments, methylated DNA is isolated from genomic DNA via immunoprecipitation. Anti-5mC antibodies are incubated with fragmented genomic DNA and precipitated, followed by DNA purification and sequencing.
[0279] Methyl-CpG-Binding Domain sequencing (MBD-seq) is similar to MeDIP-seq except that it uses methyl binding domain (MBD) proteins instead of antibodies or antibody fragments to bind methylated DNA. In a typical MBD-seq protocol, genomic DNA is first sonicated and incubated with tagged MBD proteins that can bind methylated cytosines. The protein-DNA complex is then precipitated with antibody -conjugated beads that are specific to the MBD protein tag, followed by DNA purification and sequencing.
Classifiers
[0280] In some embodiments, the present disclosure provides methods for obtaining a classifier, e.g., a classifier that can be used to determine or predict PSMA expression status and/or responsiveness to a PSMA-targeted therapeutic, or determine or predict PSA expression levels. In some embodiments, a subject is determined to have an epigenetic profile indicative of a PSMA-positive cancer or a cancer more likely to respond to treatment with a PSMA-targeted therapeutic based on analysis of a biological sample, optionally of cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject. In some embodiments, a subject is determined to have an epigenetic profile indicative of a cancer associated with elevated serum PSA levels based on analysis of a biological sample, optionally of cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject.
[0281] In some embodiments, a cancer is determined to be PSMA-positive if PSMA expression is detected that is above a threshold value. In some embodiments, the threshold value is a predetermined threshold and/or a normalized value. In some embodiments, the threshold value is a PSMA expression level determined in a reference population. In some embodiments, the reference population comprises subjects having prostate cancer and previously found to respond to treatment with a PSMA-targeted therapeutic. In some embodiments, the reference population comprises subjects having cancer and previously found to not respond to treatment with a PSMA-targeted therapy. In some embodiments, the reference population comprises subjects having a PSMA-positive cancer (e.g., as determined by PSMA PET imaging). In some embodiments, the reference population comprises subjects having a low PMSA expressing cancer (e.g., as determined by PSMA PET imaging) or subjects with a cancer having a level of PSMA expression that is associated with poor response to a PSMA-targeted therapeutic. In some embodiments, the reference population comprises subjects determined to be cancer free.
[0282] In some embodiments, PSA expression is determined or predicted to be elevated if the determined or predicted value is above a threshold value. In some embodiments, the threshold value is a predetermined threshold and/or a normalized value. In some embodiments, the threshold value is a PSA expression level determined in a reference population. In some embodiments, the reference population comprises subjects having prostate cancer. In some embodiments, the reference population comprises subjects that have not been diagnosed with cancer.
Exemplary Genomic Loci
[0283] The present disclosure includes the identification of exemplary genomic loci that are differentially modified and/or differentially accessible when PSMA expression is increased (e.g., increased in mCRPC), and show that differential modifications and/or accessibility of said exemplary genomic loci is correlated with PSMA expression as measured by PSMA PET (e.g., correlated with PSMA PET SUVmean). See Tables 1-2, 4, and 5, which show the chromosomal coordinates of each genomic locus. Table 1 also provides a measure of correlation between epigenetic modifications for each genomic locus listed and PSMA PET SUVmean, as well as the TSS (transcriptional start site) closest to each locus.
[0284] The present disclosure also includes the identification of exemplary genomic loci that are differentially modified and/or differentially accessible when PSA expression is increased (e.g., as compared to healthy subjects), and show that differential modifications and/or accessibility of said exemplary genomic loci is correlated with serum PSA levels. See Table 3 which shows the chromosomal coordinates of each genomic locus.
[0285] The present disclosure is not limited to methods that use the exact same chromosomal coordinates that are recited in Tables 1-5. The present disclosure encompasses methods that use any of the genomic loci in Tables 1-5 and also subregions thereof, i.e., references herein to methods that involve detecting and/or quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci of Tables 1-5 encompasses methods that detect these marks anywhere within these genomic loci including within any subregions. For example, where Table 1 references chr5:148969823-149003022 as a genomic locus for detecting and/or quantifying H3K27ac modification, this encompasses methods that detect and/or quantify H3K27ac modification at any position or sub-region of chr5:148969823-149003022, e.g., methods that detect and/or quantify H3K27ac modification within chr5: 148969923-149002922, etc. In some embodiments, a subregion may span at least 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500 or at least 3000 contiguous base pairs that are located between the lower and upper coordinates of a genomic locus recited in Tables 1-5. In some embodiments, a subregion may span less than 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500 or at least 3000 contiguous base pairs that are located between the lower and upper coordinates of a genomic locus recited in Tables 1-5. In some embodiments, a subregion may have the same central coordinate as a genomic locus recited in Tables 1-5. In some embodiments, a subregion may have a different central coordinate as a genomic locus recited in Tables 1-5. It is also to be understood that the lower/upper coordinates of the genomic loci in Tables 1-5 are approximate and that the present disclosure encompasses methods where any one or more of the genomic loci are expanded by increasing the size of the genomic locus by 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or up to 50% in one or both directions.
[0286] In some embodiments a classifier is generated using a set of differentially modified and/or differentially accessible genomic loci that are correlated with increased PSA or PSMA expression (e.g., increased PSMA PET SUVmean or increased PSA concentrations). Sequence reads that fall into each selected genomic locus are analyzed and counted, e.g., as described herein including the Examples. In some embodiments, counts from genomic loci that are correlated with increased PSMA or PSA expression (e.g., increased PSMA PET SUVmean or increased serum PSA) are aggregated. Other ways of using the genomic loci and related sequencing data to generate and apply a classifier to determine PSMA or PSA expression level (e.g., PSMA PET SUVmean signal or serum PSA) are described herein and known in the art, e.g., without limitation, methods that use a learning statistical classifier system or a combination of learning statistical classifier systems.
[0287] In some embodiments, exemplary genomic loci from one or more of Tables 1-5 are used in a monomodal PSMA PET Score Model Predictor, e.g., a PSMA PET Score Model Predictor that uses a single histone modification (e.g., H3K4me3 or H3K27ac) or DNA methylation at one or more genomic loci for purposes of determining PSMA expression level. In some embodiments, exemplary genomic loci from any one of Table 1-5, or any combination thereof, are used in combination in a multimodal classifier, e.g., a PSMA PET Score Model Predictor that uses more than one histone modification (e.g., H3K4me3 and H3K27ac) or one or more histone modifications (e.g., H3K4me3 and/or H3K27ac) and DNA methylation at one or more genomic loci for purposes of measuring PSMA expression.
[0288] In some embodiments, a method described herein comprises quantifying one or more of a histone modification, DNA methylation, chromatic accessibility and/or binding of a transcription factor at one or more loci provided in one or more of Tables 1-5. In some embodiments, a method described herein comprises quantifying one or more of a histone modification, DNA methylation, chromatic accessibility and/or binding of a transcription factor at 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, or 30 loci listed in one or more of Tables 1-5. In some embodiments, a method described herein comprises quantifying one or more of a histone modification, DNA methylation, chromatic accessibility and/or binding of a transcription factor at each of the loci provided in Table 1, Table 2, Table 3, Table 4, and/or Table 5. In some embodiments, a method described herein comprises quantifying one or more of a histone modification, DNA methylation, chromatic accessibility and/or binding of a transcription factor for at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of loci identified in Tables 1-5, or any combination thereof. In some embodiments, a method described herein comprises quantifying one or more of a histone modification, DNA methylation, chromatic accessibility and/or binding of a transcription factor for at least a percent of loci identified in Table 1, Table 2, Table 3, Table 4, and/or Table 5 having a lower bound selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10%, and an upper bound selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100%.
Differential H3K4me3 modification
[0289] Exemplary genomic loci whose H3K4 methylation state (in particular H3K4 trimethylation, H3K4me3) is associated with PSMA expression level (e.g., PSMA PET SUVmean signal) are provided in Tables 1, 2, 4 and 5 (see H3K4me3 analyte loci). Exemplary genomic loci whose H3K4 methylation state (in particular H3K4 trimethylation, H3K4me3) is associated with PSA expression level are provided in Tables 3.
[0290] A person of skill in the art will recognize that the methods disclosed herein do not require that every H3K4me3 analyte genomic locus listed in Tables 1-5 be assessed for H3K4me3 modification. Instead, a subset of H3K4me3 analyte loci may be assessed for H3K4me3 modification. Subsets of the H3K4me3 analyte genomic loci of Tables 1-5 can be selected (e.g., for use in determining PSMA expression level or PSA expression level) based on various performance criteria, e.g., to select genomic loci that demonstrate differential modification with a particular level of statistical significance and/or a particular threshold of differential between relevant states (e.g., a measured log2(fold-change)). Subsets of the genomic loci may also be selected based on an algorithm, e.g., during the process of obtaining a classifier. Those of skill in the art will appreciate that such subsets of loci of Tables 1-5, and loci included in such subsets, are together, individually, and/or in randomly selected subsets, at least as informative (e.g., as statistically significant and/or reliable) for uses disclosed herein, e.g., for determining PSMA expression level.
[0291] In various embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular PSMA expression level if 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or 11 H3K4me3 analyte loci identified in Tables 1 and 2 are differentially H3K4me3 modified as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
[0292] In various embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular PSMA expression level if one or both H3K4me3 analyte loci identified in Table 4 are differentially H3K4me3 modified as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
[0293] In various embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular PSMA expression level if the H3K4me3 analyte loci identified in Table 5 is differentially H3K4me3 modified as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUV mean signal)).
[0294] In various embodiments, a sample or subject from which the sample is derived, is determined to have a particular PSMA expression level if one or more promoter regions of one or more H3K4me3 analyte genes (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10) in Table 1 are differentially H3K4me3 modified as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
[0295] In various embodiments, a promoter region refers to a region a certain number of nucleotides upstream of a gene (e.g., 10,000, 9,000, 8,000, 7,000, 6,000, 5,000, 4,000, 3,000, 2,000, or 1,000 nucleotides upstream of a gene). In some embodiments, a promoter region refers to a region identified in any one of Tables 1-5.
[0296] In some embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular PSMA expression level if H3K4me3 modifications for 1, 2, 3, 4, 5, 6, or 7 of the H3K4me3 analyte loci that are identified in Table 1 as having a positive association with PSMA expression are increased relative to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
[0297] In various embodiments, differentially H3K4me3 modified refers to a methylation status characterized by an increase or decrease in a value measuring methylation (e.g., of read counts and/or normalized read counts for a given genomic locus), and/or a mean, median and/or mode thereof, and/or a log thereof e.g., log base 2 (log2)), of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4- fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40- fold, 45-fold, 50-fold, or greater, or any range in between, inclusive, such as 1% to 50%, 50% to 2-fold, 25% to 50-fold, 25% to 30-fold, 25% to 20-fold, 25% to 16-fold, 30% to 16-fold, 50% to 16-fold, 70% to 16-fold, 2-fold to 16-fold, 2.2-fold to 16-fold, 2.6-fold to 16-fold, 3-fold to 16- fold, 3.4-fold to 16-fold, 4-fold to 16-fold, 4.5-fold to 16-fold, 5.2-fold to 16-fold, 6-fold to 16- fold, 7-fold to 16-fold, or 8-fold to 16-fold, as compared to a reference, optionally where the statistical significance of the increase or decrease is at least 5e-2, le-2, 5e-3, le-3, 5e-4, le-4, 5e- 5, le-5, 5e-6, or le-6. In various embodiments, an increase or decrease in a value measuring methylation can be, or is expressed as, a log2(fold-change), e.g., a log2(fold-change) of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, or greater, or any range in between, inclusive, such as an increase or decrease of 0.1 -fold to 10- fold, 0.2-fold to 5-fold, 0.2-fold to 4.0-fold, 0.4-4.0-fold, 0.4-fold to 4.0-fold, 0.6-fold to 4.0- fold, 0.8-fold to 4.0-fold, 1.0-fold to 4.0-fold. 1.2-fold to 4.0-fold. 1.4-fold to 4.0-fold, 1.6-fold to 4.0-fold, 1.8-fold to 4.0-fold, 2.0-fold to 4.0-fold, 2.2-fold to 4.0-fold, 2.4-fold to 4.0-fold, 2.6- fold to 4.0-fold, 2.8-fold to 4.0-fold, or 3.0-fold to 4.0-fold, optionally where the statistical significance of the increase or decrease is at least 5e-2, le-2, 5e-3, le-3, 5e-4, le-4, 5e-5, le-5, 5e-6, or le-6.
Differential H3K27ac modification [0298] Exemplary genomic loci whose H3K27ac state is associated with PSMA expression level (e.g., PSMA PET SUVmean signal) are provided in Tables 1, 2, 4, and 5 (see H3K27ac analyte loci).
[0299] A person of skill in the art will recognize that the methods disclosed herein do not require that every H3K27ac analyte genomic locus listed in Tables 1-5 be assessed for H3K27ac modifications. Instead, a subset of H3K27ac analyte loci may be assessed for H3K27ac modification. Subsets of the H3K27ac analyte genomic loci of Tables 1-5 can be selected (e.g., for use in determining PSMA expression level) based on various performance criteria, e.g., to select genomic loci that demonstrate differential modification with a particular level of statistical significance and/or a particular threshold of differential between relevant states (e.g., a measured log2(fold-change)). Subsets of the genomic loci may also be selected based on an algorithm, e.g., during the process of obtaining a classifier. Those of skill in the art will appreciate that such subsets of loci of Tables 1-5, and loci included in such subsets, are together, individually, and/or in randomly selected subsets, at least as informative (e.g., as statistically significant and/or reliable) for uses disclosed herein, e.g., for determining PSMA expression level.
[0300] In various embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular PSMA expression level if 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, or 19 H3K27ac analyte loci identified in Tables 1 and 2 are differentially H3K27ac modified as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
[0301] In various embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular PSMA expression level if 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more H3K27ac analyte loci identified in Table 4 are differentially H3K27ac modified as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)). [0302] In various embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular PSMA expression level if the H3K27ac analyte locus identified in Table 5 is differentially H3K27ac modified as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
[0303] In various embodiments, a sample or subject from which the sample is derived, is determined to have a particular PSMA expression level if one or more enhancer regions of one or more H3K27ac analyte genes (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10) in Table 1 are differentially H3K27ac modified as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
[0304] In some embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular PSMA expression level if H3K27ac modifications for 1, 2, 3, or 4 of the H3K27ac analyte loci that are identified in Table 1 as having a positive association with PSMA expression are increased relative to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
[0305] In various embodiments, differentially H3K27ac modified refers to an acetylation status characterized by an increase or decrease in a value measuring acetylation (e.g., of read counts and/or normalized read counts for a given genomic locus), and/or a mean, median and/or mode thereof, and/or a log thereof (e.g., log base 2 (log2)), of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4- fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40- fold, 45-fold, 50-fold, or greater, or any range in between, inclusive, such as 1% to 50%, 50% to 2-fold, 25% to 50-fold, 25% to 30-fold, 25% to 20-fold, 25% to 16-fold, 30% to 16-fold, 50% to 16-fold, 70% to 16-fold, 2-fold to 16-fold, 2.2-fold to 16-fold, 2.6-fold to 16-fold, 3-fold to 16- fold, 3.4-fold to 16-fold, 4-fold to 16-fold, 4.5-fold to 16-fold, 5.2-fold to 16-fold, 6-fold to 16- fold, 7-fold to 16-fold, or 8-fold to 16-fold, as compared to a reference, optionally where the statistical significance of the increase or decrease is at least 5e-2, le-2, 5e-3, le-3, 5e-4, le-4, 5e- 5, le-5, 5e-6, or le-6. In various embodiments, an increase or decrease in a value measuring acetylation can be, or is expressed as, a log2(fold-change), e.g., a log2(fold-change) of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, or greater, or any range in between, inclusive, such as an increase or decrease of 0.1-fold to 10- fold, 0.2-fold to 5-fold, 0.2-fold to 4.0-fold, 0.4-4.0-fold, 0.4-fold to 4.0-fold, 0.6-fold to 4.0- fold, 0.8-fold to 4.0-fold, 1.0-fold to 4.0-fold. 1.2-fold to 4.0-fold. 1.4-fold to 4.0-fold, 1.6-fold to 4.0-fold, 1.8-fold to 4.0-fold, 2.0-fold to 4.0-fold, 2.2-fold to 4.0-fold, 2.4-fold to 4.0-fold, 2.6- fold to 4.0-fold, 2.8-fold to 4.0-fold, or 3.0-fold to 4.0-fold, optionally where the statistical significance of the increase or decrease is at least 5e-2, le-2, 5e-3, le-3, 5e-4, le-4, 5e-5, le-5, 5e-6, or le-6.
[0306] In some embodiments, one or more enhancer regions of a recited gene are provided in Tables 1 and 2. In some embodiments, one or more enhancer regions of a recited gene corresponds to: (i) one or more loci with increased or decreased H3K27ac modifications as compared to a reference (e.g., a sample from a healthy subject) within a certain number of nucleotides (e.g., 50,000 nucleotides) of the recited gene; and/or (ii) one or more loci with increased or decreased H3K27ac modifications as compared to a reference (e.g., a sample from a healthy subject) that are closest to the recited gene in the genome.
Differential DNA methylation
[0307] Exemplary genomic loci whose DNA methylated state is associated with PSMA expression level (e.g., PSMA PET SUVmean signal) are provided in Table 1 (see MBD analyte loci).
[0308] A person of skill in the art will recognize that the methods disclosed herein do not require that every MBD analyte genomic locus listed in Table 1 be assessed for DNA methylation. Instead, a subset of MBD loci may be assessed for DNA methylation. Subsets of the MBD genomic loci of Table 1 can be selected (e.g., for use in determining PSMA expression level) based on various performance criteria, e.g., to select genomic loci that demonstrate differential modification with a particular level of statistical significance and/or a particular threshold of differential between relevant states (e.g., a measured log2(fold-change)). Subsets of the genomic loci may also be selected based on an algorithm, e.g., during the process of obtaining a classifier. Those of skill in the art will appreciate that such subsets of loci of Table 1, and loci included in such subsets, are together, individually, and/or in randomly selected subsets, at least as informative (e.g., as statistically significant and/or reliable) for uses disclosed herein, e.g., for determining PSMA expression level.
[0309] In various embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular PSMA expression level if 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 MBD analyte loci identified in Table 1 are differentially DNA methylated as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
[0310] In various embodiments, a sample or subject from which the sample is derived, is determined to have a particular PSMA expression level if one or more MBD analyte loci (e g., 1,
2, 3, 4, 5, 6, 7, 8, 9, or 10) in Table 1 are differentially DNA methylated as compared to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e.g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
[0311] In some embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular PSMA expression level if DNA methylation for 1, 2,
3, 4, 5, 6, 7, or 8 of the MBD analyte loci that are identified in Table 1 as having a positive association with PSMA expression are increased relative to a reference (e.g., a sample from (i) a healthy subject or cohort of healthy subjects or (ii) a subject with aberrant PSMA expression or a cohort of subjects with aberrant PSMA expression (e g., a subject or cohort of subjects with mCRPC and that exhibit a positive PSMO PET SUVmean signal)).
[0312] In various embodiments, differentially DNA methylated refers to a methylation status characterized by an increase or decrease in a value measuring methylation (e.g., of read counts and/or normalized read counts for a given genomic locus), and/or a mean, median and/or mode thereof, and/or a log thereof (e.g., log base 2 (log2)), of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4- fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40- fold, 45-fold, 50-fold, or greater, or any range in between, inclusive, such as 1% to 50%, 50% to 2-fold, 25% to 50-fold, 25% to 30-fold, 25% to 20-fold, 25% to 16-fold, 30% to 16-fold, 50% to 16-fold, 70% to 16-fold, 2-fold to 16-fold, 2.2-fold to 16-fold, 2.6-fold to 16-fold, 3-fold to 16- fold, 3.4-fold to 16-fold, 4-fold to 16-fold, 4.5-fold to 16-fold, 5.2-fold to 16-fold, 6-fold to 16- fold, 7-fold to 16-fold, or 8-fold to 16-fold, as compared to a reference, optionally where the statistical significance of the increase or decrease is at least 5e-2, le-2, 5e-3, le-3, 5e-4, le-4, 5e- 5, le-5, 5e-6, or le-6. In various embodiments, an increase or decrease in a value measuring methylation can be, or is expressed as, a log2(fold-change), e g., a log2(fold-change) of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, or greater, or any range in between, inclusive, such as an increase of 0.1 -fold to 10-fold, 0.2-fold to 5-fold, 0.2-fold to 4.0-fold, 0.4-4.0-fold, 0.4-fold to 4.0-fold, 0.6-fold to 4.0-fold, 0.8-fold to 4.0-fold, 1.0-fold to 4.0-fold. 1.2-fold to 4.0-fold. 1.4-fold to 4.0-fold, 1.6-fold to 4.0-fold, 1.8- fold to 4.0-fold, 2.0-fold to 4.0-fold, 2.2-fold to 4.0-fold, 2.4-fold to 4.0-fold, 2.6-fold to 4.0-fold, 2.8-fold to 4.0-fold, or 3.0-fold to 4.0-fold, optionally where the statistical significance of the increase or decrease is at least 5e-2, le-2, 5e-3, le-3, 5e-4, le-4, 5e-5, le-5, 5e-6, or le-6.
Differential chromatin accessibility or transcription factor binding
[0313] Genomic loci provided in Tables 1-2 can also demonstrate differential chromatin accessibility or transcription factor binding in different PSMA expression states.
[0314] In various embodiments, without wishing to be bound by any particular scientific theory, histone methylation (e.g., H3K4me3) corresponds and/or is correlated with chromatin accessibility. In various embodiments, without wishing to be bound by any particular scientific theory, histone acetylation (e.g., H3K27ac) corresponds and/or is correlated with chromatin accessibility. In various embodiments, without wishing to be bound by any particular scientific theory, DNA methylation corresponds and/or is correlated with chromatin accessibility. [0315] In some embodiments, without wishing to be limited to any particular scientific theory, chromatin accessibility corresponds and/or is correlated with H3K4me3 modifications. As a result, in some embodiments, PSMA expression level may be determined by detecting and quantifying chromatin accessibility at one or more genomic loci in Tables 1 and 2 in accordance with the section above discussing exemplary genomic loci with differential H3K4me3 modifications.
[0316] In some embodiments, without wishing to be limited to any particular scientific theory, chromatin accessibility corresponds and/or is correlated with H3K27ac modifications. As a result, in some embodiments, PSMA expression level may be determined by detecting and quantifying chromatin accessibility at one or more genomic loci in Tables 1 and 2 in accordance with the section above discussing exemplary genomic loci with differential H3K27ac modifications.
[0317] In some embodiments, without wishing to be limited to any particular scientific theory, chromatin accessibility corresponds and/or is correlated with DNA methylation. As a result, in some embodiments, PSMA expression can be measured by detecting and quantifying chromatin accessibility at one or more genomic loci in Tables 1 and 2 in accordance with the section above discussing exemplary genomic loci with differential DNA methylation.
[0318] In various embodiments, without wishing to be bound by any particular scientific theory, histone methylation (e.g., H3K4me3) corresponds and/or is correlated with transcription factor binding. In various embodiments, without wishing to be bound by any particular scientific theory, histone acetylation (e.g., H3K27ac) corresponds and/or is correlated with transcription factor binding. In various embodiments, without wishing to be bound by any particular scientific theory, DNA methylation corresponds and/or is correlated with transcription factor binding.
[0319] In some embodiments, without wishing to be limited to any particular scientific theory, binding of RNA pol II corresponds and/or is correlated with H3K4me3 modifications. As a result, in some embodiments, PSMA expression level may be determined by detecting and quantifying binding of RNA pol II at one or more genomic loci in Tables 1 and 2 in accordance with the section above discussing exemplary genomic loci with differential H3K4me3 modifications. [0320] In some embodiments, without wishing to be limited to any particular scientific theory, binding of p300, mediator complex, cohesin complex or RNA pol II corresponds and/or is correlated with H3K27ac modifications. As a result, in some embodiments, PSMA expression level may be determined by detecting and quantifying binding of p300, mediator complex, cohesin complex or RNA pol II at one or more genomic loci in Tables 1 and 2 in accordance with the section above discussing exemplary genomic loci with differential H3K27ac modifications.
Applications
[0321] Methods, kits and systems of the present disclosure include analysis of differentially modified and/or differentially accessible genomic loci to measure disease-specific PSMA expression. Methods, kits and systems of the present disclosure can be used in any of a variety of applications. For example, methods, kits and systems of the present disclosure can be used in detecting and/or treating a disease or indication that can be associated with increased disease-specific PSMA expression (e.g., mCRPC). Methods, kits and systems of the present disclosure can also be used to detect or determine resistance of a disease or condition to a certain therapeutic (e.g., a PSMA-targeted therapeutic).
[0322] In various embodiments, methods, kits and systems of the present disclosure can be applied to an asymptomatic human subject. As used herein, a subject can be referred to as “asymptomatic” if the subject does not report, and/or demonstrate by non-invasively observable indicia (e.g., without one, several, or all of device-based probing, tissue sample analysis, bodily fluid analysis, surgery, or autoimmune screening), sufficient characteristics of a disease or condition that can be associated with increased PSMA expression to support a medically reasonable suspicion that the subject is likely suffering from a disease or condition that can be associated with increased PSMA expression. Detection of early-stage diseases or conditions that can be associated with increased PSMA expression can be achieved using methods, kits and systems of the present disclosure, with attendant medical benefits including potential for early treatment and attendant improvement in therapeutic outcomes.
[0323] In various embodiments, methods, kits and systems of the present disclosure can be applied to a symptomatic human subject. As used herein, a subject can be referred to as “symptomatic” if the subject report, and/or demonstrates by non-invasively observable indicia (e.g., without one, several, or all of device-based probing, tissue sample analysis, bodily fluid analysis, surgery, or prostate cancer screening), sufficient characteristics of a disease or condition that can be associated with increased PSMA expression (including, e.g., prostate cancer (e.g., CRPC)) to support a medically reasonable suspicion that the subject is likely suffering from a disease or condition that can be associated with increased PSMA expression. [0324] In various embodiments, methods, kits and systems of the present disclosure can be applied to a human subject previously determined to have a disease or condition that can be associated with increased PSMA expression. In various embodiments, methods, kits and systems of the present disclosure can be applied to a human subject previously determined to have prostate cancer (e.g., mCRPC)).
[0325] In some embodiments, methods, kits and systems of the present disclosure can be used to determine that a subject has a PSMA expression level that correlates with a prior determination of PSMA expression level (e.g., based on imaging and/or one or more biomarkers). In some embodiments, methods, kits and systems of the present disclosure can be used to validate or confirm a prior determination that a subject has a certain PSMA expression level.
[0326] Those of skill in the art will appreciate that regular, preventive, and/or prophylactic screening to determine PSMA expression level improves diagnosis, prognosis, and treatment of a disease or indication that can be associated with increased PSMA expression, including and/or particularly an early stage disease or indication that can be associated with increased PSMA expression (e.g., mCRPC). Thus, the present disclosure provides, among other things, methods, kits and systems particularly useful for the diagnosis and treatment of early- stage diseases that can be associated with increased PSMA expression (e.g., mCRPC). Generally, and particularly in embodiments in which PSMA expression level determined in accordance with the present disclosure is carried out annually, and/or in which a subject has recently be diagnosed with prostate cancer or mCRPC, methods, kits and systems of the present disclosure are especially likely to detect early stages of disease, which can be useful, e.g., for treatment selection and improved therapeutic outcomes. [0327] In various embodiments PSMA expression level determination in accordance with the present disclosure is performed once for a given subject or multiple times for a given subject. In various embodiments, PSMA expression level determination in accordance with the present disclosure is performed on a regular basis, e.g., every six months, annually, every two years, every three years, every four years, every five years, or every ten years.
[0328] In various embodiments, methods, kits and systems disclosed herein provide a determination of PSMA expression level. In other instances, methods, kits and systems disclosed herein will be indicative of PSMA expression level but not definitive for PSMA expression level. In various instances in which methods, kits and systems of the present disclosure are used to determine PSMA expression level, the same can be followed by a further confirmatory assay, which further assay can confirm, support, undermine, or reject a determination resulting from a prior determination, e.g., a determination in accordance with the present disclosure. As used herein, a confirmatory assay can be a test that is currently recognized by medical practitioners, e.g., based on imaging or other testing.
[0329] In various embodiments, PSMA expression level determination according to one or more methods, kits and/or systems disclosed herein is followed by treatment with a PSMA- targeted therapeutic (e.g., 177Lu-PSMA-617). In various embodiments, treatment with a PSMA- targeted therapeutic includes administration of one or more therapies provided herein, including without limitation a radioligand conjugate and/or an ADC. In various embodiments, treatment of a disease or indication associated with increased PSMA expression includes administration of a therapeutic regimen including one or more treatments provided herein as available, appropriate, and/or preferred for a particular PSMA expression level.
[0330] In various embodiments, methods, kits and systems can be used to determine whether a particular subject is likely to be and/or is characterized as responsive to a PSMA- targeted agent. In some such embodiments, methods, kits and systems can be followed by treatment of the subject with a PSMA-targeted agent.
[0331] In various embodiments, methods, kits and systems can be used to determine whether a particular subject is likely to be and/or is characterized as resistant to, non-responsive to, or not recommended treatment with a PSMA-targeted agent. In some such embodiments, methods, kits and systems can be followed by treatment with a therapeutic agent to a different target.
[0332] Responsiveness can refer to the ability or likelihood of a therapy to cause a reduction in the number and/or size of tumor lesions, an increase in the time to next treatment, slowing of disease progression (e.g., as measured by plasma PSA levels for prostate cancer, and/or clinical or radiological evidence of progression), reduced disease activity, and/or increased survival. Responsiveness can refer to improvement in prognosis. Responsiveness can refer to achievement of a treatment benefit, including e.g., improvement in one or more symptoms of a disease or indication associated with increased PSMA expression.
Responsiveness can be measured quantitatively (e.g., as in the case of tumor size and/or number, PSA concentration, histone modification, chromatin accessibility, transcription factor binding, or DNA methylation at one or more genomic loci; or as in the calculation of clinical benefit (CBR)), or qualitatively (e.g., by measures such as “pathological complete response” (pCR), “clinical stable disease” (cSD), “clinical progressive disease” (cPD), or other qualitative criteria). Resistance can refer to the inability or unlikelihood of a therapy to achieve a desired therapeutic effect (e.g., a reduction in number or size of tumors, increased overall survival, decreased disease progression, or increased time to next treatment), or other treatment benefit such as, e.g., improvement in one or more symptoms of a disease or indication) in a subject. Resistance includes natural resistance. In certain embodiments, resistance includes the extent to which one or more desired therapeutic benefits results from administration of a therapy to a subject is less than that expected and/or achieved in a reference (e.g., less than 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, or 10% of benefit achieved in a reference).
[0333] In various embodiments, methods, kits and systems can be used to detect the clinical efficacy of a course of therapy for a disease or indication that can be associated with increased PSMA expression (e.g., prostate cancer (e.g., mCRPC)). For example, methods and/or compositions of the present disclosure could be used to determine the progression of prostate cancer (e.g., mCRPC) over the course of treatment. Methods and/or compositions of the present disclosure could be used in conjunction with, or confirmed by, other means of determining the PSMA expression level of a subject including, for example measurements using techniques such as PSMA PET imaging). [0334] In some embodiments, methods, kits and systems for PSMA expression level determination provided herein can inform treatment and/or payment (e.g., reimbursement for or reduction of cost of medical care, such as detecting or treatment) decisions and/or actions, e.g., by individuals, healthcare facilities, healthcare practitioners, health insurance providers, governmental bodies, or other parties interested in healthcare cost.
[0335] In some embodiments, methods, kits and systems for PSMA expression level determination provided herein can inform decision making relating to whether health insurance providers reimburse a healthcare cost payer or recipient (or not), e.g., for (1) PSMA expression level determination itself (e.g., reimbursement for detecting otherwise unavailable, available only for periodic/regular detecting, or available only for temporally- and/or incidentally- motivated detecting); and/or for (2) treatment, including initiating, maintaining, and/or altering therapy, e g., based on the determined PSMA expression level. For example, in some embodiments, methods, kits and systems for PSMA expression level determination provided herein are used as the basis for, to contribute to, or support a determination as to whether a reimbursement or cost reduction will be provided to a healthcare cost payer or recipient. In some instances, a party seeking reimbursement or cost reduction can provide results of PSMA expression level determination conducted in accordance with the present disclosure together with a request for such reimbursement or reduction of a healthcare cost. In some instances, a party making a determination as to whether or not to provide a reimbursement or reduction of a healthcare cost will reach a determination based in whole or in part upon receipt and/or review of results of PSMA expression level determination conducted in accordance with the present disclosure.
[0336] In various embodiments, PSMA expression level determination using methods, kits and systems disclosed herein can be used in classifying subjects and/or samples (e.g., prostate cancer (e.g., mCRPC) subjects and/or samples). In various embodiments, methods, kits and systems disclosed herein can be used to generate a set of subjects, and/or samples identified according to the present methods, kits and systems each classified as corresponding to a particular PSMA expression level, and optionally using two or more of such classified subjects, and/or samples to identify biomarkers that distinguish the classes (i.e., distinguish the subjects, and/or samples according to their class, e.g., according to their PSMA expression level). [0337] For illustration purposes and without limitation, in an exemplary assay of the present disclosure, samples obtained from a subject (e.g., a liquid biopsy sample including cfDNA, e.g., a plasma sample including cfDNA) is analyzed by ChlP-seq for a histone modification (e.g., H3K4me3 and/or H3K27ac). ChlP-seq sequence reads are aligned to human genome build hgl9, e.g., using the Burrows-Wheeler Aligner (BWA). Non-uniquely mapping and redundant reads are optionally discarded. To provide one example of peak calling, MACS v2.1.1.20140616 can be used for ChlP-seq peak calling with a q-value (FDR) threshold of 0.01. ChlP-seq data quality can optionally be evaluated by any of one or more of a variety of measures, including total peak number, FriP (fraction of reads in peak) score, number of high- confidence peaks (e.g., enriched > ten-fold over background), and percent of peak overlap with “blacklist” DHS peaks derived from the ENCODE project (Amemiya et al., Sci Rep (2019) 9( 1 ): 9354). If the ChlP-seq data quality is below a particular threshold the data may be discarded and the assay repeated. ChlP-seq peaks that overlap with selected genomic loci that are differentially modified as provided herein for the relevant histone modification (Tables 1-2) can then be used to determine PSMA expression level. The number of reads overlapping the selected genomic loci for the relevant histone modification can be summed, e.g., in some embodiments all the genomic loci that are differentially modified with an absolute log2(fold-change) > 4.0 are selected. In some embodiments, the average number of reads in the local background of each ChlP-seq peak is subtracted to improve signal to noise. The data can then be log2 -transformed and quantile normalized to match the distribution of the data used to train the classifier.
[0338] For the avoidance of any doubt, those of skill in the art will appreciate from the present disclosure that methods, kits and systems for PSMA expression level determination of the present disclosure are at least for /// vitro use. Accordingly, all aspects and embodiments of the present disclosure can be performed and/or used at least in vitro.
[0339] Those of skill in the art will also appreciate that, in certain embodiments, methods of the present disclosure can be implemented on and/or in conjunction with a computer program and computer system. In some embodiments, methods of the present disclosure can be implemented on and/or in conjunction with a non-transitory computer readable storage medium encoded with the computer program, wherein the program comprises instructions that when executed by one or more processors cause the one or more processors to perform operations to perform the method. A computer system can also store and manipulate data generated by methods of the present disclosure that comprise a plurality of genomic locus modification status and/or accessibility status changes/profiles, which data can be used by a computer system in implementing methods disclosed herein. In certain embodiments, a computer system (i) receives modification status and/or accessibility status data; (ii) stores the data; and (iii) compares the data in any number of ways described herein (e.g., analysis relative to appropriate references), e.g., to measure PSMA expression. In certain embodiments, a computer system (i) compares the genomic locus modification and/or accessibility status to a reference; and (ii) outputs an indication of whether the modification status and/or accessibility status of the genomic locus is significantly different from the reference and/or provides a determination of PSMA expression levels.
[0340] Numerous types of computer systems can be used to implement methods of the present disclosure according to knowledge possessed by a skilled artisan in the bioinformatics and/or computer arts. Several software components can be loaded into memory during operation of such a computer system. The software components can comprise both software components that are standard in the art and components that are special to the present disclosure (e.g., dCHIP software described in Lin et al., Bioinformatics (2004) 20: 1233-1240, incorporated herein by reference in its entirety; radial basis machine learning algorithms (RBM) known in the art). Methods of the present disclosure can also be programmed or modeled in mathematical software packages that allow symbolic entry of equations and high-level specification of processing, including specific algorithms to be used, thereby freeing a user of the need to procedurally program individual equations and algorithms. Such packages include, e.g., Matlab from Mathworks (Natick, MA), Mathematica from Wolfram Research (Champaign, IL), S-Plus from MathSoft (Seattle, WA), R from R Foundation for Statistical Computing (Vienna, Austria), Python from Python Software Foundation (Wilmington, DE), or Perl from Perl Foundation (Holland, MI). In certain embodiments, a computer system comprises a database for storage of genomic locus modification status and/or accessibility status data. Such stored profiles can be accessed and used to perform comparisons of interest at a later point in time. In addition to the exemplary program structures and computer systems described herein, other, alternative program structures and computer systems will be readily apparent to the skilled artisan. [0341] Various algorithms can be applied to the comparison, between samples and references, of the modification status and/or accessibility status of genomic loci that are differentially modified in different ER states. In various embodiments, an algorithm can be a single learning statistical classifier system. Other suitable statistical algorithms are well known to those of skill in the art. For example, learning statistical classifier systems include a machine learning algorithmic technique capable of adapting to complex datasets (e.g., a panel of genomic loci of interest) and making decisions based upon such datasets. In some embodiments, a single learning statistical classifier system such as a classification tree (e. ., random forest) is used. In other embodiments, a combination of 2, 3, 4, 5, 6, 7, 8, 9, 10, or more learning statistical classifier systems are used, preferably in tandem. Examples of learning statistical classifier systems include, but are not limited to, those described in the Examples and also those using inductive learning (e.g., decision/classification trees such as random forests, classification and regression trees (C&RT), boosted trees, etc.), Probably Approximately Correct (PAC) learning, connectionist learning (e.g, neural networks (NN), artificial neural networks (ANN), neuro fuzzy networks (NFN), network structures, perceptrons such as multi-layer perceptrons, multilayer feed-forward networks, applications of neural networks, Bayesian learning in belief networks, etc.), reinforcement learning (e.g, passive learning in a known environment such as naive learning, adaptive dynamic learning, and temporal difference learning, passive learning in an unknown environment, active learning in an unknown environment, learning action-value functions, applications of reinforcement learning, etc ), and genetic algorithms and evolutionary programming. Other learning statistical classifier systems include support vector machines (e.g., Kernel methods), multivariate adaptive regression splines (MARS), Levenberg-Marquardt algorithms, Gauss-Newton algorithms, mixtures of Gaussians, gradient descent algorithms, and learning vector quantization (LVQ). In certain embodiments, methods of the present disclosure can include sending classification results to a medical practitioner, e.g., an oncologist.
Formulation and Administration of Therapeutic Agents
[0342] The present disclosure includes methods where a therapeutic agent or regimen is administered to a subject based on PSMA expression level (e.g., disease specific PSMA expression level). In general, the therapeutic agent or regimen provided herein will be available, appropriate, and/or preferred for a certain PSMA expression level. Those of skill in the art will be aware of recommended and/or governmentally approved formulations and/or dosages for various therapeutic agents provided herein.
[0343] The present disclosure includes pharmaceutical compositions for delivery of one or more therapeutic agents to a subject. As disclosed herein, a pharmaceutical composition may be in any form known in the art, including formulations for administration according to any route known in the art. A suitable means of administration can be selected based on the age and condition of a subject.
[0344] Pharmaceutical composition forms of the present disclosure can include, e.g., liquid, semi-solid and solid dosage forms. Pharmaceutical composition forms of the present disclosure can include, e.g., liquid solutions (e.g., injectable and infusible solutions), dispersions or suspensions, tablets, pills, powders, and liposomes. Selection or use of any particular form may depend, in part, on the intended mode of administration and therapeutic application.
Accordingly, the compositions can be formulated for administration by a parenteral mode (e.g., intravenous, subcutaneous, intraperitoneal, or intramuscular injection) or a non-parenteral mode. As used herein, parenteral administration refers to modes of administration other than enteral and topical administration, usually by injection or infusion.
[0345] In some embodiments, the compositions provided herein are present in unit dosage form, which unit dosage form can be suitable for self-administration. Such a unit dosage form may be provided within a container, e.g., a pill, vial, cartridge, prefilled syringe, or disposable pen.
[0346] A pharmaceutical composition of the present disclosure can be in an injectable or infusible form. For example, the present disclosure includes sterile formulations for injection or infusion, which can be formulated in accordance with conventional pharmaceutical practices.
Sterile solutions can be prepared by incorporating a composition described herein in the required amount in an appropriate solvent with one or a combination of ingredients enumerated above, as required, followed by filter sterilization. Solutions can be formulated, e.g., using distilled water, physiological saline, or an isotonic solution containing glucose and other supplements such as D- sorbitol, D-mannose, D-mannitol, or sodium chloride as an aqueous solution for injection, optionally in combination with a suitable solubilizing agent, for example, an alcohol such as ethanol and/or a polyalcohol such as propylene glycol or polyethylene glycol, and/or a nonionic surfactant such as polysorbate 80™ or HCO-50, and the like. In the case of sterile powders for the preparation of sterile injectable solutions, methods for preparation include vacuum drying and freeze-drying that yield a powder of a composition described herein plus any additional desired ingredient (see below) from a previously sterile-fdtered solution thereof. The proper fluidity of a solution can be maintained, for example, by the use of a coating such as lecithin, by the maintenance of the required particle size in the case of dispersion and by the use of surfactants. Prolonged absorption of injectable compositions can be brought about by including in the composition a reagent that delays absorption, for example, monostearate salts, and gelatin. In particular instances, a pharmaceutical composition can be formulated, for example, as a buffered solution at a suitable concentration and suitable for storage, e.g., at 2-8°C (e.g., 4°C). [0347] In various embodiments, a pharmaceutical composition of the present disclosure can be formulated as a solution, microemulsion, dispersion, liposome, or other ordered structure suitable for stable storage at high concentration. Generally, dispersions are prepared by incorporating a composition described herein into a sterile vehicle that contains a basic dispersion medium and the required other ingredients from those enumerated above.
[0348] In various instances, a pharmaceutical composition can be formulated to include a pharmaceutically acceptable carrier or excipient. Examples of pharmaceutically acceptable carriers include, without limitation, any and all solvents, dispersion media, coatings, antibacterial and antifungal agents, isotonic and absorption delaying agents, and the like that are physiologically compatible.
[0349] In certain embodiments, compositions can be formulated with a carrier that will protect the therapeutic agent against rapid release, such as a controlled release formulation, including implants and microencapsulated delivery systems. Biodegradable, biocompatible polymers can be used, such as ethylene vinyl acetate, poly anhydrides, polyglycolic acid, collagen, polyorthoesters, and polylactic acid. Many methods for the preparation of such formulations are known in the art. See, e.g., J. R. Robinson (1978) “Sustained and Controlled Release Drug Delivery Systems,” Marcel Dekker, Inc., New York.
[0350] Route of administration can be parenteral, for example, administration by injection. Administration by injection can be by intravenous injection, intramuscular injection, intraperitoneal injection, subcutaneous injection. Administration can be systemic or local. Tn certain embodiments, a composition described herein can be therapeutically delivered to a subject by way of local administration. As used herein, “local administration” or “local delivery,” can refer to delivery that does not rely upon transport of the composition or therapeutic agent to its intended target tissue or site via the vascular system. For example, the composition may be delivered by injection or implantation of the composition or therapeutic agent or by injection or implantation of a device containing the composition or therapeutic agent. In certain embodiments, following local administration in the vicinity of a target tissue or site, the composition or therapeutic agent, or one or more components thereof, may diffuse to an intended target tissue or site that is not the site of administration.
[0351] A pharmaceutical composition can be administered parenterally in the form of an injectable formulation comprising a sterile solution or suspension in water or another pharmaceutically acceptable liquid. For example, a pharmaceutical composition can be formulated by suitably combining the therapeutic molecule with pharmaceutically acceptable vehicles or media, such as sterile water and physiological saline, vegetable oil, emulsifier, suspension agent, surfactant, stabilizer, flavoring excipient, diluent, vehicle, preservative, binder, followed by mixing in a unit dose form required for generally accepted pharmaceutical practices. Examples of oily liquid include sesame oil and soybean oil, and it may be combined with benzyl benzoate or benzyl alcohol as a solubilizing agent. Other items that may be included are a buffer such as a phosphate buffer, or sodium acetate buffer, a soothing agent such as procaine hydrochloride, a stabilizer such as benzyl alcohol or phenol, and an antioxidant. The formulated injection can be packaged in a suitable ampule.
[0352] In various embodiments, subcutaneous administration can be accomplished by means of a device, such as a syringe, a prefilled syringe, an auto-injector (e.g., disposable or reusable), a pen injector, a patch injector, a wearable injector, an ambulatory syringe infusion pump with subcutaneous infusion sets, or other device for combining with a therapeutic agent for subcutaneous injection.
[0353] An injection system of the present disclosure may employ a delivery pen as described in U.S. Pat. No. 5,308,341. Pen devices, most commonly used for self-delivery of insulin to patients with diabetes, are well known in the art. Such devices can include at least one injection needle, are typically pre-filled with one or more therapeutic unit doses of a solution that includes the therapeutic agent and are useful for rapidly delivering solution to a subject with as little pain as possible. One medication delivery pen includes a vial holder into which a vial of a therapeutic or other medication may be received. The pen may be an entirely mechanical device or it may be combined with electronic circuitry to accurately set and/or indicate the dosage of medication that is injected into the user. See, e.g., U.S. Pat. No. 6,192,891. In some embodiments, the needle of the pen device is disposable and the kits include one or more disposable replacement needles. Pen devices suitable for delivery of any one of the presently featured compositions are also described in, e.g., U.S. Pat. Nos. 6,277,099; 6,200,296; and 6,146,361, the disclosures of each of which are incorporated herein by reference in their entirety. A microneedle-based pen device is described in, e.g., U.S. Pat. No. 7,556,615, the disclosure of which is incorporated herein by reference in its entirety. See also the Precision Pen Injector (PPI) device, MOLLY™, manufactured by Scandinavian Health Ltd.
[0354] In certain embodiments, administration of a therapeutic agent as described herein is achieved by administering to a subject a nucleic acid encoding a therapeutic agent described herein. Nucleic acids encoding a therapeutic agent described herein can be incorporated into a gene construct to be used as a part of a gene therapy protocol to deliver nucleic acids that can be used to express and produce therapeutic agent within cells. Expression constructs of such components may be administered in any therapeutically effective carrier, e.g., any formulation or composition capable of effectively delivering the component gene to cells in vivo. Approaches include insertion of the subject gene in viral vectors including recombinant retroviruses, adenovirus, adeno-associated virus, lentivirus, and herpes simplex virus-1 (HSV-1), or recombinant bacterial or eukaryotic plasmids. Viral vectors can transfect cells directly; plasmid DNA can be delivered with the help of, for example, cationic liposomes (lipofectin) or derivatized, polylysine conjugates, gramicidin S, artificial viral envelopes or other such intracellular carriers, as well as direct injection of the gene construct or CaPCL precipitation. Examples of suitable retroviruses include adenovirus-derived vectors, adeno-associated virus (AAV), pLJ, pZIP, pWE, and pEM which are known to those skilled in the art.
[0355] In some embodiments, a composition can be formulated for storage at a temperature below 0°C (e.g., -20°C or -80°C). In some embodiments, the composition can be formulated for storage for up to 2 years (e.g., one month, two months, three months, four months, five months, six months, seven months, eight months, nine months, 10 months, 11 months, 1 year, or 2 years) at 2-8°C (e.g., 4°C). Thus, in some embodiments, the compositions described herein are stable in storage for at least 1 year at 2-8°C (e.g., 4°C).
[0356] A pharmaceutical composition can include a therapeutically effective amount of a therapeutic agent described herein. Such effective amounts can be readily determined by one of ordinary skill in the art. A therapeutically effective amount can be an amount at which any toxic or detrimental effects of the composition are outweighed by therapeutically beneficial effects. In some embodiments, a dose can also be chosen to reduce or avoid production of antibodies or other host immune responses against a therapeutic agent. Those of skill in the art will appreciate that data obtained from cell culture assays and animal studies can be used in formulating a range of dosage for use in humans. In various embodiments, the amount of active ingredient included in a pharmaceutical composition is such that a suitable dose within the designated range can be administered to subjects. The dose and method of administration can vary depending on weight, age, condition, and other characteristics of a patient, and can be suitably selected as needed by those skilled in the art.
[0357] Pharmaceutical compositions including certain therapeutic agents, e.g., therapeutic antibodies, can be administered as a fixed dose, or in a milligram per kilogram (mg/kg) dose. While in no way intended to be limiting, an exemplary single dose of certain pharmaceutical compositions described herein can include certain therapeutic agents as described herein in an amount equal to, e.g., 0.001 to 1000 mg/kg, 1-1000 mg/kg, 1-100 mg/kg, 0.5-50 mg/kg, 0.1-100 mg/kg, 0.5-25 mg/kg, 1-20 mg/kg, and 1-10 mg/kg body weight. Exemplary dosages of a composition described herein include, without limitation, 0.1 mg/kg, 0.5 mg/kg, 1 mg/kg, 2 mg/kg, 4 mg/kg, 8 mg/kg, or 20 mg/kg. The present disclosure is not limited to such ranges or dosages.
[0358] The present disclosure further includes methods of preparing pharmaceutical compositions of the present disclosure and kits including pharmaceutical compositions of the present disclosure.
[0359] In various embodiments, therapeutic agents of the present disclosure can be administered to a subject in a course of treatment that further includes administration of one or more additional therapeutic agents or therapies that are not therapeutic agents (e.g., surgery or radiation). Combination therapies of the present disclosure can include simultaneous exposure of a subject to therapeutic agents of two or more therapeutic regimens.
[0360] In certain embodiments, a therapeutic agent as described herein can be administered together with (e g., at the same time and/or in the same composition as) an additional agent or therapy. In certain embodiments, a therapeutic agent of the present disclosure can be administered separately from an additional therapeutic agent or therapy (e.g., at a different time and/or in a different composition than the additional therapeutic agent or therapy). Dosing regimens of a therapeutic agent and one or more additional therapeutic agents with which it is administered in combination can be coordinated or independently determined. In various embodiments, an additional therapeutic agent or therapy administered in combination with a therapeutic agent as described herein can be administered at the same time as therapeutic agent, on the same day as therapeutic agent, or in the same week as therapeutic agent. In various embodiments, an additional therapeutic agent or therapy administered in combination with a therapeutic agent as described herein can be administered such that administration of the therapeutic agent and the additional therapeutic agent or therapy are separated by one or more hours before or after, one or more days before or after, one or more weeks before or after, or one or more months before or after administration of the therapeutic agent. In various embodiments, the administration frequency and/or dosage of one or more additional therapeutic agents can be the same as, similar to, or different from the administration frequency of a therapeutic agent. In some embodiments, the two or more regimens can be administered simultaneously; in some embodiments, such regimens can be administered sequentially (e.g., all “doses” of a first regimen are administered prior to administration of any doses of a second regimen); in some embodiments, such therapeutic agents are administered in overlapping dosing regimens.
[0361] In certain embodiments, administration of a therapeutic agent can be to a subject having previously received, scheduled to receive, or in the course of a treatment regimen including an additional cancer therapy (e.g., prostate cancer therapy). Administration of a therapeutic agent can, in some instances, improve delivery or efficacy of another therapeutic agent or therapy with which it is administered in combination. [0362] It is contemplated that therapeutic agent combination therapies can demonstrate synergy and/or greater-than-additive effects between a therapeutic agent and one or more additional therapeutic agents with which it is administered in combination. A therapeutic agent can be administered in any effective amount as determined independently or as determined by the joint action of therapeutic agent and any of one or more additional therapeutic agents or therapies administered. Administration of the therapeutic agent may, in some embodiments, reduce the therapeutically effective dosage, required dosage, or administered dosage of the additional therapeutic agent or therapy relative to a reference regimen for administration of additional therapeutic agent or therapy or therapy absent the therapeutic agent. In certain embodiment, a composition described herein can replace or augment other previously or currently administered therapy. For example, upon treating with therapeutic agent, administration of one or more additional therapeutic agents or therapies can cease or diminish, e.g., be administered at lower levels.
Kits
[0363] The present disclosure includes kits for detecting modification and/or accessibility of one or more genomic loci. In some embodiments, the present disclosure provides kits for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci. Kits of the present disclosure can include, e g., reagents such as buffers and/or antibodies useful in the detection and quantification of histone modifications. In certain embodiments, a kit of the present disclosure can include at least one antibody that selective binds a histone modification selected from H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, or H3K4me3, or pan acetylation. In certain embodiments, a kit of the present disclosure can include at least one antibody that selective binds H3K4me3 modifications. In certain embodiments, a kit of the present disclosure can include at least one antibody that selective binds H3K27ac modifications. A kit of the present disclosure can include instructional materials disclosing or describing the use of the kit in a method of measuring PSMA expression and/or treatment disclosed herein. In various embodiments, a kit of the present disclosure can include one or more therapeutic agents useful in the treatment of a disease or indication that can be associated with elevated PSMA expression, e.g., as disclosed herein, optionally in combination with instruction materials for treatment of the disease or indication.
[0364] In some embodiments, a kit of the present disclosure comprises reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci, wherein the one or more genomic loci are selected from those provided in Tables 1-2.
[0365] In some embodiments, the kit comprises reagents for quantifying H3K4me3 for 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or 11 genomic loci in Table 1 or Table 2. In some embodiments, the kit comprises reagents for quantifying H3K27ac for 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 genomic loci in Tables 1 and 2. In some embodiments, the kit comprises reagents for quantifying H3K27ac modifications for 1, 2, 3, 4, 5, 6, 7, or 8 H3K27ac genomic loci in Table 2 and/or quantifying H3K4me3 modifications for the H3K4me3 genomic loci in Table 2. In some embodiments, the kit comprises one or more antibodies for use in ChlP-seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac- modified histones.
[0366] In some embodiments, the kit comprises reagents for quantifying H3K4me3 for 1, 2, 3, or 4 of the H3K4me3 genomic loci in Table 3. In some embodiments, the kit comprises reagents for quantifying H3K4me3 for one or both of the H3K4me3 genomic loci in Table 4. In some embodiments, the kit comprises reagents for quantifying H3K4me3 for the H3K4me3 genomic locus in Table 5.
[0367] In some embodiments, the kit comprises reagents for quantifying H3K27ac for 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, or 25 of the H3K27ac genomic loci in Table 4. In some embodiments, the kit comprises reagents for quantifying H3K27ac for the H3K27ac genomic locus in Table 5.
[0368] In some embodiments, the kit comprises one or more antibodies for use in ChlP- seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac- modified histones.
[0369] In some embodiments, the kit comprises reagents for quantifying DNA methylation for 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 genomic loci in Table 1. In some embodiments, the kit comprises one or more methyl-binding domains (e.g., for use in MBD-seq). In some embodiments, the kit comprises one or more antibodies that can bind methylated DNA (e.g., for use in MeDIP).
[0370] In some embodiments, the kit comprises reagents for measuring chromatin accessibility via an ATAC-seq assay.
[0371] In some embodiments, the kit comprises reagents for isolation of cell-free DNA (cfDNA) from a liquid biopsy sample. In some embodiments, the kit comprises reagents for library preparation for sequencing. In some embodiments, the kit comprises reagents for sequencing. In some embodiments, the kit comprises instructions for determining if a subject has a disease or indication can be associated with increased PSMA expression.
Systems
[0372] The present disclosure includes systems for detecting modification and/or accessibility of one or more genomic loci. In some embodiments, the present disclosure provides systems for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci. Systems of the present disclosure can include a sequencer configured to generate a sequencing data set from a sample; and a non-transitory computer readable storage medium and/or a computer system.
[0373] In some embodiments, the non-transitory computer readable storage medium is encoded with a computer program, wherein the program comprises instructions that when executed by one or more processors cause the one or more processors to perform operations to perform a method of the present disclosure.
[0374] In some embodiments, the computer system comprises a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform a method of the present disclosure.
[0375] In some embodiments, the sequencer is configured to generate a Whole Genome Sequencing (WGS) data set from the sample. In some embodiments, the system also includes a sample preparation device configured to prepare the sample for sequencing from a biological sample, optionally a liquid biopsy sample. The sample preparation device may include reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci in cell-free DNA (cfDNA) from the biological sample, optionally the liquid biopsy sample.
[0376] Systems of the present disclosure can include, e.g., reagents such as buffers and/or antibodies useful in the detection and quantification of histone modifications. In certain embodiments, a system of the present disclosure can include at least one antibody that selective binds a histone modification selected from H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, or H3K4me3, or pan acetylation. In certain embodiments, a system of the present disclosure can include at least one antibody that selective binds H3K4me3 modifications. In certain embodiments, a system of the present disclosure can include at least one antibody that selective binds H3K27ac modifications. A system of the present disclosure can include instructional materials disclosing or describing the use of the system in a method of measuring PSMA expression and/or treatment disclosed herein.
[0377] In some embodiments, a system of the present disclosure comprises reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci, wherein the one or more genomic loci are selected from Tables 1-5.
[0378] In some embodiments, the system comprises reagents for quantifying H3K4me3 modifications for 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or 11 of the H3K4me3 analyte genomic loci in Table 1 and 2. In some embodiments, the system comprises reagents for quantifying H3K27ac modifications for 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 H3K27ac analyte loci in Tables 1 and 2. In some embodiments, the system comprises reagents for quantifying H3K27ac modifications for 1, 2, 3, 4, 5, 6, 7, or 8 H3K27ac genomic loci in Table 2 and/or H3K4me3 modifications for the H3K4me3 genomic loci in Table 2. In some embodiments, the system comprises one or more antibodies for use in ChlP-seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac-modified histones. [0379] In some embodiments, the system comprises reagents for quantifying H3K4me3 modifications for 1, 2, 3, or 4 of the H3K4me3 analyte genomic loci in Table 3. In some embodiments, the system comprises reagents for quantifying H3K4me3 modifications for one or both of the H3K4me3 analyte genomic loci in Table 4. In some embodiments, the system comprises reagents for quantifying H3K4me3 modifications for the H3K4me3 analyte genomic locus in Table 4.
[0380] In some embodiments, the system comprises reagents for quantifying H3K27ac modifications for 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, or 23 of the H3K27ac analyte genomic loci in Table 4. In some embodiments, the system comprises reagents for quantifying H3K27ac modifications for the H3K27ac analyte genomic locus in Table 4.
[0381] In some embodiments, the system comprises reagents for quantifying DNA methylation for 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 of the MBD analyte genomic loci in Table 1. In some embodiments, the system comprises one or more methyl-binding domains (e.g., for use in MBD-seq). In some embodiments, the system comprises one or more antibodies that can bind methylated DNA (e.g., for use in MeDIP).
[0382] In some embodiments, the system comprises reagents for isolation of cell-free DNA (cfDNA) from a liquid biopsy sample. In some embodiments, the sequencer comprises reagents for library preparation for sequencing. In some embodiments, the sequencer comprises reagents for sequencing. In some embodiments, the system comprises instructions for determining PSMA expression level.
[0383] In some embodiments, the system comprises reagents for measuring chromatin accessibility via an ATAC-seq assay.
Definitions
[0384] “A” or “An”: The articles “a” and “an” are used herein to refer to one or to more than one (i.e., to at least one) of the grammatical object of the article. By way of example, “an element” refers to one element or more than one element.
[0385] About: The term “about”, when used herein in reference to a value, refers to a value that is similar, in context, to the referenced value. In general, those skilled in the art, familiar with the context, will appreciate the relevant degree of variance encompassed by “about” in that context. For example, in some embodiments, the term “about” can encompass a range of values that within 25%, 20%, 19%, 18%, 17%, 16%, 15%, 14%, 13%, 12%, 11%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, or within a fraction of a percent, of the referenced value.
[0386] “Accessibility Status” or “Chromatin Accessibility Status”: As used herein, “accessibility status” or “chromatin accessibility status” of a genomic locus refers to the frequency with which DNA sequences corresponding to the genomic locus are identified in an assay for detection of accessible chromatin. Accessibility status can be determined by various assays known in the art, including without limitation ChlP-seq as one example. Where two samples are separately analyzed by the same assay or comparable assays for detection of accessible DNA sequences, differences in chromatin accessibility status of genomic loci can be detected. Accessibility status can be compared to a standard or reference. A sample that has an accessibility status that differs in accessibility status from a standard or reference can be referred to as differentially modified. Suitable assays for determining chromatin accessibility are known in the art. Exemplary assays include ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde-Assisted Isolation of Regulatory Elements sequencing), Mnase-seq (Micrococcal Nuclease digestion with sequencing), Dnase hypersensitivity assay, and/or a fragmentomics assay.
[0387] Administration: As used herein, the term “administration” typically refers to the administration of a disease appropriate (e.g., prostate cancer appropriate) treatment. In some embodiments, the disease appropriate treatment may comprise administering a composition to a subject, for example to achieve delivery of an agent that is, is included in, or is otherwise delivered by, the composition. In some embodiments, the disease appropriate treatment may comprise administering an appropriate surgical procedure or radiological procedure, optionally in combination with administration of a composition.
[0388] Agent: As used herein, the term “agent” may refer to any chemical or physical entity, including without limitation any of one or more of an atom, e.g., a radioactive atom, molecule, compound, conjugate, polypeptide, polynucleotide, polysaccharide, lipid, cell, or combination or complex thereof.
[0389] Antibody: As used herein, the term “antibody” refers to a polypeptide that includes one or more canonical immunoglobulin sequence elements sufficient to confer specific binding to a particular antigen (e.g., a heavy chain variable domain, a light chain variable domain, and/or one or more CDRs). Thus, the term antibody includes, without limitation, human antibodies, non-human antibodies, synthetic and/or engineered antibodies, fragments thereof, and agents including the same. Antibodies can be naturally occurring immunoglobulins (e.g., generated by an organism reacting to an antigen). Synthetic, non-naturally occurring, or engineered antibodies can be produced by recombinant engineering, chemical synthesis, or other artificial systems or methodologies known to those of skill in the art.
[0390] As is well known in the art, typical human immunoglobulins are approximately 150 kD tetrameric agents that include two identical heavy (H) chain polypeptides (about 50 kD each) and two identical light (L) chain polypeptides (about 25 kD each) that associate with each other to form a structure commonly referred to as a “Y-shaped” structure. Typically, each heavy chain includes a heavy chain variable domain (VH) and a heavy chain constant domain (CH). The heavy chain constant domain includes three CH domains: CHI, CH2 and CH3. A short region, known as the “switch”, connects the heavy chain variable and constant regions. The “hinge” connects CH2 and CH3 domains to the rest of the immunoglobulin. Each light chain includes a light chain variable domain (VL) and a light chain constant domain (CL), separated from one another by another “switch.” Each variable domain contains three hypervariable loops known as “complement determining regions” (CDR1, CDR2, and CDR3) and four somewhat invariant “framework” regions (FR1, FR2, FR3, and FR4). In each VH and VL, the three CDRs and four FRs are arranged from amino-terminus to carboxy -terminus in the following order: FR1, CDR1, FR2, CDR2, FR3, CDR3, and FR4. The variable regions of a heavy and/or a light chain are typically understood to provide a binding moiety that can interact with an antigen. Constant domains can mediate binding of an antibody to various immune system cells (e.g., effector cells and/or cells that mediate cytotoxicity), receptors, and elements of the complement system. Heavy and light chains are linked to one another by a single disulfide bond, and two other disulfide bonds connect the heavy chain hinge regions to one another, so that the dimers are connected to one another and the tetramer is formed. When natural immunoglobulins fold, the FR regions form the beta sheets that provide the structural framework for the domains, and the CDR loop regions from both the heavy and light chains are brought together in three- dimensional space so that they create a single hypervariable antigen binding site located at the tip of the Y structure.
[0391] In some embodiments, an antibody is a polyclonal, monoclonal, monospecific, or multispecific antibody (e.g., a bispecific antibody). In some embodiments, an antibody includes at least one light chain monomer or dimer, at least one heavy chain monomer or dimer, at least one heavy chain-light chain dimer, or a tetramer that includes two heavy chain monomers and two light chain monomers. Moreover, the term “antibody” can include (unless otherwise stated or clear from context) any art-known constructs or formats utilizing antibody structural and/or functional features including without limitation intrabodies, domain antibodies, antibody mimetics, Zybodies®, Fab fragments, Fab’ fragments, F(ab’)2 fragments, Fd’ fragments, Fd fragments, isolated CDRs or sets thereof, single chain antibodies, single-chain Fvs (scFvs), disulfide-linked Fvs (sdFv), polypeptide-Fc fusions, single domain antibodies (e.g., shark single domain antibodies such as IgNAR or fragments thereof), cameloid antibodies, camelized antibodies, masked antibodies (e.g., Probodies®), affybodies, anti -idiotypic (anti-Id) antibodies (including, e.g., anti-anti-Id antibodies), Small Modular ImmunoPharmaceuticals (SMIPs), single chain or Tandem diabodies (TandAb®), VHHs, Anticalins®, Nanobodies®, minibodies, BiTE®s, ankyrin repeat proteins or DARPINs®, Avimers®, DARTs, TCR-like antibodies, Adnectins®, Affilins®, Trans-bodies®, Affibodies®, TrimerX®, MicroProteins, Fynomers®, Centyrins®, KALBITOR®s, chimeric antigen receptors (CARs), engineered T-cell receptors (TCRs), and antigen-binding fragments of any of the above.
[0392] In various embodiments, an antibody includes one or more structural elements recognized by those skilled in the art as a complementarity determining region (CDR) or variable domain. In some embodiments, an antibody can be a covalently modified (“conjugated”) antibody (e.g., an antibody that includes a polypeptide including one or more canonical immunoglobulin sequence elements sufficient to confer specific binding to a particular antigen, where the polypeptide is covalently linked with one or more of a therapeutic agent, a detectable moiety, another polypeptide, a glycan, or a polyethylene glycol molecule). In some embodiments, antibody sequence elements are humanized, primatized, chimeric, etc., as is known in the art. [0393] An antibody including a heavy chain constant domain can be, without limitation, an antibody of any known class, including but not limited to, IgA, secretory IgA, IgG, IgE and IgM, based on heavy chain constant domain amino acid sequence (e.g., alpha (a), delta (8), epsilon (s), gamma (y) and mu (p)). IgG subclasses are also well known to those in the art and include but are not limited to human IgGl, IgG2, IgG3 and IgG4. “Isotype” refers to the Ab class or subclass (e.g., IgM or IgGl) that is encoded by the heavy chain constant region genes. As used herein, a “light chain” can be of a distinct type, e.g., kappa (K) or lambda (X), based on the amino acid sequence of the light chain constant domain. In some embodiments, an antibody has constant region sequences that are characteristic of mouse, rabbit, primate, or human immunoglobulins. Naturally produced immunoglobulins are glycosylated, typically on the CH2 domain. As is known in the art, affinity and/or other binding attributes of Fc regions for Fc receptors can be modulated through glycosylation or other modification. In some embodiments, an antibody may lack a covalent modification (e.g., attachment of a glycan) that it would have if produced naturally. In some embodiments, antibodies produced and/or utilized in accordance with the present disclosure include glycosylated Fc domains, including Fc domains with modified or engineered glycosylation.
[0394] In some embodiments, an antibody can be specific for a particular histone modification (e.g., an antibody can bind one histone modification, e.g., H3K27ac with a higher affinity than other histone modifications, under conditions that are commonly used in ChlP-seq experiments). In some embodiments, an antibody is specific for an H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, or H3K4me3 modification. In some embodiments, an antibody is specific for an H3K27ac modification. In some embodiments, an antibody is specific for an H3K4me3 modification.
[0395] In some embodiments, an antibody is a “pan” antibody. As used herein, the term pan antibody refers to an antibody that can bind a group of histone modifications having one or more features that are similar. In some embodiments, a pan antibody is a pan-methylation antibody (e.g., an antibody that can bind a histone, e.g., H3 that comprises at least one methylated lysine, wherein the at least one methylated lysine can be at any one of a plurality of amino acid positions, e.g., in some embodiments, a pan-methylation antibody can bind an H3 protein comprising a methylated lysine at any position). In some embodiments, a pan antibody is a pan-acetylation antibody (e.g., an antibody that can bind a histone, e.g., H3 that comprises at least one acetylated lysine, wherein the at least one acetylated lysine can be at any one of a plurality of amino acid positions, e.g., a pan-acetylation antibody can bind an H3 protein comprising an acetylated lysine at any position). In some embodiments, a pan antibody can bind one or more histone modifications that are associated with transcription activation. In some embodiments, a pan antibody can bind one or more histone modifications that are associated with transcription silencing.
[0396] Antibody fragment: As used herein, an “antibody fragment” refers to a portion of an antibody or antibody agent as described herein, and typically refers to a portion that includes an antigen-binding portion or variable region thereof. An antibody fragment can be produced by any means. For example, in some embodiments, an antibody fragment can be enzymatically or chemically produced by fragmentation of an intact antibody or antibody agent. Alternatively, in some embodiments, an antibody fragment can be recombinantly produced, i.e., by expression of an engineered nucleic acid sequence. In some embodiments, an antibody fragment can be wholly or partially synthetically produced. In some embodiments, an antibody fragment (particularly an antigen-binding antibody fragment) can have a length of at least about 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190 amino acids or more, in some embodiments at least about 200 amino acids.
[0397] Associated with: Two events or entities are “associated” with one another, as that term is used herein, if the presence, level and/or form of one is correlated with that of the other. For example, a particular entity (e.g., an epigenetic profile comprising one or more histone modifications at a set of genomic loci, etc.) is considered to be associated with a particular disease, disorder, or condition, if its presence, level and/or form correlates with incidence of and/or susceptibility to the disease, disorder, or condition (e.g., across a relevant population). In some embodiments, two or more entities are physically “associated” with one another if they interact, directly or indirectly, so that they are and/or remain in physical proximity with one another. In some embodiments, two or more entities that are physically associated with one another are covalently linked to one another; in some embodiments, two or more entities that are physically associated with one another are not covalently linked to one another but are non- covalently associated, for example by means of hydrogen bonds, van der Waals interaction, hydrophobic interactions, magnetism, or a combination thereof.
[0398] “Between” or “From”: As used herein, the term “between” refers to content that falls between indicated upper and lower, or first and second, boundaries, inclusive of the boundaries. Similarly, the term “from”, when used in the context of a range of values, indicates that the range includes content that falls between indicated upper and lower, or first and second, boundaries, inclusive of the boundaries.
[0399] Biological Sample: As used herein, the term “biological sample” typically refers to a sample obtained or derived from a biological source (e.g., a tissue or organism or cell) of interest, as described herein. In some embodiments, a biological source is or includes an organism, such as a human subject. In some embodiments, a biological sample is or includes a biological tissue or fluid. In some embodiments, a biological sample can be or include cells, tissue, or bodily fluid. “Bodily fluids” refer to fluids that are excreted or secreted from the body as well as fluids that are normally not (e.g., blood, serum, plasma, Cowper’s fluid or preejaculate fluid, chyle, chyme, stool, interstitial fluid, intracellular fluid, lymph, menses, saliva, sebum, semen, serum, sweat, synovial fluid, tears, urine, vitreous humor, vomit). In some embodiments, a biological sample can be or include blood, blood components, cell-free DNA (cfDNA), circulating-tumor DNA (ctDNA), ascites, biopsy samples, surgical specimens, cellcontaining body fluids, sputum, saliva, feces, urine, cerebrospinal fluid, peritoneal fluid, pleural fluid, lymph, gynecological fluids, secretions, excretions, skin swabs, vaginal swabs, oral swabs, nasal swabs, washings or lavages such as a ductal lavages or bronchoalveolar lavages, aspirates, scrapings, or bone marrow. In some embodiments, a biological sample is a liquid biopsy sample obtained from a bodily fluid. In some embodiments, a biological sample is or includes DNA obtained from a single subject or from a plurality of subjects. A biological sample can be a “primary sample” obtained directly from a biological source or can be a “processed sample”, i.e., a sample that was derived from a primary sample, e.g., via dilution, purification, mixing with one or more reagents, or any other processing step(s) as described herein. A biological sample can also be referred to as a “sample.”
[0400] Blood component: As used herein, the term “blood component” refers to any component of whole blood, including red blood cells, white blood cells, plasma, platelets, endothelial cells, mesothelial cells, epithelial cells, cell-free DNA (cfDNA), and circulatingtumor DNA (cfDNA). Blood components also include the components of plasma, including proteins, metabolites, lipids, nucleic acids, and carbohydrates, and any other cells that can be present in blood, e.g., due to pregnancy, organ transplant, infection, injury, or disease.
[0401] Cancer: As used herein, the terms “cancer,” “malignancy,” “tumor,” and “carcinoma,” are used interchangeably to refer to a disease, disorder, or condition in which cells exhibit or exhibited relatively abnormal, uncontrolled, and/or autonomous growth, so that they display or displayed an abnormally elevated proliferation rate and/or aberrant growth phenotype. In some embodiments, a cancer can include one or more tumors. In some embodiments, a cancer can be or include cells that are precancerous e.g., benign), malignant, pre-metastatic, metastatic, and/or non-metastatic. In some embodiments, a cancer can be or include a solid tumor.
[0402] Examples of cancer include but are not limited to, carcinoma, lymphoma, blastoma, sarcoma, and leukemia or lymphoid malignancies. More particular examples of such cancers include, but are not limited to, breast cancer (e.g., an HR+ breast cancer (e.g., an ER+ breast cancer (e.g., luminal A breast cancer or luminal B breast cancer)), DCIS, and/or a metastatic or a locally advanced breast cancer)); lung cancer, including small-cell lung cancer, non-small cell lung cancer, adenocarcinoma of the lung, and squamous carcinoma of the lung; bladder cancer (e.g., urothelial bladder cancer (UBC), muscle invasive bladder cancer (MIBC), and BCG-refractory non-muscle invasive bladder cancer (NMIBC)); kidney or renal cancer (e.g., renal cell carcinoma (RCC)); cancer of the urinary tract; prostate cancer, such as castrationresistant prostate cancer (CRPC); cancer of the peritoneum; hepatocellular cancer; gastric or stomach cancer, including gastrointestinal cancer and gastrointestinal stromal cancer; pancreatic cancer; glioblastoma; cervical cancer; ovarian cancer; liver cancer; hepatoma; colon cancer; rectal cancer; colorectal cancer; endometrial or uterine carcinoma; salivary gland carcinoma; prostate cancer; vulval cancer; thyroid cancer; hepatic carcinoma; anal carcinoma; penile carcinoma; melanoma, including superficial spreading melanoma, lentigo maligna melanoma, acral lentiginous melanomas, and nodular melanomas; multiple myeloma and B-cell lymphoma (including low grade/follicular non-Hodgkin’s lymphoma (NHL); small lymphocytic (SL) NHL; intermediate grade/follicular NHL; intermediate grade diffuse NHL; high grade immunoblastic NHL; high grade lymphoblastic NHL; high grade small non-cleaved cell NHL; bulky disease NHL; mantle cell lymphoma; AIDS-related lymphoma; and Waldenstrom’s Macroglobulinemia); chronic lymphocytic leukemia (CLL); acute lymphoblastic leukemia (ALL); acute myologenous leukemia (AML); hairy cell leukemia; chronic myeloblastic leukemia (CML); post-transplant lymphoproliferative disorder (PTLD); and myelodysplastic syndromes (MDS), as well as abnormal vascular proliferation associated with phakomatoses, edema (such as that associated with brain tumors), Meigs’ syndrome, brain cancer, head and neck cancer, and associated metastases.
[0403] Combination therapy: As used herein, the term “combination therapy” refers to administration to a subject of two or more therapeutic agents or therapeutic regimens such that the two or more therapeutic agents or therapeutic regimens together treat a disease, condition, or disorder of the subject. In some embodiments, the two or more therapeutic agents or therapeutic regimens can be administered simultaneously, sequentially, or in overlapping dosing regimens. Those of skill in the art will appreciate that combination therapy includes but does not require that the two therapeutic agents or therapeutic regimens be administered together in a single composition, nor at the same time.
[0404] Corresponding to-. As used herein, the term “corresponding to” may be used to designate the position/identity of a structural element in a compound or composition through comparison with an appropriate reference compound or composition. For example, in some embodiments, a monomeric residue in a polymer (e.g., an amino acid residue in a polypeptide or a nucleic acid residue in a polynucleotide) may be identified as “corresponding to” a residue in an appropriate reference polymer. For example, those of skill in the art appreciate that residues in a provided polypeptide or polynucleotide sequence are often designated (e.g., numbered or labeled) according to the scheme of a related reference sequence (even if, e.g., such designation does not reflect literal numbering of the provided sequence). By way of illustration, if a reference sequence includes a particular amino acid motif at positions 100-110, and a second related sequence includes the same motif at positions 110-120, the motif positions of the second related sequence can be said to “correspond to” positions 100-110 of the reference sequence. Those of skill in the art appreciate that corresponding positions can be readily identified, e.g., by alignment of sequences, and that such alignment is commonly accomplished by any of a variety of known tools, strategies, and/or algorithms, including without limitation software programs such as, for example, BLAST, CS-BLAST, CUDASW++, DIAMOND, FASTA, GGSEARCH/GL SEARCH, Genoogle, HMMER, Hhpred/Hhsearch, IDF, Infernal, KLAST, USEARCH, parasail, PSI-BLAST, PSI-Search, ScalaBLAST, Sequilab, SAM, SSEARCH, SWAPHI, SWAPHI-LS, SWIMM, or SWIPE. Two sequences can be identified as corresponding if they are identical or if they share substantial identity, e.g., at least 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% identity, e.g., over a length of at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500 or more residues. In various embodiments, a nucleic acid sequence can correspond to a sequence that is identical or substantially identical (e.g., at least 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% identical) to the complement of the nucleic acid sequence, e.g., over a length of at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500 or more nucleic acid residues.
[0405] “Diagnosing”, “Detecting”, “Determining” or “Screening for”: As used herein, “diagnosing”, “detecting”, “determining”, “screening for” the presence of a condition or disease (e.g., mCRPC), or a related state (e.g., responsiveness of mCRPC to one or more therapies) includes the act, process, and/or outcome of determining whether, and/or the qualitative of quantitative probability that, a subject has or will develop the condition, disease, or related state. In some instances, diagnosing can include a determination relating to prognosis and/or likely response to one or more general or particular therapeutic agents or regimens.
[0406] Differentially accessible: As used herein, the term “differentially accessible” describes a genomic locus for which chromatin accessibility status differs between a first condition or sample and a second condition or sample (e.g., a standard or reference). A differentially accessible genomic locus can include a greater or smaller measured accessibility under a selected condition of interest, such as mCRPC, as compared to a reference state, such as a healthy subject.
[0407] Differentially modified: As used herein, the term “differentially modified” describes a genomic locus for which histone modification status and/or DNA methylation status differs between a first condition or sample and a second condition or sample (e.g., a standard or reference). A differentially modified genomic locus can include a greater or smaller number or frequency of histone modification and/or DNA methylations under a selected condition of interest, such as mCRPC, as compared to a reference state, such as a healthy subject. Enhancer signal. As used herein, the term “enhancer signal” refers to an epigenetic modification or chromatin state in an enhancer region that is associated with increased expression of a gene regulated by the enhancer region. Examples of such enhancer signals are known in the art, and include histone acetylation (e.g., H3K27ac). In some embodiments, enhancer signal can be measured by quantifying histone acetylation (e.g., H3K27ac), chromatin accessibility, and/or transcription factor binding.
[0408] Expression level, amount, or level: As used herein, the terms “expression level,” “amount,” or “level,” or used herein interchangeably, of a biomarker is a detectable level in a biological sample. “Expression” generally refers to the process by which information (e.g., gene-encoded and/or epigenetic) is converted into the structures present and operating in the cell. Therefore, as used herein, “expression” may refer to transcription into a polynucleotide, translation into a polypeptide, or even polynucleotide and/or polypeptide modifications (e.g., posttranslational modification of a polypeptide). Expression level, amount, or level of a given polypeptide (e.g., PSA or PSMA), is a measure of the expression process for that polypeptide. Fragments of the transcribed polynucleotide, the translated polypeptide, or polynucleotide and/or polypeptide modifications (e.g., posttranslational modification of a polypeptide) shall also be regarded as expressed whether they originate from a transcript generated by alternative splicing or a degraded transcript, or from a post-translational processing of the polypeptide, e.g., by proteolysis. “Expressed genes” include those that are transcribed into a polynucleotide as mRNA and then translated into a polypeptide, and also those that are transcribed into RNA but not translated into a polypeptide (for example, transfer and ribosomal RNAs). Expression levels can be measured by methods known to one skilled in the art and also disclosed herein. The expression level or amount of a biomarker can be used to identify/characterize a subject having a prostate cancer (e.g., mCRPC) who may be likely to respond to, or benefit from, a particular therapy (e.g., a PSMA-targeted therapy). The expression level or amount of a biomarker provided herein in a subject having a prostate cancer described herein can also be used to determine and/or track the benefit of an administered therapy over time.
[0409] Identity: As used herein, the term “identity” refers to the overall relatedness between polymeric molecules, e.g., between nucleic acid molecules (e.g., DNA molecules) and/or between polypeptide molecules. Methods for the calculation of a percent identity as between two provided sequences are known in the art. The term “% sequence identity” refers to a relationship between two or more sequences, as determined by comparing the sequences. In the art, “identity” also means the degree of sequence relatedness between protein and nucleic acid sequences as determined by the match between strings of such sequences. “Identity” (often referred to as “similarity”) can be readily calculated by known methods, including those described in: Computational Molecular Biology (Lesk, A. M. ed.) Oxford University Press, NY (1988); Biocomputing: Informatics and Genome Projects (Smith, D. W. ed.) Academic Press, NY (1994); Computer Analysis of Sequence Data, Part I (Griffin, A. M. and Griffin, H. G. eds.) Humana Press, NJ (1994); Sequence Analysis in Molecular Biology (Von Heijne, G. ed.) Academic Press (1987); and Sequence Analysis Primer (Gribskov, M. and Devereux, J. eds.) Oxford University Press, NY (1992), each of which are separately incorporated by reference in their entirety. Preferred methods to determine identity are designed to give the best match between the sequences tested. Methods to determine identity and similarity are codified in publicly available computer programs. For example, calculation of the percent identity of two nucleic acid or polypeptide sequences can be performed by aligning the two sequences (or the complement of one or both sequences) for optimal comparison purposes (e g., gaps can be introduced in one or both of a first and a second sequences for optimal alignment and nonidentical sequences can be disregarded for comparison purposes). The nucleotides or amino acids at corresponding positions are then compared. When a position in the first sequence is occupied by the same residue (e.g., nucleotide or amino acid) as the corresponding position in the second sequence, then the molecules are identical at that position. The percent identity between the two sequences is a function of the number of identical positions shared by the sequences, optionally accounting for the number of gaps, and the length of each gap, which may need to be introduced for optimal alignment of the two sequences. The comparison of sequences and determination of percent identity between two sequences can be accomplished using a computational algorithm, such as BLAST (basic local alignment search tool). Sequence alignments and percent identity calculations may be performed using the Megalign program of the LASERGENE bioinformatics computing suite (DNASTAR, Inc., Madison, Wisconsin). Multiple alignment of the sequences can also be performed using the Clustal method of alignment (Higgins and Sharp, Comp Appl Biosci (1989) 5(2): 151-153), incorporated by reference herein in its entirety, with default parameters (GAP PENALTY=10, GAP LENGTH PENALTY=10). Relevant programs also include the GCG suite of programs (Wisconsin Package Version 9.0, Genetics Computer Group (GCG), Madison, Wisconsin); BLASTP, BLASTN, BLASTX (Altschul et al., J Mol Biol (1990) 215:403-410); DNASTAR (DNASTAR, Inc., Madison, Wisconsin); and the FASTA program incorporating the Smith-Waterman algorithm (Pearson, Comput Methods Genome Res [Proc Int Symp] (1994), Meeting Date 1992, 111-120. Eds. Suhai, Sandor. Plenum, New York, NY (the contents of each of which is separately incorporated herein by reference in its entirety). Within the context of this disclosure, it will be understood that where sequence analysis software is used for analysis, the results of the analysis are based on the “default values” of the program referenced. “Default values” will mean any set of values or parameters, which originally load with the software when first initialized.
[0410] “Improve,” “increase,” “inhibit,” or “reduce”: As used herein, the terms “improve”, “increase”, “inhibit”, and “reduce”, and grammatical equivalents thereof, indicate qualitative or quantitative difference from a reference.
[0411] Methylation Status: As used herein, “methylation status” of a genomic locus refers to the frequency with which DNA sequences corresponding to the genomic locus are identified in an assay for detection of DNA methylated sequences and/or the density (e.g., the measured density) of DNA methylation corresponding to the genomic locus. Methylation status can be determined by various assays known in the art, including without limitation Bisulfite sequencing (BS-Seq), Whole Genome Bisulfite Sequencing (WGBS), Methylated DNA ImmunoPrecipitation sequencing (MeDIP-seq), or Methyl-CpG-Binding Domain sequencing (MBD-seq). Where two samples are separately analyzed by the same assay or comparable assays for detection of DNA methylated sequences, differences in methylation status of genomic loci can be detected. Methylation status can be compared to a standard or reference. A sample that has a methylation status that differs from a standard or reference can be referred to as differentially modified.
[0412] “Modification Status” or “Histone Modification Status” : As used herein, “modification status” or “histone modification status” of a genomic locus refers to the frequency with which DNA sequences corresponding to the genomic locus are identified in an assay for detection of DNA sequences associated with histones bearing one or more histone modifications (e g., one or more particular histone modifications) and/or the density (e g., the measured density) of histone modifications (e.g., one or more particular histone modifications) corresponding to the genomic locus. Modification status can be determined by various assays known in the art, including without limitation ChlP-seq as one example. Other well-known assays include CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing and CUT&Tag (Cleavage Under Targets and Tagmentation). Where two samples are separately analyzed by the same assay or comparable assays for detection of DNA sequences associated with histones bearing one or more histone modifications (e.g., one or more particular histone modifications), differences in modification status of genomic loci can be detected. Modification status can be compared to a standard or reference. A sample that has a modification status that differs in modification status or histone modification status from a standard or reference can be referred to as differentially modified.
[0413] PSMA Expression: As used herein, “PSMA expression” refers to the amount of PSMA produced in a subject and/or the amount of PSMA produced in a subset of cells within a subject. In some embodiments, the subset of cells includes or consists of cells from a particular organ or tissue type (e.g., prostate tissue) of interest. In some embodiments, the subset of cells includes or consists of diseased cells. In some embodiments the subset of cells includes or consists of cancer cells. In some embodiments, the subset of cells includes or consists of prostate cancer cells. In some embodiments, the subset of cells includes or consists of mCRPC cells. In some embodiments, “disease specific PSMA expression” refers to PSMA produced by diseased cells. In some embodiments, PSMA expression refers to cell surface and/or extracellular expression.
[0414] As shown herein, PSMA expression measured using technologies described herein can be associated with estimates of PSMA expression determined using other methods. Thus, in some embodiments, technologies provided herein for measuring PSMA expression level can be used to predict values that would be provided by other technologies, including, e.g., measurements provided by other approaches that have been shown to be associated with clinical outcomes and/or be suitable for determining patient eligibility for a certain therapeutic. In some embodiment, technologies provided herein can be used to predict a PSMA expression level determined using an imaging method, including, e.g., a PSMA PET imaging method. In some embodiments, technologies provided herein can be used to predict a PSMA PET SUVmean measurement.
[0415] PSMA Targeted Therapeutic: As used herein, a “PSMA targeted therapeutic” or “PSMA targeted therapy” refers to a therapeutic or administration of a therapeutic that can bind to or associate with PSMA (e.g., bind to or associate with PSMA in a subject). In some embodiments, a PSMA targeted therapeutic comprises a moiety that can bind to or associate with PSMA in a subject. In some embodiments, a PSMA targeted therapeutic comprises an antibody moiety that can bind to or associate with PSMA in a subject. In some embodiments, a PSMA targeted therapeutic comprises a small molecule moiety that can bind to or associate with PSMA in a subject. In some embodiments, a PSMA targeted therapeutic is an ADC comprising an antibody moiety that can bind PSMA (e.g., an antibody moiety of an ADC described herein). A PSMA targeted therapeutic is a radiolabeled conjugate.
[0416] Promoter signal: As used herein, the term “promoter signal” refers to an epigenetic modification in a promoter region that is associated with increased expression of a gene regulated by the promoter region. Examples of such promoter signals are known in the art, and include, e.g., histone methylation (e.g., H3K4me3). In some embodiments, promoter signal can be measured by quantifying histone methylation (e.g., H3K4me3), chromatin accessibility, and/or transcription factor binding.
[0417] Regulatory sequence: As used herein in the context of expression of a nucleic acid coding sequence, a regulatory sequence is a nucleic acid sequence that controls expression of a coding sequence, e.g., a promoter sequence or an enhancer sequence. In some embodiments, a regulatory sequence can control or impact one or more aspects of gene expression (e.g., celltype-specific expression, inducible expression, etc.).
[0418] Subject: As used herein, the term “subject” refers to an organism, typically a mammal (e.g., a human). In some embodiments, a subject is suffering from a disease, disorder or condition (e.g., mCRPC). In some embodiments, a subject is susceptible to a disease, disorder, or condition. In some embodiments, a subject displays one or more symptoms or characteristics of a disease, disorder or condition. In some embodiments, a subject is not suffering from a disease, disorder or condition. In some embodiments, a subject does not display any symptom or characteristic of a disease, disorder, or condition. In some embodiments, a subject has one or more features characteristic of susceptibility to or risk of a disease, disorder, or condition. Tn some embodiments, a subject is a subject that has been tested for a disease, disorder, or condition, and/or to whom therapy has been administered. In some instances, a human subject can be interchangeably referred to as a “patient” or “individual”.
[0419] Therapeutic agent: As used herein, the term “therapeutic agent” refers to any agent that elicits a desired pharmacological effect when administered to a subject. In some embodiments, an agent is considered to be a therapeutic agent if it demonstrates a statistically significant effect across an appropriate population. In some embodiments, the appropriate population can be a population of model organisms or a human population. In some embodiments, an appropriate population can be defined by various criteria, such as a certain age group, gender, genetic background, preexisting clinical conditions, etc. In some embodiments, a therapeutic agent is a substance that can be used for treatment of a disease, disorder, or condition (e.g., mCRPC). In some embodiments, a therapeutic agent is an agent that has been or is required to be approved by a government agency before it can be marketed for administration to humans. In some embodiments, a therapeutic agent is an agent for which a medical prescription is required for administration to humans.
[0420] Therapeutically effective amount: As used herein, “therapeutically effective amount” refers to an amount that produces the desired effect for which it is administered. In some embodiments, the term refers to an amount that is sufficient, when administered to a population suffering from or susceptible to a disease, disorder, and/or condition (e.g., mCRPC) in accordance with a therapeutic dosing regimen, to treat the disease, disorder, and/or condition. In some embodiments, a therapeutically effective amount is one that reduces the incidence and/or severity of, and/or delays onset of, one or more symptoms of the disease, disorder, and/or condition. Those of ordinary skill in the art will appreciate that the term “therapeutically effective amount” does not in fact require successful treatment be achieved in a particular individual. Rather, a therapeutically effective amount may be that amount that provides a particular desired pharmacological response in a significant number of subjects when administered to patients in need of such treatment. In some embodiments, reference to a therapeutically effective amount may be a reference to an amount as measured in one or more specific tissues (e.g., a tissue affected by the disease, disorder or condition) or fluids (e.g., blood, saliva, serum, sweat, tears, urine, etc ). Those of ordinary skill in the art will appreciate that, in some embodiments, a therapeutically effective amount of a particular agent or therapy may be formulated and/or administered in a single dose. In some embodiments, a therapeutically effective amount of a particular agent or therapy may be formulated and/or administered in a plurality of doses, for example, as part of a dosing regimen.
[0421] Treatment: As used herein, the term “treatment” (also “treat” or “treating”) refers to administration of a therapy that partially or completely alleviates, ameliorates, relieves, inhibits, delays onset of, reduces severity of, and/or reduces incidence of one or more symptoms, features, and/or causes of a particular disease, disorder, or condition, or is administered for the purpose of achieving any such result. In some embodiments, such treatment can be of a subject who does not exhibit signs of the relevant disease, disorder, or condition and/or of a subject who exhibits only early signs of the disease, disorder, or condition (e g., mCRPC). Alternatively, or additionally, such treatment can be of a subject who exhibits one or more established signs of the relevant disease, disorder and/or condition. In some embodiments, treatment can be of a subject who has been diagnosed as suffering from the relevant disease, disorder, and/or condition. In some embodiments, treatment can be of a subject known to have one or more susceptibility factors that are statistically correlated with increased risk of development of the relevant disease, disorder, or condition. A “prophylactic treatment” includes a treatment administered to a subject who does not display signs or symptoms of a condition to be treated or displays only early signs or symptoms of the condition to be treated such that treatment is administered for the purpose of diminishing, preventing, or decreasing the risk of developing the condition. Thus, a prophylactic treatment functions as a preventive treatment against a condition. A “therapeutic treatment” includes a treatment administered to a subject who displays symptoms or signs of a condition and is administered to the subject for the purpose of reducing the severity or progression of the condition.
Exemplary Embodiments
1. A method of measuring PSMA expression in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) or circulating tumor DNA (ctDNA) from a liquid biopsy sample, obtained or derived from the subject: (i) one or more histone modifications,
(ii) chromatin accessibility,
(iii) binding of one or more transcription factors, and/or
(iv) DNA methylation.
2. The method of embodiment 1, wherein the method measures PSMA expression in one or more tumors in a subject.
3. The method of embodiment 1 or 2, wherein the PSMA expression is cell surface expression of PSMA.
4. The method of any one of embodiments 1-3, wherein the PSMA expression is tumor cell specific, cell surface expression of PSMA.
5. A method of predicting tumor specific PSMA expression (e.g., predicting PSMA expression measurements determined using (i) an imaging procedure, (ii) a radioligand, and/or (iii) PSMA PET imaging (e.g., PSMA PET SUVmax or PSMA PET SUVmean)) in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) or ctDNA from a liquid biopsy sample, obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility,
(iii) binding of one or more transcription factors, and/or
(iv) DNA methylation.
6. The method of any one of embodiments 1-5, wherein the one or more histone modifications are quantified using a histone modification assay that measures one or more of H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, H3K4me3, and panacetylation.
7. The method of embodiment 6, wherein the histone modification assay detects H3K4me3 modifications.
8. The method of embodiment 6, wherein the histone modification assay detects H3K27ac modifications.
9. The method of any one of embodiments 1-8, wherein the histone modification assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
10. The method of any one of embodiments 1-9, wherein chromatin accessibility is quantified using a chromatin accessibility assay selected from ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde- Assisted Isolation of Regulatory Elements sequencing), MNase-seq (Micrococcal Nuclease digestion with sequencing), a DNase hypersensitivity assay, and a fragmentomics assay.
11. The method of any one of embodiments 1-10, wherein the binding of one or more transcription factors is quantified using a transcription factor binding assay.
12. The method of embodiment 11, wherein the transcription factor binding assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
13. The method of any one of embodiments 1-12, wherein DNA methylation is quantified using Bisulfite sequencing (BS-Seq), Whole Genome Bisulfite Sequencing (WGBS), Methylated DNA ImmunoPrecipitation sequencing (MeDIP-seq), or Methyl -CpG-Binding Domain sequencing (MBD-seq).
14. The method of any one of embodiments 1-13, comprising quantifying two or more of the following, each at one or more genomic loci in cell-free DNA (cfDNA) or ctDNA from a liquid biopsy sample obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility,
(iii) transcription factor binding, and/or
(iv) DNA methylation.
15. The method of embodiment 14, comprising quantifying two or more histone modifications.
16. The method of embodiment 15, comprising quantifying H3K4me3 and H3K27ac modifications. 17. The method of embodiment 14, comprising quantifying one or more histone modifications and DNA methylation.
18. The method of embodiment 17, comprising quantifying (i) H3K4me3 and/or H3K27ac modifications and (ii) DNA methylation.
19. The method of embodiment 18, comprising quantifying H3K4me3 modifications, H3K27ac modifications, and DNA methylation.
20. The method of any one of embodiments 1-19, wherein an increase of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at the one or more genomic loci as compared to a reference indicates that the subject has increased PSMA expression (e.g., increased as compared to a healthy subject).
21. The method of any one of embodiments 1-20, comprising quantifying one or more prostate cancer specific markers (e.g., PSA).
22. The method of any one of embodiments 1-21, comprising quantifying one or more histone modifications and/or DNA methylation at one or more prostate cancer specific marker genes or regulatory regions thereof (e.g., one or more promoters and/or enhancers of one or more prostate cancer specific marker genes).
23. The method of embodiment 21 or 22, wherein the one or more prostate cancer specific marker genes comprise HXB13, KLK2, KLK3, SPDEF, or FOLH1, or any combination thereof.
24. The method of any one of embodiments 1-23, comprising quantifying one or more histone modifications and/or DNA methylation for one or more of AMN, ARHGEF37, C4orf36, CADM1, CCDC175, CDC7, CLSTN1, COL5A1, EDNRA, FOLH1, GALR3, MED13L, MICB, NDRG3, NEDD1, NPAS2, NPVF, OLFM1, PCBP4, PROZ, PRRG3, RREB1, SCUBE3, SERPINA5, SNRPF, SORCS3, ST8SIA5, TEX19, TMEM132B, or TTC29 or any combination thereof, or one or more regulatory regions of any one of the foregoing (e.g., one or more promoter and/or enhancer regions o AMN, ARHGEF37, C4orf36, CADM1, CCDC175, CDC7, CLSTN1, COL5A1, EDNRA, FOLH1, GALR3, MEDI3L, MICB, NDRG3, NEDD1, NPAS2, NPVF, 0LFM1, PCBP4, PROZ, PRRG3, RREB1, SCUBE3, SERPINA5, SNRPF, SORCS3, ST8S1A5, TEXI9, TMEM132B, or TTC29, or any combination thereof).
25. The method of embodiment 24, comprising quantifying: a) promoter signal (e g., H3K4me3 signal) at one or more promoter regions of C4orf36, CADM1, CDC7, COL5A1, EDNRA, MED13L, NEDD1, PROZ, SNRPF, TEXJ9, or any combination thereof; b) enhancer signal (e.g., H3K27ac signal) at one or more enhancer regions of ARHGEF37, CLSTN1, F0LH1, NDRG3, NPAS2, NPVF, 0LFM1, RREB1, SCUBE3, or TTC29, or any combination thereof; c) DNA methylation of AMN, CCDC175, GALR3, MICB, PCBP4, PRRG3, SERPINA5, SORCS3, ST8SIA5, TMEM 132B, or any combination thereof.
26. The method of any one of embodiments 1-25, wherein the method comprises quantifying:
(a) promoter signal (e.g., H3K4me3 modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K4me3 analyte genomic loci in Table 1;
(b) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 1;
(c) DNA methylation for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 MBD analyte genomic loci in Table 1; or
(d) or any combination of (a)-(c).
27. The method of any one of embodiments 1-26, wherein the method comprises:
(a) quantifying enhancer signal (e.g., H3K27ac modifications) at one or more (e.g., all) of genomic loci 1-8 in Table 2;
(b) quantifying promoter signal (e.g., H3K4me3 modifications) at genomic locus 9 in Table 2; or
(c) a combination of (a) and (b).
28. The method of any one of embodiments 1-25, wherein the method comprises quantifying:
(a) promoter signal (e.g., H3K4me3 modifications) for 1 or 2 H3K4me3 analyte genomic loci in Table 4;
(b) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 4;
(c) or a combination of (a) and (b). 29. The method of any one of embodiments 1 -28, wherein the method comprises quantifying
(a) promoter signal (e.g., H3K4me3 modifications) at chrl 1 :49,228,902-49,230,855; and/or (b) enhancer signal (e.g., H3K27ac modifications) at chrl 1 :49, 229, 019-49, 230, 275.
30. The method of any one of embodiments 1-29, further comprising:
(a) aggregating promoter signal (e g., H3K4me3 modifications) for one or more genomic loci;
(b) aggregating enhancer signal (e.g., H3K27ac modifications) for one or more genomic loci; or
(c) a combination of (a) and (b).
31. The method of embodiment 30, wherein the aggregated promoter signal and aggregated enhancer signal are aggregated.
32. The method of embodiment 30 or 31, wherein the promoter signal and enhancer signal are normalized prior to aggregating (e.g., normalized based on sequence read depth or ctDNA fraction).
33. The method of any one of embodiments 1-32, wherein:
(i) the subject has previously been diagnosed with a disease or condition that is associated with increased PSMA expression, optionally wherein the disease or condition that is associated with increased PSMA expression is prostate cancer; and/or
(ii) the one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and DNA/or DNA methylation is quantified before administering a PSMA-targeted agent.
34. A method of measuring PSA expression in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free
DNA (cfDNA) or circulating tumor DNA (ctDNA) from a liquid biopsy sample, obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility,
(iii) binding of one or more transcription factors, and/or
(iv) DNA methylation.
35. A method of predicting PSA expression in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) or circulating tumor DNA (ctDNA) from a liquid biopsy sample, obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility,
(iii) binding of one or more transcription factors, and/or
(iv) DNA methylation.
36. The method of embodiment 34 or 35, wherein the PSA expression is or comprises serum PSA.
37. The method of any one of embodiments 34-36, wherein the method measures or predicts PSA expressed by one or more cancer cells in the subject.
38. The method of any one of embodiments 34-37, wherein the method measures or predicts serum concentration of total PSA.
39. The method of any one of embodiments 35-38, wherein the method predicts PSA expression as determined using an assay that (a) utilizes one or more antibodies that bind PSA (e g., an ELISA assay) and/or (b) measures PSA enzymatic activity.
40. The method of any one of embodiments 34-39, wherein the one or more histone modifications are quantified using a histone modification assay that measures one or more of H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, H3K4me3, and panacetylation.
41. The method of embodiment 40, wherein the histone modification assay detects H3K4me3 modifications and/or H3K27ac modifications.
42. The method of any one of embodiments 34-41, wherein the histone modification assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
43. The method of any one of embodiments 34-42, wherein chromatin accessibility is quantified using a chromatin accessibility assay selected from ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde- Assisted Isolation of Regulatory Elements sequencing), MNase-seq (Micrococcal Nuclease digestion with sequencing), a DNase hypersensitivity assay, and a fragmentomics assay.
44. The method of any one of embodiments 34-43, wherein the binding of one or more transcription factors is quantified using a transcription factor binding assay.
45. The method of embodiment 44, wherein the transcription factor binding assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
46. The method of any one of embodiments 34-45, wherein DNA methylation is quantified using Bisulfite sequencing (BS-Seq), Whole Genome Bisulfite Sequencing (WGBS), Methylated DNA ImmunoPrecipitation sequencing (MeDIP-seq), or Methyl-CpG-Binding Domain sequencing (MBD-seq).
47. The method of any one of embodiments 34-46, comprising quantifying two or more of the following, each at one or more genomic loci in cell-free DNA (cfDNA) or ctDNA from a liquid biopsy sample obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility,
(iii) transcription factor binding, and/or
(iv) DNA methylation.
48. The method of embodiment 47, comprising quantifying two or more histone modifications.
49. The method of embodiment 48, comprising quantifying H3K4me3 modifications.
50. The method of embodiment 48, comprising quantifying H3K27ac modifications.
51. The method of embodiment 47, comprising quantifying one or more histone modifications and DNA methylation.
52. The method of embodiment 51, comprising quantifying (i) H3K4me3 and/or H3K27ac modifications and (ii) DNA methylation.
53. The method of embodiment 52, comprising quantifying H3K4me3 modifications, H3K27ac modifications, and DNA methylation. 54. The method of any one of embodiments 34-53, wherein an increase of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at the one or more genomic loci as compared to a reference indicates that the subject has increased PSA expression (e.g., increased as compared to a healthy subject).
55. The method of any one of embodiments 34-54, wherein the method comprises:
(i) quantifying enhancer signal (e.g., H3K27ac modifications) at one or more loci within 200 kB of a KLK3 gene;
(ii) quantifying enhancer signal (e.g., H3K27ac modifications) at one or more loci within 200 kB of a KLK3 gene;
(iii) quantifying DNA methylation at one or more loci within 200 kB of a KLK3 gene; or
(iv) any combination of (i)-(iii).
56. The method of any one of embodiments 34-55, wherein the method comprises quantifying enhancer signal (e.g., H3K27ac modifications) at one or more (e.g., all) genomic loci in Table 3.
57. The method of any one of embodiments 34-56, comprising:
(a) aggregating promoter signal (e.g., H3K4me3 modifications) at the one or more genomic loci;
(b) aggregating enhancer signal (e.g., H3K27ac modifications) at the one or more genomic loci; or
(c) a combination of (a) and (b).
58. The method of embodiment 57, wherein the aggregated promoter signal and aggregated enhancer signal are aggregated.
59. The method of embodiment 57 or 58, wherein the promoter signal and enhancer signal are normalized prior to aggregating (e.g., normalized based on sequence read depth or ctDNA fraction).
60. The method of any one of embodiments 34-59, wherein the method further comprises predicting or determining PSMA expression in the subject, and/or wherein PSMA expression has already been determined in the subject. 61 . The method of embodiment 60, wherein PSMA expression is or has been determined or predicted using the method of any one of embodiments 1-31, optionally wherein the same biological sample is or has been used to determine or predict PSMA and PSA expression.
62. The method of any one of embodiments 34-61, wherein the subject has previously been diagnosed with a disease or condition that is associated with increased PSA expression.
63. The method of any one of embodiments 1-62, wherein the biological sample comprises a ctDNA fraction of at least 0.03%, at least 0.05%, or at least 0.10%.
64. The method of any one of embodiments 1-63, wherein the liquid biopsy sample is a plasma sample, serum sample, or urine sample.
65. The method of any one of embodiments 1-64, wherein the subject has previously been diagnosed with cancer (e.g., breast cancer, prostate cancer, or lung cancer (e.g., SCLC)).
66. The method of embodiment 65, wherein the cancer is prostate cancer, optionally wherein:
(i) the prostate cancer is metastatic castration resistant prostate cancer (mCRPC);
(ii) the subject has previously been administered an androgen receptor pathway inhibitor (ARPI) therapy;
(iii) it has been determined to be appropriate to delay administering a taxane-based chemotherapy to the subject or the subject has previously received taxane-based chemotherapy; or
(iv) any combination of (i)-(iii).
67. The method of embodiment 65 or 66, wherein the prostate cancer is prostate adenocarcinoma (PRAD) or neuroendocrine prostate cancer (NEPC).
68. A method of identifying a subject with elevated PSMA expression, comprising:
(a) measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) using a method of any one of embodiments 1-33 or 63-67, and optionally
(b) comparing the measured PSMA expression or predicted tumor specific PSMA expression to a reference.
69. A method of identifying a subject with elevated PSA expression, comprising:
(a) measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total PSA) using a method of any one of embodiments 34-67, and optionally
(b) comparing the measured or predicted PSA expression to a reference. 70. A method of diagnosing a subject as having a disease or disorder associated with elevated PSMA expression, the method comprising:
(a) measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) using a method of any one of embodiments 1-31 or 63-67, and optionally
(b) comparing the measured PSMA expression or predicted tumor specific PSMA expression to a reference.
71. A method of diagnosing a subject as having a disease or disorder associated with elevated PSA expression, the method comprising:
(a) measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total PSA) using a method of any one of embodiments 34-67, and optionally
(b) comparing the measured or predicted PSA expression to a reference.
72. The method of any one of embodiments 68-71, wherein the reference is a predetermined threshold, a measurement from a liquid biopsy sample, a measurement from an imaging test, and/or a normalized value, optionally wherein the reference is a measurement from an imaging test (e.g., PSMA PET SUVmean) or sample obtained from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with a disease or disorder associated with increased PSMA and/or PSA expression.
73. A method of prognosing a subject having a disease or disorder associated with increased PSMA expression, comprising:
(a) measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) using a method of any one of embodiments 1-33 or 63-67, and optionally
(b) comparing the measured PSMA expression or predicted tumor specific PSMA expression to a reference.
74. A method of prognosing a subject having a disease or disorder associated with increased PSA expression, comprising:
(a) measuring or predicting PSA expression (e.g., serum PSA) using a method of any one of embodiments 34-67, and optionally
(b) comparing the measured or predicted PSA expression to a reference.
75. The method of embodiment 73 or 74, wherein the reference is a predetermined threshold, a measurement from a liquid biopsy sample, a measurement from an imaging test (e.g., PSMA PET SUVmean), and/or a normalized value, optionally wherein the reference is a measurement from a liquid biopsy sample or imaging test (e.g., PSMA PET SUVmean) obtained from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with the disease or disorder associated with increased PSMA and/or PSA expression.
76. The method of embodiment 75, wherein the reference is a PSMA expression level measured, a tumor specific PSMA expression level (e.g., PSMA PET SUVmean) predicted, or a tumor specific PSMA expression level (e.g., PSMA PET SUVmean) measured in a cohort of subjects having the disease or disorder associated with increased PSMA expression.
77. The method of embodiment 76, wherein the reference is the median, lower bound of the top tertile, or lower bound of the top quartile value of the PSMA expression level measured, tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) predicted, or tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) measured in the cohort of subjects having the disease or disorder associated with increased PSMA expression; and if the PSMA expression level or predicted tumor specific PSMA expression level in the subject is equal to or greater than the reference, the subject is predicted to have a higher-than- normal risk of experiencing worse than normal disease progression as measured by one or more clinical outcomes.
78. The method of embodiment 76 or 77, wherein:
(a) the PSMA PET SUVmean median is about 4 to about 8, about 5 to about 8, 5 to about 7, about 6 to about 9, about 5, about 6, about 7, or about 8;
(b) the lower bound of the top tertile of PSMA PET SUVmean is about 6 to about 12, about 6 to about 10, about 8 to about 12, about 6, about 7, about 8, about 9, about 10, about 11, or about 12; or
(c) the lower bound of the top quartile of PSMA PET SUVmean is about 6 to about 14, about 6 to about 12, about 8 to about 14, about 8, about 9, about 10, about 11, about 12, about 13, or about 14.
79. The method of any one of embodiments 68-78, wherein the reference is a measurement from a sample taken from the subject at an earlier point in time, optionally wherein: (i) the measurement is from a liquid biopsy sample (e.g., a measurement or prediction obtained using the method of any one of embodiments 1-36),
(ii) a measurement from an imaging test (e.g., PSMA PET SUVmean), or
(iii) the measurement is a serum PSA measurement.
80. The method of any one of embodiments 77-79, wherein the one or more clinical outcomes include (i) overall survival, (ii) time to next treatment, or (iii) progression free survival (e.g., as determined by PSA-PFS (plasma PSA levels) and/or crPFS (clinical or radiological evidence of progression).
81. The method of any one of embodiments 68-80, wherein the disease or indication associated with increased PSMA and/or PSA expression is cancer.
82. The method of embodiment 82, wherein the cancer is prostate cancer, optionally wherein the prostate cancer is mCRPC.
83. The method of embodiment 82, wherein the prostate cancer is PRAD or NEPC.
84. A method of monitoring progression of a disease associated with elevated PSMA expression in a subject, the method comprising, at a first and second point in time:
(a) measuring PSMA expression or predicting tumor specific PSMA expression using the method of any one of embodiments 1-34 or 63-67;
(b) testing whether the subject has elevated PSMA expression or diagnosing the subject using the method of any one of embodiments 68, 70, or 72; or
(c) prognosing the subject using the method of any one of embodiments 73 or 75-79; and
(d) comparing PSMA expression, predicted tumor specific PSMA expression, PSMA expression status, diagnosis, or prognosis for the first and the second time point.
85. A method of monitoring progression of a disease associated with elevated PSA expression in a subject, the method comprising, at a first and second point in time:
(a) measuring or predicting PSA expression using the method of any one of embodiments 34-67;
(b) testing whether the subject has elevated PSA expression or diagnosing the subject using the method of embodiment 69, 71, or 72; or (c) prognosing the subject using the method of any one of embodiments 74, 75, or 79-83; and
(d) comparing the measured or predicted PSA expression, PSA expression status, diagnosis, or prognosis for the first and the second time point.
86. A method of treating a subject having a disease or disorder associated with increased PSMA expression, the method comprising measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) in the subject using the method of any one of embodiments 1-33 or 63-67, and comparing the measured PSMA expression level or predicted tumor specific PSMA expression to a reference, and
(a) if the measured PSMA expression level or predicted tumor specific PSMA expression is equal to or greater than the reference, administering a therapeutic, and
(b) if the measured PSMA expression level or predicted tumor specific PSMA expression is less than the reference, not administering the therapeutic.
87. A method of identifying a subject having a disease or disorder associated with increased PSMA expression that is likely to respond to a therapeutic, the method comprising measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) in the subject using the method of any one of embodiments 1-33 or 63-67, and comparing the measured PSMA expression level or predicted tumor specific PSMA expression to a reference, and
(a) if the measured PSMA expression level or predicted tumor specific PSMA expression is equal to or greater than the reference, identifying the subject as likely to respond to the therapeutic, and
(b) if the measured PSMA expression level or predicted tumor specific PSMA expression is less than the reference, identifying the subject as not likely to respond to the therapeutic.
88. A method of predicting the likelihood that a subject having a disease or disorder associated with increased PSMA expression will respond to a therapeutic, the method comprising measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) in the subject using the method of any one of embodiments 1-33 or 63-67, and comparing the measured PSMA expression level or predicted tumor specific PSMA expression to a reference, wherein
(a) if the measured PSMA expression level or predicted tumor specific PSMA expression is equal to or greater than the reference, the subject is likely to respond to the therapeutic, and
(b) if the measured PSMA expression level or predicted tumor specific PSMA expression is less than the reference, the subject is not likely to respond to the therapeutic.
89. The method of any one of embodiments 86-88, wherein the reference is a predetermined threshold, a measurement from a liquid biopsy sample, a measurement from an imaging test, and/or a normalized value, optionally wherein the reference is a measurement from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with the disease or disorder associated with increased PSMA expression.
90. The method of any one of embodiments 86-89, wherein the reference is a PSMA expression level measured, a tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) predicted, or a tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) measured in a cohort of subjects having the disease or disorder associated with increased PSMA expression.
91. The method of embodiment 90 wherein the reference is the median, lower bound of the top tertile, or lower bound of the top quartile value of the PSMA expression level measured, tumor specific PSMA expression level (e g., PSMA PET SUVmean value) predicted, or tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) measured in the cohort of subjects having the disease or disorder associated with increased PSMA expression.
92. The method of any one of embodiments 86-91, wherein the reference is the median, lower bound of the top tertile, or lower bound of the top quartile value of the PSMA expression level measured, tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) predicted, or tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) measured in the cohort of subjects having the disease or disorder associated with increased PSMA expression; and if the PSMA expression level or predicted tumor specific PSMA expression level in the subject is equal to or greater than the reference, administering the therapeutic; and if the PSMA expression level or predicted tumor specific PSMA expression level in the subject is less than the reference, not administering the therapeutic.
93. The method of embodiment 91 or 92, wherein:
(a) the PSMA PET SUVmean median is about 4 to about 8, about 5 to about 8, 5 to about 7, about 6 to about 9, about 5, about 6, about 7, or about 8;
(b) the lower bound of the top tertile of PSMA PET SUVmean is about 6 to about 12, about 6 to about 10, about 8 to about 12, about 6, about 7, about 8, about 9, about 10, about 11, or about 12; or
(c) the lower bound of the top quartile of PSMA PET SUVmean is about 6 to about 14, about 6 to about 12, about 8 to about 14, about 8, about 9, about 10, about 11, about 12, about 13, or about 14.
94. A method of treating a subject having a disease or disorder associated with increased PSA expression, the method comprising measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total serum PSA) in the subject using the method of any one of embodiments 34-67, and comparing the measured PSA or predicted PSA expression to a reference, and
(a) if the measured PSA or predicted PSA expression is equal to or greater than the reference, administering a therapeutic, and
(b) if the measured or predicted PSA expression is less than the reference, not administering the therapeutic.
95. A method of identifying a subject having a disease or disorder associated with increased PSA expression that is likely to respond to a therapeutic, the method comprising measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total PSA) in the subject using the method of any one of embodiments 33-67, and comparing the measured or predicted PSA expression to a reference, and
(a) if the measured or predicted PSA expression is equal to or greater than the reference, identifying the subject as likely to respond to the therapeutic, and
(b) if the measured or predicted PSA expression is less than the reference, identifying the subject as not likely to respond to the therapeutic. 96. A method of predicting the likelihood that a subject having a disease or disorder associated with increased PSA expression will respond to a therapeutic, the method comprising measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total PSA) in the subject using the method of any one of embodiments 33-67, and comparing the measured or predicted PSA expression to a reference, wherein
(a) if the measured or predicted PSA expression is equal to or greater than the reference, the subject is likely to respond to the therapeutic, and
(b) if the measured or predicted PSA expression is less than the reference, the subject is not likely to respond to the therapeutic.
97. The method of embodiment 94-96, wherein the reference is a predetermined threshold, a measurement from a liquid biopsy sample, and/or a normalized value, optionally wherein the reference is a measurement from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with the disease or disorder associated with increased PSA expression.
98. The method of any one of embodiments 94-97, wherein the reference is a PSA expression that has previously been shown to be predictive of response to the therapeutic and/or previously been shown to be predictive of the presence of a disease that has been shown to respond to the therapeutic.
99. The method of any one of embodiments 94-98, wherein the measured or predicted PSA expression is at least about 4 ng/mL, or at least about 10 ng/mL.
100. The method of any one of embodiments 87-99, wherein the disease or indication associated with increased PSMA or PSA expression is a cancer.
101. The method of embodiment 100, wherein the cancer is prostate cancer, optionally wherein the prostate cancer is mCRPC.
102. The method of embodiment 101, wherein the prostate cancer is PRAD.
103. The method of any one of embodiments 86-102, wherein the therapeutic is a PSMA- targeted therapeutic.
104. The method of embodiment 103, wherein the therapeutic is an ADC (e.g., PSMA- MMAE, MLN2704, ARX517), and/or wherein the therapeutic is a PSMA-targeted radionuclide (e.g., 177Lu-PSMA-617). 105. The method of embodiment 104, wherein the therapeutic is 177Lu-PSMA-617.
106. The method of any one of embodiments 86-105, wherein the therapeutic is administered via one or more intravenous, subcutaneous, intraperitoneal, or intramuscular injections;
107. The method of any one of embodiments 68-106, wherein the subject has previously been diagnosed as having a disease or indication associated with increased PSMA or PSA expression (e.g., a cancer, prostate cancer, mCRPC, and/or PRAD).
108. The method of embodiment 107, wherein the prostate cancer is localized or metastatic.
109. The method of embodiment 107 or 108, wherein the prostate cancer has metastasized to one or more site(s) that include lymph node, bone, lung, and/or liver tissue.
110. The method of any one of embodiments 68-109, wherein the subject has previously been administered one or more (e.g., 2-7, 2-5, 3-4, 1, 2, 3, 4, 5, 6, or 7) systemic therapies for metastatic prostate cancer.
111. The method of any one of embodiments 68-110, wherein the subject has a plasma PSA concentration of 0-2000 ng/mL (e.g., at least about 4 ng/mL, at least about 10 ng/mL, 10-2000 ng/mL, 25-2000 ng/mL, 50-2000 ng/mL, 75-2000 ng/ML, 100-2000 ng/mL, 150-1000 ng/mL, 100-500 ng/mL, or 100-200 ng/mL), optionally wherein the plasma PSA concentration has been determined using the method of any one of embodiments 33-67.
112. A kit comprising reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci, wherein the one or more genomic loci are selected from Tables 1-5.
113. The kit of embodiment 112, wherein the kit comprises reagents for quantifying:
(a) promoter signal (e.g., H3K4me3 modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K4me3 analyte genomic loci in Table 1;
(b) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 1;
(c) DNA methylation for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 MBD analyte genomic loci in Table 1;
(d) enhancer signal (e.g., H3K27ac modifications) at one or more (e.g., all) of genomic loci 1-8 in Table 2;
(e) promoter signal (e.g., H3K4me3 modifications) at genomic locus 9 in Table 2; (f) enhancer signal (e.g., H3K27ac modifications) for 1, 2, 3, or 4 H3K27ac analyte genomic loci in Table 3;
(g) promoter signal (e.g., H3K4me3 modifications) for 1 or 2 H3K4me3 analyte genomic loci in Table 4;
(h) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 4;
(i) promoter signal (e.g., H3K4me3 modifications) at chrl 1:49,228,902-49,230,855;
(j) enhancer signal (e.g., H3K27ac modifications) at chrl 1 :49, 229, 019-49, 230, 275; or
(k) any combination of (a)-(j).
114. The kit of embodiment 112 or 113, wherein the kit comprises one or more antibodies for use in ChlP-seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac-modified histones.
115. The kit of any one of embodiments 112-114, wherein the kit comprises one or more methyl-binding domains for use in MBD-seq or wherein the kit comprises one or more antibodies that bind methylated DNA for use in MeDIP.
116. The kit of any one of embodiments 112-115, wherein the kit comprises reagents for isolation of cell-free DNA (cfDNA) or ctDNA from a liquid biopsy sample.
117. The kit of any one of embodiments 112-116, wherein the kit comprises reagents for library preparation for sequencing.
118. The kit of any one of embodiments 112-117, wherein the kit comprises reagents for sequencing.
119. The kit of any one of embodiments 112-118, wherein the kit comprises instructions for determining if a subject has a disease or disorder associated with increased PSMA (e.g., a cancer, prostate cancer, or mCRPC).
120. A non-transitory computer readable storage medium encoded with a computer program, wherein the program comprises instructions that when executed by one or more processors cause the one or more processors to perform operations to perform the method of any one of embodiments 1-119. 121. A computer system comprising a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform operations to perform the method of any one of embodiments 1-111.
122. A system for determining the disease or disorder status of a subject, the system comprising a sequencer configured to generate a sequencing data set from a sample; and a non- transitory computer readable storage medium of embodiment 120 and/or a computer system of embodiment 121.
123. The system of embodiment 122, wherein the sequencer is configured to generate a Whole Genome Sequencing (WGS) data set from the sample.
124. The system of embodiment 122 or 123, further comprising a sample preparation device configured to prepare the sample for sequencing from a biological sample, optionally a liquid biopsy sample.
125. The system of embodiment 124, wherein the sample preparation device comprises reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci in cell- free DNA (cfDNA) or ctDNA from the biological sample, optionally the liquid biopsy sample.
126. The system of embodiment 125, wherein the one or more genomic loci are selected from Tables 1-5.
127. The system of any one of embodiments 122-126, wherein the device comprises reagents for quantifying:
(a) promoter signal (e.g., H3K4me3 modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K4me3 analyte genomic loci in Table 1;
(b) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 1;
(c) DNA methylation for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 MBD analyte genomic loci in Table 1;
(d) enhancer signal (e.g., H3K27ac modifications) at one or more (e.g., all) of genomic loci 1-8 in Table 2;
(e) promoter signal (e.g., H3K4me3 modifications) at genomic locus 9 in Table 2; (f) enhancer signal (e.g., H3K27ac modifications) for 1, 2, 3, or 4 H3K27ac analyte genomic loci in Table 3;
(g) promoter signal (e.g., H3K4me3 modifications) 1 or 2 H3K4me3 analyte genomic loci in Table 4;
(h) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 4;
(i) promoter signal (e.g., H3K4me3 modifications) at chrl 1:49,228,902-49,230,855;
(j) enhancer signal (e.g., H3K27ac modifications) at chrl 1 :49, 229, 019-49, 230, 275; or
(k) any combination of (a)-(j).
128. The system of any one of embodiments 122-127, wherein the reagents comprise one or more antibodies for use in ChlP-seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac-modified histones.
129. The system of any one of embodiments 122-128, wherein the reagents comprise one or more methyl-binding domains for use in MBD-seq.
130. The system of any one of embodiments 122-129, wherein the device comprises reagents for isolation of cell-free DNA (cfDNA) or ctDNA from the biological sample, optionally the liquid biopsy sample.
131. The system of any one of embodiments 122-130, wherein the device comprises reagents for library preparation for sequencing.
132. The system of any one of embodiments 122-131, wherein the sequencer comprises reagents for sequencing.
EXAMPLES
[0422] The present Examples demonstrate the identification and use of differentially modified and/or differentially accessible genomic loci in cfDNA in plasma samples obtained from subjects with mCRPC. Loci identified in the present example can be useful, e.g., for detecting mCRPC, characterizing mCRPC disease severity, monitoring mCRPC, prognosing subjects with mCRPC, and informing patient treatment decisions. Example 1: Materials and Methods
[0423] The present Example describes the materials and methods that were used to generate sequencing data that was then used in Examples 2 and 3 to identify differentially modified genomic loci and create models to predict PSMA PET SUVmean.
Materials
Plasma samples
[0424] Plasma samples were prepared from whole blood collected in EDTA blood collection tubes or Streck cell-free DNA BCT with 4-6 hours of collection and plasma was stored at -80°C until use. Whole blood was obtained from metastatic Castration-Resistant Prostate Cancer (mCRPC) patients under a protocol approved by an IRB. Patients had previously been determined to have mCRPC. Informed content was obtained in each case and samples were de-identified.
Methods
Chromatin immunoprecipitation (ChIP)
[0425] Chromatin immunoprecipitation (ChIP) for histone marks (H3K4me3 and H3K27ac) in plasma samples can be performed using methods similar to those previously described in Baca et al. “Liquid biopsy epigenomic profiling for cancer subtyping.” Nature medicine 29.11 (2023): 2737-2741, which is incorporated by reference herein in its entirety. Briefly, about 1 mL frozen plasma was thawed and then prepared for ChIP. The thawed plasma was incubated with antibodies that bind H3K4me3 modifications or H3K27ac modifications that were previously conjugated to magnetic epoxy beads (Invitrogen) with constant mild shaking overnight. The beads were then washed and rinsed. Sequencing libraries were generated from purified immunoprecipitated sample DNA and then sequenced.
Methylated DNA enrichment
[0426] Enrichment of DNA methylation was performed on DNA extracted from human plasma samples using the EpiMark® Methylated DNA Enrichment Kit (E2600S, available from New England Biolabs) following the manufacturer’s protocol. Briefly, cfDNA libraries were prepared and adaptors ligated. Then, the EpiMark® capture reagent was applied to each library sample following the manufacturer’s protocol. Enriched DNA libraries were amplified and sequenced.
ChlP-seq and DNA methylation data analysis
[0427] ChlP-sequencing reads and MBD-sequencing reads were aligned to the human genome build hgl9 using the Burrows-Wheeler Aligner (BWA) version 0.7.15. Non-uniquely mapping and redundant reads were discarded. MACS v2.2.7.1 was used for peak calling with a q- value (FDR) threshold of 0.01. Data quality was evaluated by a variety of measures, including total peak number, FRiP (fraction of reads in peak) score, number of high-confidence peaks (enriched > ten-fold over background), and percent of peak overlap with “blacklist” DHS peaks derived from the ENCODE project (Amemiya et al., Sci Rep (2019) 9(1):9354). Peaks were assessed for overlap with gene features and CpG islands using annotatr. IGV was used to visualize normalized read counts at specific genomic loci. Overlap of peaks was assessed using BEDTools and the GenomicRanges package in Bioconductor. Peaks were considered overlapping if they shared one or more nucleotide.
Example 2: Determination of Tumor PSMA Expression in Prostate Cancer From Blood Using a Novel Epigenomic Liquid Biopsy Platform
[0428] PSMA (Prostate-Specific Membrane Antigen), a highly expressed cell surface protein in prostate cancer encoded by FOLH1, has emerged as a pivotal biomarker for both diagnosis and therapeutic targeting in patients with advanced disease. It is a target of the FDA approved radioligand therapy Pluvicto (177Lu-PSMA-617) in metastatic castration-resistant prostate cancer (mCRPC), and a number of additional radioimmune conjugate therapies are in development.
[0429] Treatment eligibility currently requires collecting a PSMA PET SUVmean measurement, a PET scan quantification of the level of PSMA positivity in tumor lesions throughout the body. With therapeutic strategies in development targeting an array of cell surface proteins, there is an emerging unmet need to quantify tumor drug target expression minimally invasively. [0430] The present Example provides data demonstrating that technologies described herein can be used as an accurate, minimally invasive readout of tumor PSMA expression in mCRPC. The present Example also demonstrates that technologies provided herein can be used to monitor the transcription state of tumor cells in a patient, and can also accurately predict PSMA PET SUVmean, which can be useful, e.g., for prognostic prediction and as a companion diagnostic for PSMA radioimmune conjugates (RICs) (e.g., RICs approved or in development).
Methods
[0431] Schematics summarizing the method used to characterize the epigenome of patients in the present Example are provided in Figs. 1(A) and 1(B). Plasma samples were collected for 50 men previously diagnosed with mCRPC. PET images were collected for 29 of the 50 men at the time of plasma collection, and the PET images were analyzed to quantify PSMA PET SUVmean.
[0432] Provided in the below Table B is information regarding the 29 subjects studied in the present Example.
Table B: Patient Characteristics
Tile creation and filtering
[0433] For each patient sample and analyte, MACS2 (—nolambda) was used to determine regions of the genome enriched for epigenomic signal. Consensus peak maps were then created for each analyte by merging maps across all patients (requiring a region to be covered by at least 3 patients’ peak maps) and removing regions known to be artifactual/technical (ENCODE blacklist). For each analyte’s consensus peak map, tiling across their regions was then performed using a 500 bp window, with a 100 bp step. Tiles were then analyzed to identify tiles having high-confidence mCRPC signal. Finally, high-confidence tiles were merged based on genomic coordinate overlaps. This set of merged tiles are hereafter referred to as the “peaks”. Fragments within the peak regions (above local background) were quantified, normalized for read-depth, log2 -transformed (with a pseudo count of 0.01, and quantile normalized). For model validation this process was performed in a leave-one-out cross-validation schema.
PSMA PET SUVmean prediction
[0434] The peaks with high-confidence mCRPC signal were used to predict PSMA PET SUVmean. First, quantile-normalized log2 quantifications were averaged to yield a mean value. A linear regression was then used to model log2(PSMA PET SUVmean) using two coefficients: 1) the above-mentioned value computed from FOLH1 H3K27ac and H3K4me3 signal, and 2) the sample’s corresponding estimated logit ctDNA fraction. Model training was performed only on samples with ctDNA% > 3, and validation was assessed in a LOO CV schema.
Results
[0435] A genome wide analysis of differential epigenomic signal between healthy volunteers and mCRPC patients was performed using the methods described above. Fold enrichment and significance was calculated using DESeq with Benjamini-Hochberg p-value correction to confirm detection of known prostate cancer biology. Genes associated with the differentially modified loci were determined by the nearest TSS to statistically significant peak of interest. [0436] Results of the genome wide analysis are shown in Fig. 2(A). As shown in Fig 2(A), differential analysis identified a number of regions having changes in epigenetic modifications in mCRPC subjects as compared to healthy subjects, including 15,174 loci with increased enhancer signal, 10,121 loci with decreased enhancer signal, 10,804 loci with increased promoter signal, 9,518 loci with decreased promoter signal, 41,198 loci with increased DNA methylation, and 9,238 loci with decreased DNA methylation. Among the genes associated with differential modifications were multiple prostate-cancer specific signals, including H0XB13, KLK2, KLK3, and SPDEF. The detection of epigenetic modifications associated with multiple prostate-cancer specific signals demonstrates that technologies provided herein can be used to identify biologically relevant changes in the epigenome, that are reflective of transcription activity in tumor cells in a subject.
[0437] A genome wide analysis correlating epigenomic signal to PSMA PET SUVmean quantifications was also performed. For each analyte, robust mCRPC-specific epigenomic features were identified and normalized to reduce technical variability and dependence on ctDNA fraction. Each feature was then tested for its association with PSMA PET SUV mean VI cl linear regression. Results are shown in Fig. 2(B). Genomic loci most highly associated with PSMA PET SUVmean signal for each of H3K27AC, H3K4me3, and DNAme are provided in the below Table 1.
Table 1: Genomic Loci With Highest Association to PSMA PET SUVmean for H3K27ac, H3K4me3, and DNAme.
[0438] From this analysis, enhancer signal at the FOLH1 locus was identified as being most highly associated with PSMA PET SUVmean.
[0439] Fig. 4 provides exemplary epigenomic maps for H3K4me3 (promoter), H3K27ac (enhancers), and methylated DNA (DNAme) at the FOLH1 locus in subjects with low PSMA PET signal (defined as being below the median SUVmean of subjects tested), high PSMA PET signal (defined as being above the median SUVmean of subjects tested), and healthy subjects. Epigenetic signal at the loci listed in the Table 2 (below) were found to provide particularly robust mCRPC-specific signal.
Table 2: Loci with particularly robust mCRPC-specific signal.
[0440] The loci in Table 2 were used to train a machine learning (ML) model to predict PSMA PET SUVmean. Samples were first split into training and validation cohorts, which were matched for ctDNA% and PSMA PET SUVmean distributions. Characteristics of the training and validation cohorts are shown in the below Table C.
Table C: Characteristics of Training and Validation Cohorts: [0441] All prostate cancer specific regions of the genome were normalized, allowing for per-experiment normalization of tumor specific regions and aggregated (aggregation can be performed, e.g., using a weighted sum product).
[0442] Performance was assessed via Pearson correlation in both a leave-one-out (LOO) cross-validation (CV) setting within the training cohort, as well as the held-out validation cohort using a final model trained on all data from the training cohort.
[0443] The LOOCV schema entailed:
(1) Leaving one sample out of N training samples;
(2) Empirically determining regions of robust FOLH1 enhancer/promoter signal;
(3) Training a machine learning (ML) model to predict PSMA PET SUVmean from enhancer/promoter signal;
(4) Predicting the left-out sample; and
(5) Repeating N times.
[0444] The validation schema entailed:
(1) Using all samples in training cohort;
(2) Empirically determining regions of robust FOLH1 enhancer/promoter signal;
(3) Training an ML model to predict PSMA PET SUVmean from enhancer/promoter signal;
(4) Predicting the validation cohort; and
(5) Repeating N times.
[0445] Results from the training cohort LOOCV and validation cohort analysis are shown in Fig. 5. A positive correlation was observed between predicted PSMA PET SUVmean values and observed PSMA PET SUVmean values, demonstrating that epigenomic cfDNA profiling can provide an accurate surrogate of tumor PSMA expression in men with mCRPC, and can be useful for, e.g., detecting prostate cancer, characterizing prostate cancer in a subject, monitoring progression of prostate cancer, informing treatment selection, and optimizing patient selection.
[0446] Among other things, the present Example provides a set of loci and analytes that are particularly useful for predicting PSMA expression levels. Surprisingly, it was found that monitoring epigenetic modifications at one or more of the small set of loci identified in Table 2 provided superior PSMA PET SUVmean predictive ability as compared to use of genome-wide epigenetic signal. Moreover, the ability of an ML model with loci identified in the present Example to predict PSMA PET SUVmean is a significant advancement in the field, as loci previously identified in the region were not found to be PRAD-specific/robust (data not provided).
Example 3: Association of Predicted PSMA PET Scores and Clinical Outcomes
[0447] The present Example provides results from a study testing the correlation between a PSMA scoring algorithm described herein and patient health outcomes.
[0448] PSMA PET SUVmean values were predicted for 84 samples, include 72 samples from subjects administered Pluvicto. Samples were then screened for a ctDNA fraction of > 0.03, resulting in 45 samples. The 45 samples were then split into tertiles based on PSMA PET SUVmean prediction scores and a logrank test was performed for 5 time-to-event clinical outcomes: PSA-PFS, crPFS, Time to Next Treatment, and Overall Survival.
[0449] Results are shown in Figs. 6(A)-(D), which demonstrate a clear difference in all 4 clinical outcomes for subjects in different tertiles. The HR for top vs bottom tertiles was highly significant for all clinical outcomes. Thus, these results demonstrate that technologies provided herein can be useful, e.g., for predicting clinical outcomes and selecting subjects likely to respond to a treatment (e g., a radioligand treatment (e.g., Pluvicto)).
[0450] The same analysis was performed for patients in the top tertile vs. the lower and middle tertiles for PSMA PET SUVmean (actual) and predicted PSMA PET SUVmean for 24 subjects with ctDNA > 3%. Results are shown in Figs. 7(A)-(H) and demonstrate that clinical outcomes of subjects segmented by PSMA PET SUVmean actual values do not significantly differ from clinical outcomes of subjects segmented by PSMA PET SUV predicted values (comparing Harrell’s C-statistics, PMID: 6878708, P > 0.5 for all clinical outcomes). Thus, the predicted PSMA PET SUVmean values are a good proxy for PSMA PET SUVmean measurements, and can be used for similar purposes (including, e.g., disease monitoring and characterization, and therapeutic selection). Example 4: Predicting PSA Expression
[0451] The present Example provides data showing that technologies described herein can be used to measure PSA serum levels using epigenetic modifications measured in plasma samples.
[0452] A model for predicting PSA expression was generated using prostate cancer tumor biopsies. For each biopsy, genome wide maps of H3K4me3 and H3K27ac modifications were obtained using ChlP-seq. PSA expression was also determined for each biopsy using RNA- seq data. Simulated plasma samples were then generated by serially diluting the tumor biopsy sequencing data in silico with sequencing data from healthy plasma samples to create samples with a range of ctDNA%. Regions proximal to KLK3 (i.e., within KLK3 and +/- 200 kB of the transcript encoding portion of KI.K3) JVCQ identified that had epigenetic modification signal that correlated with PSA expression. These regions were then used to build a model for predicting PSA expression. The loci used in the present Example to measure PSA expression are provided in Table 3, below.
Table 3: Exemplary Genomic Loci Associated with PSA Expression
[0453] The model for predicting PSA expression was then applied to plasma samples obtained from subjects with prostate cancer to predict PSA expression level, and these predicted expression values were compared to serum PSA measurements in matched samples. Results of this comparison are shown in Fig. 8. As shown, predicted PSA expression was shown to correlate with measured serum PSA, demonstrating that technologies described herein can be used to measure serum PSA.
Example 5: Further PSMA PET SUVmean Predictions in Prostate Cancer Patients [0454] The present Example provides further data demonstrating that technologies provided herein can be used predict PSMA PET SUVmean.
[0455] First, a model for measuring PSMA expression was generated using publicly available prostate tumor biopsy H3K4me3, H3K27Ac, and RNA-seq data. For each biopsy, genome wide maps of H3K4me3 and H3K27ac, and DNAme modifications were obtained. PSMA expression was also measured for each biopsy using RNA-seq.
[0456] Simulated plasma samples were then generated by serially diluting prostate cancer biopsy data hi silica with sequencing data from healthy plasma samples to create samples with a range of ctDNA%. Regions proximal to F0LH1 (within the transcript encoding portion of F0LH1 and +/- 200 kB of the transcript encoding portion of FOLHF) were then identified that had epigenetic modification signal that correlated with PSMA expression (as determined using RNA-seq). These regions were then used to build a model for predicting PSMA expression. The loci identified using this approach are provided in Table 4, below.
Table 4: Exemplary Genomic Loci Associated with PSMA Expression
[0457] The biopsy generated model was then applied to plasma samples obtained from patients with prostate cancer to obtain predicted PSMA expression values. These predicted values were compared to measured PSMA PET SUVmean in the same patients. Results are shown in Fig. 9(A). As shown, PSMA expression predicted using a biopsy model was shown to correlate with PSMA PET SUVmean signal, demonstrating that technologies described herein can be used to predict PSMA PET SUV mean signal.
[0458] Fig. 9(B) provides another characterization of the model constructed using the approach described in Examples 2 and 3. As shown, the model generated in Example 3 (trained using PSMA PET SUVmean and epigenetic modifications from patient plasma samples) provided a model with improved accuracy as compared to a model generated using biopsy data. [0459] Next, sequencing data from plasma samples of patients with prostate cancer were diluted in silica with sequencing data from healthy subjects to generate in silico plasma samples having a range of ctDNA% values. PSMA PET SUVmean was then predicted for each in silico sample using the biopsy model and the model trained using PSMA PET SUVmean (described in Example 3) and Pearson’s coefficients were determined. Results are shown in Fig. 9(C). As shown, both models showed a strong Spearman correlation with PSMA PET SUVmean signal at clinically relevant concentrations, with the PSMA PET SUVmean trained model providing higher Spearman correlation at ctDNA% higher than ~2%.
Example 6: Identification of promoter and enhancer epigenomic activation signals at F0LH1
[0460] The present Example provides further regions proximal to FOLH1 with H3K4me3 and H3K27ac signal that correlate with PSMA expression. In the present Example, promoter and enhancer signal were identified in plasma samples from patients with lung cancer (SCLC). In some embodiments, the loci identified in the present Example can be used to measure or predict PSMA expression in prostate cancer.
[0461] Plasma samples (from cancer patients and healthy volunteers) were collected from commercial biobanks and stored at -80°C until use. The percentage of ctDNA in the plasma samples from cancer patients was assessed using ichorCNA, which estimates the percentage of ctDNA in a sample probabilistically (see Adalsteinsson et al., Nat Commun (2017) 8(1): 1324, the entire contents of which are incorporated herein by reference). Plasma samples from cancer patients with at least 5.5% ctDNA were used in the present Example.
[0462] To identify promoter (H3K4me3) epigenomic activation signals a. FOLHl, we defined a peak within +/- Ikb of the transcription site (TSS) of FOLH1. To identify enhancer (H3K27ac) epigenomic activation signals at FOLH1, we defined a peak within +/- lOkb of the transcription site (TSS) of FOLHl. As a control, H3K4me3 and H3K27ac epigenomic activation signals were measured at housekeeping genes using a similar approach.
[0463] To identify peaks, a consensus map of all peaks (by MACS) was created by taking the union of all base pairs covered by any peak in any of the cancer patient or healthy volunteer plasma samples. This set of regions was then combined with the set of “regions of interest” defined above to produce a set of “enriched regions”. The number of sequencing fragments (reads) overlapping each enriched region (by at least 1 bp) were quantified for each analyte. Counts of reads in all enriched regions between experiments (any region called a peak in at least one sample) were quantile normalized together. Quantile normalized counts of reads in the regions of interest were corrected for local ChlP-seq background to improve signal-to-noise. Promoter and enhancer epigenomic activation signals were ctDNA corrected independently. To correct for ctDNA%, we used the ichorCNA estimated values for each sample and regressed the log of the normalized, corrected counts against logit-transformed estimated ctDNA% with standard linear regression, and then subtracted the estimated percent of each count due to ctDNA% based on its regression weight. Corrected enhancer and promoter counts were summed for F0LH1 to produce an integrated activation score. The mean and standard-deviation of the summed enhancer and promoter counts within the healthy volunteers were used to calculate a z- score for each patient sample, which was then logged and 0-1 scaled for the final activation score.
[0464] Genomic coordinates of an exemplary H3K4me3 peak and an exemplary H3K27ac peak are provided in Table 5.
Table 5: Exemplary genomic coordinates of H3K4me3 and H3K27ac peaks for FOLH1.
[0465] Figs. 10(A) and (B) shows a trend line and confidence intervals for promoter signal (H3K4me3) and enhancer signal (H3K27ac), respectively, based on ctDNA% for PSMA.
Example 7: Association of Predicted PSMA SUVmean and Clinical Outcomes
[0466] The present Example provides further clinical trial data demonstrating that technologies described herein can predict responsiveness to treatment with a PSMA-targeted therapy (Pluvicto in the present Example). In particular, the present Example provides data demonstrating that technologies provided herein can predict clinicoradiographic (CR) PFS, which provides a holistic assessment of progression by a clinician based on the totality of clinical data (including radiographic results). Without wishing to be bound by theory, this metric may more accurately reflect response to treatment with a PSMA-targeted agent (compared to PSA- PFS, time to next treatment (TTNT), and/or overall survival (OS).
[0467] Plasma samples and PSMA PET SUVmean measurements were obtained from an expanded cohort of subjects as compared to Example 3 (>3% ctDNA, N=77). PSMA PET SUVmean was predicted for each patient using the models described in Examples 2 and 3.
[0468] Subjects were divided into tertiles based on predicted PSMA PET SUVmean values. Fig. 11 shows a comparison of CR PFS outcomes for subjects in (i) the bottom and middle tertiles of PSMA PET SUVmean values as compared to (ii) subjects in the top tertile. As shown, technologies described herein were shown to be strong predictors of responsiveness of a PSMA-targeted therapy.
[0469] The prognostic ability of PSMA PET SUVmean was then compared to ctDNA%, another cfDNA-based method. ctDNA% was measured for each patient, and patients were split into tertiles on the basis of ctDNA%. Outcomes for four clinical trial metrics (PSA, time to next treatment, CR PFS, and overall survival) were compared for patients having a ctDNA% in the top tertile vs. patients having a ctDNA% in the middle and bottom tertiles. Results are shown in Figs. 12(A)-(D). As shown, ctDNA% was predictive of each of the clinical trial outcomes tested. Predicted PSMA PET SUVmean was also shown to predict patient response to treatment, (see, e.g., Fig. 11, showing an HR of 0.27 for predicted PSMA PET SUVmean). This data demonstrates that technologies described herein, which use epigenetic modifications to predict PSMA PET SUVmean, can provide a predictor of responsiveness to a PSMA-targeted agent.
OTHER EMBODIMENTS
[0470] It will be appreciated that the scope of the present disclosure is to be defined by that which may be understood from the disclosure and claims rather than by the specific embodiments that have been presented by way of example. Elements described with respect to one aspect or embodiment of the present disclosure are also contemplated with respect to other aspects or embodiments of the present disclosure. For example, elements of claims that depend directly or indirectly from a certain independent claim presented herein serve as support for those elements being presented in additional dependent claims of one or more other independent claims. Throughout the description, where compositions or methods are described as having, including, or comprising specific elements, it is to be understood that compositions or methods that consist essentially of, consist of, or do not comprise the recited elements are likewise hereby disclosed. All references cited herein are hereby incorporated by reference.

Claims

CLAIMS What is claimed is:
1. A method of measuring PSMA expression in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free
DNA (cfDNA) or circulating tumor DNA (ctDNA) from a liquid biopsy sample, obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility,
(iii) binding of one or more transcription factors, and/or
(iv) DNA methylation.
2. The method of claim 1, wherein the method measures PSMA expression in one or more tumors in a subject.
3. The method of claim 1 or 2, wherein the PSMA expression is cell surface expression of PSMA.
4. The method of any one of claims 1-3, wherein the PSMA expression is tumor cell specific, cell surface expression of PSMA.
5. A method of predicting tumor specific PSMA expression (e.g., predicting PSMA expression measurements determined using (i) an imaging procedure, (ii) a radioligand, and/or (iii) PSMA PET imaging (e.g., PSMA PET SUVmax or PSMA PET SUVmean)) in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) or ctDNA from a liquid biopsy sample, obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility,
(iii) binding of one or more transcription factors, and/or (i v) DN A m ethyl ati on .
6. The method of any one of claims 1-5, wherein the one or more histone modifications are quantified using a histone modification assay that measures one or more of H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, H3K4me3, and pan-acetylation.
7. The method of claim 6, wherein the histone modification assay detects one or more H3K4me3 modifications.
8. The method of claim 6, wherein the histone modification assay detects one or more H3K27ac modifications.
9. The method of any one of claims 1-8, wherein the histone modification assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
10. The method of any one of claims 1-9, wherein chromatin accessibility is quantified using a chromatin accessibility assay selected from ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde-Assisted Isolation of Regulatory Elements sequencing), MNase-seq (Micrococcal Nuclease digestion with sequencing), a DNase hypersensitivity assay, and a fragmentomics assay.
11. The method of any one of claims 1-10, wherein the binding of one or more transcription factors is quantified using a transcription factor binding assay.
12. The method of claim 11, wherein the transcription factor binding assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
13. The method of any one of claims 1-12, wherein DNA methylation is quantified using Bisulfite sequencing (BS-Seq), Whole Genome Bisulfite Sequencing (WGBS), Methylated DNA ImmunoPrecipitation sequencing (MeDIP-seq), or Methyl-CpG-Binding Domain sequencing (MBD-seq).
14. The method of any one of claims 1-13, comprising quantifying two or more of the following, each at one or more genomic loci in cell-free DNA (cfDNA) or ctDNA from a liquid biopsy sample obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility,
(iii) transcription factor binding, and/or
(iv) DNA methylation.
15. The method of claim 14, comprising quantifying two or more histone modifications.
16. The method of claim 15, comprising quantifying H3K4me3 and H3K27ac modifications.
17. The method of claim 14, comprising quantifying one or more histone modifications and
DNA methylation.
18. The method of claim 17, comprising quantifying (i) H3K4me3 and/or H3K27ac modifications and (ii) DNA methylation.
19. The method of claim 18, comprising quantifying H3K4me3 modifications, H3K27ac modifications, and DNA methylation.
20. The method of any one of claims 1-19, wherein an increase of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at the one or more genomic loci as compared to a reference indicates that the subject has increased PSMA expression (e.g., increased as compared to a healthy subject).
21. The method of any one of claims 1-20, comprising quantifying one or more prostate cancer specific markers (e.g., PSA).
22. The method of any one of claims 1-21, comprising quantifying one or more histone modifications and/or DNA methylation at one or more prostate cancer specific marker genes or regulatory regions thereof (e.g., one or more promoters and/or enhancers of one or more prostate cancer specific marker genes).
23. The method of claim 21 or 22, wherein the one or more prostate cancer specific marker genes comprise HXB13, KLK2, KLK3, SPDEF, or FOLH1, or any combination thereof.
24. The method of any one of claims 1-23, comprising quantifying one or more histone modifications and/or DNA methylation for one or more of AMN, ARHGEF37, C4orf36, CADM1, CCDC175, CDC7, CLSTN1, COL5A1, EDNRA, FOLH1, GALR3, MED13L, MICB, NDRG3, NEDD1, NPAS2, NPVF, OLFM1, PCBP4, PROZ, PRRG3, RREB1, SCUBE3, SERPINA5, SNRPF, SORCS3, ST8SIA5, TEX19, TMEM 132B. or TTC29 or any combination thereof, or one or more regulatory regions of any one of the foregoing (e.g., one or more promoter and/or enhancer regions of AMN, ARHGEF37, C4orf36, CADM1, CCDC175, CDC7, CLSTN1, COL5AI, EDNRA, FOLH1, GALR3, MED13L, MICB, NDRG3, NEDD1, NPAS2, NPVF, 0LFM1, PCBP4, PROZ, PRRG3, RREB1, SCUBE3, SERPINA5, SNRPF, SORCS3, ST8SIA5, TEX19, TMEM132B, or TTC29, or any combination thereof).
25. The method of claim 24, comprising quantifying: a) promoter signal (e g., H3K4me3 signal) at one or more promoter regions of C4orf36, CADM1, CDC7, COL5A1, EDNRA, MED13L, NEDD1, PROZ, SNRPF, TEXJ9, or any combination thereof; b) enhancer signal (e.g., H3K27ac signal) at one or more enhancer regions of ARHGEF37, CLSTN1, F0LH1, NDRG3, NPAS2, NPVF, 0LFM1, RREB1, SCUBE3, or TTC29, or any combination thereof; c) DNA methylation of AMN, CCDC175, GALR3, MICB, PCBP4, PRRG3, SERPINA5, SORCS3, ST8SIA5, TMEM 132B, or any combination thereof.
26. The method of any one of claims 1-25, wherein the method comprises quantifying:
(a) promoter signal (e.g., H3K4me3 modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K4me3 analyte genomic loci in Table 1;
(b) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 1;
(c) DNA methylation for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 MBD analyte genomic loci in Table 1; or
(d) or any combination of (a)-(c).
27. The method of any one of claims 1-26, wherein the method comprises:
(a) quantifying enhancer signal (e.g., H3K27ac modifications) at one or more (e.g., all) of genomic loci 1-8 in Table 2;
(b) quantifying promoter signal (e.g., H3K4me3 modifications) at genomic locus 9 in Table 2; or
(c) a combination of (a) and (b).
28. The method of any one of claims 1-25, wherein the method comprises quantifying:
(a) promoter signal (e.g., H3K4me3 modifications) for 1 or 2 H3K4me3 analyte genomic loci in Table 4;
(b) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 4; (c) or a combination of (a) and (b).
29. The method of any one of claims 1-28, wherein the method comprises quantifying (a) promoter signal (e.g., H3K4me3 modifications) at chrl 1 :49,228,902-49,230,855; and/or (b) enhancer signal (e.g., H3K27ac modifications) at chrl 1 :49, 229, 019-49, 230, 275.
30. The method of any one of claims 1-29, further comprising:
(a) aggregating promoter signal (e g., H3K4me3 modifications) for one or more genomic loci;
(b) aggregating enhancer signal (e.g., H3K27ac modifications) for one or more genomic loci; or
(c) a combination of (a) and (b).
31. The method of claim 30, wherein the aggregated promoter signal and aggregated enhancer signal are aggregated.
32. The method of claim 30 or 31, wherein the promoter signal and enhancer signal are normalized prior to aggregating (e.g., normalized based on sequence read depth or ctDNA fraction).
33. The method of any one of claims 1-32, wherein:
(i) the subject has previously been diagnosed with a disease or condition that is associated with increased PSMA expression, optionally wherein the disease or condition that is associated with increased PSMA expression is prostate cancer; and/or
(ii) the one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and DNA/or DNA methylation is quantified before administering a PSMA-targeted agent.
34. A method of measuring PSA expression in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) or circulating tumor DNA (ctDNA) from a liquid biopsy sample, obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility,
(iii) binding of one or more transcription factors, and/or
(iv) DNA methylation.
35. A method of predicting PSA expression in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free
DNA (cfDNA) or circulating tumor DNA (ctDNA) from a liquid biopsy sample, obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility,
(iii) binding of one or more transcription factors, and/or
(iv) DNA methylation.
36. The method of claim 34 or 35, wherein the PSA expression is or comprises serum PSA.
37. The method of any one of claims 34-36, wherein the method measures or predicts PSA expressed by one or more cancer cells in the subject.
38. The method of any one of claims 34-37, wherein the method measures or predicts serum concentration of total PSA.
39. The method of any one of claims 35-38, wherein the method predicts PSA expression as determined using an assay that (a) utilizes one or more antibodies that bind PSA (e.g., an ELISA assay) and/or (b) measures PSA enzymatic activity.
40. The method of any one of claims 34-39, wherein the one or more histone modifications are quantified using a histone modification assay that measures one or more of H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, H3K4me3, and panacetylation.
41. The method of claim 40, wherein the histone modification assay detects H3K4me3 modifications and/or H3K27ac modifications.
42. The method of any one of claims 34-41, wherein the histone modification assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
43. The method of any one of claims 34-42, wherein chromatin accessibility is quantified using a chromatin accessibility assay selected from ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde-Assisted Isolation of Regulatory Elements sequencing), MNase-seq (Micrococcal Nuclease digestion with sequencing), a DNase hypersensitivity assay, and a fragmentomics assay.
44. The method of any one of claims 34-43, wherein the binding of one or more transcription factors is quantified using a transcription factor binding assay.
45. The method of claim 44, wherein the transcription factor binding assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
46. The method of any one of claims 34-45, wherein DNA methylation is quantified using Bisulfite sequencing (BS-Seq), Whole Genome Bisulfite Sequencing (WGBS), Methylated DNA ImmunoPrecipitation sequencing (MeDIP-seq), or Methyl-CpG-Binding Domain sequencing (MBD-seq).
47. The method of any one of claims 34-46, comprising quantifying two or more of the following, each at one or more genomic loci in cell-free DNA (cfDNA) or ctDNA from a liquid biopsy sample obtained or derived from the subject:
(i) one or more histone modifications,
(ii) chromatin accessibility,
(iii) transcription factor binding, and/or
(iv) DNA methylation.
48. The method of claim 47, comprising quantifying two or more histone modifications.
49. The method of claim 48, comprising quantifying H3K4me3 modifications.
50. The method of claim 48, comprising quantifying H3K27ac modifications.
51. The method of claim 47, comprising quantifying one or more histone modifications and
DNA methylation.
52. The method of claim 51, comprising quantifying (i) H3K4me3 and/or H3K27ac modifications and (ii) DNA methylation.
53. The method of claim 52, comprising quantifying H3K4me3 modifications, H3K27ac modifications, and DNA methylation.
54. The method of any one of claims 34-53, wherein an increase of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at the one or more genomic loci as compared to a reference indicates that the subject has increased PSA expression (e.g., increased as compared to a healthy subject).
55. The method of any one of claims 34-54, wherein the method comprises:
(i) quantifying enhancer signal (e.g., H3K27ac modifications) at one or more loci within 200 kB of a KLK3 gene;
(ii) quantifying enhancer signal (e.g., H3K27ac modifications) at one or more loci within 200 kB of a KLK3 gene;
(iii) quantifying DNA methylation at one or more loci within 200 kB of a KLK3 gene; or
(iv) any combination of (i)-(iii).
56. The method of any one of claims 34-55, wherein the method comprises quantifying enhancer signal (e.g., H3K27ac modifications) at one or more (e.g., all) genomic loci in Table 3.
57. The method of any one of claims 34-56, comprising:
(a) aggregating promoter signal (e.g., H3K4me3 modifications) at the one or more genomic loci;
(b) aggregating enhancer signal (e.g., H3K27ac modifications) at the one or more genomic loci; or
(c) a combination of (a) and (b).
58. The method of claim 57, wherein the aggregated promoter signal and aggregated enhancer signal are aggregated.
59. The method of claim 57 or 58, wherein the promoter signal and enhancer signal are normalized prior to aggregating (e.g., normalized based on sequence read depth or ctDNA fraction).
60. The method of any one of claims 34-59, wherein the method further comprises predicting or determining PSMA expression in the subject, and/or wherein PSMA expression has already been determined in the subject.
61. The method of claim 60, wherein PSMA expression is or has been determined or predicted using the method of any one of claims 1-31, optionally wherein the same biological sample is or has been used to determine or predict PSMA and PSA expression.
62. The method of any one of claims 34-61, wherein the subject has previously been diagnosed with a disease or condition that is associated with increased PSA expression.
63. The method of any one of claims 1-62, wherein the biological sample comprises a ctDNA fraction of at least 0.03%, at least 0.05%, or at least 0.10%.
64. The method of any one of claims 1-63, wherein the liquid biopsy sample is a plasma sample, serum sample, or urine sample.
65. The method of any one of claims 1-64, wherein the subject has previously been diagnosed with cancer (e.g., breast cancer, prostate cancer, or lung cancer (e.g., SCLC)).
66. The method of claim 65, wherein the cancer is prostate cancer, optionally wherein:
(i) the prostate cancer is metastatic castration resistant prostate cancer (mCRPC);
(ii) the subject has previously been administered an androgen receptor pathway inhibitor (ARPI) therapy;
(iii) it has been determined to be appropriate to delay administering a taxane-based chemotherapy to the subject or the subject has previously received taxane-based chemotherapy; or
(iv) any combination of (i)-(iii).
67. The method of claim 65 or 66, wherein the prostate cancer is prostate adenocarcinoma (PRAD) or neuroendocrine prostate cancer (NEPC).
68. A method of identifying a subject with elevated PSMA expression, comprising: (a) measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) using a method of any one of claims 1-33 or 63-67, and optionally
(b) comparing the measured PSMA expression or predicted tumor specific PSMA expression to a reference.
69. A method of identifying a subject with elevated PSA expression, comprising:
(a) measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total PSA) using a method of any one of claims 34-67, and optionally
(b) comparing the measured or predicted PSA expression to a reference.
70. A method of diagnosing a subject as having a disease or disorder associated with elevated PSMA expression, the method comprising:
(a) measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) using a method of any one of claims 1-31 or 63-67, and optionally
(b) comparing the measured PSMA expression or predicted tumor specific PSMA expression to a reference.
71. A method of diagnosing a subject as having a disease or disorder associated with elevated PSA expression, the method comprising:
(a) measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total PSA) using a method of any one of claims 34-67, and optionally
(b) comparing the measured or predicted PSA expression to a reference.
72. The method of any one of claims 68-71, wherein the reference is a predetermined threshold, a measurement from a liquid biopsy sample, a measurement from an imaging test, and/or a normalized value, optionally wherein the reference is a measurement from an imaging test (e.g., PSMA PET SUVmean) or sample obtained from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with a disease or disorder associated with increased PSMA and/or PSA expression.
73. A method of prognosing a subject having a disease or disorder associated with increased PSMA expression, comprising:
(a) measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) using a method of any one of claims 1-33 or 63-67, and optionally
(b) comparing the measured PSMA expression or predicted tumor specific PSMA expression to a reference.
74. A method of prognosing a subject having a disease or disorder associated with increased PSA expression, comprising:
(a) measuring or predicting PSA expression (e.g., serum PSA) using a method of any one of claims 34-67, and optionally
(b) comparing the measured or predicted PSA expression to a reference.
75. The method of claim 73 or 74, wherein the reference is a predetermined threshold, a measurement from a liquid biopsy sample, a measurement from an imaging test (e.g., PSMA PET SUVmean), and/or a normalized value, optionally wherein the reference is a measurement from a liquid biopsy sample or imaging test (e.g., PSMA PET SUVmean) obtained from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with the disease or disorder associated with increased PSMA and/or PSA expression.
76. The method of claim 75, wherein the reference is a PSMA expression level measured, a tumor specific PSMA expression level (e.g., PSMA PET SUVmean) predicted, or a tumor specific PSMA expression level (e.g., PSMA PET SUVmean) measured in a cohort of subjects having the disease or disorder associated with increased PSMA expression.
77. The method of claim 76, wherein the reference is the median, lower bound of the top tertile, or lower bound of the top quartile value of the PSMA expression level measured, tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) predicted, or tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) measured in the cohort of subjects having the disease or disorder associated with increased PSMA expression; and if the PSMA expression level or predicted tumor specific PSMA expression level in the subject is equal to or greater than the reference, the subject is predicted to have a higher-than- normal risk of experiencing worse than normal disease progression as measured by one or more clinical outcomes.
78. The method of claim 76 or 77, wherein:
(a) the PSMA PET SUVmean median is about 4 to about 8, about 5 to about 8, 5 to about 7, about 6 to about 9, about 5, about 6, about 7, or about 8;
(b) the lower bound of the top tertile of PSMA PET SUVmean is about 6 to about 12, about 6 to about 10, about 8 to about 12, about 6, about 7, about 8, about 9, about 10, about 11, or about 12; or
(c) the lower bound of the top quartile of PSMA PET SUVmean is about 6 to about 14, about 6 to about 12, about 8 to about 14, about 8, about 9, about 10, about 11, about 12, about 13, or about 14.
79. The method of any one of claims 68-78, wherein the reference is a measurement from a sample taken from the subject at an earlier point in time, optionally wherein:
(i) the measurement is from a liquid biopsy sample (e.g., a measurement or prediction obtained using the method of any one of claims 1-36),
(ii) a measurement from an imaging test (e.g., PSMA PET SUVmean), or
(iii) the measurement is a serum PSA measurement.
80. The method of any one of claims 77-79, wherein the one or more clinical outcomes include (i) overall survival, (ii) time to next treatment, or (iii) progression free survival (e.g., as determined by PSA-PFS (plasma PSA levels) and/or crPFS (clinical or radiological evidence of progression).
81 . The method of any one of claims 68-80, wherein the disease or indication associated with increased PSMA and/or PSA expression is cancer.
82. The method of claim 82, wherein the cancer is prostate cancer, optionally wherein the prostate cancer is mCRPC.
83. The method of claim 82, wherein the prostate cancer is PRAD or NEPC.
84. A method of monitoring progression of a disease associated with elevated PSMA expression in a subject, the method comprising, at a first and second point in time:
(a) measuring PSMA expression or predicting tumor specific PSMA expression using the method of any one of claims 1-34 or 63-67;
(b) testing whether the subject has elevated PSMA expression or diagnosing the subject using the method of any one of claims 68, 70, or 72; or
(c) prognosing the subject using the method of any one of claims 73 or 75-79; and
(d) comparing PSMA expression, predicted tumor specific PSMA expression, PSMA expression status, diagnosis, or prognosis for the first and the second time point.
85. A method of monitoring progression of a disease associated with elevated PSA expression in a subject, the method comprising, at a first and second point in time:
(a) measuring or predicting PSA expression using the method of any one of claims 34-67;
(b) testing whether the subject has elevated PSA expression or diagnosing the subject using the method of claim 69, 71, or 72; or
(c) prognosing the subject using the method of any one of claims 74, 75, or 79-83; and
(d) comparing the measured or predicted PSA expression, PSA expression status, diagnosis, or prognosis for the first and the second time point.
86. A method of treating a subject having a disease or disorder associated with increased PSMA expression, the method comprising measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) in the subject using the method of any one of claims 1-33 or 63-67, and comparing the measured PSMA expression level or predicted tumor specific PSMA expression to a reference, and
(a) if the measured PSMA expression level or predicted tumor specific PSMA expression is equal to or greater than the reference, administering a therapeutic, and
(b) if the measured PSMA expression level or predicted tumor specific PSMA expression is less than the reference, not administering the therapeutic.
87. A method of identifying a subject having a disease or disorder associated with increased PSMA expression that is likely to respond to a therapeutic, the method comprising measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) in the subject using the method of any one of claims 1-33 or 63-67, and comparing the measured PSMA expression level or predicted tumor specific PSMA expression to a reference, and
(a) if the measured PSMA expression level or predicted tumor specific PSMA expression is equal to or greater than the reference, identifying the subject as likely to respond to the therapeutic, and
(b) if the measured PSMA expression level or predicted tumor specific PSMA expression is less than the reference, identifying the subject as not likely to respond to the therapeutic.
88. A method of predicting the likelihood that a subject having a disease or disorder associated with increased PSMA expression will respond to a therapeutic, the method comprising measuring PSMA expression or predicting tumor specific PSMA expression (e.g., PSMA PET SUVmean) in the subject using the method of any one of claims 1-33 or 63-67, and comparing the measured PSMA expression level or predicted tumor specific PSMA expression to a reference, wherein (a) if the measured PSMA expression level or predicted tumor specific PSMA expression is equal to or greater than the reference, the subject is likely to respond to the therapeutic, and
(b) if the measured PSMA expression level or predicted tumor specific PSMA expression is less than the reference, the subject is not likely to respond to the therapeutic.
89. The method of any one of claims 86-88, wherein the reference is a predetermined threshold, a measurement from a liquid biopsy sample, a measurement from an imaging test, and/or a normalized value, optionally wherein the reference is a measurement from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with the disease or disorder associated with increased PSMA expression.
90. The method of any one of claims 86-89, wherein the reference is a PSMA expression level measured, a tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) predicted, or a tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) measured in a cohort of subjects having the disease or disorder associated with increased PSMA expression.
91. The method of claim 90 wherein the reference is the median, lower bound of the top tertile, or lower bound of the top quartile value of the PSMA expression level measured, tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) predicted, or tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) measured in the cohort of subjects having the disease or disorder associated with increased PSMA expression.
92. The method of any one of claims 86-91, wherein the reference is the median, lower bound of the top tertile, or lower bound of the top quartile value of the PSMA expression level measured, tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) predicted, or tumor specific PSMA expression level (e.g., PSMA PET SUVmean value) measured in the cohort of subjects having the disease or disorder associated with increased PSMA expression; and if the PSMA expression level or predicted tumor specific PSMA expression level in the subject is equal to or greater than the reference, administering the therapeutic; and if the PSMA expression level or predicted tumor specific PSMA expression level in the subject is less than the reference, not administering the therapeutic.
93. The method of claim 91 or 92, wherein:
(a) the PSMA PET SUVmean median is about 4 to about 8, about 5 to about 8, 5 to about 7, about 6 to about 9, about 5, about 6, about 7, or about 8;
(b) the lower bound of the top tertile of PSMA PET SUVmean is about 6 to about 12, about 6 to about 10, about 8 to about 12, about 6, about 7, about 8, about 9, about 10, about 11, or about 12; or
(c) the lower bound of the top quartile of PSMA PET SUVmean is about 6 to about 14, about 6 to about 12, about 8 to about 14, about 8, about 9, about 10, about 11, about 12, about 13, or about 14.
94. A method of treating a subject having a disease or disorder associated with increased PSA expression, the method comprising measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total serum PSA) in the subject using the method of any one of claims 34- 67, and comparing the measured PSA or predicted PSA expression to a reference, and
(a) if the measured PSA or predicted PSA expression is equal to or greater than the reference, administering a therapeutic, and
(b) if the measured or predicted PSA expression is less than the reference, not administering the therapeutic.
95. A method of identifying a subject having a disease or disorder associated with increased PSA expression that is likely to respond to a therapeutic, the method comprising measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total PSA) in the subject using the method of any one of claims 33-67, and comparing the measured or predicted PSA expression to a reference, and (a) if the measured or predicted PSA expression is equal to or greater than the reference, identifying the subject as likely to respond to the therapeutic, and
(b) if the measured or predicted PSA expression is less than the reference, identifying the subject as not likely to respond to the therapeutic.
96. A method of predicting the likelihood that a subject having a disease or disorder associated with increased PSA expression will respond to a therapeutic, the method comprising measuring or predicting PSA expression (e.g., serum PSA, including, e.g., total PSA) in the subject using the method of any one of claims 33-67, and comparing the measured or predicted PSA expression to a reference, wherein
(a) if the measured or predicted PSA expression is equal to or greater than the reference, the subject is likely to respond to the therapeutic, and
(b) if the measured or predicted PSA expression is less than the reference, the subject is not likely to respond to the therapeutic.
97. The method of claim 94-96, wherein the reference is a predetermined threshold, a measurement from a liquid biopsy sample, and/or a normalized value, optionally wherein the reference is a measurement from (i) a healthy subject or a cohort of healthy subjects, or (ii) a subject or a cohort of subjects that have been diagnosed with the disease or disorder associated with increased PSA expression.
98. The method of any one of claims 94-97, wherein the reference is a PSA expression that has previously been shown to be predictive of response to the therapeutic and/or previously been shown to be predictive of the presence of a disease that has been shown to respond to the therapeutic.
99. The method of any one of claims 94-98, wherein the measured or predicted PSA expression is at least about 4 ng/mL, or at least about 10 ng/mL.
100. The method of any one of claims 87-99, wherein the disease or indication associated with increased PSMA or PSA expression is a cancer.
101. The method of claim 100, wherein the cancer is prostate cancer, optionally wherein the prostate cancer is mCRPC.
102. The method of claim 101, wherein the prostate cancer is PRAD.
103. The method of any one of claims 86-102, wherein the therapeutic is a PSMA-targeted therapeutic.
104. The method of claim 103, wherein the therapeutic is an ADC (e g., PSMA-MMAE, MLN2704, ARX517), and/or wherein the therapeutic is a PSMA-targeted radionuclide (e g., 177Lu-PSMA-617).
105. The method of claim 104, wherein the therapeutic is 177Lu-PSMA-617.
106. The method of any one of claims 86-105, wherein the therapeutic is administered via one or more intravenous, subcutaneous, intraperitoneal, or intramuscular injections.
107. The method of any one of claims 68-106, wherein the subject has previously been diagnosed as having a disease or indication associated with increased PSMA or PSA expression (e.g., a cancer, prostate cancer, mCRPC, and/or PRAD).
108. The method of claim 107, wherein the prostate cancer is localized or metastatic.
109. The method of claim 107 or 108, wherein the prostate cancer has metastasized to one or more site(s) that include lymph node, bone, lung, and/or liver tissue.
110. The method of any one of claims 68-109, wherein the subject has previously been administered one or more (e.g., 2-7, 2-5, 3-4, 1, 2, 3, 4, 5, 6, or 7) systemic therapies for metastatic prostate cancer.
111. The method of any one of claims 68-110, wherein the subject has a plasma PSA concentration of 0-2000 ng/mL (e.g., at least about 4 ng/mL, at least about 10 ng/mL, 10-2000 ng/mL, 25-2000 ng/mL, 50-2000 ng/mL, 75-2000 ng/ML, 100-2000 ng/mL, 150-1000 ng/mL, 100-500 ng/mL, or 100-200 ng/mL), optionally wherein the plasma PSA concentration has been determined using the method of any one of claims 33-67.
112. A kit comprising reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci, wherein the one or more genomic loci are selected from Tables 1-5.
113. The kit of claim 112, wherein the kit comprises reagents for quantifying:
(a) promoter signal (e.g., H3K4me3 modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K4me3 analyte genomic loci in Table 1;
(b) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 1;
(c) DNA methylation for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 MBD analyte genomic loci in Table 1;
(d) enhancer signal (e.g., H3K27ac modifications) at one or more (e.g., all) of genomic loci 1-8 in Table 2;
(e) promoter signal (e.g., H3K4me3 modifications) at genomic locus 9 in Table 2;
(f) enhancer signal (e.g., H3K27ac modifications) for 1, 2, 3, or 4 H3K27ac analyte genomic loci in Table 3;
(g) promoter signal (e.g., H3K4me3 modifications) for 1 or 2 H3K4me3 analyte genomic loci in Table 4;
(h) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 4; (i) promoter signal (e.g., H3K4me3 modifications) at chrl 1 : 49, 228, 902-49, 230, 855;
(j) enhancer signal (e.g., H3K27ac modifications) at chrl 1 :49, 229, 019-49, 230, 275; or
(k) any combination of (a)-(j).
114. The kit of claim 112 or 113, wherein the kit comprises one or more antibodies for use in ChlP-seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac-modified histones.
115. The kit of any one of claims 112-114, wherein the kit comprises one or more methyl- binding domains for use in MBD-seq or wherein the kit comprises one or more antibodies that bind methylated DNA for use in MeDIP.
116. The kit of any one of claims 112-115, wherein the kit comprises reagents for isolation of cell-free DNA (cfDNA) or ctDNA from a liquid biopsy sample.
117. The kit of any one of claims 112-116, wherein the kit comprises reagents for library preparation for sequencing.
118. The kit of any one of claims 112-117, wherein the kit comprises reagents for sequencing.
119. The kit of any one of claims 112-118, wherein the kit comprises instructions for determining if a subject has a disease or disorder associated with increased PSMA (e.g., a cancer, prostate cancer, or mCRPC).
120. A non-transitory computer readable storage medium encoded with a computer program, wherein the program comprises instructions that when executed by one or more processors cause the one or more processors to perform operations to perform the method of any one of claims 1- 119.
121. A computer system comprising a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform operations to perform the method of any one of claims 1-111.
122. A system for determining the disease or disorder status of a subject, the system comprising a sequencer configured to generate a sequencing data set from a sample; and a non- transitory computer readable storage medium of claim 120 and/or a computer system of claim 121.
123. The system of claim 122, wherein the sequencer is configured to generate a Whole Genome Sequencing (WGS) data set from the sample.
124. The system of claim 122 or 123, further comprising a sample preparation device configured to prepare the sample for sequencing from a biological sample, optionally a liquid biopsy sample.
125. The system of claim 124, wherein the sample preparation device comprises reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci in cell-free DNA (cfDNA) or ctDNA from the biological sample, optionally the liquid biopsy sample.
126. The system of claim 125, wherein the one or more genomic loci are selected from Tables 1-5.
127. The system of any one of claims 122-126, wherein the device comprises reagents for quantifying:
(a) promoter signal (e.g., H3K4me3 modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K4me3 analyte genomic loci in Table 1;
(b) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 1; (c) DNA methylation for at least 1, 2, 3, 4, 5, 6, 1, 8, 9, or 10 MBD analyte genomic loci in Table 1;
(d) enhancer signal (e.g., H3K27ac modifications) at one or more (e.g., all) of genomic loci 1-8 in Table 2;
(e) promoter signal (e.g., H3K4me3 modifications) at genomic locus 9 in Table 2;
(f) enhancer signal (e.g., H3K27ac modifications) for 1, 2, 3, or 4 H3K27ac analyte genomic loci in Table 3;
(g) promoter signal (e.g., H3K4me3 modifications) for 1 or 2 H3K4me3 analyte genomic loci in Table 4;
(h) enhancer signal (e.g., H3K27ac modifications) for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 H3K27ac analyte genomic loci in Table 4;
(i) promoter signal (e.g., H3K4me3 modifications) at chrl 1 : 49, 228, 902-49, 230, 855;
(j) enhancer signal (e.g., H3K27ac modifications) at chrl 1 :49, 229, 019-49, 230, 275; or
(k) any combination of (a)-(j).
128. The system of any one of claims 122-127, wherein the reagents comprise one or more antibodies for use in ChlP-seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac-modified histones.
129. The system of any one of claims 122-128, wherein the reagents comprise one or more methyl-binding domains for use in MBD-seq.
130. The system of any one of claims 122-129, wherein the device comprises reagents for isolation of cell-free DNA (cfDNA) or ctDNA from the biological sample, optionally the liquid biopsy sample.
131. The system of any one of claims 122-130, wherein the device comprises reagents for library preparation for sequencing.
132. The system of any one of claims 122-131, wherein the sequencer comprises reagents for sequencing.
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