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WO2025081121A1 - Procédés, kits et systèmes pour déterminer l'état du cancer du poumon et méthodes de traitement du cancer du poumon les utilisant - Google Patents

Procédés, kits et systèmes pour déterminer l'état du cancer du poumon et méthodes de traitement du cancer du poumon les utilisant Download PDF

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WO2025081121A1
WO2025081121A1 PCT/US2024/051147 US2024051147W WO2025081121A1 WO 2025081121 A1 WO2025081121 A1 WO 2025081121A1 US 2024051147 W US2024051147 W US 2024051147W WO 2025081121 A1 WO2025081121 A1 WO 2025081121A1
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sclc
subject
sample
luad
modifications
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Matthew FREEDMAN
Sylvan BACA
Jacob E. BERCHUCK
Xintao QIU
Geoff Otto
Travis CLARK
Jamey GUESS
Matthew EATON
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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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    • 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
    • C12Q2600/112—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
    • C12Q2600/154—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
    • C12Q2600/156—Polymorphic or mutational 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

  • NSCLC non-small cell lung cancer
  • LUAD adenocarcinoma
  • SCC squamous cell carcinoma
  • LCC large cell carcinoma
  • SCLC small cell lung cancer
  • de novo SCLC and transformed SCLC have different pathogenesis and tumor microenvironment.
  • SCLC transformation is one of the mechanisms of resistance to chemotherapy, immunotherapy, and targeted therapy in NSCLC.
  • EGFR epidermal growth factor receptor
  • LAD lung adenocarcinoma
  • TKIs tyrosine kinase inhibitors
  • SCLC transformation can also occur in anaplastic lymphoma kinase (ALK)-positive lung cancer after treatment with ALK inhibitors and in wild-type EGFR or ALK NSCLC treated with immunotherapy (Ferrer et al., J Thorac Oncol (2019) 14:130-134).
  • ALK aplastic lymphoma kinase
  • Chemotherapy is currently used to treat transformed SCLC, yet it is associated with an unsatisfactory prognosis.
  • the present disclosure is based, at least in part, on the demonstration that the SCLC/LUAD status of a lung cancer 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 the 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 and/or DNA methylation.
  • the present disclosure is also based, at least in part, on the demonstration that 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) and/or DNA methylation can be combined into multimodal classifiers to determine SCLC/LUAD status.
  • histone modifications e.g., histone methylation marks such as H3K4me3 and histone acetylation marks such as H3K27ac
  • DNA methylation e.g., DNA methylation
  • H3K4me3 histone methylation marks
  • H3K27ac histone acetylation marks
  • the present disclosure demonstrates that epigenomic cfDNA profiling can be used to detect small cell transformation in patients with EGFRm LU AD progressing on EGFR TKIs. Diagnosing tSCLC by cfDNA profiling would be immediately clinically actionable, as guidelines recommend that tSCLC be treated with a de novo SCLC regimen of platinum-etoposide chemotherapy which would not otherwise be used in patients with LUAD.
  • the present disclosure includes, among other things, technologies for the determination of SCLC/LUAD status and for the detection, monitoring, and/or treatment of lung cancer based on SCLC/LUAD status.
  • the present disclosure relates to the measurement of histone modifications in a sample obtained or derived from a subject to detect and/or treat lung cancer based on SCLC/LUAD status.
  • the present disclosure includes, among other things, histone modification measurements in cell-free DNA (cfDNA) that are characteristic of lung cancer, and which in various embodiments are useful, e.g., for detecting, monitoring, selecting treatment for, and/or treating lung cancer based on SCLC/LUAD status.
  • cfDNA cell-free DNA
  • genomic loci differentially modified in SCLC vs. LU AD cancer 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 healthy subject or a subject with LU AD cancer).
  • 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 relates to the measurement of DNA methylation in a sample obtained or derived from a subject to detect and/or treat lung cancer based on SCLC/LUAD status.
  • the present disclosure includes, among other things, DNA methylation measurements in cell-free DNA (cfDNA) that are characteristic of cancer, and which in various embodiments are useful, e.g., for detecting, monitoring, selecting treatment for, and/or treating lung cancer based on SCLC/LUAD status.
  • the present disclosure includes, among other things, DNA methylation measurements in cfDNA that are characteristic of SCLC cancers, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating an SCLC cancer.
  • the present disclosure includes, among other things, DNA methylation measurements in cfDNA that are characteristic of LU AD cancers, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating LU AD cancer.
  • DNA methylation measurements in cfDNA can be used to detect or determine resistance of a lung cancer, e.g., LU AD cancer to a therapy or transformation of a lung cancer, e.g., from LU AD to SCLC.
  • the present disclosure includes exemplary genomic loci that are differentially DNA methylated in SCLC vs. LUAD cancer.
  • 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 or a subject with LUAD cancer).
  • 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.
  • the present disclosure further relates, in various embodiments, to the measurement of chromatin accessibility in cell-free DNA (cfDNA) to determine SCLC/LUAD status.
  • the present disclosure includes, among other things, chromatin accessibility measurements in cfDNA that are characteristic of SCLC cancers, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating an SCLC cancer.
  • the present disclosure includes, among other things, chromatin accessibility measurements in cfDNA that are characteristic of LUAD cancers, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating LUAD cancer.
  • chromatin accessibility measurements in cfDNA can be used to detect or determine resistance of a lung cancer, e.g., LUAD cancer to a therapy or transformation of a lung cancer, e.g., from LUAD to SCLC.
  • genomic loci that are differentially accessible in SCLC vs. LUAD cancer.
  • 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 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.
  • 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 or a subject with LU AD cancer).
  • 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 further relates, in various embodiments, to the measurement of transcription factor binding in cell-free DNA (cfDNA) to determine SCLC/LUAD status.
  • cfDNA cell-free DNA
  • the present disclosure includes, among other things, transcription factor binding measurements in cfDNA that are characteristic of SCLC cancers, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating an SCLC cancer.
  • transcription factor binding measurements in cfDNA that are characteristic of LU AD cancers which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating LU AD cancer.
  • transcription factor binding measurements in cfDNA can be used to detect or determine resistance of a lung cancer, e.g., LU AD cancer to a therapy or transformation of a lung cancer, e.g., from LU AD to SCLC.
  • the present disclosure includes genomic loci that are differentially bound by transcription factors in SCLC vs. LU AD cancer.
  • 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 or a subject with LUAD cancer).
  • 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 the SCLC/LUAD status of a lung cancer 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), and a DNase hypersensitivity 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
  • 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.
  • binding of one or more transcription factors is quantified using a transcription factor binding assay that detects binding of one or more of p300, mediator complex, cohesin complex, RNA pol II, FOXA1, ESRI, PR, MYC, EN1, FOXM1, KLF4, AP-2, RARa, or RUNX1.
  • DNA methylation is quantified using Bisulfite sequencing (BS-Scq), Whole Genome Bisulfite Sequencing (WGBS), Methylated DNA ImmunoPrecipitation sequencing (MeDIP-seq), or Methyl-CpG-Binding Domain sequencing (MBD-seq).
  • the 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.
  • the method comprises quantifying one or more histone modifications and DNA methylation, e.g., quantifying H3K4me3 and/or H3K27ac modifications and DNA methylation.
  • the method comprises quantifying H3K4me3 modifications, H3K27ac modifications and DNA methylation.
  • a sample is a liquid biopsy sample comprising cfDNA, and a method comprises:
  • peaks in high noise regions are ignored when identifying genomic loci with a higher number of sequence reads than the local background and/or when identifying genomic loci associated with an SCLC/LUAD disease state.
  • peaks in white blood cell regions are ignored when identifying genomic loci with a higher number of sequence reads than the local background and/or identifying genomic loci associated with an SCLC/LUAD disease state.
  • peaks in regions likely to be artifactual are removed. In some embodiments, peaks that are less than 50 bp in length are removed.
  • a method comprises comparing a measure of one or more epigenetic biomarkers to a reference.
  • a reference is a predetermined threshold, a measurement from a liquid biopsy sample, a measurement from liquid biopsy samples obtained from a cohort of subjects, and/or a normalized value.
  • a predetermined threshold or a normalized value were previously shown to distinguish LU AD and SCLC subjects (e.g., distinguish with an AUROC of greater than 0.5).
  • a reference is a measurement from a liquid biopsy sample obtained from a cohort of subjects who have previously been determined to have LU AD or SCLC.
  • a method comprises calculating sequence read density at one or more genomic loci. In some embodiments, calculating sequence read density can be calculated by:
  • one or more genomic loci include one or more genomic loci with an increased level of the one or more epigenetic biomarkers in (a) sample(s) obtained from a subject with SCLC as compared to sample(s) obtained from a subject with LU AD, and/or (b) sample(s) obtained from a subject with LU AD as compared to sample(s) obtained from a subject with SCLC.
  • a method described herein comprises calculating an SCLC/LUAD ratio score.
  • an SCLC/LUAD ratio score can be calculated by a method comprising:
  • a method comprises determining an SCLC/LUAD ratio score for one or more epigenetic biomarkers. In some embodiments, a method comprises determining an SCLC/LUAD ratio score for two or more epigenetic biomarkers. In some embodiments, a method comprises determining an SCLC/LUAD ratio score for two or more epigenetic biomarkers and combining the two or more SCLC/LUAD ratio scores. In some embodiments, a method comprises determining an SCLC/LUAD ratio score for each of H3K4me3 modifications, H3K27ac modifications, and methylated DNA, and combining each of the ratio scores. In some embodiments, two or more ratio scores can be combined using fitted values determined using a logistic regression.
  • a method comprises comparing one or more quantified epigenetic biomarkers to a reference, wherein an increase or decrease in the one or more epigenetic biomarkers as compared to the reference indicates that the subject has SCLC or LU AD.
  • the reference is a predetermined threshold, a measurement from a liquid biopsy sample, and/or a normalized value.
  • the reference is a measurement from liquid biopsy samples obtained from a cohort of subjects who have previously been determined to have LU AD or to be cancer free.
  • the predetermined threshold and the normalized value were previously shown to distinguish LU AD and SCLC subjects (e.g., to provide an AUROC value of at least 0.5).
  • the cohort of subjects had previously been determined to have lung cancer (e.g., LUAD or SCLC).
  • 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 SCLC cancer (e.g., de novo SCLC cancer or transformed SCLC cancer).
  • 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 subjects who have previously been determined to have LUAD cancer.
  • a subject has previously been determined to have lung cancer, an increased susceptibility to lung cancer, and/or a method further comprises determining whether the subject has lung cancer. In some embodiments, a subject has an increased susceptibility to SCLC.
  • 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 LUAD cancer.
  • 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 subjects who have previously been determined to have SCLC cancer.
  • the lung cancer is metastatic lung cancer.
  • the lung cancer exhibits loss of TP53 and/or RBI (c.g., comprises one or more loss of function mutations).
  • 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 one or more genomic loci arc selected from those provided Table 4.
  • the SCLC cancer has been subtyped on the basis of increased ASCL1 activity (e.g., expression), and the SCLC therapy is one that has been associated with providing an improved therapeutic benefit in subjects diagnosed with an ASCL1 subtype of SCLC (e.g., improved relative to alternative therapeutics that are commonly administered to subjects having SCLC).
  • the SCLC therapy is a BCL2 apoptosis regulator, a BCL2 inhibitor, a DLL3 inhibitor (e.g., rovalpituzumab tesirine), an LSD1 inhibitor, and/or a therapeutic targeting CEACAM5 (e.g., labetuzumab govitecan).
  • the SCLC cancer has been subtyped on the basis of increased NEURODI activity (e.g., expression), and the SCLC therapy is one that has been associated with providing an improved therapeutic benefit in subjects diagnosed with a NEURODI subtype of SCLC (e.g., improved relative to alternative therapeutics that are commonly administered to subjects having SCLC).
  • the SCLC therapy is an Aurora kinase inhibitor, a Somatostatin receptor 2 (SSTR2) inhibitor (e.g., lanreotide), a therapeutic targeting SSTR2 (e.g., PEN-221), or an immunotherapy (e.g., durvalumab) coadministered with platinum-etoposide.
  • SSTR2 Somatostatin receptor 2
  • PEN-221 a therapeutic targeting SSTR2
  • an immunotherapy e.g., durvalumab
  • the SCLC cancer has been subtyped on the basis of increased YAP1 activity (e.g., expression), and the SCLC therapy is one that has been associated with an improved therapeutic benefit in subjects diagnosed with a YAP1 subtype of SCLC.
  • the SCLC therapy comprises durvalumab co-administered with platinum- etoposide.
  • the SCLC subtype is an inflamed SCLC subtype (SCLC-I) and is optionally characterized by (i) low activity (e.g., low expression) of ASCL1, NEURODI, and POU2F3 (e.g., low relative to activity in a healthy subject, an average subject having SCLC, and/or one or more alternative SCLC subtypes), and/or (ii) is characterized by poor response to immune checkpoint blockade.
  • SCLC-I inflamed SCLC subtype
  • the SCLC therapy comprises an anti-PD- L1 therapeutic and a chemotherapeutic, immune checkpoint blockade, a Bruton’s tyrosine kinase (BTK) inhibitor, ibrutinib, an EMT-inhibitor (e.g., HDACi (e.g., mocetinostat)), a MICA inhibitor (e.g., IPH43), and/or an immunotherapy (e.g., durvalumab) co-administered with platinum-ctopo side .
  • BTK ton’s tyrosine kinase
  • HDACi e.g., mocetinostat
  • MICA inhibitor e.g., IPH43
  • an immunotherapy e.g., durvalumab
  • the lung cancer has been determined to be LU AD cancer and the cancer therapy is a LU AD cancer therapy.
  • the LU AD cancer therapy comprises administering a selective EGFR tyrosine kinase inhibitor (e.g., Osimertinib).
  • a selective EGFR tyrosine kinase inhibitor e.g., Osimertinib.
  • the present disclosure provides a method of monitoring the SCLC/LUAD status of a lung cancer in a subject, and optionally treating the lung cancer, the method comprising; determining the SCLC/LUAD status of the lung cancer using any one of the aforementioned methods of determining SCLC/LUAD status at first and second time points.
  • the subject is being treated with a therapeutic agent that can lead to transformation from LU AD cancer (or more generally a NSCLC cancer) to SCLC cancer, e.g., where the subject has epidermal growth factor receptor (EGFR) mutant LU AD cancer and is being treated with a tyrosine kinase inhibitor (TKI), the subject has anaplastic lymphoma kinase (ALK)-positive LUAD cancer and is being treated with an ALK inhibitor, or the subject has wild-type EGFR or ALK LUAD cancer and is being treated with immunotherapy.
  • a therapeutic agent that can lead to transformation from LU AD cancer (or more generally a NSCLC cancer) to SCLC cancer, e.g., where the subject has epidermal growth factor receptor (EGFR) mutant LU AD cancer and is being treated with a tyrosine kinase inhibitor (TKI), the subject has anaplastic lymphoma kinase (ALK)-positive LUAD cancer and is being treated with an A
  • the method further comprises administering a lung cancer therapy, optionally a SCLC cancer therapy or LUAD cancer therapy, to the subject based on the SCLC/LUAD status of the lung cancer at the second time point, optionally wherein the type, dose and/or frequency of administration of the cancer therapy is adjusted based on the SCLC/LUAD status of the lung cancer at the second time point.
  • a lung cancer therapy optionally a SCLC cancer therapy or LUAD cancer therapy
  • the present disclosure provides a method of treating a subject having a lung cancer, the method comprising: (i) administering an SCLC therapeutic agent to the subject, wherein the subject has been determined to have a validated epigenetic profile indicative of an SCLC cancer based on analysis of a biological sample, optionally of cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject; or (ii) administering a LUAD therapeutic agent to the subject, wherein the subject has been determined to have a validated epigenetic profile indicative of LUAD cancer based on analysis of a biological sample, optionally of cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject, wherein the presence of the validated epigenetic profile has been determined using a validated classifier, wherein the validated classifier has been obtained by: (a) determining a genomic profile of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation
  • the differential loci in step (c) were identified by comparing the genomic profile of one or more histone modifications and/or DNA methylation in (i) one or more biological samples from the first cohort and (ii) one or more biological samples from the second cohort.
  • the classifier in step (d) was trained on histone modification and/or DNA methylation levels in (i) one or more biological samples from the first cohort and (ii) one or more biological samples from the second cohort. [0067] In some embodiments, the validated classifier in step (e) was validated using liquid biopsy samples from the third cohort.
  • the classifier in step (d) was trained on two or more histone modification levels in the differential loci.
  • the two or more histone modification levels comprise H3K4me3 and H3K27ac modification levels.
  • the classifier in step (d) was trained on one or more histone modification levels and DNA methylation in the differential loci.
  • the one or more histone modification levels comprise H3K4me3 and/or H3K27ac modification levels.
  • the classifier in step (d) was trained using ridge regression, elastic- net regression, or lasso regression.
  • the one or more histone modification levels comprise H3K4me3 and/or H3K27ac modification levels.
  • the one or more histone modification levels comprise H3K4me3 and H3K27ac modification levels.
  • the biological sample is a liquid biopsy sample, e.g., a plasma sample, serum sample, or urine sample.
  • the present disclosure provides 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 1-3.
  • the kit comprises reagents for quantifying H3K4me3 for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1.
  • the kit comprises reagents for quantifying H3K27ac for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2.
  • the kit comprises reagents for quantifying H3K27ac for at least 1, 2, 3, or 4 genomic loci in Table 4.
  • the kit comprises reagents for quantifying H3K4me3 or H3K27ac for at least 5, 10, 15, 20, 25 or 30 genomic loci in Table 5. In some embodiments, the kit comprises reagents for quantifying DNA methylation for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 3. In some embodiments, the kit comprises reagents for quantifying DNA methylation for at least 5, 10, 15, 20, 25 or 30 genomic loci in Table 5.
  • 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. In some embodiments, the kit comprises one or more methyl-binding domains for use in MBD-seq. [0072] 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.
  • cfDNA cell-free DNA
  • the kit comprises instructions for determining if a subject has SCLC cancer or LU AD cancer, optionally instructions for determining if a subject has a subtype of SCLC cancer characterized by increased activity (e.g., expression) of ASCL1, NEURODI, YAP1, and/or POU2F3.
  • the present disclosure provides 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 the aforementioned methods of determining SCLC/LUAD status.
  • the present disclosure provides 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 the aforementioned methods of determining SCLC/LUAD status.
  • the present disclosure provides a system for determining the SCLC/LUAD status of a lung cancer in 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 and/or a computer system of the present disclosure.
  • the sequencer is configured to generate a Whole Genome Sequencing (WGS) data set from the sample.
  • the system further comprises a sample preparation device.
  • the sample preparation device is configured to prepare the sample for sequencing from a biological sample, optionally a liquid biopsy sample.
  • a classifier has been trained based on two or more histone modification levels in the differential loci.
  • a genomic profile comprises two or more histone modification levels.
  • such two or more histone modification levels comprise H3K4me3 and H3K27ac modification levels.
  • a genomic profile comprises one or more histone modification levels and DNA methylation.
  • a classifier has been trained based on one or more histone modification levels and DNA methylation in the differential loci.
  • such one or more histone modification levels comprise H3K4mc3 and/or H3K27ac modification levels.
  • such one or more histone modification levels comprise H3K4me3 and H3K27ac modification levels.
  • method of treating a subject having a cancer includes administering a LU AD therapeutic agent to the subject, wherein the subject has been determined to have a validated epigenetic profile indicative of LU AD based on analysis of a biological sample, optionally of cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject.
  • a validated epigenetic profile has been determined using a classifier (e.g., a validated classifier) according to a method for determining SCLC and/or LU AD of a cancer in a subject (e.g., patient).
  • Fig. 1 shows representative ROC curves for exemplary SCLC/LUAD status classifiers that were generated in accordance with Example 2.
  • different classifiers were generated using genomic loci from Tables 1-3 for different modifications, namely (i) H3K4me3 modifications, (ii) H3K27ac modifications, (iii) DNA methylation (MBD) or (iv) all of the above (combined).
  • AUC for individual modifications was calculated based on SCLC/LUAD ratio for each modification individually.
  • AUC for the combined modifications was calculated on the fitted values from a logistic regression. Each individual modification and the combination of all three were able to correctly classify SCLC from LU AD.
  • AUC values were 0.85 for H3K4me3 modifications, 0.83 for H3K27ac modifications, 0.9 for DNA methylation (MBD) and 0.92 for the combination of all three.
  • Fig. 2 shows representative, non-limiting graphs that demonstrate the accuracy of SCLC/LUAD status (based on AUCROC) determination using the classifiers that were generated in accordance with Example 2.
  • average AUC and 95% confidence intervals are shown from 500 repeated samplings of regions used to calculate SCLC/LUAD ratios.
  • the different sampling used different subsets of the genomic loci in Table 1 (H3K4me3), Table 2 (H3K27ac), Table 3 (MBD) and Tables 1-3 (combined).
  • FIG. 3 shows representative, non-limiting graphs that demonstrate the accuracy of SCLC/LUAD status (based on AUCROC) determination using the classifiers that were generated in accordance with Example 2.
  • the widths of genomic loci in Tables 1-3 were increased/decreased and AUCs calculated on re-computed SCLC/LUAD ratios.
  • increasing or decreasing the classifier input genomic region width hy up to 50% had little effect on predictive performance.
  • Fig. 4 shows the results of experiments performed in accordance with Example 5 where different machine learning (ML) approaches were used to generate different SCLC/LUAD status classifiers using the genomic loci in Tables 1-3.
  • the results show the average (95% CI) AUC from 50 repeats of 5-fold cross validation.
  • the background adjusted counts normalized to library size in each individual genomic locus were provided to three different ML algorithms instead of being used to calculate SCLC/LUAD ratio scores.
  • the different ML approaches (glmnet, Random forest and SVM) yielded similar predictive performance.
  • FIG. 5 shows normalized H3K4me3 cfChlP-seq signal at the DLL3 promoter stratified by cancer type. As shown, H3K4me3 cfChlP-seq signal was highest for Merkel cell carcinoma, neuroendocrine prostate cancer (NEPC), melanoma and small cell lung cancer (SCLC). Lower and upper hinges indicate 25 th and 75 th percentiles; whiskers extend to 1.5 x the inter-quartile ranges (IQR).
  • IQR inter-quartile ranges
  • Fig. 6 shows heatmaps of quantified and scaled enhancer and promoter activity at established SCLC subtype driver genes (columns) in SCLC patient plasma samples
  • Fig. 7 shows patient- specific promoter signals for genes that are associated with differential transcriptional biology across SCLC and LU AD. As shown in the figure, clear differences were seen between SCLC and LUAD. Samples were grouped by histology and sorted by ichorCNA ctDNA fraction estimate within each group.
  • Fig. 8. shows the ability of a classifier that uses enhancer, promoter and methylation signal quantified at loci determined to be differential between SCLC and NSCLC in cell lines (e.g., loci described herein) to distinguish between subjects having SCLC and LUAD.
  • 5-fold cross validation was performed using regularized logistic regression to estimate the predictive performance of classifying SCLC and LUAD.
  • Selected features comprise 65% promoters, 23% enhancers and 13% methylation.
  • predictive performance remained high even for samples with ctDNA levels below the ichorCNA limit of detection, indicating that the assay is sensitive below 3% ctDNA.
  • Fig. 9 shows results from an in silico experiment to determine the limit of detection of assays described herein.
  • silico plasma samples were created to simulate lower ctDNA levels by diluting the high ctDNA profiles of 17 LU AD and 12 SCLC plasma samples with each of 24 healthy plasma samples.
  • Regularized logistic regression was used to classify in silico mixtures using a leave-one-out scheme in which all mixtures generated from a given pair of cancer and healthy samples were held out and then predicted based on a model fit to the remaining mixture samples.
  • AUC estimates from these simulations remain above 0.90 even at 0.5% ctDNA and above 0.80 at 0.4% ctDNA.
  • Fig. 10 is a block diagram of an example network environment for use in the methods and systems described herein, according to illustrative embodiments of the present disclosure.
  • FIG. 11 is a block diagram of an example computing device and an example mobile computing device, for use in illustrative embodiments of the present disclosure.
  • Figure 12 Overview of an experimental approach to perform comprehensive epigenomic profiling of lung cancer patient-derived xenografts (PDXs) and multi-analyte epigenomic profiling of cfDNA from 1 mL of patient plasma and non-invasively detect SCLC transformation in patients with EGFRm LU AD.
  • PDXs lung cancer patient-derived xenografts
  • multi-analyte epigenomic profiling of cfDNA from 1 mL of patient plasma and non-invasively detect SCLC transformation in patients with EGFRm LU AD e.g., all of the analytes indicated in Figure 1 can be used in a method described in the present disclosure.
  • analytes can be assessed in any order, to the extent permitted by experimental protocols.
  • FIG. 13 Comprehensive epigenomic profiling of LU AD, tSCLC, and de novo SCLC reveals widespread epigenomic reprogramming in small transformation.
  • PCA Principal component analysis
  • FIG. 14 Comparative analysis identifies a robust set of highly differential epigenomic features between LU AD and SCLC.
  • A Heatmap of normalized H3K27ac tag densities at differential H3K27ac sites between LU AD and SCLC tumors (FDR- adjusted P ⁇ 0.001 and log2 fold-change > 2) located ⁇ 2 kb from peak center.
  • B Volcano plot showing overlap of the log2 fold-change differentially expressed genes between LU AD and SCLC PDXs with respective differential H3K27ac peaks enriched in LUAD (blue) and SCLC (red). Two- sided p-values were corrected for multiple hypothesis testing (FDR-adjusted P ⁇ 0.05).
  • Figure 20 Unsupervised hierarchical clustering of lung adenocarcinoma (LUAD), transformed small cell lung cancer (SCLC), and de novo SCLC patient-derived xenografts (PDXs) for ATAC-seq (A), H3K27ac ChlP-seq (B), H3K4me3 ChlP-seq (C), H3K27me3 ChlP-seq (D), and MeDIP-seq (E) data.
  • LAD lung adenocarcinoma
  • SCLC transformed small cell lung cancer
  • PDXs de novo SCLC patient-derived xenografts
  • FIG. 21 Venn diagram showing overlap of lung adenocarcinoma (LUAD), transformed small cell lung cancer (SCLC), and de novo SCLC patient-derived xenografts (PDX) H3K27ac ChlP-seq (A), H3K4me3 ChlP-seq (B), ATAC-seq (C), and MeDIP-seq (D) peaks.
  • LAD lung adenocarcinoma
  • SCLC transformed small cell lung cancer
  • PDX de novo SCLC patient-derived xenografts
  • Figure 22 Number of differential (A) H3K27ac, (B) H3K4me3, (C) DNA methylation, and (D) open chromatin sites enriched in lung adenocarcinoma (LUAD) or small cell lung cancer (SCLC) patient-derived xenografts before and after removal of peaks also present in white blood cells (WBCs).
  • A H3K27ac
  • B H3K4me3
  • C DNA methylation
  • D open chromatin sites enriched in lung adenocarcinoma
  • SCLC small cell lung cancer
  • FIG. 23 Volcano plot showing overlap of the log2 fold-change differentially expressed genes between LUAD and SCLC PDXs with respective differential (A) H3K4me3 ChlP-seq and (B) ATAC-seq peaks enriched in lung adenocarcinoma (LUAD; blue) and small cell lung cancer (SCLC; red) patient-derived xenografts. Two-sided p-values were corrected for multiple hypothesis testing (FDR-adjusted P ⁇ 0.05).
  • Figure 24 Epigenomic datasets generated from cfDNA plasma samples from patients with metastatic lung cancer. Abbreviations: cfDNA, cell-free DNA; LUAD, lung adenocarcinoma; SCLC, small cell lung cancer; tSCLC, transformed SCLC; EGFRm, EGFR mutant.
  • Figure 25 Representative epigenomic data from an EGFRm tSCLC and EGFRm LUAD showing the distribution of H3K27ac and H3K4me3 signal intensity near INSMI, a neural lineage-defining gene. Grey bars indicate the nearest enhancers characterized as Elite GeneHancer and Elite GeneHancer-gene association for INSMI.
  • FIG. 26 H3K27ac signal at select genes in representative cfDNA samples from a healthy cancer-free control, a patient with metastatic EGFRm lung adenocarcinoma (LUAD), and a patient with metastatic EGFRm transformed small cell lung cancer (tSCLC).
  • Samples from cancer patients were selected based on high estimated cfDNA tumor content from low-pass whole genome sequencing data: 55% for the EGFRm LUAD patient and 46% for the EGFRm tSCLC patient.
  • Each track depicts signal intensity for the indicated epigenetic mark in the indicated sample.
  • Each sample is scaled to the peak signal intensity in GAPDH for that sample.
  • FIG. 27 Classification of LUAD and SCLC cell lines based on H3K27ac ChlP- seq data.
  • LUAD lung adenocarcinoma
  • SCLC small cell lung cancer
  • Y YAP1, P, POU2F3, A
  • Figure 28 Number of base pairs covered by differential H3K27ac, DNA methylation, and open chromatin sites enriched in lung adenocarcinoma (LUAD) or small cell lung cancer (SCLC) patient-derived xenografts (PDXs) after removal of peaks also present in white blood cells.
  • LAD lung adenocarcinoma
  • SCLC small cell lung cancer
  • PDXs patient-derived xenografts
  • the present disclosure is based, at least in part, on the demonstration that the SCLC/LUAD status of a lung cancer 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 the 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 and/or DNA methylation.
  • the present disclosure is also based, at least in part, on the demonstration that 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) and/or DNA methylation can be combined into multimodal classifiers to determine SCLC/LUAD status.
  • histone modifications e.g., histone methylation marks such as H3K4me3 and histone acetylation marks such as H3K27ac
  • DNA methylation e.g., DNA methylation
  • H3K4me3 histone methylation marks
  • H3K27ac histone acetylation marks
  • NSCLC non-small cell lung cancer
  • LU AD adenocarcinoma
  • SCC squamous cell carcinoma
  • LCC large cell carcinoma
  • LU AD adenocarcinoma
  • SCC squamous cell carcinoma
  • LCC large cell carcinoma
  • LU AD adenocarcinoma
  • SCC squamous cell carcinoma
  • LCC large cell carcinoma
  • LU AD mEGFR (mutated Epidermal growth factor receptor) LUAD, in which a mutation in the EGFR receptor results in the receptor being constitutively rather than being activated only in the presence an endogenous cognate ligand.
  • Exemplary mutations include E19del and L858R.
  • SCLC small cell lung cancer
  • EGFR epidermal growth factor receptor
  • LU AD epidermal growth factor receptor
  • TKIs tyrosine kinase inhibitors
  • SCLC transformation can also occur in anaplastic lymphoma kinase (ALK)-positive lung cancer after treatment with ALK inhibitors and in wild-type EGFR or ALK NSCLC treated with immunotherapy (Ferrer et al., J Thorac Oncol (2019) 14:130-134).
  • Chemotherapy was previously used to treat transformed SCLC, yet it is associated with an unsatisfactory prognosis.
  • SCLC cancers can be treated with any SCLC cancer therapies, e.g., those disclosed herein.
  • LU AD cancers can be treated with any LU AD cancer therapies, e.g., those disclosed herein.
  • SCLC cancer therapies include chemotherapy and immunotherapy.
  • Chemotherapy is typically part of the treatment for small cell lung cancer (SCLC). This is because SCLC has usually already spread by the time it is found , so other treatments such as surgery or radiation therapy would not reach all areas of cancer.
  • SCLC small cell lung cancer
  • chemotherapeutic agents may be tried.
  • the choice of chemotherapeutic agents depends to some extent on how soon the cancer begins to grow again. The longer it takes for the cancer to return, the more likely it is to respond to further treatment. If cancer returns more than 6 months after treatment, it might respond again to the same chemotherapeutic agents that were given the first time. If the cancer comes back sooner, or if it keeps growing during treatment, further treatment with the same chemotherapeutic agents is unlikely to be helpful. If further chemotherapy is given, most medical practitioners prefer treatment with a single, different chemotherapeutic agent to help limit side effects. Topotecan and lurbinectedin are most often used, although other chemotherapeutic agents might also be tried.
  • An important part of the immune system is its ability to keep itself from attacking normal cells in the body. To do this, it uses “checkpoints” or proteins on immune cells that need to be turned on (or off) to start an immune response. Cancer cells sometimes use checkpoints to avoid being attacked by the immune system. Therapeutic agents that target these checkpoints can be used to treat some subjects with small cell lung cancer (SCLC).
  • SCLC small cell lung cancer
  • Atezolizumab and durvalumab are exemplary checkpoint inhibitors that target PD-L1, a protein related to PD-1 that is found on some tumor cells and immune cells.
  • Camrelizumab is an exemplary checkpoint inhibitor that targets PD- 1. Blocking of these proteins can help boost the immune response against cancer cells.
  • These therapeutic agents can be used as part of the first-line treatment for advanced SCLC, along with etoposide and a platinum chemotherapy (e.g., carboplatin or cisplatin). Either therapeutic agent can then be continued alone as maintenance therapy. This combination of PD-L1 immunotherapy with chemotherapy also seems to help some subjects with SCLC live longer.
  • These therapeutic agents are administered as an intravenous (IV) infusion, typically every 2, 3 or 4 weeks.
  • PARPi Poly ADP-ribose polymerase (PARP) inhibitors
  • PARPi Poly ADP-ribose polymerase inhibitors
  • olaparib, fluzoparib and talazoparib have been approved in ovarian cancer, prostate cancer and/or breast cancer and are currently under investigation in SCLC, given their potential of enhancing cytotoxic response to chemotherapy, radiotherapy, and immunotherapy (Barayan et al., J Thorac Dis (2020) 12:6240-6252).
  • Exemplary combination therapies under clinical assessment for first- line therapy in combination with platinum chemotherapy e.g., carboplatin or cisplatin
  • platinum chemotherapy e.g., carboplatin or cisplatin
  • camrelizumab and fluzoparib, and atezolizumab and talazoparib are being assessed for maintenance therapy of SCLC.
  • the combination of durvalumab and ceralasertib, an ATR inhibitor (ATRi), and the combination of durvalumab and AZD2811, Aurora Kinase B inhibitors (AurKBi), are also being investigated for maintenance therapy of SCLC.
  • DLL3 Delta-like ligand 3
  • NECs neuroendocrine cancers
  • Rovalpituzumab tesirine is an antibody-drug conjugate (ADC) comprising a DLL3-specific humanized monoclonal antibody (SC 16) conjugated to a membrane- permeable pyrrolobenzodiazepine (PBD) dimer toxin via a lysosomal, protease-sensitive dipeptide linker (Saunders et al., Sci Transl Med (2015) 7:302ral36). Binding of rovalpituzumab tesirine to cell surface DLL3 causes internalization of the ADC-target complex by endocytosis.
  • ADC antibody-drug conjugate
  • SC 16 DLL3-specific humanized monoclonal antibody
  • PBD membrane- permeable pyrrolobenzodiazepine
  • Rovalpituzumab tesirine s valine-alanine linker is subsequently cleaved by lysosome-associated cathepsin B, releasing PBD into the cytoplasm. PBD then enters the nucleus, cross-links DNA, and induces tumor cell death by apoptosis.
  • a DLL3-targeted therapeutic e.g., an ADC such as rovalpituzumab tesirine can be used to treat a subject that has been determined to have a cancer in accordance with a method of the present disclosure, e.g., a subject determined to have SCLC.
  • such methods may involve a further step of detecting or quantifying the presence of an H3K4me3 modification at the DLL3 promoter in accordance with methods of the present disclosure, e.g., in a plasma sample, e.g., within genomic locus chrl9:39, 988, 452-39, 990, 287 (hgl9) or one or more subregions thereof, e.g., via cfChlP- seq.
  • such methods include a step of administering a DLL3-targeted therapeutic, e.g., an ADC such as rovalpituzumab tesirine to the subject.
  • the present disclosure encompasses methods that involve a step of detecting or quantifying the presence of an H3K4me3 modification at the DLL3 promoter, e.g., in a plasma sample, e.g., within genomic locus chrl9:39, 988, 452-39, 990, 287 (hg 19) or one or more subregions thereof, e.g., via cfChlP-seq where the subject is not or has not previously been determined to have SCLC in accordance with a method of the present disclosure, e.g., where the subject is independently diagnosed as having SCLC or where the subject has a non-SCLC cancer, e.g., Merkel cell carcinoma, neuroendocrine prostate cancer (NEPC) or melanoma.
  • a non-SCLC cancer e.g., Merkel cell carcinoma, neuroendocrine prostate cancer (NEPC) or melanoma.
  • detection or quantification of an H3K4me3 modification at the DLL3 promoter e.g., in a plasma sample, e.g., within genomic locus chr 19:39,988,452-39,990,287 (hg 19) or one or more subregions thereof, e.g., via cfChlP-scq may be used for the selection of a DLL3- targeted therapeutic, e.g., an ADC such as rovalpituzumab tesirine to treat such a subject.
  • a DLL3-targeted therapeutic e.g., an ADC such as rovalpituzumab tesirine
  • NSCLC non-small cell lung cancer
  • LUAD neoadjuvant
  • chemotherapy may be used (sometimes with radiation therapy) to try to shrink a tumor to remove it with less extensive surgery.
  • adjuvant chemotherapy may be used (sometimes with radiation therapy) to try to kill any cancer cells that might have been left behind or have spread but can't be seen even on imaging tests.
  • NSCLC e.g., LUAD
  • chemotherapy along with radiation therapy is sometimes given as the main treatment for more advanced cancers that have grown into nearby structures so that surgery is not an option or for subjects who aren’t healthy enough for surgery.
  • metastatic (stage IV) NSCLC e.g., LUAD
  • chemotherapy may be given for lung cancer that has spread to areas outside the lung such as the bones, liver, or adrenal gland.
  • the chemotherapeutic agents most often used for NSCLC include cisplatin, carboplatin, paclitaxel, albumin-bound paclitaxel (nab-paclitaxel), docetaxel, gemcitabine, vinorelbine, etoposide and pemetrexed.
  • Combinations of two chemotherapeutic agents are often used to treat early-stage lung cancer. If a combination is used, it often includes cisplatin or carboplatin plus one other chemotherapeutic agent. Sometimes other combinations that do not include these chemotherapeutic agents, such as gemcitabine with vinorelbine or paclitaxel, may be used.
  • Chemotherapeutic agents for lung cancer are typically administered intravenously, either as an injection over a few minutes or as an infusion over a longer period of time.
  • Adjuvant and neoadjuvant chemotherapy is often administered for 3 to 4 months, depending on the chemotherapeutic agents used.
  • the length of treatment for advanced lung cancer is based on how well it is working for the subject in question.
  • the medical practitioner may recommend second-line treatment with a single chemotherapeutic agent such as docetaxel or pemetrexed, or with immunotherapy or a targeted therapy.
  • a single chemotherapeutic agent such as docetaxel or pemetrexed
  • NSCLC non-small cell lung cancer
  • PD-1 and PD-L1 inhibitors [0140] Nivolumab, pembrolizumab, and cemiplimab target PD- 1 , a protein on T cells that normally helps keep these cells from attacking other cells in the body. By blocking PD-1, these therapeutic agents boost the immune response against cancer cells. This can shrink some tumors or slow their growth.
  • Atezolizumab and durvalumab target PD-L1, a protein related to PD-1 that is found on some tumor cells and immune cells. Blocking this protein can help boost the immune response against cancer cells. This can shrink some tumors or slow their growth.
  • Nivolumab can be used along with chemotherapy as a first treatment before surgery (known as neoadjuvant treatment) in some subjects with early-stage NSCLC, e.g., LU AD.
  • Pembrolizumab, atezolizumab, or cemiplimab can be used (sometimes with chemotherapy) as part of the first treatment in some subjects with metastatic NSCLC, e.g., LU AD.
  • pembrolizumab or cemiplimab can be given as the first treatment.
  • Durvalumab can be used in subjects with Stage III NSCLC, e.g., LU AD patients whose cancer cannot be removed with surgery and has not gotten worse after they have received chemotherapy with radiation (chemoradiation). The goal of treatment with this therapeutic agent (also called consolidation therapy) is to keep the cancer from getting worse for as long as possible.
  • Atezolizumab or pembrolizumab can be used in subjects with some earlier stages of NSCLC, e.g., LU AD patients who have already been treated with surgery followed by chemotherapy. This is known as adjuvant therapy.
  • IV intravenous
  • Ipilimumab and tremelimumab are also immunotherapies that boost the immune response, but they block CTLA-4, another protein on T cells that normally helps keep them in check.
  • These therapeutic agents are used along with a PD- 1 inhibitor (ipilimumab with nivolumab, and tremelimumab with durvalumab); they are not used alone. They might be an option as part of the first treatment for certain types of advanced NSCLC, e.g., LU AD, most often along with chemotherapy as well.
  • IV intravenous
  • NSCLC non-small cell lung cancer
  • LU AD cells e.g., LU AD cells that help them grow
  • Targeted therapies work differently from standard chemotherapy. They sometimes work when chemotherapy does not, and they often have different side effects. At this time, targeted therapeutic agents are most often used for advanced lung cancers, either along with chemotherapy or by themselves.
  • angiogenesis inhibitors block this new blood vessel growth:
  • Bevacizumab is used to treat advanced NSCLC, e.g., LU AD. It is an antibody that targets vascular- endothelial growth factor (VEGF), a protein that helps new blood vessels to form. This therapeutic agent is often used with chemotherapy for a time. Then if the cancer responds, the chemotherapy may be stopped and bevacizumab given by itself until the cancer starts growing again.
  • VEGF vascular- endothelial growth factor
  • Ramucirumab can also be used to treat advanced NSCLC, e.g., LU AD.
  • This therapeutic agent is an antibody that targets a VEGF receptor. It helps stop the formation of new blood vessels. This therapeutic agent is often combined with chemotherapy, typically after another treatment stops working.
  • Either of these therapeutic agents might also be used along with the targeted therapeutic agent erlotinib (see below) as the first treatment in subjects whose cancer cells have certain EGFR gene mutations.
  • NSCLCs e.g., LUADs have changes in the KRAS gene that cause them to make an abnormal form of the KRAS protein. This abnormal protein helps the cancer cells grow and spread.
  • NSCLC e.g., LUAD
  • KRAS G12C mutation a specific type of KRAS gene change
  • NSCLCs e.g., LUADs with this mutation are often resistant to other targeted therapeutic agents such as EGFR inhibitors (see below).
  • Sotorasib and adagrasib are therapeutic agents known as KRAS inhibitors. They work by attaching to the KRAS G12C protein, which helps keep cancer cells from growing. One of these therapeutic agents may be helpful if the subject has advanced NSCLC, e.g., LUAD, and the cancer cells are found to have the KRAS G12C mutation.
  • These therapeutic agents are administered as pills, typically once or twice a day.
  • Epidermal growth factor receptor is a protein on the surface of cells. It normally helps the cells grow and divide. Sometimes NSCLC, e.g., LUAD cells have high levels of overactive EGFR, which makes them grow faster. Therapeutic agents called EGFR inhibitors can block the signal from EGFR that tells the cells to grow. Some of these therapeutic agents can be used to treat NSCLC, e.g., LUAD.
  • EGFR inhibitors used in NSCLC include erlotinib, afatinib, gefitinib, osimertinib and dacomitinib.
  • advanced NSCLC e.g., LU AD one of these therapeutic agents is often used as the first treatment for advanced NSCLCs, e.g., LUADs that have certain mutations in the EGFR gene. Most of these therapeutic agents are used alone, although erlotinib can also be used along with a targeted therapeutic agent that affects new blood vessel growth (see above).
  • LU AD osimertinib can also be used as an adjuvant (additional) treatment after surgery for some earlier stage lung cancers with certain EGFR gene mutations.
  • EGFR inhibitors can be used to target cells with the T790M mutation.
  • EGFR inhibitors can often shrink tumors for several months or more. But eventually these therapeutic agents stop working for most subjects, usually because the cancer cells develop another mutation in the EGFR gene.
  • T790M One such mutation is known as T790M.
  • Osimertinib is an EGFR inhibitor that often works against cells with the T790M mutation.
  • a subset of EGFR inhibitors can be used to target cells with an exon 20 mutation. While the EGFR inhibitors listed above can help many subjects whose cancer cells have EGFR gene mutations, they do not help everyone. For example, cancer cells with an EGFR gene change known as an exon 20 insertion mutation are much less likely to affected by these therapeutic agents. However, other therapeutic agents that target cancer cells with an exon 20 mutation are now available.
  • Amivantamab is a bispecific antibody that targets two proteins that help cancer cells grow: EGFR and MET. This therapeutic agent is given as an intravenous infusion.
  • Mobocertinib is a therapeutic agent that targets the EGFR protein in a slightly different way. This therapeutic agent is administered as pills, typically once a day. These therapeutic agents can be used to treat advanced NSCLC, e.g., LU AD when the cancer cells have an exon 20 mutation, typically after chemotherapy has been tried.
  • NSCLCs e.g., LUADs
  • ALK gene rearrangement produces an abnormal ALK protein that causes the cells to grow and spread.
  • Therapeutic agents that target the abnormal ALK protein include crizotinib, ceritinib, alectinib, brigatinib, and lorlatinib. These therapeutic agents can often shrink tumors in subjects whose advanced lung cancers have an ALK gene change. Although they can help after chemotherapy has stopped working, they are often used instead of chemotherapy in subjects whose cancers have an ALK gene rearrangement. These therapeutic agents are administered as pills.
  • NSCLCs e.g.. LUADs
  • R OS1 a gene that has a rearrangement in a gene called R OS1.
  • This change is most often seen in subjects who have the adenocarcinoma subtype of NSCLC, i.e., LU AD and whose tumors are also negative for ALK, KRAS and EGFR mutations.
  • the ROS1 gene rearrangement is similar to the ALK gene rearrangement, and some therapeutic agents can work on cells with either ALK or ROS1 gene changes.
  • Therapeutic agents that target the abnormal ROS1 protein include crizotinib, ceritinib, lorlatinib, lorbrena, and entrectinib.
  • These therapeutic agents can often shrink tumors in subjects whose advanced lung cancers have a ROS1 gene change.
  • Crizotinib or ceritinib might be used as first treatment, instead of chemotherapy, and lorlatinib may be used when crizotinib or ceritinib have stopped working.
  • Entrectinib can be used in subjects with metastatic NSCLC, e.g., LU AD that has a ROS1 gene change.
  • These therapeutic agents are administered as pills.
  • NSCLCs e.g., LUADs
  • the cells have changes in the BRAF gene. Cells with these changes make an altered BRAF protein that helps them grow.
  • Dabrafenib is a type of therapeutic agent known as a BRAF inhibitor, which attacks the BRAF protein directly.
  • Trametinib is known as a MEK inhibitor because it attacks the related MEK proteins.
  • These therapeutic agents can be used together to treat metastatic NSCLC, e.g., LU AD if it has a certain type of BRAF gene change. These therapeutic agents are administered as pills or capsules each day.
  • NSCLCs e.g., LUADs
  • the cells have certain changes in the RET gene that cause them to make an abnormal form of the RET protein.
  • This abnormal protein helps the cells grow.
  • Selpercatinib and pralsetinib are therapeutic agents known as RET inhibitors. They work by attacking the RET protein. These therapeutic agents can be used to treat advanced NSCLC, e.g., LU AD if the cancer cells have certain types of RET gene changes. These therapeutic agents are administered by mouth as capsules, typically once or twice a day.
  • NSCLCs e.g., LUADs
  • the cells have changes in the MET gene that cause them to make an abnormal form of the MET protein. This abnormal protein helps the cells grow and spread.
  • Capmatinib and tepotinib are types of therapeutic agents known as MET inhibitors. They work by attacking the MET protein. These therapeutic agents can be used to treat metastatic NSCLC, e.g., LU AD if the cancer cells have certain types of MET gene changes.
  • Capmatinib is administered as pills, typically twice a day. Tepotinib is also administered as pills, but usually once a day.
  • Trastuzumab deruxtecan is an antibody-drug conjugate (ADC). It is composed of an antibody that targets the HER2 protein (trastuzumab), which is linked to a chemotherapeutic agent (deruxtecan). The antibody acts like a homing signal by attaching to the HER2 protein on cancer cells, bringing the chemotherapy directly to them.
  • ADC antibody-drug conjugate
  • This therapeutic agent can be used to treat NSCLC, e.g., LU AD that cannot be removed by surgery or that has spread, if the cancer cells have certain types of HER2 gene changes, and if at least one other treatment has already been tried.
  • This therapeutic agent is infused into a vein (IV). It is typically given once every 3 weeks.
  • NSCLCs e.g., LUADs
  • LUADs have changes in one of the NTRK genes.
  • Cells with these gene changes can lead to abnormal cell growth and cancer.
  • Larotrectinib and entrectinib target and disable the proteins made by the NTRK genes.
  • These therapeutic agents can be used in subjects with advanced lung cancer that is still growing despite other treatments and whose tumor has an NTRK gene change. These therapeutic agents are administered as pills, once or twice daily.
  • a sample analyzed using methods, kits and systems provided herein can be any biological sample including any processed sample that includes circulating tumor DNA (ctDNA) 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 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 lung cancer, e.g., SCLC cancer, etc.
  • a human subject is a subject identified as needing SCLC/LUAD status screening.
  • a human subject is a subject identified as needing SCLC/LUAD status screening by a medical practitioner.
  • the subject may not have undergone previous treatments for cancer, such as the treatments recited in this disclosure. In other embodiments, the subject has undergone previous treatments for cancer, such as the treatments recited in this disclosure.
  • a subject has one or more biomarkers and/or risk factors for cancer, e.g., lung cancer, e.g., SCLC cancer, etc.
  • a human subject is identified as in need of SCLC/LUAD status screening based on an initial cancer diagnosis, e.g., a lung cancer diagnosis.
  • 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 a cancer, e.g., a lung cancer.
  • 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 circulating tumor DNA (ctDNA).
  • ctDNA circulating tumor DNA
  • a sample is derived from about 1 mL of blood obtained from the subject.
  • a sample is derived from about 0.5-5 mL of blood obtained from the subject, e.g., about 0.5 to about 2 mL, about 0.5 to 1.75 mL, about 0.5 to 1.5 mL, about 0.75 to 1.25 mL, about 0.9 to 1.1 mL, about 1 mL, about 2 mL, about 3 mL, about 4 mL, or about 5 mL of blood.
  • 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 the 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.
  • 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.
  • a method comprises isolating DNA (e.g., cfDNA) from a liquid biopsy sample.
  • DNA e.g., cfDNA
  • Various methods of isolating nucleic acids from a sample e.g., of isolating cfDNA from blood or plasma
  • 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).
  • 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.
  • 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.
  • 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.
  • 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
  • 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.
  • lysine Lys or K
  • arginine Arg or R
  • His or H histidine
  • Histone methylation only occurs at specific lysine and arginine sites of histone H3 and H4.
  • histone H3 lysine 4, 9, 26, 27, 36, 56, and 79 and arginine 2, 8, and 17 can be methylated.
  • 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.
  • 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., a lung cancer, stage of lung cancer, or subtype of lung cancer, e.g., SCLC or LU AD cancer.
  • a reference can represent SCLC cancer based on IHC testing.
  • a reference can represent LU AD cancer based on IHC testing.
  • a reference can correspond to a subject having lung cancer and/or a lung cancer subtype, e.g., SCLC or LU AD cancer.
  • a reference is a predetermined threshold. In some embodiments, the predetermined threshold has previously been shown to be capable of distinguishing LU AD and SCLC subjects (e.g., distinguish with an AUROC of greater than 0.5).
  • a reference is a measurement from a liquid biopsy sample. In some embodiments, a reference is a measurement from liquid biopsy samples obtained from a cohort of subjects. In some embodiments, a reference is a normalized sample. In some embodiments, a reference is a measurement obtained from liquid biopsy samples obtained from a cohort of subjects who have previously been determined to have lung cancer, including, e.g., LU AD and/or SCLC.
  • 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., SCLC cancer or LU AD cancer).
  • 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., SCLC cancer or LU AD cancer).
  • 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-scq) 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.
  • 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 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 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 enriched for a particular histone modification using an agent that binds the histone modification (e.g., immunoprecipitating using one or more antibodies that bind a target epitope).
  • an agent that binds the histone modification e.g., immunoprecipitating 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 Sei 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 C15210016 (available from Diagenode in Denville, NJ).
  • 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.
  • 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 scqucnccd 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 arc then analyzed, e.g., aligned and/or 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.
  • histone modifications at a given genomic loci can be quantified using sequencing data.
  • histone modifications can be quantified by counting the number of sequence reads that fall within a genomic loci (e.g., have at least one nucleotide overlapping with a genomic loci). In some embodiments, non-uniquely mapped and/or redundant sequence reads are discarded prior to quantifying histone modifications. In some embodiments, when quantifying histone modifications, sequence reads that fall within high noise regions of the genome are ignored.
  • sequence reads are adjusted on the basis of sequencing depth prior to counting. Adjusting on the basis of sequencing depth can include, e.g., quantile normalizing sequence reads to a common reference distribution. In some embodiments, sequence reads are adjusted on the basis of ChIP quality prior to counting. In some embodiments, sequence reads are normalized relative to aggregate counts across a set of regions (e.g., 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, 10,000 or more regions) previously determined to have DNAse hypersensitivity in most cell types. In some embodiments, an estimate of local background signal is subtracted from the count of sequence reads at each genomic loci.
  • regions e.g., 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, 10,000 or more regions
  • 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 transposomc 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 CaCE 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.
  • a method described herein comprises attaching (e.g., ligating) DNA adapters to cfDNA.
  • DNA adapters can be attached prior to, during, or after enrichment for a histone modification.
  • a method comprises amplifying cfDNA after attaching DNA adapters.
  • 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-scq 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).
  • 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. MNasc-scq 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 m 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.
  • 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 transposasc. 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.
  • 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.
  • 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).
  • BS-Seq Bisulfite sequencing
  • WGBS Whole-Genome Bisulfite Sequencing
  • BS-Seq Bisulfite sequencing
  • WGBS Whole-Genome Bisulfite Sequencing
  • genomic DNA is treated with sodium bisulfite and then sequenced, providing single-base resolution of methylated cytosines in the genome.
  • unmethylated cytosines are deaminated to uracils which, upon sequencing, are converted to thymidines.
  • 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.
  • methylated DNA can be sequenced using a method that comprises enriching for cfDNA that comprises methylated DNA. Enrichment can be accomplished e.g., using an agent that selectively binds methylated DNA (e.g., an antibody as in MeDIP-seq or a methyl-CpG-Binding Domain (MBD), as in MBD-seq).
  • an agent that selectively binds methylated DNA e.g., an antibody as in MeDIP-seq or a methyl-CpG-Binding Domain (MBD), as in MBD-seq.
  • an agent that binds methylated DNA is attached (e.g., via a covalent or noncovalent bond) to a physical support (e.g., a bead, a magnetic bead, an agarose bead, or a magnetic epoxy bead), wherein the attaching can be prior to, during, or after incubation with a sample.
  • a physical support e.g., a bead, a magnetic bead, an agarose bead, or a magnetic epoxy bead
  • 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.
  • DNA methylation at a given genomic loci can be quantified by sequencing methylated DNA.
  • DNA methylation at a genomic loci can be quantified by counting the number of sequence reads that overlap with the genomic loci (e.g., comprise at least one nucleotide that overlaps with the genomic loci).
  • Suitable DNA sequencing technologies include, e.g., next generation sequencing (NGS) approaches. Additional steps that are required to prepare DNA for sequencing via an appropriate sequencing approach can be incorporated into methods described herein.
  • NGS next generation sequencing
  • a method described herein comprises attaching (e.g., ligating) DNA adapters to cfDNA.
  • DNA adapters can be attached prior to, during, or after enrichment for a histone modification.
  • the present disclosure provides methods for obtaining a classifier, e.g., a validated classifier that can be used to determine SCLC/LUAD status.
  • a subject is determined to have a validated epigenetic profile indicative of an SCLC or LU AD cancer based on analysis of a biological sample, optionally of cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject, wherein the presence of the validated epigenetic profile has been determined using a validated classifier.
  • the validated classifier may be obtained by:
  • step (c) comparing the genomic profile determined in step (a) and the genomic profile determined in step (b), to identify genomic loci that have statistically different histone modification, chromatin accessibility, binding of transcription factor, and/or DNA methylation levels (“differential loci”);
  • a person of ordinary skill will appreciate that other methods can be used to obtain a classifier, e.g., a validated classifier that can be used to determine SCLC/LUAD status and that the present disclosure is not limited to classifiers obtained in accordance with this method.
  • the present disclosure includes the identification of exemplary genomic loci that are differentially modified and/or differentially accessible in SCLC vs. LU AD cancer. See Tables 1-3 which show the chromosomal coordinates of each genomic locus and whether they are correlated with SCLC or LUAD cancer (genomic loci in columns with “Genomic locus (SCLC)” in the header correlate with SCLC while genomic loci with “Genomic locus (LUAD)” in the header correlate with LUAD cancer). The genomic loci are sorted based on their chromosomal coordinates which are based on human genome build hgl9.
  • the present disclosure is not limited to methods that use the exact same chromosomal coordinates that are recited in Tables 1-13.
  • the present disclosure encompasses methods that use any of the genomic loci in Table 1-13 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 Table 1-13 encompasses methods that detect these marks anywhere within these genomic loci including within any subregions.
  • Table 2 references chrl:110800810-110801156 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 chrl: 110800810- 110801156, e.g., methods that detect and/or quantify H3K27ac modification within chrl:110800910-110801056, etc.
  • 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 arc located between the lower and upper coordinates of a genomic locus recited in Tables 1-13. 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 1-13. In some embodiments, a subregion may have the same central coordinate as a genomic locus recited in Tables 1-13.
  • a subregion may have a different central coordinate as a genomic locus recited in Tables 1-13. It is also to be understood that the lower/upper coordinates of the genomic loci in Tables 1-13 are approximate and that the present disclosure encompasses methods where any one or more of the genomic loci arc 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.
  • a classifier is generated using a set of differentially modified and/or differentially accessible genomic loci that are correlated with SCLC and a set of differentially modified and/or differentially accessible loci that are correlated with LU AD cancer. 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 SCLC are aggregated and counts from genomic loci that are correlated with LU AD cancer are aggregated. In some embodiments, a ratio of the aggregated SCLC and LU AD cancer counts is used to determine SCLC/LUAD status.
  • exemplary genomic loci from one or more of Tables 1-13 are used in a monomodal classifier, e.g., a classifier that uses a single histone modification (e.g., H3K4me3 or H3K27ac) or DNA methylation at one or more genomic loci for purposes of determining SCLC/LUAD status.
  • a monomodal classifier e.g., a classifier that uses a single histone modification (e.g., H3K4me3 or H3K27ac) or DNA methylation at one or more genomic loci for purposes of determining SCLC/LUAD status.
  • exemplary genomic loci from any one of Table 1-13, or any combination thereof are used in combination in a multimodal classifier, e.g., a classifier 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 determining SCLC/LUAD status.
  • 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 1-13.
  • 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, 30, 35, 40, 45, 50, 75, 100, 200, 300, 400, 500, 600, 800, 1,000, 1,500, 2,000, 3,000, 4,000, or more loci listed in one or more of Tables 1-13 (e.g., 1-200, 5-200, 10-200, 15-200, 20-200, 30-200, 40-200, 50-200, 60-200, 70-200, 80-200, 90-200, 100- 200, 1-150, 5-150, 10-150, 15-150, 20-150, 30-150, 40-150, 50-150, 60-150, 70-150, 80-150, 90-150, 100-150, 1-100, 5-100, 10-100, 15-100, 20-100, 30-100, 40-100, 50-100, 60-100, 70- 100, 80-100, 90-100).
  • 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 one or more of Tables 1-13. 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 one or more of Tables 1-13.
  • 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 13 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%.
  • Genomic loci demonstrating differential H3K4 methylation (in particular H3K4 trimethylation, H3K4me3) in SCLC vs. LU AD cancer are provided in Table 1 which shows the chromosomal coordinates of each genomic locus and whether they are correlated with SCLC or LU AD cancer (genomic loci in columns with “Genomic locus (SCLC)” in the header correlate with SCLC while genomic loci with “Genomic locus (LU AD)” in the header correlate with LU AD cancer). The genomic loci are sorted based on their chromosomal coordinates which are based on human genome build hgl9. [0247] A person of skill in the art will recognize that the methods disclosed herein do not require that every genomic locus listed in Table 1 be assessed for H3K4mc3 modification.
  • a subset of loci may be assessed for H3K4me3 modification.
  • Subsets of the genomic loci of Table 1 can be selected (e.g., for use in determining SCLC/LUAD status) 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, 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 SCLC/LUAD status. See also the Examples of the present disclosure for experiments showing that informative classifiers can be generated using many different combinations of the loci.
  • the present disclosure particularly includes, among other things, subsets of the genomic loci of Table 1, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 or higher, 5.0 or higher, 4.5 or higher, 4.0 or higher, 3.5 or higher, 3.0 or higher, 2.5 or higher, 2.0 or higher, 1.9 or higher, 1.8 or higher, 1.7 or higher, 1.6 or higher, 1.5 or higher, 1.4 or higher, 1.3 or higher, 1.2 or higher, 1.1 or higher, 1.0 or higher, 0.9 or higher, 0.8 or higher, 0.7 or higher, 0.6 or higher, or 0.5 or higher.
  • the present disclosure also includes subsets of the genomic loci of Table 1, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 to less than 6.0, 5.0 to less than 5.5, 4.5 to less than 5.0, 4.0 to less than 4.5, 3.8 to less than 4.0, 3.6 to less than 3.8, 3.4 to less than 3.6, 3.2 to less than 3.4, 3.0 to less than 3.2, 2.8 to less than 3.0, 2.6 to less than 2.8, 2.4 to less than 2.6, 2.2 to less than 2.4, 2.0 to less than 2.2, 1.8 to less than 2.0, 1.6 to less than 1.8, 1.4 to less than 1.6, 1.2 to less than 1.4, 1.0 to less than 1.2, 0.8 to less than 1.0, or 0.6 to less than 0.8.
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 1 (or any subset thereof) are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a number of loci identified in a Table 1 (or any subset thereof) having a lower bound selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, or 300 and an upper bound selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 is found to be differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • a reference e.g., a sample from a healthy subject or a subject with LU AD cancer
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 loci identified in Table 1 (e.g., about 1 to about 1,000, about 5 to about 3,000, about 10 to about 1000, about 5, about 10, about 15, about 20, about 25, about 30, about 35, about 40, about 45, about 50, about 55, about 60, about 65, about 70, about 75, about 80, about 85, about 90, about 95, about 100, about 105, about 110, about 115, about 120, about 125, about 130, about 135, about 140, about 145, or about 150 loci) are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • a reference e.g., a sample from a healthy subject or a subject with LU AD cancer
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if 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 Table 1 are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a percent of loci identified in Table 1 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% is found to be differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one (e.g., at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10) of the top 3, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 1 are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer) (wherein, e.g., the “top” 10 loci refers to the loci with 10 highest absolute log2(fold-changc) in Table 1).
  • SCLC/LUAD status e.g., SCLC status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 25 loci identified in Table 1 is differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 50 loci identified in Table 1 is differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least five of the top 10 loci identified in Table 1 are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least five of the top 25 loci identified in Table 1 are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least five of the top 50 loci identified in Table 1 are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 10 loci (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or 10) identified in Table 1 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 1 (or any subset thereof) in total are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 25 loci identified in Table 1 (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or 25) and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 1 (or any subset thereof) in total are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 50 loci (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or at least 25, at least 30, at least 35, at least 40, at least 45, or 50) identified in Table 1 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 1 (or any subset thereof) in total are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least five of the top 25 loci identified in Table 1 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 1 (or any subset thereof) in total are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least five of the top 50 loci identified in Table 1 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 1 (or any subset thereof) in total are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • 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-
  • 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)
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, or 20 loci identified in Table 5 (or any subset thereof), e.g., of those loci listed as H3K4me3 loci, are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a number of loci identified in a Table 5 (or any subset thereof) having a lower bound selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, and 15 and an upper bound selected from 10, 15, and 20 is found to be differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1 , 2, 3, 4, 5, 10, 15 or 20 loci identified in Table 5 (e.g., about 1 to about 20, about 2 to about 20, about 5 to about 20, about 5, about 10, about 15, about 20 loci) are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if 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 Table 5 are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a percent of loci identified in 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% is found to be differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, or 130 loci identified in Table 12 (or any subset thereof) are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a number of loci identified in a Table 12 (or any subset thereof) having a lower bound selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100 and an upper bound selected from 10, 15, 20, 25, 50, 75, 100, or 135 is found to be differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 loci identified in Table 12 (e.g., about 1 to about 135, about 5 to about 135, about 10 to about 135, about 1 to about 135, about 1 to about 135, about 1 to about 135, about 1 to about 135, about 1 to about 135, about 1 to about 135, about 1 to about 135, about 1 to about 100, about 2 to about 135, about 5 to about 135, about 10 to about 135, about 20 to about 135, about 25 to about 135, about 50 to about 135, about 20 to about 135, about 50 to about 135, about 50 to about 100, about 5, about 10, about 15, about 20, about 25, about 30, about 35, about 40, about 45, about 50, about 55, about 60, about 65, about 70, about 75, about 80, about 85, about 90, about 95, about 100, about 105, about 110, about 115, about 120, about
  • a sample or subject from which the sample is obtained or derived is determined to have a particular’ SCLC/LUAD status (e.g., SCLC status) if 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 Table 12 are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a percent of loci identified in Table 12 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% is found to be differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LUAD status) if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or 15 loci identified in Table 13 (or any subset thereof) are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • SCLC/LUAD status e.g., LUAD status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LUAD status) if 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17 loci identified in Table 13 are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • SCLC/LUAD status e.g., LUAD status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LUAD status) if 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 Table 13 are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • a reference e.g., a sample from a healthy subject or a subject with SCLC.
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LU AD status) if at least a percent of loci identified in Table 13 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% is found to be differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • a reference e.g., a sample from a healthy subject or a subject with SCLC.
  • Genomic loci demonstrating differential H3K27ac modification in SCLC vs. LU AD cancer are provided in Table 2 which shows the chromosomal coordinates of each genomic locus and whether they are correlated with SCLC or LU AD cancer (genomic loci in columns with “Genomic locus (SCLC)” in the header correlate with SCLC while genomic loci with “Genomic locus (LUAD)” in the header correlate with LU AD cancer).
  • the genomic loci are sorted based on their chromosomal coordinates which are based on human genome build hgl9.
  • a person of skill in the art will recognize that the methods disclosed herein do not require that every genomic locus listed in Table 2 be assessed for H3K27ac modification.
  • a subset of loci may be assessed for H3K27ac modification.
  • Subsets of the genomic loci of Table 2 can be selected (e.g., for use in determining SCLC/LUAD status) 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.
  • Such subsets of loci of Table 2, 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 SCLC/LUAD status. See also the Examples of the present disclosure for experiments showing that informative classifiers can be generated using many different combinations of the loci.
  • the present disclosure particularly includes, among other things, subsets of the genomic loci of Table 2, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 or higher, 5.0 or higher, 4.5 or higher, 4.0 or higher, 3.5 or higher, 3.0 or higher, 2.5 or higher, 2.0 or higher, 1.9 or higher, 1.8 or higher, 1.7 or higher, 1.6 or higher, 1.5 or higher, 1.4 or higher, 1.3 or higher, 1.2 or higher, 1.1 or higher, 1 .0 or higher, 0.9 or higher, 0.8 or higher, 0.7 or higher, 0.6 or higher, or 0.5 or higher.
  • the present disclosure also includes subsets of the genomic loci of Tabic 2, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 to less than 6.0, 5.0 to less than 5.5, 4.5 to less than 5.0, 4.0 to less than 4.5, 3.8 to less than 4.0, 3.6 to less than 3.8, 3.4 to less than 3.6, 3.2 to less than 3.4, 3.0 to less than 3.2, 2.8 to less than 3.0, 2.6 to less than 2.8, 2.4 to less than 2.6, 2.2 to less than 2.4, 2.0 to less than 2.2, 1.8 to less than 2.0, 1.6 to less than 1.8, 1.4 to less than 1.6, 1.2 to less than 1.4, 1.0 to less than 1.2, 0.8 to less than 1.0, or 0.6 to less than 0.8.
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 2 (or any subset thereof) are H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a number of loci identified in a Table 2 (or any subset thereof) having a lower bound selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, or 300 and an upper bound selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 is found to be H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • a reference e.g., a sample from a healthy subject or a subject with LU AD cancer
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 loci identified in Table 2 (e.g., about 1 to about 1,000, about 5 to about 3,000, about 10 to about 1000, about 1 to about 900, about 1 to about 800, about 1 to about 700, about 1 to about 600, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, , about 50 to about 200, about 20 to about 150, about 50 to about 150, about 50 to about 100, about 5, about 10, about 15, about 20, about 25, about 30, about 35, about 40, about 45, about 50, about 55, about 60, about 65, about 70, about 75, about 80, about 85, about 90, about 95, about 100
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if 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 Table 2 are H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a percent of loci identified in Table 2 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% is found to be H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one (e.g., at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10) of the top 3, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 2 are H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer) (wherein, e.g., the “top” 10 loci refers to the loci with 10 highest absolute log2(fold-change) in Table 2).
  • SCLC/LUAD status e.g., SCLC status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 10 loci identified in Table 2 is H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 25 loci identified in Table 2 is H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 50 loci identified in Table 2 is H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least five of the top 10 loci identified in Table 2 arc H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least five of the top 25 loci identified in Table 2 are H3K27ac modified as compared to a reference (e.g.. a sample from a healthy subject or a subject with LUAD cancer).
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least five of the top 50 loci identified in Table 2 are H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 10 loci (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or 10) identified in Table 2 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 2 (or any subset thereof) in total are H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 25 loci identified in Table 2 (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or 25) and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 2 (or any subset thereof) in total are H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 50 loci (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or at least 25, at least 30, at least 35, at least 40, at least 45, or 50) identified in Table 2 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 2 (or any subset thereof) in total are H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least five of the top 25 loci identified in Table 2 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 2 (or any subset thereof) in total are H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least five of the top 50 loci identified in Table 2 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 2 (or any subset thereof) in total are H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • 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%
  • 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
  • Genomic loci demonstrating differential H3K27ac modification in different subtypes of SCLC are provided in Table 4, which shows chromosomal coordinates of each genomic locus and which subtype they are associated with.
  • a method described herein comprises assessing H3K27ac modifications at 1, 2, 3, or 4 of the genomic loci listed in Table 4.
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 6, or 7 loci identified in Table 5 (or any subset thereof), e.g., of those loci listed as H3K27ac loci, are differentially H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if 1, 2, 3, 4, 5, 6, or 7 loci of Table 5 arc differentially H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, or 5500 loci identified in Table 6 (or any subset thereof) are differentially H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a number of loci identified in a Table 6 (or any subset thereof) having a lower bound selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, or 300 and an upper bound selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, or 5500 is found to be differentially H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • a reference e.g., a sample from a healthy subject or a subject with LU AD cancer
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 loci identified in Table 6 (e.g., about 1 to about 5500, about 5 to about 5500, about 10 to about 5500, about 1 to about 1000, about 1 to about 900, about 1 to about 800, about 1 to about 700, about 1 to about 600, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, , about 50 to about 200, about 20 to about 150, about 50 to about 150, about 50 to about 100, about 5, about 10, about 15, about 20, about 25, about 30, about 35, about 40, about 45, about 50, about 55, about 60, about 65, about 70, about 75, about 80, about 85,
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if 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 Table 6 are differentially H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a percent of loci identified in Table 6 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% is found to be differentially H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LU AD status) if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, or 5000 loci identified in Table 7 (or any subset thereof) are differentially H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • a reference e.g., a sample from a healthy subject or a subject with SCLC.
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LU AD status) if at least a number of loci identified in a Table 7 (or any subset thereof) having a lower bound selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, or 300 and an upper bound selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, or 5000 is found to be differentially H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • a reference e.g., a sample from a healthy subject or a subject with SCLC.
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LU AD status) if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 loci identified in Table 7 (e.g., about 1 to about 5000, about 5 to about 5000, about 10 to about 5000, about 1 to about 1000, about 1 to about 900, about 1 to about 800, about 1 to about 700, about 1 to about 600, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, , about 50 to about 200, about 20 to about 150, about 50 to about 150, about 50 to about 100, about 5, about 10, about 15, about 20, about 25, about 30, about 35, about 40, about 45, about 50, about 55, about 60, about 65, about 70, about 75, about 80, about 85
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LU AD status) if 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 Table 7 are differentially H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • a reference e.g., a sample from a healthy subject or a subject with SCLC.
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LU AD status) if at least a percent of loci identified in Table 7 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% is found to be differentially H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • a reference e.g., a sample from a healthy subject or a subject with SCLC.
  • Genomic loci demonstrating differential DNA methylation in SCLC vs. LU AD cancer are provided in Table 3 which shows the chromosomal coordinates of each genomic locus and whether they are correlated with SCLC or LU AD cancer (genomic loci in columns with “Genomic locus (SCLC)” in the header correlate with SCLC while genomic loci with “Genomic locus (LU AD)” in the header correlate with LUAD cancer).
  • the genomic loci are sorted based on their chromosomal coordinates which are based on human genome build hgl9.
  • a person of skill in the art will recognize that the methods disclosed herein do not require that every genomic locus listed in Table 3 be assessed for DNA methylation. Instead, a subset of loci may be assessed for DNA methylation. Subsets of the genomic loci of Table 3 can be selected (e.g., for use in determining SCLC/LUAD status) 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.
  • Such subsets of loci of Table 3, 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 SCLC/LUAD status. See also the Examples of the present disclosure for experiments showing that informative classifiers can be generated using many different combinations of the loci.
  • the present disclosure particularly includes, among other things, subsets of the genomic loci of Table 3, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 or higher, 5.0 or higher, 4.5 or higher, 4.0 or higher, 3.5 or higher, 3.0 or higher, 2.5 or higher, 2.0 or higher, 1.9 or higher, 1.8 or higher, 1.7 or higher, 1.6 or higher, 1.5 or higher, 1.4 or higher, 1.3 or higher, 1.2 or higher, 1.1 or higher, 1.0 or higher, 0.9 or higher, 0.8 or higher, 0.7 or higher, 0.6 or higher, or 0.5 or higher.
  • the present disclosure also includes subsets of the genomic loci of Table 3, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 to less than 6.0, 5.0 to less than 5.5, 4.5 to less than 5.0, 4.0 to less than 4.5, 3.8 to less than 4.0, 3.6 to less than 3.8, 3.4 to less than 3.6, 3.2 to less than 3.4, 3.0 to less than 3.2, 2.8 to less than 3.0, 2.6 to less than 2.8, 2.4 to less than 2.6, 2.2 to less than 2.4, 2.0 to less than 2.2, 1 .8 to less than 2.0, 1 .6 to less than 1 .8, 1 .4 to less than 1 .6, 1 .2 to less than 1.4, 1.0 to less than 1.2, 0.8 to less than 1.0, or 0.6 to less than 0.8.
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, or 5,000 loci identified in Table 3 (or any subset thereof) are differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a number of loci identified in a Table 3 (or any subset thereof) having a lower bound selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, or 300 and an upper bound selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000 is found to be differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • a reference e.g., a sample from a healthy subject or a subject with LU AD cancer
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 loci identified in Table 3 (e.g., about 1 to about 1,000, about 5 to about 3,000, about 10 to about 1000, about 25 to about 200, about 1 to about 900, about 1 to about 800, about 1 to about 700, about 1 to about 600, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, , about 50 to about 200, about 20 to about 150, about 50 to about 150, about 50 to about 100, about 5, about 10, about 15, about 20, about 25, about 30, about 35, about 40, about 45, about 50, about 55, about 60, about 65, about 70, about 75, about 80, about 85, about 90
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if 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 Table 3 are differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a percent of loci identified in Table 3 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% is found to be differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one (e.g., at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10) of the top 3, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 3 are differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer) (wherein, e.g., the “top” 10 loci refers to the loci with 10 highest absolute log2(fold-change) in Table 3).
  • SCLC/LUAD status e.g., SCLC status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 10 loci identified in Table 3 is differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 25 loci identified in Table 3 is differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 50 loci identified in Table 3 is differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least five of the top 10 loci identified in Table 3 are differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least five of the top 25 loci identified in Table 3 are differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least five of the top 50 loci identified in Table 3 are differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 10 loci (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or 10) identified in Table 3 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 3 (or any subset thereof) in total are differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 25 loci identified in Table 3 (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or 25) and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 3 (or any subset thereof) in total are differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least one of the top 50 loci (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or at least 25, at least 30, at least 35, at least 40, at least 45, or 50) identified in Table 3 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 3 (or any subset thereof) in total are differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least five of the top 25 loci identified in Table 3 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 3 (or any subset thereof) in total arc differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least five of the top 50 loci identified in Table 3 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 3 (or any subset thereof) in total are differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • 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
  • 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.
  • a log2(fold-change) e.g., a log2(fold-change) of at
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, or 4 loci identified in Table 5 (or any subset thereof), e.g., of those loci listed as MBD genomic loci, are differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if 1, 2, 3, or 4 loci of Table 5 are differentially methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, 300, 350, 400, 450, 500, 600, or 650 loci identified in Table 8 (or any subset thereof) are differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a number of loci identified in a Table 8 (or any subset thereof) having a lower bound selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, or 300 and an upper bound selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 600, or 650 is found to be differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD cancer).
  • a reference e.g., a sample from a healthy subject or a subject with LUAD cancer
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 loci identified in Table 8 (e.g., about 1 to about 650, about 5 to about 650, about 10 to about 650, about 1 to about 600, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, , about 50 to about 200, about 20 to about 150, about 50 to about 150, about 50 to about 100, about 5, about 10, about 15, about 20, about 25, about 30, about 35, about 40, about 45, about 50, about 55, about 60, about 65, about 70, about 75, about 80, about 85, about 90, about 95, about 100, about 105, about 110, about 115, about 120, about
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if 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 Table 8 are differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a percent of loci identified in Table 8 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% is found to be differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD cancer).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LU AD status) if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, 300, 350, 400, 450, 500, or 600 loci identified in Table 9 (or any subset thereof) are differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • SCLC/LUAD status e.g., LU AD status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LU AD status) if at least a number of loci identified in a Table 9 (or any subset thereof) having a lower bound selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, or 300 and an upper bound selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, or 600 is found to be differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • a reference e.g., a sample from a healthy subject or a subject with SCLC.
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LU AD status) if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 loci identified in Table 9 (e.g., about 1 to about 600, about 5 to about 600, about 10 to about 600, about 1 to about 550, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, , about 50 to about 200, about 20 to about 150, about 50 to about 150, about 50 to about 100, about 5, about 10, about 15, about 20, about 25, about 30, about 35, about 40, about 45, about 50, about 55, about 60, about 65, about 70, about 75, about 80, about 85, about 90, about 95, about 100, about 105, about 110, about 115, about 120, about 125
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LUAD status) if 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 Table 9 are differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • SCLC/LUAD status e.g., LUAD status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LUAD status) if at least a percent of loci identified in Table 9 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% is found to be differentially DNA methylated as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • a reference e.g., a sample from a healthy subject or a subject with SCLC.
  • Genomic loci provided in Tables 1-13 can also demonstrate differential chromatin accessibility or transcription factor binding in SCLC cancer vs. LUAD cancer.
  • 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.
  • SCLC/LUAD status may be determined by detecting and quantifying chromatin accessibility at one or more genomic loci in Table 1 in accordance with the section above discussing exemplary genomic loci with differential H3K4mc3 modifications.
  • chromatin accessibility corresponds and/or is correlated with H3K27ac modifications.
  • SCLC/LUAD status may be determined by detecting and quantifying chromatin accessibility at one or more genomic loci in Table 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.
  • SCLC/LUAD status may be determined by detecting and quantifying chromatin accessibility at one or more genomic loci in Table 3 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.
  • binding of RNA pol II corresponds and/or is correlated with H3K4me3 modifications.
  • SCLC/LUAD status may be determined by detecting and quantifying binding of RNA pol II at one or more genomic loci in Table 1 in accordance with the section above discussing exemplary genomic loci with differential H3K4me3 modifications.
  • binding of p300, mediator complex, cohesin complex or RNA pol II corresponds and/or is correlated with H3K27ac modifications.
  • SCLC/LUAD status 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 Table 2 in accordance with the section above discussing exemplary genomic loci with differential H3K27ac modifications.
  • binding of NKX2-1, ASCL1, POU2F3, NEURODI, YAP1, MYC, SOX2, or HNF4a corresponds and/or is correlated with histone methylation (e.g., H3K4me3), histone acetylation (e.g., H3K27ac) or DNA methylation.
  • histone methylation e.g., H3K4me3
  • histone acetylation e.g., H3K27ac
  • SCLC/LUAD status may be determined by detecting and quantifying binding of NKX2-1, ASCL1, POU2F3, NEURODI, YAP1, MYC, SOX2, or HNF4a at one or more genomic loci in Tables 1-3 in accordance with the sections above discussing exemplary genomic loci with differential histone methylation (e.g., H3K4me3), histone acetylation (e.g., H3K27ac) or DNA methylation.
  • differential histone methylation e.g., H3K4me3
  • histone acetylation e.g., H3K27ac
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, or 5000 loci identified in Table 10 (or any subset thereof) have differential chromatin accessibility as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD).
  • SCLC/LUAD status e.g., SCLC status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a number of loci identified in a Table 10 (or any subset thereof) having a lower bound selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, or 300 and an upper bound selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, or 5000 is found to have differential chromatin accessibility as compared to a reference (e.g., a sample from a healthy subject or a subject with LU AD).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 loci identified in Table 10 (e.g., about 1 to about 5000, about 5 to about 5000, about 10 to about 5000, about 1 to about 1000, about 1 to about 900, about 1 to about 800, about 1 to about 700, about 1 to about 600, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, , about 50 to about 200, about 20 to about 150, about 50 to about 150, about 50 to about 100, about 5, about 10, about 15, about 20, about 25, about 30, about 35, about 40, about 45, about 50, about 55, about 60, about 65, about 70, about 75, about 80, about 85,
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if 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 Table 10 have differential chromatin accessibility as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., SCLC status) if at least a percent of loci identified in Table 10 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% is found to have differential chromatin accessibility as compared to a reference (e.g., a sample from a healthy subject or a subject with LUAD).
  • SCLC/LUAD status e.g., SCLC status
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LUAD status) if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, or 4500 loci identified in Table 11 (or any subset thereof) have differential chromatin accessibility as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • SCLC/LUAD status e.g., LUAD status
  • a subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LUAD status) if at least a number of loci identified in a Table 11 (or any subset thereof) having a lower bound selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, or 300 and an upper bound selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, or 4500 is found to have differential chromatin accessibility as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • a reference e.g., a sample from a healthy subject or a subject with SCLC.
  • a sample or subject from which the sample is obtained or derived is determined to have a particular’ SCLC/LUAD status (e.g., LUAD status) if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 loci identified in Table 11 (e.g., about 1 to about 4500, about 5 to about 4500, about 10 to about 4500, about 1 to about 1000, about 1 to about 900, about 1 to about 800, about 1 to about 700, about 1 to about 600, about 1 to about 500, about 1 to about 400, about 1 to about 300, about 1 to about 200, about 1 to about 100, about 2 to about 200, about 5 to about 200, about 10 to about 200, about 20 to about 200, about 25 to about 200, , about 50 to about 200, about 20 to about 150, about 50 to about 150, about 50 to about 100, about 5, about 10, about 15, about 20, about 25, about 30, about 35, about 40, about 45, about 50, about 55, about 60, about 65, about 70, about 75, about 80, about
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g., LU AD status) if 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 Table 11 have differential chromatin accessibility as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • a sample or subject from which the sample is obtained or derived is determined to have a particular SCLC/LUAD status (e.g.
  • LU AD status if at least a percent of loci identified in Table 11 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% is found to have differential chromatin accessibility as compared to a reference (e.g., a sample from a healthy subject or a subject with SCLC).
  • a reference e.g., a sample from a healthy subject or a subject with SCLC.
  • Methods, kits and systems of the present disclosure include analysis of differentially modified and/or differentially accessible genomic loci to determine the SCLC/LUAD status of a lung cancer.
  • Methods, kits and systems of the present disclosure can be used in any of a variety of applications.
  • methods, kits and systems of the present disclosure can be used in detecting and/or treating cancers based on SCLC/LUAD status.
  • Methods, kits and systems of the present disclosure can also be used to detect or determine resistance of a lung cancer, e.g., LU AD cancer to a therapy or transformation of a lung cancer, e.g., from LU AD to SCLC.
  • 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 cancer screening), sufficient characteristics of cancer to support a medically reasonable suspicion that the subject is likely suffering from cancer, e.g., lung cancer.
  • Detection of early-stage cancer 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.
  • methods, kits, and systems of the present disclosure can be applied to a human subject that has increased susceptibility for lung cancer (including SCLC and/or LU AD).
  • exemplary factors that increase susceptibility for lung cancer include a history of smoking, exposure to secondhand smoke, exposure to certain toxins, and family history.
  • kits and systems of the present disclosure can be applied to a symptomatic human subject.
  • 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 cancer screening), sufficient characteristics of cancer to support a medically reasonable suspicion that the subject is likely suffering from lung cancer.
  • a sample from a subject can be assayed according to one or more embodiments of the present disclosure to determine if the lung cancer is SCLC cancer or LU AD cancer.
  • a sample from a subject, where the subject has a lung cancer that is known or suspected of having SCLC cancer (or LU AD cancer) can be assayed according to one or more embodiments of the present disclosure to determine if the lung cancer is in fact SCLC cancer (or LU AD cancer).
  • methods, kits and systems of the present disclosure can be used to determine that a subject has SCLC cancer that correlates with a prior determination based on IHC testing. In some embodiments, methods, kits and systems of the present disclosure can be used to determine that a subject has LU AD cancer that correlates with a prior determination based on IHC testing.
  • methods, kits and systems of the present disclosure can be used to validate or confirm a prior determination that a subject has SCLC cancer, optionally SCLC cancer that correlates with IHC testing. 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 LU AD cancer, optionally LU AD cancer that correlates with IHC testing.
  • methods, kits and systems of the present disclosure are used to identify and detect new SCLC or LU AD related categories that are independent of IHC testing. For example, instead of training the classifier on samples from cohorts that were defined based on IHC testing, classifiers are trained on samples from cohorts that are defined based on whether they respond or do not respond to a particular therapeutic agent. The resulting classifiers are then used to identify subjects that are more likely to respond to the therapeutic agent independent of any IHC testing.
  • SCLC/LUAD status is not limited to SCLC and LU AD status based on IHC or other histological testing but can encompass any SCLC or LU AD related categories including whether a subject will or will not respond to a particular therapeutic agent.
  • the present disclosure provides, among other things, methods, kits and systems particularly useful for the diagnosis and treatment of early-stage cancer.
  • SCLC cancer detection in accordance with the present disclosure is carried out annually, and/or in which a subject is asymptomatic at time of detecting, methods, kits and systems of the present disclosure are especially likely to detect early-stage SCLC cancer including transformed SCLC.
  • detecting in accordance with methods, kits and systems of the present disclosure reduces cancer mortality, e.g., by early cancer diagnosis.
  • detecting in accordance with methods, kits and systems of the present disclosure is performed when a subject with LU AD cancer (or more generally a NSCLC cancer) is being treated with a therapeutic agent that can lead to transformation from LU AD cancer (or more generally a NSCLC cancer) to SCLC cancer, e.g., in epidermal growth factor receptor (EGFR) mutant LU AD cancer after treatment with tyrosine kinase inhibitors (TKIs), in anaplastic lymphoma kinase (ALK)-positive LU AD cancer after treatment with ALK inhibitors, in wild-type EGFR or ALK LU AD cancer treated with immunotherapy.
  • EGFR epidermal growth factor receptor
  • TKIs tyrosine kinase inhibitors
  • ALK anaplastic lymphoma kinase
  • SCLC/LUAD status determination in accordance with the present disclosure is performed once for a given subject or multiple times for a given subject. In various embodiments, SCLC/LUAD status 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 SCLC/LUAD status. In other instances, methods, kits and systems disclosed herein will be indicative of SCLC/LUAD status but not definitive for SCLC/LUAD status. In various instances in which methods, kits and systems of the present disclosure are used to determine SCLC/LUAD status, 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 IHC or other histological testing.
  • SCLC/LUAD status determination is followed by treatment of cancer.
  • treatment of cancer includes administration of a therapeutic regimen including one or more cancer therapies provided herein, including without limitation one or more of an SCLC or LU AD therapy, surgery, radiation, endocrine therapy, chemotherapy, and/or immunotherapy.
  • treatment of cancer includes administration of a therapeutic regimen including one or more treatments provided herein as available, appropriate, and/or preferred for a particular SCLC/LUAD status.
  • methods, kits and systems can be used to determine whether a particular subject and/or cancer is likely to be and/or is characterized as responsive to a SCLC or LUAD therapeutic agent. In some such embodiments, methods, kits and systems can be followed by treatment of the subject with a SCLC or LUAD therapeutic agent.
  • methods, kits and systems can be used to determine whether a particular subject and/or cancer is likely to be and/or is characterized as resistant to, non-responsive to, or not recommended treatment with a SCLC or LUAD therapeutic agent.
  • methods, kits and systems can be followed by treatment with one or more of surgery and/or radiation, HER2-targeted therapy (if HER2-positive), endocrine therapy (if positive for a hormone receptor such as estrogen receptor), chemotherapy and immunotherapy instead of a SCLC or LUAD therapeutic agent.
  • Responsiveness can refer to the ability or likelihood of a therapy to cause a reduction in tumor size or inhibit tumor growth or metastasis.
  • Responsiveness can refer to improvement in prognosis (e.g., increased time to cancer recurrence or increased life expectancy, e.g., overall survival, recurrence-free survival, metastasis-free survival, or disease-free survival). Responsiveness can refer to achievement of a treatment benefit, including e.g., improvement in one or more symptoms of cancer, e.g., lung cancer.
  • Responsiveness can be measured quantitatively (e.g., as in the case of tumor size; as in the case of measurement of 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 complete remission” (cCR), “clinical partial remission” (cPR), “clinical stable disease” (cSD), “clinical progressive disease” (cPD), or other qualitative criteria).
  • CBR clinical benefit
  • Resistance can refer to the inability or unlikelihood of a therapy to achieve a desired therapeutic effect (e.g., a reduction in tumor size, improvement in prognosis, or other treatment benefit such as, e.g., improvement in one or more symptoms of cancer) in a subject and/or cancer. Resistance includes both acquired and 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 and/or cancer 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).
  • methods, kits and systems can be used to detect the clinical efficacy of a course of therapy for cancer, e.g., lung cancer.
  • methods and/or compositions of the present disclosure could be used to determine the presence, absence, or SCLC/LUAD status of a lung cancer in a subject 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 presence, absence, or SCLC/LUAD status of a lung cancer including, for example measurements of tumor size or character by techniques such as CT, PET, mammogram, ultrasound, palpation, histology, caliper measurement after biopsy or surgical resection, or by various qualitative, quantitative, or semi quantitative scoring systems including without limitation based on IHC testing, residual cancer burden (Symmans et al., J Clin Oncol (2007) 25:4414-4422, incorporated by reference herein in its entirety) or Miller-Payne score (Ogston et al., Breast (2003) 12:320-327, incorporated by reference herein in its entirety) in a qualitative fashion like “pathological complete response” (pCR), “clinical complete remission” (cCR), “clinical partial remission” (cPR), “clinical stable disease” (cSD), or “clinical progressive disease” (cPD).
  • pathological complete response pCR
  • methods, kits, and systems described herein can be used to monitor progression of disease in a subject.
  • monitoring progression entails obtaining and characterizing samples from a subject at at least a first and a second time point.
  • a subject has already been diagnosed with lung cancer (e.g., SCLC or LU AD).
  • a subject has been determined to have lung cancer and therapy is administered before or close to (e.g., the same day as) the first time point or between the first time point and the second time point; in such embodiments, determination of SCLC/LUAD status at at least the first and the second time points can be used to monitor treatment efficacy and/or determine when a change in therapy should be made.
  • a subject has previously been diagnosed with LU AD at the first time point, a LU AD therapy is being or will be administered to the subject, and disease status can be monitored for transformation into SCLC, which can be useful, e.g., for determining whether a change to an SCLC therapy should be made.
  • treatment efficacy can be monitored, e.g., by using a method described herein to determine a decrease or increase in disease state signal, which can be useful, e.g., for determining whether an administered therapy is effective and/or whether a change in therapy should be made.
  • a lung cancer has gone into remission for a subject (e.g., the subject has minimal residual disease).
  • methods, kits, and systems described herein can be useful, e.g., for detecting reoccurrence of cancer, and can be faster, less expensive, and/or less invasive than, e.g., approaches that rely on tissue biopsies and/or imaging techniques.
  • methods, kits and systems for SCLC/LUAD status 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.
  • 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.
  • methods, kits and systems for SCLC/LUAD status determination can inform decision making relating to whether health insurance providers reimburse a healthcare cost payer or recipient (or not), e.g., for (1) SCLC/LUAD status 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 SCLC/LUAD status.
  • SCLC/LUAD status determination e.g., reimbursement for detecting otherwise unavailable, available only for periodic/regular detecting, or available only for temporally- and/or incidentally- motivated detecting
  • treatment including initiating, maintaining, and/or altering therapy, e.g., based on the determined SCLC/LUAD status.
  • methods, kits and systems for SCLC/LUAD status determination 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.
  • a party seeking reimbursement or cost reduction can provide results of SCLC/LUAD status determination conducted in accordance with the present disclosure together with a request for such reimbursement or reduction of a healthcare cost.
  • 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 SCLC/LUAD status determination conducted in accordance with the present disclosure.
  • SCLC/LUAD status determination using methods, kits and systems disclosed herein can be used in classifying subjects, samples, and/or tumors (e.g., lung cancer subjects, samples, and/or tumors).
  • methods, kits and systems disclosed herein can be used to generate a set of subjects, samples, and/or tumors identified according to the present methods, kits and systems each classified as corresponding to a particular SCLC/LUAD status, and optionally using two or more of such classified subjects, samples, and/or tumors to identify biomarkers that distinguish the classes (i.e., distinguish the subjects, samples, and/or tumors according to their class, e.g., according to their SCLC/LUAD status).
  • one or more samples obtained from a subject are analyzed by a method comprising enriching for cfDNA comprising a particular histone modification, wherein enriching is performed by a method that comprises incubating the sample with a reagent that specifically binds the histone modification being enriched for, and sequencing the enriched cfDNA.
  • a method comprising enriching for cfDNA comprising a particular histone modification wherein enriching is performed by a method that comprises incubating the sample with a reagent that specifically binds the histone modification being enriched for, and sequencing the enriched cfDNA.
  • a histone modification e.g., H3K4me3 and/or H3K27ac.
  • Sequence reads can be aligned to human genome build hg!9, e.g., using the Burrows-Wheeler Aligner (BWA). Non-uniquely mapping and redundant reads arc optionally discarded.
  • BWA Burrows-Wheeler Aligner
  • MACS v2.1.1.20140616 can be used for sequence (e.g., ChlP-seq) peak calling with a q-value (FDR) threshold of 0.01.
  • Sequence (e.g., 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 el al., Sci Rep (2019) 9( 1 ):9354).
  • sequence e.g., ChlP-seq
  • sequence e.g., ChlP-seq
  • peaks that overlap with selected genomic loci that arc differentially modified as provided herein for the relevant histone modification (Tables 1-2) can then be used to determine SCLC/LUAD status.
  • 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.
  • the average number of reads in the local background of each ChlP-seq peak is subtracted to improve signal to noise.
  • a sequence read density for one or more histone modifications can be calculated by a method that comprises (1) summing background adjusted sequence counts at one or more genomic loci and dividing the resulting sum by the total number of kilobases of the one or more genomic loci, or (2) for each genomic loci, determining the ratio of background adjusted fragment counts to the number of kilobases of the genomic loci, and then summing the ratios for each loci.
  • a method comprises determining an SCLC/LUAD ratio score, e.g., by a method that comprises (a) calculating an SCLC sequence read density, calculating a LU AD sequence read density, and dividing the SCLC sequence read density by the LU AD sequence read density.
  • an SCLC sequence read density can be determined by a method that comprises calculating sequence read density using one or more genomic loci with increased epigenetic modifications in sample(s) obtained from one or more subjects with SCLC as compared to one or more sample(s) obtained from subjects with LU AD.
  • a LU AD sequence read density can be determined by a method that comprises calculating sequence read density using one or more genomic loci with increased epigenetic modifications in sample(s) obtained from one or more subjects with LUAD as compared to one or more sample(s) obtained from subjects with SCLC.
  • an SCLC/LUAD ratio score is determined for H3K4me3 modifications.
  • an SCLC/LUAD ratio score is determined for H3K27ac modifications. In some embodiments, an SCLC/LUAD ratio score is determined for methylated DNA. In some embodiments, an SCLC/LUAD ratio score is determined for H3K4me3 modifications and H3K27ac modifications, H3K4me3 and methylated DNA, or H3K27ac and methylated DNA. In some embodiments, an SCLC/LUAD ratio score is determined for each of H3K4me3 modifications, H3K27ac modifications, and methylated DNA. In some embodiments, two or more SCLC/LUAD ratio scores for different epigenetic modifications can be combined. In some embodiments, each ratio score can be combined using fitted values that have been determined using a logistic regression.
  • the data can then be log2-transformed and quantile normalized to match the distribution of the data used to train a classifier. Normalized data can be used as input into a classifier that was trained using the same histone modification(s) and selected genomic loci. The classifier can then use inputted data to determine SCLC/LUAD status of a subject’s cancer. It will be appreciated that this or similar approaches can be applied to assays of the present disclosure that quantify chromatin accessibility, transcription factor binding and/or DNA methylation.
  • multiple epigenetic markers e.g., one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation
  • two or more assays for assessing the epigenetic markers can be performed in sequence (meaning a single sample can be probed for each modification in sequence) or in parallel (meaning that a single sample can be divided into multiple fractions, and then each fraction analyzed to quantifying an epigenetic modification).
  • H3K4me3 and H3K27ac histone modifications are quantified in a single sample.
  • methods of the present disclosure can be implemented on and/or in conjunction with a computer program and computer system.
  • 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.
  • a computer system 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 determine SCLC/LUAD status.
  • a computer system 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 regarding SCLC/LUAD status.
  • 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).
  • dCHIP software described in Lin et al., Bioinformatics (2004) 20:1233-1240, incorporated herein by reference in its entirety
  • RBM radial basis machine learning algorithms
  • 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. Such stored profiles can be accessed and used to perform comparisons of interest at a later point in time.
  • other, alternative program structures and computer systems will be readily apparent to the skilled artisan.
  • an algorithm can be a single learning statistical classifier system.
  • Other suitable statistical algorithms are well known to those of skill in the art.
  • learning statistical classifier systems include a machine learning algorithmic technique capable of adapting to complex data sets (e.g., a panel of genomic loci of interest) and making decisions based upon such data sets.
  • a single learning statistical classifier system such as a classification tree (e.g., random forest) is used.
  • a combination of 2, 3, 4, 5, 6, 7, 8, 9, 10, or more learning statistical classifier systems are used, preferably in tandem.
  • 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, multi-layer 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
  • 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 area under the receiver operating characteristic (AUROC) for determining if a subject has a particular status is greater than 0.5 (e.g., greater than 0.55, greater than 0.6, greater than 0.65, greater than 0.7, greater than 0.75, greater than 0.8, greater than 0.85, greater than 0.9, or greater than 0.95).
  • the present disclosure includes methods where a therapeutic agent or regimen is administered to a subject based on the SCLC/LUAD status of a lung cancer.
  • the therapeutic agent or regimen provided herein will be available, appropriate, and/or preferred for the determined SCLC/LUAD status.
  • 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.
  • compositions provided herein are present in unit dosage form, which unit dosage form can be suitable for self-administration.
  • a unit dosage form may be provided within a container, e.g., a pill, vial, cartridge, prefilled syringe, or disposable pen.
  • 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 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 80TM or HCO-50, and the like.
  • 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 80TM or HCO-50, and the like.
  • 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-filtered 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.
  • 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).
  • 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.
  • 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.
  • a pharmaceutical composition can be formulated to include a pharmaceutically acceptable carrier or excipient.
  • 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.
  • 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.
  • a carrier that will protect the therapeutic agent against rapid release
  • a controlled release formulation including implants and microencapsulated delivery systems.
  • Biodegradable, biocompatible polymers can be used, such as ethylene vinyl acetate, poly anhydrides, poly glycolic 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.
  • 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.
  • 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.
  • 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.
  • 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
  • an antioxidant an antioxidant.
  • the formulated injection can be packaged in a suitable ampule.
  • 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.
  • 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.
  • a device such as a syringe, a prefilled syringe, an auto-injector (e.g., disposable or reusable), a pen injector, a patch injector,
  • 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.
  • 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 IM , manufactured by Scandinavian Health Ltd.
  • PPI Precision Pen Injector
  • 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.
  • Retroviruses 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 CaPCV precipitation.
  • suitable retroviruses include adenovirus-derived vectors, adeno-associated virus (AAV), pLJ, pZIP, pWE, and pEM which are known to those skilled in the art.
  • a composition can be formulated for storage at a temperature below 0°C (e.g., -20°C or -80°C).
  • 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).
  • the compositions described herein are stable in storage for at least 1 year at 2-8°C (e.g., 4°C).
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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 arc administered in overlapping dosing regimens.
  • 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.
  • 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.
  • kits of the present disclosure can include instructional materials disclosing or describing the use of the kit in a method of determining SCLC/LUAD status and/or treatment disclosed herein.
  • a kit of the present disclosure can include one or more therapeutic agents useful in the treatment of cancer, e.g., as disclosed herein, optionally in combination with instruction materials for treatment of lung cancer based on SCLC/LUAD status.
  • kits 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 1-13, e.g., Table 1-3.
  • the kit comprises reagents for quantifying H3K4me3 for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1. In some embodiments, the kit comprises reagents for quantifying H3K27ac for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2. In some embodiments, the kit comprises reagents for quantifying H3K27ac for at least 1, 2, 3, or 4 genomic loci in Table 4. In some embodiments, the kit comprises reagents for quantifying H3K4me3 or H3K27ac for at least 5, 10, 15, 20, 25 or 30 genomic loci in Table 5.
  • the kit comprises reagents for quantifying H3K27ac for at least 5, 10, 15, 20, 25 or 30 genomic loci in Table 6. In some embodiments, the kit comprises reagents for quantifying H3K27ac for at least 5, 10, 15, 20, 25 or 30 genomic loci in Table 7. In some embodiments, the kit comprises reagents for quantifying H3K4me3 for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 12. In some embodiments, the kit comprises reagents for quantifying H3K4me3 for at least 5, 10, or 18 genomic loci in Table 13. 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.
  • the kit comprises reagents for quantifying DNA methylation for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 3. In some embodiments, the kit comprises reagents for quantifying DNA methylation for at least 5, 10, 15, 20, 25 or 30 genomic loci in Table 5. In some embodiments, the kit comprises reagents for quantifying DNA methylation for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 8. In some embodiments, the kit comprises reagents for quantifying DNA methylation for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 9. Tn some embodiments, the kit comprises one or more methyl-binding domains (c.g., for use in MBD-scq). In some embodiments, the kit comprises one or more antibodies that can bind methylated DNA (e.g., for use in MeDIP).
  • the kit comprises reagents for measuring chromatin accessibility for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 10. In some embodiments, the kit comprises reagents for measuring chromatin accessibility for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 11. In some embodiments, the kit comprises reagents for measuring chromatin accessibility via an ATAC-seq assay.
  • 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 SCLC or LU AD cancer.
  • the present disclosure includes systems for detecting modification and/or accessibility of one or more genomic loci.
  • 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.
  • 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.
  • 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.
  • the sequencer is configured to generate a Whole Genome Sequencing (WGS) data set from the sample.
  • 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.
  • 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.
  • 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.
  • a system of the present disclosure can include at least one antibody that selective binds H3K4me3 modifications.
  • 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 determining SCLC/LUAD status and/or treatment disclosed herein.
  • 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 1-13, e.g., Tables 1-3.
  • the system comprises reagents for quantifying H3K4me3 for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1. In some embodiments, the system comprises reagents for quantifying H3K27ac for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2. In some embodiments, the system comprises reagents for quantifying H3K27ac for at least 1, 2, 3, or 4 genomic loci in Table 4. In some embodiments, the system comprises reagents for quantifying H3K4me3 or H3K27ac for at least 5, 10, 15, 20, 25 or 30 genomic loci in Table 5.
  • the system comprises reagents for quantifying H3K27ac for at least 5, 10, 15, 20, 25 or 30 genomic loci in Table 6. In some embodiments, the system comprises reagents for quantifying H3K27ac for at least 5, 10, 15, 20, 25 or 30 genomic loci in Table 7. In some embodiments, the system comprises reagents for quantifying H3K4me3 for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 12. In some embodiments, the system comprises reagents for quantifying H3K4me3 for at least 5, 10, or 18 genomic loci in Table 13.
  • the system comprises one or more antibodies for use in ChlP-seq, optionally wherein the one or more antibodies specifically bind H3K4mc3- or H3K27ac-modificd histones.
  • the system comprises reagents for quantifying DNA methylation for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 3.
  • the system comprises reagents for quantifying DNA methylation for at least 5, 10, 15, 20, 25 or 30 genomic loci in Table 5.
  • the system comprises reagents for quantifying DNA methylation for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 8.
  • the system comprises reagents for quantifying DNA methylation for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 9.
  • 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 if a subject has SCLC or LU AD cancer.
  • the system comprises reagents for measuring chromatin accessibility for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 10. In some embodiments, the system comprises reagents for measuring chromatin accessibility for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 11. In some embodiments, the system comprises reagents for measuring chromatin accessibility via an ATAC-seq assay.
  • FIG. 10 shows an illustrative network environment 1000 for use in the methods and systems described herein.
  • the cloud computing environment 1000 may include one or more resource providers 1002a, 1002b, 1002c (collectively, 1002).
  • Each resource provider 1002 may include computing resources.
  • computing resources may include any hardware and/or software used to process data.
  • computing resources may include hardware and/or software capable of executing algorithms, computer programs, and/or computer applications.
  • illustrative computing resources may include application servers and/or databases with storage and retrieval capabilities.
  • Each resource provider 1002 may be connected to any other resource provider 1002 in the cloud computing environment 1000.
  • the resource providers 1002 may be connected over a computer network 1008.
  • Each resource provider 1002 may be connected to one or more computing device 1004a, 1004b, 1004c (collectively, 1004), over the computer network 1008.
  • the cloud computing environment 1000 may include a resource manager 1006.
  • the resource manager 1006 may be connected to the resource providers 1002 and the computing devices 1004 over the computer network 1008.
  • the resource manager 1006 may facilitate the provision of computing resources by one or more resource providers 1002 to one or more computing devices 1004.
  • the resource manager 1006 may receive a request for a computing resource from a particular computing device 1004.
  • the resource manager 1006 may identify one or more resource providers 1002 capable of providing the computing resource requested by the computing device 1004.
  • the resource manager 1006 may select a resource provider 1002 to provide the computing resource.
  • the resource manager 1006 may facilitate a connection between the resource provider 1002 and a particular computing device 1004.
  • the resource manager 1006 may establish a connection between a particular resource provider 1002 and a particular computing device 1004.
  • the resource manager 1006 may redirect a particular' computing device 1004 to a particular resource provider 1002 with the requested computing resource.
  • Fig. 11 shows an example of a computing device 1100 and a mobile computing device 1150 that can be used in the methods and systems described in this disclosure.
  • the computing device 1100 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers.
  • the mobile computing device 1150 is intended to represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smartphones, and other similar' computing devices.
  • the components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not meant to be limiting.
  • the computing device 1100 includes a processor 1102, a memory 1104, a storage device 1106, a high-speed interface 1108 connecting to the memory 1104 and multiple high- speed expansion ports 1 110, and a low-speed interface 1112 connecting to a low-speed expansion port 1114 and the storage device 1106.
  • Each of the processor 1102, the memory 1104, the storage device 1106, the high-speed interface 1108, the high-speed expansion ports 1110, and the low- speed interface 1112 are interconnected using various busses, and may be mounted on a common motherboard or in other manners as appropriate.
  • the processor 1102 can process instructions for execution within the computing device 1100, including instructions stored in the memory 1104 or on the storage device 1106 to display graphical information for a GUI on an external input/output device, such as a display 1116 coupled to the high-speed interface 1108.
  • multiple processors and/or multiple buses may be used, as appropriate, along with multiple memories and types of memory.
  • multiple computing devices may be connected, with each device providing portions of the necessary operations (e.g., as a server bank, a group of blade servers, or a multi-processor system).
  • multiple computing devices may be connected, with each device providing portions of the necessary operations (e.g., as a server bank, a group of blade servers, or a multi-processor system).
  • a processor any number of processors (e.g., one or more processors) of any number of computing devices (e.g., one or more computing devices).
  • a function is described as being performed by “a processor”
  • this encompasses embodiments wherein the function is performed by any number of processors (e.g., one or more processors) of any number of computing devices (e.g., one or more computing devices) (e.g., in a distributed computing system).
  • the memory 1104 stores information within the computing device 1100.
  • the memory 1104 is a volatile memory unit or units.
  • the memory 1104 is a non-volatile memory unit or units.
  • the memory 1104 may also be another form of computer-readable medium, such as a magnetic or optical disk.
  • the storage device 1106 is capable of providing mass storage for the computing device 1100.
  • the storage device 1106 may be or contain a computer- readable medium, such as a hard disk device, an optical disk device, a flash memory or other similar solid state memory device, or an array of devices, including devices in a storage area network or other configurations.
  • Instructions can be stored in an information carrier.
  • the instructions when executed by one or more processing devices (for example, processor 1102), perform one or more methods, such as those described above.
  • the instructions can also be stored by one or more storage devices such as computer- or machine-readable mediums (for example, the memory 1104, the storage device 1106, or memory on the processor 1102).
  • the high-speed interface 1108 manages bandwidth-intensive operations for the computing device 1100, while the low-speed interface 1112 manages lower bandwidth-intensive operations. Such allocation of functions is an example only.
  • the highspeed interface 1108 is coupled to the memory 1104, the display 1116 (e.g., through a graphics processor or accelerator), and to the high-speed expansion ports 1110, which may accept various expansion cards (not shown).
  • the low-speed interface 1112 is coupled to the storage device 1106 and the low-speed expansion port 1114.
  • the low-speed expansion port 1114 which may include various communication ports (e.g., USB, Bluetooth®, Ethernet, wireless Ethernet) may be coupled to one or more input/output devices, such as a keyboard, a pointing device, a scanner, or a networking device such as a switch or router, e.g., through a network adapter.
  • input/output devices such as a keyboard, a pointing device, a scanner, or a networking device such as a switch or router, e.g., through a network adapter.
  • the computing device 1100 may be implemented in a number of different forms, as shown in the figure. For example, it may be implemented as a standard server 1120, or multiple times in a group of such servers. In addition, it may be implemented in a personal computer such as a laptop computer 1122. It may also be implemented as part of a rack server system 1124. Alternatively, components from the computing device 1100 may be combined with other components in a mobile device (not shown), such as a mobile computing device 1150. Each of such devices may contain one or more of the computing device 1100 and the mobile computing device 1150, and an entire system may be made up of multiple computing devices communicating with each other.
  • the mobile computing device 1150 includes a processor 1152, a memory 1164, an input/output device such as a display 1154, a communication interface 1166, and a transceiver 1168, among other components.
  • the mobile computing device 1150 may also be provided with a storage device, such as a micro-drive or other device, to provide additional storage.
  • a storage device such as a micro-drive or other device, to provide additional storage.
  • Each of the processor 1152, the memory 1164, the display 1154, the communication interface 1166, and the transceiver 1168, are interconnected using various buses, and several of the components may be mounted on a common motherboard or in other manners as appropriate.
  • the processor 1152 can execute instructions within the mobile computing device 1150, including instructions stored in the memory 1164.
  • the processor 1152 may be implemented as a chipset of chips that include separate and multiple analog and digital processors.
  • the processor 1152 may provide, for example, for coordination of the other components of the mobile computing device 1150, such as control of user interfaces, applications run by the mobile computing device 1150, and wireless communication by the mobile computing device 1150.
  • the processor 1152 may communicate with a user through a control interface 1158 and a display interface 1156 coupled to the display 1154.
  • the display 1154 may be, for example, a TFT (Thin-Film-Transistor Liquid Crystal Display) display or an OLED (Organic Light Emitting Diode) display, or other appropriate display technology.
  • the display interface 1156 may comprise appropriate circuitry for driving the display 1154 to present graphical and other information to a user.
  • the control interface 1158 may receive commands from a user and convert them for submission to the processor 1152.
  • an external interface 1162 may provide communication with the processor 1152, so as to enable near area communication of the mobile computing device 1150 with other devices.
  • the external interface 1162 may provide, for example, for wired communication in some implementations, or for wireless communication in other implementations, and multiple interfaces may also be used.
  • the memory 1164 stores information within the mobile computing device 1150.
  • the memory 1164 can be implemented as one or more of a computer-readable medium or media, a volatile memory unit or units, or a non-volatile memory unit or units.
  • An expansion memory 1174 may also be provided and connected to the mobile computing device 1150 through an expansion interface 1172, which may include, for example, a SIMM (Single In Line Memory Module) card interface.
  • SIMM Single In Line Memory Module
  • the expansion memory 1174 may provide extra storage space for the mobile computing device 1150, or may also store applications or other information for the mobile computing device 1150.
  • the expansion memory 1174 may include instructions to carry out or supplement the processes described above, and may include secure information also.
  • the expansion memory 1174 may be provided as a security module for the mobile computing device 1150, and may be programmed with instructions that permit secure use of the mobile computing device 1150.
  • secure applications may be provided via the SIMM cards, along with additional information, such as placing identifying information on the SIMM card in a non-hackablc manner.
  • the memory may include, for example, flash memory and/or NVRAM memory (non-volatile random access memory), as discussed below.
  • instructions are stored in an information carrier and, when executed by one or more processing devices (for example, processor 1152), perform one or more methods, such as those described above.
  • the instructions can also be stored by one or more storage devices, such as one or more computer- or machine-readable mediums (for example, the memory 1164, the expansion memory 1174, or memory on the processor 1152).
  • the instructions can be received in a propagated signal, for example, over the transceiver 1168 or the external interface 1162.
  • the mobile computing device 1150 may communicate wirelessly through the communication interface 1166, which may include digital signal processing circuitry where necessary.
  • the communication interface 1166 may provide for communications under various modes or protocols, such as GSM voice calls (Global System for Mobile communications), SMS (Short Message Service), EMS (Enhanced Messaging Service), or MMS messaging (Multimedia Messaging Service), CDMA (code division multiple access), TDMA (time division multiple access), PDC (Personal Digital Cellular), WCDMA (Wideband Code Division Multiple Access), CDMA2000, or GPRS (General Packet Radio Service), among others.
  • GSM voice calls Global System for Mobile communications
  • SMS Short Message Service
  • EMS Enhanced Messaging Service
  • MMS messaging Multimedia Messaging Service
  • CDMA code division multiple access
  • TDMA time division multiple access
  • PDC Personal Digital Cellular
  • WCDMA Wideband Code Division Multiple Access
  • CDMA2000 Code Division Multiple Access
  • GPRS General Packet Radio Service
  • a GPS (Global Positioning System) receiver module 1170 may provide additional navigation- and location-related wireless data to the mobile computing device 1150, which may be used as appropriate by applications running on the mobile computing device 1150.
  • the mobile computing device 1150 may also communicate audibly using an audio codec 1160, which may receive spoken information from a user and convert it to usable digital information.
  • the audio codec 1160 may likewise generate audible sound for a user, such as through a speaker, e.g., in a handset of the mobile computing device 1150.
  • Such sound may include sound from voice telephone calls, may include recorded sound (e.g., voice messages, music files, etc.) and may also include sound generated by applications operating on the mobile computing device 1150.
  • the mobile computing device 1150 may be implemented in a number of different forms, as shown in the figure. For example, it may be implemented as a cellular telephone 1180. It may also be implemented as part of a smart-phone 1182, personal digital assistant, or other similar mobile device.
  • Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.
  • ASICs application specific integrated circuits
  • machine-readable medium and computer- readable medium refer to any computer program product, apparatus and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal.
  • machine-readable signal refers to any signal used to provide machine instructions and/or data to a programmable processor.
  • the systems and techniques described here can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer.
  • a display device e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor
  • a keyboard and a pointing device e.g., a mouse or a trackball
  • Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.
  • Systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components.
  • the components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.
  • LAN local area network
  • WAN wide area network
  • the Internet the global information network
  • the computing system can include clients and servers.
  • a client and server are generally remote from each other and typically interact through a communication network.
  • the relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
  • a machine learning module refers to a computer implemented process (e.g., a software function) that implements one or more specific machine learning techniques, e.g., artificial neural networks (ANNs), e.g., convolutional neural networks (CNNs), random forest, decision trees, support vector machines, and the like, in order to determine, for a given input, one or more output values.
  • ANNs artificial neural networks
  • CNNs convolutional neural networks
  • RNNs convolutional neural networks
  • the input comprises image data and/or alphanumeric data which can include 2D and/or 3D datasets, numbers, words, phrases, or lengthier strings, for example.
  • the one or more output values comprise image data (e.g. 2D and/or 3D datasets) and/or values representing numeric values, words, phrases, or other alphanumeric strings.
  • machine learning modules implementing machine learning techniques are trained, for example, using datasets that include categories of data described herein. Such training may be used to determine various parameters of machine learning algorithms implemented by a machine learning module, such as weights associated with layers in neural networks.
  • a machine learning module is trained, e.g., to accomplish a specific task such as identifying certain response strings, values of determined parameters are fixed and the (e.g., unchanging, static) machine learning module is used to process new data (e.g., different from the training data) and accomplish its trained task without further updates to its parameters (e.g., the machine learning module does not receive feedback and/or updates).
  • available input data includes training data and validation data, e.g., where the validation data is separate and non-overlapping with the training data.
  • training data is used during the training process to optimize a model, whereas validation data is used to check the accuracy of the model while operating on previously unseen data.
  • training data is divided into batches (e.g., portions) that is sequentially used (e.g., in random order) as sets of inputs to train a model.
  • a model is trained multiple times (e.g., epochs) on the entire set of training data.
  • machine learning modules may receive feedback, e.g., based on user review of accuracy, and such feedback may be used as additional training data, to dynamically update the machine learning module.
  • two or more machine learning modules may be combined and implemented as a single module and/or a single software application.
  • two or more machine learning modules may also be implemented separately, e.g., as separate software applications.
  • a machine learning module may be software and/or hardware.
  • a machine learning module may be implemented entirely as software, or certain functions of a ANN module may be carried out via specialized hardware (e.g., via an application specific integrated circuit (ASIC) and/or field programmable gate arrays (FPGAs)).
  • ASIC application specific integrated circuit
  • FPGAs field programmable gate arrays
  • machine learning modules implementing machine learning techniques may be composed of individual nodes (e.g. units, neurons).
  • a node may receive a set of inputs that may include at least a portion of a given input data for the machine learning module and/or at least one output of another node.
  • a node may have at least one parameter to apply and/or a set of instructions to perform (e.g., mathematical functions to execute) over the set of inputs.
  • node instructions may include a step to provide various relative importance to the set of inputs using various parameters, such as weights.
  • the weights may be applied by performing scalar multiplication (e.g., or other mathematical function) between a set of inputs values and the parameters, resulting in a set of weighted inputs.
  • a node may have a transfer function to combine the set of weighted inputs into one output value.
  • a transfer function may be implemented by a summation of all the weighted inputs and the addition of an offset (e.g., bias) value.
  • a node may have an activation function to introduce non-linearity into the output value.
  • Non-limiting examples of the activation function include Rectified Linear Activation (ReLu), logistic (e.g., sigmoid), hyperbolic tangent (tanh), and softmax.
  • a node may have a capability of remembering previous states (e.g., recurrent nodes). Previous states may be applied to the input and output values using a set of learning parameters.
  • the machine learning module comprises a deep learning architecture composed of nodes organized into layers.
  • a layer is a set of nodes that receives data input (e.g., weighted or non-weighted input), transforms it (e.g., by carrying out instructions, e.g., applying a set of functions e.g., linear and/or non-linear functions), and passes transformed values as output (e.g., to the next layer).
  • the set of nodes in a particular layer may share the same parameters and instructions without interacting with each other.
  • a machine learning module may be composed of at least one layer (e.g., ordered).
  • Examples of types of layers include convolutional layers (e.g., layers with a kernel, a matrix of parameters that is slid across an input to be multiplied with multiple input values to reduce them to a single output value); fully connected (FC) layers (e.g.
  • convolutional layers e.g., layers with a kernel, a matrix of parameters that is slid across an input to be multiplied with multiple input values to reduce them to a single output value
  • FC layers e.g.
  • recurrent layers long/short term memory (LSTM) layers, gated recurrent unit (GRU) layers (e.g., nodes with the various abilities to memorize and apply their previous inputs and/or outputs); batch normalization (BN) layers (e.g., layers that normalize a set of outputs from another layer, allowing for more independent learning of individual layers); activation layers (e.g., layers with nodes that only contain an activation function); and/or (un)pooling layers [e.g., layers that reduce (increase) dimensions of an input by summarizing (splitting) input values in defined patches).
  • BN batch normalization
  • activation layers e.g., layers with nodes that only contain an activation function
  • unpooling layers e.g., layers that reduce (increase) dimensions of an input by summarizing (splitting) input values in defined patches).
  • the performance of a machine learning module may be characterized by its ability to produce an output data with specific accuracy.
  • a training process is performed to find optimal parameters, such as weights, for each node in each layer of the machine learning module.
  • the training process of a machine learning module may involve using output data to calculate an objective function (e.g., cost function, loss function, error function) that needs to be optimized (e.g., minimized, maximized).
  • an objective function e.g., cost function, loss function, error function
  • a machine learning objective function may be a combination of a loss function and regularization parameter. The loss function is related to how well the output is able to predict the input.
  • the loss function may take various forms, like mean squared error, mean absolute error, binary cross-entropy, categorical cross-cntropy, for example.
  • the regularization term may be needed to prevent overfitting and improve generalization of the training process. Examples of regularization techniques include LI Regularization or Lasso Regression, L2 Regularization or Ridge Regression, and Dropout (e.g., dropping layer outputs at random during training process).
  • objective function optimization of a machine learning module may involve finding at least one (e.g., all) of the present global optima (e.g., as opposed to local optima).
  • the algorithm for objective function optimization follows principles of mathematical optimization for a multi-variable function and relies on achieving specific accuracy of the process. Examples of objective function optimization algorithms include gradient descent, nonlinear conjugate gradient, random search, Levenberg- Marquardt algorithm, limited-memory Broyden-Fietcher-Goldfarb-Shanno algorithm, pattern search, basin hopping method, Krylov method, Adam method, genetic algorithm, particle swarm optimization, surrogate optimization, and simulated annealing.
  • a machine-learned model may be or include an artificial neural network.
  • a machine- learned model may employ, for example, an attention-based model (e.g., a transformer model, such as, for example, a vision transformer), a transformer model (e.g., a vision transformer), a regression-based model (e.g., a logistic regression model), a regularization-based model (e.g., an elastic net model or a ridge regression model), an instance-based model (e.g., a support vector machine or a k-nearest neighbor model), a Bayesian-based model (e.g., a naive-based model or a Gaussian naive-based model), a clustering-based model (e.g., an expectation maximization model), an ensemble -based model (e.g., an adaptive boosting model, a random forest model, a bootstrap-aggregation model, or
  • an attention-based model e.g., a transformer model, such as, for
  • a machine-learned model used as a classifier is or is derived from a decision tree methodology, a neural boosted methodology, a bootstrap forest methodology, a boosted tree methodology, a k nearest neighbors methodology, a generalized regression forward selection methodology, a generalized regression pruned forward selection methodology, a fit stepwise methodology, a generalized regression lasso methodology, a generalized regression clastic net methodology, a generalized regression ridge methodology, a nominal logistic methodology, a support vector machines methodology, a discriminant methodology, a naive Bayes methodology, or a combination thereof.
  • a machine-learned model is or is derived from a decision tree methodology, a neural boosted methodology, a bootstrap forest methodology, a boosted tree methodology, a generalized regression lasso methodology, a generalized regression elastic net methodology, a generalized regression ridge methodology, a nominal logistic methodology, a support vector machines methodology, a discriminant methodology, or a combination thereof.
  • a machine-learned model is or is derived from a decision tree methodology, a neural boosted methodology, a bootstrap forest methodology, a boosted tree methodology, a support vector machines methodology, or a combination thereof.
  • 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), and/or a DNase hypersensitivity assay.
  • the term “administration” typically refers to the administration of a disease appropriate (e.g., SCLC 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.
  • 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).
  • a particular antigen e.g. , a heavy chain variable domain, a light chain variable domain, and/or one or more CDRs.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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 ImmunoPharmaccuticals (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 (5), epsilon (e), 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, fcccs, 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.”
  • 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 (ctDNA). 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.
  • 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.
  • a cancer can include one or more tumors.
  • a cancer can be or include cells that are precancerous (e.g., benign), malignant, pre-metastatic, metastatic, and/or non-metastatic.
  • a cancer can be or include a solid tumor.
  • a cancer be associated with SCLC or LU AD status.
  • 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.
  • 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).
  • a reference sequence includes a particular amino acid motif at positions 100-110
  • 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.
  • 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/GLSEARCH, Genoogle, HMMER, HHpred/HHsearch, IDF, Infernal, KLAST, USEARCH, parasail, PSLBLAST, PSI-Search, ScalaBLAST, Sequilab, SAM, SSEARCH, SWAPHI, SWAPHI-LS, SWIMM, or SWIPE.
  • software programs such as, for example, BLAST, CS-BLAST, CUDASW++, DIAMOND, FASTA, GGSEARCH/GLSEARCH, Genoogle, HMMER, HHpred/HHsearch, IDF, Infernal, KLAST, USEARCH, parasail, PSLBL
  • 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.
  • 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 SCLC cancer, as compared to a reference state, such as LU AD cancer.
  • 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 SCLC cancer, as compared to a reference state, such as LU AD cancer.
  • Epigenetic modification refers to heritable alterations to the genome that are not due to changes in DNA sequence.
  • Epigenetic modifications include chemical modifications such as, e.g., DNA methylation and histone modification.
  • epigenetic modifications can cause a change in chromatin structure, DNA accessibility, and/or transcription factor binding.
  • epigenetic modifications can be detected or measured directly (e.g., by using an agent that binds an epigenetic modification (e.g., an antibody that binds H3K4me3 or H3K27ac)).
  • epigenetic modifications can be measured indirectly, e.g., by measuring or detecting one or more attributes, changes in which are indicative of changes in epigenetic modifications.
  • chromatin accessibility and/or transcription factor binding can be used as a measure of epigenetic modifications at a given locus.
  • the term “epigenetic marker” refers to an indicator of epigenetic state, and includes, e.g., epigenetic modifications and assays that measure transcription factor biding or chromatin accessibility.
  • epigenetic biomarker refers to an epigenetic marker that can be used in the detection of a disease or condition.
  • 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).
  • 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 MethyLCpG-Binding Domain sequencing (MBD-seq).
  • BS-Seq Bisulfite sequencing
  • WGBS Whole Genome Bisulfite Sequencing
  • Methylated DNA ImmunoPrecipitation sequencing Methylated DNA ImmunoPrecipitation sequencing
  • MBD-seq MethyLCpG-Binding Domain sequencing
  • 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.
  • Modification Status'’ or “Histone Modification Status” refers to the frequency with which DNA sequences corresponding to the genomic locus arc 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 ail, 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.
  • 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., cell- type-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., lung cancer, e.g., SCLC cancer, etc.).
  • 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., lung cancer, e.g., SCLC cancer, etc.).
  • 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., lung cancer, e.g., SCLC cancer, etc.) 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.
  • a 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.
  • 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.).
  • a therapeutically effective amount of a particular agent or therapy may be formulated and/or administered in a single dose.
  • 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.
  • 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., lung cancer, e.g., SCLC cancer, etc.).
  • 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 determining the SCLC/LUAD status of a lung cancer in a subject 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 one or more epigenetic biomarkers, wherein the one or more epigenetic biomarkers comprise:
  • 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), and a DNase hypersensitivity 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 Meicrococcal Nuclease digestion with sequencing
  • DNase hypersensitivity assay selected from ATAC-seq (Assay of Transpose Accessible Chromatin sequencing)
  • NOMe-seq Nucle
  • 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.
  • liquid biopsy sample is a plasma sample, serum sample, or urine sample.
  • (c) quantifying methylated DNA using an assay that comprises enriching for methylated cfDNA and sequencing the enriched cfDNA to determine a count of sequences with one or more methylated nucleotides (e.g., using an MBD-seq assay).
  • the cfDNA comprising H3K27ac modifications is enriched using a method that comprises incubating the sample with an agent (e.g., an antibody) that binds H3K27ac modifications; and/or
  • methylated cfDNA is enriched using a method that comprises incubating the sample with an agent (e.g., an antibody or a methyl binding domain) that binds methylated DNA.
  • an agent e.g., an antibody or a methyl binding domain
  • sequence reads are adjusting on the basis of sequencing depth (e.g., quantile normalizing sequence reads to a common reference distribution) and/or ChIP quality prior to summing.
  • sequence counts are normalized to aggregate counts in a given sample across a set of regions (e.g., 10,000 regions) previously determined to have DNAse hypersensitivity in most cell types.
  • the one or more genomic loci include one or more genomic loci with an increased level of the one or more epigenetic biomarkers in (a) sample(s) obtained from a subject with SCLC as compared to a sample obtained from a subject with LU AD, and/or (b) sample(s) obtained from a subject with LU AD as compared to a sample obtained from a subject with SCLC.
  • sample(s) obtained from subjects with LU AD as compared to samples obtained from subjects with SCLC (e.g., wherein the sample(s) are liquid biopsy samples, tumor samples (including, e.g., pdx samples); and
  • H3K4me3 modifications for at least 5, 10, 20, 30, 40, 50, 100, 150, or 200 genomic loci listed in Table 1;
  • H3K27ac modifications for at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, or 2000 genomic loci listed in Table 2;
  • H3K27ac modifications for at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000, 5000, or 5500 genomic loci listed in Table 6;
  • H3K27ac modifications for at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000, or 5000 genomic loci listed in Table 7;
  • DNA methylation for at least 5, 10, 20, 30, 40, 50, 100, 150, 200, 250, 300, 400, 500, or 600 genomic loci listed in Table 8;
  • chromatin accessibility e.g., using ATAC-seq
  • chromatin accessibility for at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, or 4000 genomic loci listed in Table 11;
  • 63 The method of any one of embodiments 1-62, wherein the sample comprises a detectable amount of ctDNA (e.g., wherein estimated tumor fraction is >3% for the cfDNA, e.g., as determined by iChorCNA). 64. The method of any one of embodiments 1 -63, wherein, if the subject is determined to have SCLC, the method further comprises subtyping the SCLC.
  • ctDNA e.g., wherein estimated tumor fraction is >3% for the cfDNA, e.g., as determined by iChorCNA.
  • the cfDNA comprising H3K4me3 modifications is enriched using a method that comprises incubating cfDNA with an agent (e.g., an antibody) that binds H3K4me3 modifications;
  • the cfDNA comprising H3K27ac modifications is enriched using a method that comprises incubating cfDNA with an agent (c.g., an antibody) that binds H3K27ac modifications;
  • methylated cfDNA is enriched using a method that comprises incubating cfDNA with an agent (e.g., an antibody or a methyl binding domain) that binds methylated DNA.
  • an agent e.g., an antibody or a methyl binding domain
  • the reference is a predetermined threshold, a measurement from a liquid biopsy sample, a measurement from liquid biopsy samples obtained from a cohort of subjects, and/or a normalized value, optionally wherein: the predetermined threshold and the normalized value were previously shown to distinguish an SCLC subtype from other SCLC subtypes (e.g., distinguish with an AUROC of greater than 0.5); the reference is a measurement from a liquid biopsy sample obtained from a cohort of subjects who have previously been determined to have an SCLC subtype; or the cohort of subjects had previously been determined to have an SCLC subtype.
  • ASCL1 activity e.g., expression
  • SCLC therapy is one that has been associated with providing an improved therapeutic benefit in subjects diagnosed with an ASCL1 subtype of SCLC (e.g., improved relative to alternative therapeutics that are commonly administered to subjects having SCLC).
  • SCLC therapy is a BCL2 apoptosis regulator, a BCL2 inhibitor, a DLL3 inhibitor (e.g., rovalpituzumab tesirine), an LSD1 inhibitor, and/or a therapeutic targeting CEACAM5 (e.g., labetuzumab govitecan).
  • a BCL2 apoptosis regulator e.g., a BCL2 inhibitor, a DLL3 inhibitor (e.g., rovalpituzumab tesirine), an LSD1 inhibitor, and/or a therapeutic targeting CEACAM5 (e.g., labetuzumab govitecan).
  • NEURODI activity e.g., expression
  • SCLC therapy is one that has been associated with providing an improved therapeutic benefit in subjects diagnosed with a NEURODI subtype of SCLC (e.g., improved relative to alternative therapeutics that are commonly administered to subjects having SCLC).
  • a LU AD therapy e.g., administering a selective EGFR tyrosine kinase inhibitor (e.g., Osimertinib)).
  • a selective EGFR tyrosine kinase inhibitor e.g., Osimertinib
  • SCLC therapy comprises administering (i) an agent that targets DLL3 (e.g., Tarlatlamab), and/or (ii) a PD-L1 inhibitor in combination with platinum-etoposide chemotherapy or PARP inhibitors.
  • an agent that targets DLL3 e.g., Tarlatlamab
  • a PD-L1 inhibitor in combination with platinum-etoposide chemotherapy or PARP inhibitors.
  • the method comprises administering platinum/etoposide chemotherapy in combination with Osimertinib.
  • the lung cancer is determined to be SCLC at the second time point, an SCLC therapy (e.g., as described herein) is administered to the subject.
  • an SCLC therapy e.g., as described herein
  • a method of treating a subject having a lung cancer comprising:
  • step (e) obtaining the validated classifier by validating the classifier from step (d) on a third cohort comprising an independent and group of subjects with SCLC and LUAD cancers and selecting a threshold such that the validated classifier predicts SCLC cancers, with an area under the receiver operating characteristic (AUROC) greater than 0.5 (e.g., greater than 0.55, greater than 0.6, greater than 0.65, greater than 0.7, greater than 0.75, greater than 0.8, greater than 0.85, greater than 0.9, or greater than 0.95), wherein subjects falling within the group of predicted SCLC cancers display the validated epigenetic profile and subjects that do not fall within the group of SCLC cancers lack the validated epigenetic profile.
  • AUROC receiver operating characteristic
  • step (c) were identified by comparing the genomic profile of one or more histone modifications and/or DNA methylation in (i) one or more biological samples from the first cohort and (ii) one or more biological samples from the second cohort.
  • step (d) was trained on histone modification and/or DNA methylation levels in (i) one or more biological samples from the first cohort and (ii) one or more biological samples from the second cohort.
  • step (e) was validated using liquid biopsy samples from the third cohort.
  • liquid biopsy sample is a plasma sample, serum sample, or urine sample.
  • H3K27ac modifications for at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000, 5000, or 5500 genomic loci in Table 6;
  • chromatin accessibility e.g., using ATAC-seq
  • chromatin accessibility for at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, or 4000 genomic loci in Table 11;
  • cfDNA cell-free DNA
  • a system for determining the SCLC/LUAD status of a lung cancer in 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 142 and/or a computer system of embodiment 143.
  • H3K27ac modifications for at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000, 5000, or 5500 genomic loci in Table 6;
  • H3K27ac modifications for at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000, or 5000 genomic loci in Table 7;
  • chromatin accessibility e.g., using ATAC-seq
  • chromatin accessibility for at least 5, 10, 20, 30, 40, 50, 100, 500, 1000, 1500, 2000, 3000, 4000, or 5000 genomic loci in Table 10;
  • 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.
  • a method of determining SCLC and/or LU AD status of a cancer in a subject comprising: receiving (e.g., by a processor of a computing device) a genomic profile of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation for a subject; and determining whether the subject has an epigenetic profile indicative of an SCLC or LU AD by classifying (e.g., by the processor) the genomic profile using an SCLC/LUAD classifier.
  • the one or more genomic profiles used to train the SCLC/LUAD classifier are for differential loci having statistically significant differences in the levels of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation levels between one or more biological samples (e.g., liquid biopsy samples and/or tumor samples (including, e.g., pdx samples)) obtained from cohorts of subjects who have previously have been determined to have SCLC (e.g., de novo SCLC or transformed SCLC) or LU AD.
  • biological samples e.g., liquid biopsy samples and/or tumor samples (including, e.g., pdx samples)
  • 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 155-170.
  • a method of treating a subject having a cancer comprising: administering an SCLC therapeutic agent to the subject, wherein the subject has been determined to have a validated epigenetic profile indicative of an SCLC based on analysis of a biological sample, optionally of cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject, wherein the presence of the validated epigenetic profile has been determined using a classifier (e.g., a validated classifier) according to a method of any one of embodiments 155-170.
  • a classifier e.g., a validated classifier
  • a method of treating a subject having a cancer comprising: administering a LUAD therapeutic agent to the subject, wherein the subject has been determined to have a validated epigenetic profile indicative of LUAD based on analysis of a biological sample, optionally of cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject, wherein the presence of the validated epigenetic profile has been determined using a classifier (e.g., a validated classifier) according to a method of any one of embodiments 155-170.
  • a classifier e.g., a validated classifier
  • 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 SCLC cancer or LUAD cancer.
  • the present Examples show that differentially modified and/or differentially accessible genomic loci of the present disclosure can be used to determine SCLC/LUAD status from cfDNA in plasma samples obtained from subjects with SCLC cancer and LUAD cancer.
  • Example 1 Materials and Methods
  • 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 lung cancer patients under a protocol approved by an IRB .
  • Lung cancer patients had previously been determined to have SCLC cancer or LU AD cancer. Informed content was obtained in each case and samples were de-identified.
  • Chromatin immunoprecipitation (ChIP)
  • Enrichment of DNA methylation was performed on DNA extracted from cell lines and 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 MeDIP- 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).
  • Example 2 SCLC/LUAD status classifiers based on ratios of aggregate signals across different subsets of genomic loci that are correlated with SCLC cancer or LUAD cancer
  • genomic loci likely to differentiate SCLC and LUAD samples based on H3K4me3 modification, H3K27ac modification or DNA methylation were first identified.
  • a universal peak map across cell lines was created using a set of exemplary SCLC and LUAD cell lines. Reads in each peak region were quantified in a manner that accounts for different sequencing depths and ChIP QC quality (e.g., based on count reads and then quantile normalizing each sample to a common reference distribution).
  • Genomic loci that had differential analyte signal between SCLC and LUAD cell lines were determined using DESeq2 (Love et al., Genome Biol (2014) 15(12):550). These differential loci are shown in Table 1 (H3K4me3), Table 2 (H3K27ac) and Table 3 (DNA methylation) and grouped in accordance with the SCLC/LUAD status they correlated with, i.e., Genomic locus (SCLC) or Genomic locus (LU AD).
  • SCLC Genomic locus
  • LU AD Genomic locus
  • the number of sequencing fragments overlapping each SCLC or NSCLC associated genomic locus by at least 1 bp for the corresponding modification was calculated. An estimate of local background was subtracted from the count in each region.
  • the fragment density in SCLC associated genomic loci was calculated as the sum of background adjusted fragment counts in each SCLC associated genomic locus divided by the total kilobases in the SCLC associated genomic loci.
  • the fragment density in LUAD associated genomic loci was calculated as the sum of background adjusted fragment counts in each LUAD associated genomic locus divided by the total number of kilobases in the LUAD associated genomic loci.
  • the SCLC/LUAD ratio score was then calculated by dividing the SCLC fragment density by the LUAD fragment density.
  • Fig. 1 shows representative ROC curves for exemplary SCLC/LUAD status classifiers that were generated in accordance with Example 2.
  • different classifiers were generated using genomic loci from Tables 1-3 for different modifications, namely (i) H3K4me3 modifications, (ii) H3K27ac modifications, (iii) DNA methylation (MBD) or (iv) all of the above (combined).
  • AUC for individual modifications was calculated based on SCLC/LUAD ratio for each modification individually.
  • AUC for the combined modifications was calculated on the fitted values from a logistic regression. Each individual modification and the combination of all three were able to correctly classify SCLC from LUAD.
  • AUC values were 0.85 for H3K4me3 modifications, 0.83 for H3K27ac modifications, 0.9 for DNA methylation (MBD) and 0.92 for the combination of all three.
  • Example 3 Subsets of regions retain ability to classify
  • Fig. 2 shows representative, non-limiting graphs that demonstrate the accuracy of SCLC/LUAD status (based on AUCROC) determination using the classifiers that were generated in accordance with Example 2. Average AUC and 95% confidence intervals are shown from 500 repeated samplings of regions used to calculate SCLC/LUAD ratios. As shown, each separate sampling used different subsets of the genomic loci in Table 1 (H3K4me3), Table 2 (H3K27ac), Table 3 (MBD) and Tables 1-3 (combined), where the x-axis shows the number of genomic loci that were sampled.
  • Table 1 H3K4me3
  • Table 2 H3K27ac
  • MBD Table 3
  • Tables 1-3 combined
  • Example 4 Varying the width of the regions has minimal effect on predictive performance
  • Fig. 3 shows representative, non-limiting graphs that demonstrate the accuracy of SCLC/LUAD status (based on AUCROC) determination using the classifiers that were generated in accordance with Example 2.
  • the widths of genomic loci in Tables 1-3 were increased/decreased and AUCs calculated on re-computed SCLC/LUAD ratios. As shown, increasing or decreasing the regions by up to 50% had little effect on predictive performance.
  • Fig. 4 shows the results of these experiments where different machine learning (ML) approaches were used to generate different SCLC/LUAD status classifiers using the genomic loci in Tables 1-3.
  • the results show the average (95% CI) AUC from 50 repeats of 5- fold cross validation.
  • the background adjusted counts normalized to library size in each individual genomic locus were provided to three different ML algorithms instead of being used to calculate SCLC/LUAD ratio scores.
  • the different ML approaches (glmnet, Random forest and SVM) yielded similar’ predictive performance.
  • Example 6 Detection of H3K4me3 cfChlP-seq signal at the DLL3 promoter in plasma samples from subjects with SCLC and other cancers
  • Fig. 5 shows normalized H3K4me3 cfChlP-seq signal at the DLL3 promoter stratified by cancer type.
  • H3K4mc3 cfChlP-scq signal was highest for Merkel cell carcinoma, neuroendocrine prostate cancer (NEPC), melanoma and small cell lung cancer (SCLC).
  • Lower and upper hinges indicate 25 th and 75 th percentiles; whiskers extend to 1.5 x the inter-quartile ranges (IQR).
  • H3K4me3 cfChlP-seq experiments were performed using 1 mL plasma samples that were obtained from patient cohorts with the identified cancers as described in Baca et al., Nat Med (2023) 29(11):2737-2741, the entire contents of which are incorporated herein by reference.
  • 200bp windows were selected with any of the following “active” chromatin states in > 50% of tissues in Epimap: l_TssA, 2_TssFlnk, 3_TssFlnkU, 4_TssFlnkD, 8_EnhG2, and 14_TssBiv.
  • Off-target sites were defined as 200bp windows that lacked the on-target annotations in all of 129 samples used to generate chromatin state maps in Epimap.
  • On-target and off-target windows were merged and retained if the merged windows spanned 1 ,OOObp or more. Off-target regions within 10,000bp of on-target regions were excluded.
  • ctDNA estimates were obtained from LP-WGS data using ichorCNA24 with default settings. For samples that lacked LP-WGS, signal at CREs was used to estimate ctDNA content. A linear model was fit to predict LP-WGS-based tumor fraction estimates (T) given the signal at CREs that were negatively and positively correlated at CRE (Cpos and Cneg, respectively):
  • CREs identified on a given cancer type were used to estimate ctDNA in samples of that type.
  • CREs identified using all cancer types were used. Estimates were scaled such that the mean estimate for healthy plasma, which was not used for CRE identification, was 0.
  • CREs ctDNA-correlated regulatory elements
  • CREs were assessed for overlap with gene features and CpG islands using annotatr and ChlPSeeker. Normalized cfChlP-seq read counts at specific genomic loci were visualized with IGV v2.8.243. The GREAT tool48 (V3.0) was used to assess for enrichment of Gene Ontology (GO) and MSigDB perturbation annotations among genes near CREs. Published TFs and histone modification ChlP-seq datasets were ranked by similarity to the query cfChlP- seq dataset based on the top 1,000 peaks by enrichment in each published dataset.
  • H3K4me3 was quantified near promoters.
  • All H3K4me3 cfChlP-seq peak calls were merged into single GRanges objects and reduced to non-overlapping intervals using the reduce() function. Peaks in high-noise regions were removed (website: github.com/Boyle-Lab/Blacklist/blob/master/lists/hgl9-blacklist.v2.bed.gz).
  • H3K4me3 fragment counts were normalized to the aggregate counts in a given sample across a set of 10,000 regions with DNAse hypersensitivity across most cell types, as described above.
  • Genomic loci at the DLL3 promoter with H3K4me3 modifications in plasma samples from SCLC subjects include those within genomic locus at chrl9:39, 988, 452-39, 990, 287 (hgl9) and can also be found in Baca et al., Nat Med (2023) 29(11):2737-2741 and related data uploaded to GEO ⁇ e.g., peak calls and bed files), the entire contents of which are incorporated herein by reference.
  • Example 7 Determining subtype of SCLC using H3K4me3 and H3Kac27 in plasma samples obtained from subjects with SCLC
  • Determination of SCLC subtype can be useful, e.g., for determining appropriate treatment of a subject.
  • exemplary therapeutics to administer to subjects determined to have a given SCLC subtype are discussed, e.g., in Xie et al., “Durvalumab+ platinum-etoposide in first- line extensive-stage small cell lung cancer (ES-SCLC): exploratory analysis of SCLC molecular subtypes in CASPIAN” AACR Annual Meeting 2022; Gay et al., Cancer Cell (2021) 39:346- 360; Rudin et al., Nature Reviews Cancer (2019) 19(5):289-297; Park et al., Ebiomedicine (2024) 102: 105062; Chemi et al., Nature Cancer (2022) 3(10):1260-1270; and Heeke et al., Cancer Cell (2024) 42(2):225-237; the contents of each of which is incorporated by reference herein in their entirety.
  • Table 4 Exemplary genetic loci of enhancer regions associated with SCLC subtypes.
  • a multi-analyte cfDNA-based classifier integrating these three epigenomic features discriminated between EGFRm LU AD versus tSCLC with an AUROC of 0.94.
  • liquid biopsies which can detect somatically-acquired genomic alterations in circulating tumor cell-free DNA (cfDNA).
  • cfDNA tumor cell-free DNA
  • liquid biopsies are minimally invasive, can easily be repeated at multiple timepoints, and may better capture intra-patient tumor heterogeneity.
  • limitations in current commercially- available liquid biopsies preclude detection of certain clinically actionable resistance phenotypes that lack defining genomic alterations.
  • the diagnosis of tSCLC cannot be made by currently-available liquid biopsy assays.
  • Peripheral blood was collected in EDTA Vacutainer tubes (BD) or Streck Cell-
  • Frozen tissue was pulverized using the Covaris CryoPrep system and fixed with 2 mmol/L disuccinimidyl glutarate for 10 minutes followed by 1% formaldehyde buffer for 10 minutes and quenched with glycine.
  • Chromatin was sheared to 300 to 500bp using the Covaris E220 ultrasonicator and then incubated overnight with the following antibodies coupled with 40 pl protein A and protein G beads (Invitrogen) at 4°C overnight: H3K27ac: (Abeam #ab4729, Lot GR3442890-1), H3K4me3 (ThermoFisher #PA5-27029, Lot XI3696063), H3K27me3 (Cell Signaling #9733S, Lot 19). 5% of the sample was not exposed to antibody and was used as a control.
  • DNA sequencing libraries were prepared from the purified immunoprecipitated and non-immunoprecipitated DNA using the ThruPLEX DNA-seq Kit (TakaraBio). Libraries were sequenced on an Illumina HiSeq 4000 to generate 150bp paired-end reads (Novogene Corporation, CA).
  • ChlP-seq reads were aligned to the human genome build hgl9 using the Burrows- Wheeler Aligner (BWA) version 0.7.17 (RRID:SCR_010910; see, e.g., Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory -efficient alignment of short DNA sequences to the human genome, Genome Biol [Internet], 2009 [cited 2021 Jul 8];10:R25. Available from: https://doi.org/10.1186/gb-2009-10-3-r25). Non-uniquely mapped and redundant reads were discarded.
  • BWA Burrows- Wheeler Aligner
  • Frozen tissue was resuspended and dounce homogenized in 1000 pl of Homogenization Buffer. Nuclei were filtered using a 70-pm Flowmi strainer, isolated using iodixanol density-gradient centrifugation method, and washed with RSB buffer (10 mM Tris-HCl pH 7.4, 10 mM NaCl, and 3 mM MgC12 in water).
  • the number of unique aligned reads overlapping each peak in each sample was calculated from BAM files using BEDtools. Quantile normalization was applied to this matrix of normalized read counts for clustering and PCA analysis. Unsupervised hierarchical clustering was performed based on Spearman correlation between samples. Principal component analysis was performed using the preomp R function. Raw read counts for each peak were normalized to the total number of mapped reads for each sample.
  • Cufflinks (RRID:SCR_014597) was used to assemble transcript-level expression data from filtered alignments (e.g., as described in Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks, Nat Protoc [Internet], 2012 [cited 2021 Jul 8];7: 562-78. Available from: https://www.nature.com/ailicles/nprot.2012.016. Differential gene expression analysis was conducted using DESeq2 (e.g., as described in Love MI, Huber W, Anders S.
  • MeDIP-seq was performed on tissue and plasma following published methods. (see, e.g., Berchuck JE, Baca SC, McClure HM, Korthauer K, Tsai HK, Nuzzo PV, et al. Detecting Neuroendocrine Prostate Cancer Through Tissue-Informed Cell-Free DNA Methylation Analysis, Clin Cancer Res Off J Am Assoc Cancer Res. 2022;28:928-38).
  • Library preparation was performed on 10 ng of DNA using the KAPA HyperPrep Kit (KAPA Biosystems). End-repair, A-tailing, and ligation of NEBNext adaptors (NEBNext Multiplex Oligos for Illumina kit, New England BioLabs) was then performed.
  • the MeDIPs R package was used to calculate CpG-normalized relative methylation scores across 300bp windows across the genome for each cfMeDIP-seq library ( Berchuck JE, et al., "Detecting neuroendocrine prostate cancer through tissue- informed cell-free DNA methylation analysis. Clin. Cancer Res Off J Am Assoc Cancer Res.

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Abstract

La présente divulgation concerne, entre autres, des procédés, des kits et des systèmes pour déterminer l'état du cancer du poumon. Dans divers modes de réalisation, la présente invention concerne l'utilisation d'une ou de plusieurs modifications d'histone, l'accessibilité de la chromatine, la liaison d'un ou de plusieurs facteurs de transcription, et/ou la méthylation de l'ADN qui sont caractéristiques de l'état du cancer du poumon. Dans certains modes de réalisation, des modifications différentielles et/ou une accessibilité différentielle sont détectées et quantifiées au niveau d'un ou de plusieurs loci génomiques d'un échantillon biologique, par exemple, dans de l'ADN acellulaire (ADNcf) à partir d'un échantillon de biopsie liquide obtenu ou dérivé d'un sujet atteint d'un cancer du poumon. Dans divers modes de réalisation, un état déterminé est utile, par exemple, dans la sélection du traitement et/ou le traitement d'un cancer du poumon.
PCT/US2024/051147 2023-10-13 2024-10-11 Procédés, kits et systèmes pour déterminer l'état du cancer du poumon et méthodes de traitement du cancer du poumon les utilisant Pending WO2025081121A1 (fr)

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