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WO2024238523A2 - Sequencing adapters for methylation sequencing - Google Patents

Sequencing adapters for methylation sequencing Download PDF

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Publication number
WO2024238523A2
WO2024238523A2 PCT/US2024/029221 US2024029221W WO2024238523A2 WO 2024238523 A2 WO2024238523 A2 WO 2024238523A2 US 2024029221 W US2024029221 W US 2024029221W WO 2024238523 A2 WO2024238523 A2 WO 2024238523A2
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sequencing
nucleic acid
cancer
instances
sequence
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WO2024238523A3 (en
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Nicole Lambert
James Yu
Peter George
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Foundation Medicine Inc
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Foundation Medicine 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
    • C12Q1/6806—Preparing nucleic acids for analysis, e.g. for polymerase chain reaction [PCR] assay

Definitions

  • the present disclosure relates generally to sequencing adapters, and methods and systems for their use in performing nucleic acid sequencing and determining a methylation state associated with one or more nucleotides in nucleic acid molecules. More specifically, the present disclosure relates to sequencing adapters for performing methylation sequencing and determining a methylation signature therefrom.
  • methylation sequencing refers to a family of related nucleic acid sequencing techniques that can be used to identify methylated and non-methylated cytosines in nucleic acid sequences.
  • Some methylation sequencing methods include library preparation steps that comprise the addition of enzymes that convert non-methylated cytosines to thymine, while preserving the states of methylated cytosines.
  • the use of such enzymes in methylation sequencing methods confers advantages over other approaches but can, however, be problematic in terms of, e.g., unexpectedly low sequence read yields. Improved compositions and methods are thus needed for performing enzymatic conversion-based methylation sequencing. The present disclosure addresses these needs.
  • sequencing adapter compositions and associated methods and systems configured for use in performing methylation sequencing.
  • Existing sequencing adapters include 5-methylcytosine (5mC) within the adaptor sequences to prevent unwanted conversion of the cytosines in the adaptor sequences while performing conversion of non- methylated cytosines.
  • Many DNA modifying enzymes including those used for methylation sequencing, have sequence- specific biases.
  • studies that demonstrate the erroneous conversion of 5mC into uracil in enzymatic methylation sequencing workflows, and that indicate how sequencing read depth and coverage output could be affected if these erroneous conversion events occur in the adapter sequences.
  • modified sequencing adapters that mitigate erroneous cytosine conversion in the adapter sequences and provide for higher sequence read yields and improved sequencing performance when performing enzymatic conversion-based methylation sequencing.
  • the sequencing adapter compositions described herein comprise modified nucleobases (e.g., alternatives to 5mC) that are better protected from erroneous conversion to uracil when subjected to enzymatic conversion-based methylation sequencing protocols.
  • the modified cytosines (and other modified nucleobases) incorporated into the sequencing adapters disclosed herein exhibit reduced erroneous conversion to uracil compared to that for 5 -methylcytosine.
  • the disclosed sequencing adapter compositions and methods incorporating their use enable improved sequencing performance for detection of methylation states and determining methylation signatures in nucleic acid molecules using enzymatic conversion-based methylation sequencing protocols.
  • the at least one modified cytosine can be 5- hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, 5-formylcytosine, 5- carboxycytosine, or a combination thereof. In any of the embodiments herein, the at least one modified cytosine can be 5-hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, or a combination thereof. In any of the embodiments herein, the at least one modified cytosine can be 5 -hydroxy methylcytosine.
  • the oligonucleotide sequence can comprise 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 modified bases.
  • the oligonucleotide sequence can comprise at least four cytosines, and the three cytosines closest to the 3’ end of the oligonucleotide sequence can be modified cytosines.
  • all or substantially all of the cytosines of the oligonucleotide sequence can be modified cytosines.
  • all or substantially all of the cytosines of the oligonucleotide sequence can be 5-hydroxymethy Icy to sines.
  • the sequencing adapter can comprise two complementary oligonucleotide sequences, each comprising at least four cytosines, and the three cytosines closest to a 3’ end or a 5’ end in at least one of the two complementary oligonucleotide sequences can be modified cytosines.
  • the oligonucleotide sequence can comprise at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 contiguous nucleotides selected from the sequence 5’ CAA GCA GAA GAC GGC ATA CGA GAT 3’ (SEQ ID NO: 2) or its complement.
  • the oligonucleotide sequence can comprise at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, or 33 contiguous nucleotides selected from the sequence 5’ AC A CTC TTT CCC TAC ACG ACG CTC TTC CGA TCT 3’ (SEQ ID NO: 3) or its complement.
  • the oligonucleotide sequence can comprise at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, or 34 contiguous nucleotides selected from the sequence 5’ GTG ACT GGA GTT CAG ACG TGT GCT CTT CCG ATC T 3’ (SEQ ID NO: 4) or its complement.
  • Also disclosed is a method for performing nucleic acid sequencing comprising: a) providing a plurality of nucleic acid molecules obtained from a sample from a subject; b) performing an enzymatic ligation of one or more of any of the sequencing adapters described herein onto the plurality of nucleic acid molecules; c) sequencing, by a sequencer, the ligated nucleic acid molecules to obtain a plurality of sequence reads derived from the sample; and d) receiving, at one or more processors, sequence read data for the plurality of sequence reads derived from the sample.
  • the enzymatic ligation can comprise single- stranded ligation. In some embodiments, the enzymatic ligation can comprise double-stranded ligation.
  • the nucleic acid sequencing may comprise a whole genome sequencing, whole exome sequencing, or targeted sequencing method. In any of the embodiments herein, the nucleic acid sequencing can comprise a methylation sequencing method. In any of the embodiments herein, the methylation sequencing method can comprise an enzymatic cytosine conversion step.
  • the sample can comprise a tissue sample or a buffy coat sample.
  • the methods disclosed can further comprise shearing nucleic acids extracted from the sample to provide the plurality of nucleic acid molecules.
  • the methods disclosed can further comprise performing an end repair reaction on the plurality of nucleic acid molecules prior to performing the enzymatic ligation.
  • the methods disclosed can further comprise performing an A-tailing reaction on the plurality of nucleic acid molecules prior to performing the enzymatic ligation.
  • the methods disclosed can further comprise contacting the ligated nucleic acid molecules with a TET2 enzyme to oxidize 5-methyl-cytosine (5mC) or 5-hydroxymethyl-cytosine (5hmC) to 5-carboxycytosine (5caC) prior to performing the sequencing step.
  • the methods disclosed can further comprise contacting the ligated nucleic acid molecules with a combination of TET2 and T4-PGT enzymes to convert 5-methyl-cytosine (5mC) or 5- hydroxymethyl-cytosine (5hmC) to 5-(D-glucosyl)oxymethyl-cytosine prior to performing the sequencing step.
  • the methods disclosed can further comprise contacting the ligated nucleic acid molecules with an APOBEC enzyme to convert cytosines to uracil prior to performing the sequencing step.
  • the methods disclosed can further comprise performing a nucleic acid amplification reaction to generate amplified nucleic acid molecules prior to performing the sequencing step.
  • the nucleic acid amplification reaction can comprise a polymerase chain reaction.
  • the nucleic acid amplification reaction comprises a rolling circle amplification reaction.
  • the methods disclosed can further comprise capturing a subset of nucleic acid molecules from the amplified nucleic acid molecules prior to performing the sequencing step.
  • the sequencer is a nextgeneration sequencer.
  • the next-generation sequencer comprises a cyclic array sequencer, a nanopore sequencer, or a single mode waveguide sequencer.
  • the methods disclosed can further comprise determining a methylation status for each of a plurality of genomic loci based on the sequence read data.
  • the methods disclosed can further comprise diagnosing or confirming a diagnosis of disease in the subject based at least in part on a variant or a methylation signature identified in the sequence read data.
  • the variant can comprise a single nucleotide variant or a copy number alteration.
  • the methods disclosed can further comprise detecting minimum residual disease in the subject based on the sequence read data.
  • the disease can be cancer.
  • a method comprising: providing a plurality of nucleic acid molecules obtained from a sample from a subject; ligating one or more sequencing adapters onto one or more nucleic acid molecules from the plurality of nucleic acid molecules, wherein the one or more sequencing adapters can comprise an oligonucleotide sequence comprising at least one modified cytosine, wherein the at least one modified cytosine is not 5- methylcytosine, and wherein a rate of conversion of the at least one modified cytosine to uracil when contacted with a deaminating enzyme is less than that of 5-methylcytosine; amplifying the one or more ligated nucleic acid molecules from the plurality of nucleic acid molecules; capturing amplified nucleic acid molecules from the amplified nucleic acid molecules; sequencing, by a sequencer, the captured nucleic acid molecules to obtain a plurality of sequence reads that represent the captured nucleic acid molecules; receiving, at one or more processors, sequence
  • the cancer is a B cell cancer (multiple myeloma), a melanoma, breast cancer, lung cancer, bronchus cancer, colorectal cancer, prostate cancer, pancreatic cancer, stomach cancer, ovarian cancer, urinary bladder cancer, brain cancer, central nervous system cancer, peripheral nervous system cancer, esophageal cancer, cervical cancer, uterine cancer, endometrial cancer, cancer of an oral cavity, cancer of a pharynx, liver cancer, kidney cancer, testicular cancer, biliary tract cancer, small bowel cancer, appendix cancer, salivary gland cancer, thyroid gland cancer, adrenal gland cancer, osteosarcoma, chondrosarcoma, a cancer of hematological tissue, an adenocarcinoma, an inflammatory myofibroblastic tumor, a gastrointestinal stromal tumor (GIST), colon cancer, multiple myeloma (MM), myelodysplastic syndrome (MDS), myeloproliferative disorder (MaB cell cancer (GIST
  • the method may further comprise treating the subject with an anti-cancer therapy.
  • the anti-cancer therapy comprises a targeted anticancer therapy.
  • the targeted anti-cancer therapy comprises abemaciclib (Verzenio), abiraterone acetate (Zytiga), acalabrutinib (Calquence), ado- trastuzumab emtansine (Kadcyla), afatinib dimaleate (Gilotrif), aldesleukin (Proleukin), alectinib (Alecensa), alemtuzumab (Campath), alitretinoin (Panretin), alpelisib (Piqray), amivantamab-vmjw (Rybrevant), anastrozole (Arimidex), apalutamide (Erleada), asciminib hydrochloride (Scemblix), atezoli
  • the method may further comprise obtaining the sample from the subject.
  • the sample comprises a tissue biopsy sample, a liquid biopsy sample, or a normal control.
  • the sample is a liquid biopsy sample and comprises blood, plasma, cerebrospinal fluid, sputum, stool, urine, or saliva.
  • the sample is a liquid biopsy sample and comprises circulating tumor cells (CTCs).
  • the sample is a liquid biopsy sample and comprises cell- free DNA (cfDNA), circulating tumor DNA (ctDNA), or any combination thereof.
  • the plurality of nucleic acid molecules comprises a mixture of tumor nucleic acid molecules and non-tumor nucleic acid molecules.
  • the tumor nucleic acid molecules are derived from a tumor portion of a heterogeneous tissue biopsy sample, and the non-tumor nucleic acid molecules are derived from a normal portion of the heterogeneous tissue biopsy sample.
  • the sample comprises a liquid biopsy sample, and wherein the tumor nucleic acid molecules are derived from a circulating tumor DNA (ctDNA) fraction of the liquid biopsy sample, and the non-tumor nucleic acid molecules are derived from a non-tumor, cell-free DNA (cfDNA) fraction of the liquid biopsy sample.
  • ctDNA circulating tumor DNA
  • cfDNA non-tumor, cell-free DNA
  • the one or more adapters comprise amplification primers, flow cell adaptor sequences, substrate adapter sequences, or sample index sequences.
  • the captured nucleic acid molecules may be captured from the amplified nucleic acid molecules by hybridization to one or more bait molecules.
  • the one or more bait molecules comprise one or more nucleic acid molecules, each comprising a region that is complementary to a region of a captured nucleic acid molecule.
  • amplifying nucleic acid molecules comprises performing a polymerase chain reaction (PCR) amplification technique, a non- PCR amplification technique, or an isothermal amplification technique.
  • PCR polymerase chain reaction
  • the sequencing comprises use of a massively parallel sequencing (MPS) technique, whole genome sequencing (WGS), whole exome sequencing, targeted sequencing, direct sequencing, or Sanger sequencing technique.
  • MPS massively parallel sequencing
  • WGS whole genome sequencing
  • GNS whole exome sequencing
  • targeted sequencing targeted sequencing
  • direct sequencing direct sequencing
  • Sanger sequencing technique e.g., a sequencing with a massively parallel sequencing
  • NGS next generation sequencing
  • the sequencer comprises a next generation sequencer.
  • one or more of the plurality of sequencing reads may overlap one or more gene loci within one or more subgenomic intervals in the sample.
  • the one or more gene loci comprises between 10 and 20 loci, between 10 and 40 loci, between 10 and 60 loci, between 10 and 80 loci, between 10 and 100 loci, between 10 and 150 loci, between 10 and 200 loci, between 10 and 250 loci, between 10 and 300 loci, between 10 and 350 loci, between 10 and 400 loci, between 10 and 450 loci, between 10 and 500 loci, between 20 and 40 loci, between 20 and 60 loci, between 20 and 80 loci, between 20 and 100 loci, between 20 and 150 loci, between 20 and 200 loci, between 20 and 250 loci, between 20 and 300 loci, between 20 and 350 loci, between 20 and 400 loci, between 20 and 500 loci, between 40 and 60 loci, between 40 and 80 loci, between 40 and 100 loci, between 40 and 150 loci, between 40 and 150 loci, between 40 and 80 loci,
  • the one or more gene loci may comprise ABL1, ACVR1B, AKT1, AKT2, AKT3, ALK, ALOX12B, AMER1, APC, AR, ARAF, ARFRP1, ARID1A, ASXL1, ATM, ATR, ATRX, AURKA, AURKB, AXIN1, AXL, BAP1, BARD1, BCL2, BCL2L1, BCL2L2, BCL6, BCOR, BCORL1, BCR, BRAF, BRCA1, BRCA2, BRD4, BRIP1, BTG1, BTG2, BTK, CALR, CARD11, CASP8, CBFB, CBL, CCND1, CCND2, CCND3, CCNE1, CD22, CD274, CD70, CD74, CD79A, CD79B, CDC73, CDH1, CDK12, CDK4, CDK6, CDK8, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CDKN2C, CEBPA
  • the one or more gene loci may comprise ABL, ALK, ALL, B4GALNT1, BAFF, BCL2, BRAF, BRCA, BTK, CD19, CD20, CD3, CD30, CD319, CD38, CD52, CDK4, CDK6, CML, CRACC, CS1, CTLA-4, dMMR, EGFR, ERBB1, ERBB2, FGFR1-3, FLT3, GD2, HDAC, HER1, HER2, HR, IDH2, IL-ip, IL-6, IL-6R, JAK1, JAK2, JAK3, KIT, KRAS, MEK, MET, MSI-H, mTOR, PARP, PD-1, PDGFR, PDGFRa, PDGFRP, PD-L1, PI3K5, PIGF, PTCH, RAF, RANKL, RET, ROS1, SLAMF7, VEGF, VEGFA, VEGFB, or any combination thereof.
  • a method of selecting an anti-cancer therapy comprising: responsive to determining the methylation signature for a sample from a subject, selecting an anti-cancer therapy for the subject, wherein the methylation signature is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to any of the embodiments herein.
  • a method of treating a cancer in a subject comprising: responsive to determining the methylation signature for a sample from the subject, administering an effective amount of an anti-cancer therapy to the subject, wherein the methylation signature is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to any of the embodiments herein.
  • a method for monitoring cancer progression or recurrence in a subject comprising: determining a first methylation signature in a first sample obtained from the subject at a first time point, wherein the first methylation signature is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to any of the embodiments herein; determining a second methylation signature in a second sample obtained from the subject at a second time point; and comparing the first methylation signature to the second methylation signature, thereby monitoring the cancer progression or recurrence.
  • the second methylation signature for the second sample is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to any of the embodiments disclosed herein.
  • the methods disclosed herein can further comprise selecting an anti-cancer therapy for the subject in response to the cancer progression.
  • the methods disclosed herein can further comprise administering an anti-cancer therapy to the subject in response to the cancer progression.
  • the methods disclosed herein can further comprise adjusting an anti-cancer therapy for the subject in response to the cancer progression.
  • the methods disclosed herein can further comprise adjusting a dosage of the anti-cancer therapy or selecting a different anti-cancer therapy in response to the cancer progression.
  • the methods disclosed herein can further comprise administering the adjusted anti-cancer therapy to the subject.
  • the first time point is before the subject has been administered an anti-cancer therapy
  • the second time point is after the subject has been administered the anti-cancer therapy.
  • the subject has a cancer, and can be at risk of having a cancer, is being routine tested for cancer, or is suspected of having a cancer.
  • the cancer can be a solid tumor.
  • the cancer can be a hematological cancer.
  • the anti- cancer therapy can comprise chemotherapy, radiation therapy, immunotherapy, a targeted therapy, or surgery.
  • FIG. 1 depicts a non-limiting example of data that illustrates a histogram depicting the percentage of sequence reads passing a quality filter, in accordance with some instances of the present disclosure.
  • FIG. 2 depicts a non-limiting example of schematics that illustrate primer sequences (ACACTCTTTCCCTACACGACGCTCTTCCGATCT (SEQ ID NO: 3);
  • FIG. 3 depicts a non-limiting example of schematics that illustrate primer sequences (ACACTCTTTCCCTACACGACGCTCTTCCGATCT (SEQ ID NO: 3)) and their complementary sequences (AGATCGGAAGAGCGTCGAGTAGGGAAAGAGTGT (SEQ ID NO: 5); AAATCGGAAAAACGTCGAGTAGGGAAAGAGTGT (SEQ ID NO: 6)), in accordance with some instances of the present disclosure.
  • FIG. 4 depicts a non-limiting example of schematics that illustrate primer sequences (GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT (SEQ ID NO: 4) and their complementary sequences (AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC (SEQ ID NO: 7); AAATCGGAAAAACACACGTCTGAACTCCAGTCAC (SEQ ID NO: 8)), in accordance with some instances of the present disclosure.
  • FIG. 5 depicts a non-limiting example of schematics that illustrates a potential mechanism of action of 5mC modifications, in accordance with some instances of the present disclosure.
  • FIGS. 6A-C depict non-limiting examples of schematics that illustrate the steps of a workflow for processing DNA, in accordance with some instances of the present disclosure.
  • FIG. 6A non-limiting schematic illustration of a process for extracting and purifying DNA from a sample.
  • FIG. 6B non-limiting schematic illustration of a process for performing endrepair and tailing reactions on extracted and purified DNA.
  • FIG. 6C non-limiting schematic illustration of a process for performing enzymatic conversion of cytosines in a DNA sample and performing methylation sequencing.
  • FIG. 7 depicts a non-limiting example of data that illustrates the SNP filtered error rate for different sequencing workflows, in accordance with some instances of the present disclosure.
  • FIG. 8 depicts a non-limiting example of typical adapter sequences provided for use in preparing double-stranded DNA libraries for methylation sequencing, in accordance with some instances of the present disclosure.
  • FIG. 9 depicts a non-limiting example of a modified sequencing adaptor for performing methylation sequencing that comprises incorporated 5hmC nucleotide residues, in accordance with some instances of the present disclosure.
  • FIG. 10 depicts a non-limiting example of a modified sequencing adaptor for performing methylation sequencing that comprises incorporated 5hmC nucleotide residues, in accordance with some instances of the present disclosure.
  • FIG. 11 depicts a non-limiting example of a modified sequencing adaptor for performing methylation sequencing that comprises a single incorporated 5hmC nucleotide residue.
  • FIG. 12 depicts a non-limiting example of data that illustrates the percentage of reads passing a quality filter, for various sequencing platforms and adapter sequences, in accordance with some instances of the present disclosure.
  • FIG. 13 depicts a non-limiting example of schematics that illustrates an assay for validating the effects of modified cytosines, in accordance with some instances of the present disclosure.
  • FIG. 14 depicts a non-limiting example of schematics that illustrates an assay for validating the effects of modified cytosines, in accordance with some instances of the present disclosure.
  • FIG. 15 depicts a non-limiting example of schematics that illustrates an assay for validating the effects of modified cytosines, in accordance with some instances of the present disclosure.
  • FIG. 16 depicts a non-limiting example of data that illustrates the percentage of reads passing a quality filter, for various sequencing methods and adapter sequences, in accordance with some instances of the present disclosure.
  • FIG. 17 depicts a non-limiting example of data that illustrates a ratio of the percentage sequence reads passing filter, for various sequencing methods, in accordance with some instances of the present disclosure.
  • the present disclosure describes novel sequencing adapters.
  • the disclosed sequencing adapters feature an oligonucleotide sequence that contains at least one modified base (e.g., a modified cytosine), where at least one modified base is not 5-methylcytosine, and where the rate of conversion of at least one modified base to uracil, when contacted by a deaminating enzyme, is less than the corresponding rate of conversion of 5-methylcytosine (5mC).
  • modified base e.g., a modified cytosine
  • 5mC 5-methylcytosine
  • the at least one modified base can include, for example, inosine, 5-nitroindole, N4-ethyl- deoxycytidine, 5-propynylcytosine, 5-vinylcytosine, 5-ethynylcytosine, pyrrolo- deoxycytidine, propynyl-deoxycytidine, 5-hydroxymethylcytosine, 5-(D- glucosyl)oxymethylcytosine, 5-formylcytosine, 5-carboxycytosine, or any combination of the above.
  • Some methylation sequencing methods use protective enzymes (e.g. tet methylcytosine dioxygenase 2 (TET2) and/or a glycosylase) to shield methylated cytosines from deaminating enzymes (e.g. apolipoprotein B mRNA editing enzyme catalytic polypeptide (APOBEC)), so the methylated cytosines are not converted into uracil.
  • deaminating enzymes e.g. apolipoprotein B mRNA editing enzyme catalytic polypeptide (APOBEC)
  • APOBEC apolipoprotein B mRNA editing enzyme catalytic polypeptide
  • this protection is configured to be efficient for most methylated cytosines, including 5mC.
  • the TET2 and/or glycosylase enzymes are expected to protect 5mC from being deaminated into cytosine/uracil.
  • the protective enzymes do not act efficiently on certain methylated cytosines, such as 5mC. This poor protecting of 5mC from deamination appears especially prevalent in the context of certain nucleotide sequence motifs. Such poor protection from deamination can affect the 5-methylcytosines of sequencing adapters used in methylation sequencing methods. Failure to protect 5-methylcytosines of sequencing adapters from unintended deamination results in the unprotected 5- methylcytosines deaminating — that is, effectively mutating — into uracil, which can abrogate the complementary binding between the sequencing adapter and flow cell adapters and/or sequencing primers.
  • the expected C-G hybridization between the adapter and the flow cell adapters or sequencing primers will have mutated into a non-hybridizing U-G / T-G pairing, if the protective enzymes fail to prevent the conversion of 5-methylcytosine into uracil.
  • the present disclosure describes a sequencing adapter having a composition that is more resilient to the erroneous conversion of 5-methlycytosine to uracil.
  • the sequencing adapter described herein uses at least one modified base (e.g., a modified base that is not 5mC) that exhibits reduced erroneous conversion to uracil, relative to 5-methylcytosine.
  • the sequencing adapters described herein By being more resilient to the erroneous conversion effects of deaminating enzymes, the sequencing adapters described herein exhibit improvements in retaining their expected nucleic acid sequence, and accordingly, can better hybridize to their target adapter and/or corresponding primer sequences.
  • the sequencing adapters described herein as a result provide improvements to the read depth and/or coverage of genome sequences achieved when applied to enzymatic conversion-based methylation sequencing methods.
  • the sequencing adapters described herein may provide improvements to not only methylation sequencing methods, but also to general technologies comprising the use of deaminating enzymes.
  • a sequencing adapter comprising an oligonucleotide sequencing comprising at least one modified base, wherein the at least one modified cytosine is not 5- methylcytosine, and wherein a rate of conversion of the at least one modified cytosine to uracil when contacted with a deaminating enzyme or enzyme combination is less than that of 5-methylcytosine.
  • the at least one modified base can be inosine, 5-nitroindole, N4-ethyl- deoxycytidine, 5-propynylcytosine, 5-vinylcytosine, 5-ethynylcytosine, pyrrolo- deoxycytidine, or propynyl-deoxy cytidine.
  • the at least one modified base can be a modified cytosine.
  • the modified cytosine of the sequencing adapter can be, for example, 5- hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, 5-formylcytosine, 5- carboxycytosine, or a combination thereof. Definitions
  • ‘About” and “approximately” shall generally mean an acceptable degree of error for the quantity measured given the nature or precision of the measurements. Exemplary degrees of error are within 20 percent (%), typically, within 10%, and more typically, within 5% of a given value or range of values.
  • the terms “comprising” (and any form or variant of comprising, such as “comprise” and “comprises”), “having” (and any form or variant of having, such as “have” and “has”), “including” (and any form or variant of including, such as “includes” and “include”), or “containing” (and any form or variant of containing, such as “contains” and “contain”), are inclusive or open-ended and do not exclude additional, un-recited additives, components, integers, elements, or method steps.
  • the terms “individual,” “patient,” or “subject” are used interchangeably and refer to any single animal, e.g., a mammal (including such non-human animals as, for example, dogs, cats, horses, rabbits, zoo animals, cows, pigs, sheep, and non- human primates) for which treatment is desired.
  • a mammal including such non-human animals as, for example, dogs, cats, horses, rabbits, zoo animals, cows, pigs, sheep, and non- human primates
  • the individual, patient, or subject herein is a human.
  • cancer and “tumor” are used interchangeably herein. These terms refer to the presence of cells possessing characteristics typical of cancer-causing cells, such as uncontrolled proliferation, immortality, metastatic potential, rapid growth and proliferation rate, and certain characteristic morphological features. Cancer cells are often in the form of a tumor, but such cells can exist alone within an animal, or can be a non-tumorigenic cancer cell, such as a leukemia cell. These terms include a solid tumor, a soft tissue tumor, or a metastatic lesion. As used herein, the term “cancer” includes premalignant, as well as malignant cancers.
  • treatment refers to clinical intervention (e.g., administration of an anti-cancer agent or anticancer therapy) in an attempt to alter the natural course of the individual being treated, and can be performed either for prophylaxis or during the course of clinical pathology.
  • Desirable effects of treatment include, but are not limited to, preventing occurrence or recurrence of disease, alleviation of symptoms, diminishment of any direct or indirect pathological consequences of the disease, preventing metastasis, decreasing the rate of disease progression, amelioration or palliation of the disease state, and remission or improved prognosis.
  • genomic interval refers to a portion of a genomic sequence.
  • subject interval refers to a subgenomic interval or an expressed subgenomic interval (e.g., the transcribed sequence of a subgenomic interval).
  • variant sequence As used herein, the terms “variant sequence” or “variant” are used interchangeably and refer to a modified nucleic acid sequence relative to a corresponding “normal” or “wildtype” sequence.
  • a variant sequence may be a “short variant sequence” (or “short variant”), i.e., a variant sequence of less than about 50 base pairs in length.
  • allele frequency and “allele fraction” are used interchangeably herein and refer to the fraction of sequence reads corresponding to a particular allele relative to the total number of sequence reads for a genomic locus.
  • variant allele frequency and “variant allele fraction” are used interchangeably herein and refer to the fraction of sequence reads corresponding to a particular variant allele relative to the total number of sequence reads for a genomic locus.
  • sequencing adapter refers to a short oligonucleotide sequence that may be ligated to template DNA fragments in preparation for performing nucleic acid sequencing, and that may be configured to enable template DNA fragments from a sequencing library to bind to complementary flow cell adapter sequences and/or may comprise sequencing primer binding sites.
  • nucleobase e.g., cytosine
  • cytosine a nucleobase comprising a chemical modification that protects the base from deamination by a combination of enzymes (e.g., glycosylase and/or TET2 and APOBEC).
  • modified cytosine or “protected cytosine” can refer to a cytosine comprising 5- methylcytosine, 5-hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, 5- formylcytosine, or 5-carboxycytosine.
  • modified or “protected” when used to describe a base herein, imply that the base exhibits reduced erroneous conversion to uracil when contacted with a deaminating enzyme (or combination of enzymes) than an “unprotected” base.
  • the modified sequencing adapters configured for methylation sequencing comprise at least one modified cytosine that possesses a rate of conversion to uracil that is less than that of 5-methylcytosine, when in the presence of deaminating enzymes.
  • modified cytosines that exhibit a rate of conversion to uracil by deaminating enzymes that is less than that of 5-methylcytosine and that can be incorporated into the disclosed adapter sequences include, but are not limited to, 5-hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, 5-formylcytosine, or 5-carboxycytosine, and any combination of the aforementioned.
  • 5-hydroxymethylcytosine can be generated from 5- methylcytosine via a ten-eleven translocation (TET) enzyme, and 5-formylcytosine can be generated from 5-hydroxymethylcytosine, also via the TET enzyme.
  • 5- carboxycytosine can be generated from 5-formylcytosine via the TET enzyme.
  • the modified cytosines that are derived from the activity of the TET enzyme on 5-methylcytosine are inefficiently converted into uracil by deaminating enzymes, like APOBEC.
  • these modified cytosines may be included in sequencing adapters for methylation sequencing in place of 5-methylcytosine such that the modified cytosines of the sequencing adapters exhibit reduced erroneous conversion to uracil uracil when used in any technology comprising the application of deaminating enzymes including, but not limited to, methylation sequencing methods.
  • the erroneous conversion of 5-methylcytosine into uracil can be unusually prevalent if the 5-methylcytosine is located in certain nucleotide subsequences. Consequently, adapter sequences comprising such problematic nucleotide subsequences may especially benefit from the inclusion of modified cytosine bases.
  • sequencing adapter comprising an oligonucleotide sequence comprising at least one modified cytosine, where a rate of conversion of the at least one modified cytosine to uracil when contacted with a deaminating enzyme is less than that of 5-methylcytosine.
  • the at least one modified cytosine can be located at any position within the oligonucleotide sequence, e.g., at or in close proximity to the 5’ end or the 3’ end of the adapter sequence, or at a position somewhere in between.
  • the at least one modified cytosine incorporated into the disclosed modified sequencing adapters can be 5-hydroxymethylcytosine, 5-(D- glucosyl)oxymethylcytosine, 5-formylcytosine, 5-carboxycytosine, or a combination thereof. In any of the instances herein, the at least one modified cytosine can be 5- hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, or a combination thereof. In any of the instances herein, the at least one modified cytosine can be 5-hydroxymethylcytosine.
  • the at least one modified cytosine incorporated into the disclosed modified sequencing adapters can be generated via chemical synthesis, or can be isolated and extracted via biotechnological methods.
  • the oligonucleotide sequence can comprise at least four cytosines, and the three cytosines closest to the 3’ end of the oligonucleotide sequence can be modified cytosines.
  • the cytosines of the oligonucleotide sequence can all be modified cytosines.
  • the sequencing adapter can comprise two complementary oligonucleotide sequences, each comprising at least four cytosines, and the three cytosines closest to a 3’ end or a 5’ end in at least one of the two complementary oligonucleotide sequences can be modified cytosines.
  • the deaminating enzyme can be an APOBEC enzyme.
  • the oligonucleotide sequence can be between about 20 and 100 nucleotides in length.
  • the oligonucleotide sequence can be about 20 nucleotides, 25 nucleotides, 30 nucleotides, 35 nucleotides, 40 nucleotides, 45 nucleotides, 50 nucleotides, 55 nucleotides, 60 nucleotides, 65 nucleotides, 70 nucleotides, 75 nucleotides, 80 nucleotides, 85 nucleotides, 90 nucleotides, 95 nucleotides, or 100 nucleotides in length. In some instances, the oligonucleotide sequence can have a length corresponding to any value within the range of 20 nucleotides to 100 nucleotides.
  • the oligonucleotide sequence can comprise at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 contiguous nucleotides selected from the sequence 5’ AAT GAT ACG GCG ACC ACC GA 3’ (SEQ ID NO: 1) or its complement. In any of the instances herein, the oligonucleotide sequence can comprise at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 contiguous nucleotides selected from the sequence 5’ CAA GCA GAA GAC GGC ATA CGA GAT 3’ (SEQ ID NO: 2) or its complement.
  • the oligonucleotide sequence can comprise at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, or 33 contiguous nucleotides selected from the sequence 5’ ACA CTC TTT CCC TAC ACG ACG CTC TTC CGA TCT 3’ (SEQ ID NO: 3) or its complement.
  • the oligonucleotide sequence can comprise at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, or 34 contiguous nucleotides selected from the sequence 5’ GTG ACT GGA GTT CAG ACG TGT GCT CTT CCG ATC T 3’ (SEQ ID NO: 4) or its complement.
  • a method for performing nucleic acid sequencing comprising: a) providing a plurality of nucleic acid molecules obtained from a sample from a subject; b) performing an enzymatic ligation of one or more of the sequence adapters of any one of claims 1 to 14 onto the plurality of nucleic acid molecules; c) sequencing, by a sequencer, the ligated nucleic acid molecules to obtain a plurality of sequence reads derived from the sample; and d) receiving, at one or more processors, sequence read data for the plurality of sequence reads derived from the sample.
  • the enzymatic ligation can comprise single- stranded ligation. In some instances, the enzymatic ligation can comprise double-stranded ligation.
  • the nucleic acid sequencing can comprise a methylation sequencing method.
  • the methylation sequencing method can comprise an enzymatic cytosine conversion step.
  • the methylation sequencing method can comprise a PCR-based detection assay, a quantitative PCR-based detection assay, a digital droplet PCR-based detection assay, a methylation- specific PCR-based detection assay, a methylation- specific selection assay, such as immunoprecipitation of methylated DNA, or a microarray-based DNA methylation profiling assay.
  • the sample can comprise a tissue sample or a buffy coat sample.
  • the methods disclosed can further comprise shearing nucleic acids extracted from the sample to provide the plurality of nucleic acid molecules.
  • the methods disclosed can further comprise performing an end repair reaction on the plurality of nucleic acid molecules prior to performing the enzymatic ligation. In any of the instances herein, the methods disclosed can further comprise performing an A-tailing reaction on the plurality of nucleic acid molecules prior to performing the enzymatic ligation.
  • the end repair reaction and/or the A-tailing reaction can be performed as part of sequencing library preparation, or any other protocol that configures or optimizes nucleic acid molecules for a methylation sequencing method.
  • the end repair reactions can also comprise blunt ligations without any 3’ tailing, the addition of an indeterminate length of bases on the 3’ end, and/or a ligation-free addition of adapters during PCR.
  • terminal deoxytransferase can be used to add an oligo-A tail rather than a single A tail.
  • the methods disclosed can further comprise contacting the ligated nucleic acid molecules with a TET2 enzyme to oxidize 5-methyl-cytosine (5mC) or 5-hydroxymethyl-cytosine (5hmC) to 5-carboxycytosine (5caC) prior to performing the sequencing step.
  • the methods disclosed can further comprise contacting the ligated nucleic acid molecules with a combination of TET2 and T4-PGT enzymes to convert 5-methyl-cytosine (5mC) or 5-hydroxymethyl-cytosine (5hmC) to 5-(D- glucosyl)oxymethyl-cytosine prior to performing the sequencing step.
  • the methods disclosed can further comprise contacting the ligated nucleic acid molecules with an APOBEC enzyme to convert cytosines to uracil prior to performing the sequencing step.
  • the methods disclosed can further comprise performing a nucleic acid amplification reaction to generate amplified nucleic acid molecules prior to performing the sequencing step.
  • the nucleic acid amplification reaction can comprise a polymerase chain reaction.
  • the methods disclosed can further comprise capturing a subset of nucleic acid molecules from the amplified nucleic acid molecules prior to performing the sequencing step.
  • the sequencing can be performed using a next-generation sequencer.
  • the methods disclosed can further comprise determining a methylation status for each of a plurality of genomic loci based on the sequence read data.
  • the methods disclosed can further comprise diagnosing or confirming a diagnosis of disease in the subject based on a variant or a methylation signature identified in the sequence read data.
  • the variant can comprise a single nucleotide variant or a copy number alteration.
  • the methods disclosed can further comprise detecting minimum residual disease in the subject based on the sequence read data.
  • the disease can be cancer.
  • a method comprising: providing a plurality of nucleic acid molecules obtained from a sample from a subject; ligating one or more sequencing adapters onto one or more nucleic acid molecules from the plurality of nucleic acid molecules, wherein the one or more sequencing adapters can comprise an oligonucleotide sequence comprising at least one modified cytosine, wherein a rate of conversion of the at least one modified cytosine to uracil when contacted with a deaminating enzyme is less than that of 5- methylcytosine; amplifying the one or more ligated nucleic acid molecules from the plurality of nucleic acid molecules; capturing amplified nucleic acid molecules from the amplified nucleic acid molecules; sequencing, by a sequencer, the captured nucleic acid molecules to obtain a plurality of sequence reads that represent the captured nucleic acid molecules; receiving, at one or more processors, sequence read data for the plurality of sequence reads; identifying, using the one or more processor
  • a method for diagnosing a disease comprising: diagnosing that a subject has the disease based on a determination of a methylation signature for a sample from the subject, wherein the methylation signature can be determined according to any of the instances herein.
  • a method of selecting an anti-cancer therapy comprising: responsive to determining the methylation signature for a sample from a subject, selecting an anti-cancer therapy for the subject, wherein the methylation signature is determined according to any of the instances herein.
  • a method of treating a cancer in a subject comprising: responsive to determining the methylation signature for a sample from the subject, administering an effective amount of an anti-cancer therapy to the subject, wherein the methylation signature is determined according to any of the instances herein.
  • a method for monitoring cancer progression or recurrence in a subject comprising: determining a first methylation signature in a first sample obtained from the subject at a first time point according to any of the instances herein; determining a second methylation signature in a second sample obtained from the subject at a second time point; and comparing the first methylation signature to the second methylation signature, thereby monitoring the cancer progression or recurrence.
  • the second methylation signature for the second sample is determined according to the instances disclosed herein.
  • the methods disclosed herein can further comprise selecting an anti-cancer therapy for the subject in response to the cancer progression.
  • the methods disclosed herein can further comprise administering an anti-cancer therapy to the subject in response to the cancer progression.
  • the methods disclosed herein can further comprise adjusting an anti-cancer therapy for the subject in response to the cancer progression.
  • the methods disclosed herein can further comprise adjusting a dosage of the anti-cancer therapy or selecting a different anti-cancer therapy in response to the cancer progression.
  • the methods disclosed herein can further comprise administering the adjusted anti-cancer therapy to the subject.
  • the first time point is before the subject has been administered an anti-cancer therapy
  • the second time point is after the subject has been administered the anti-cancer therapy.
  • the subject has a cancer, and can be at risk of having a cancer, is being routine tested for cancer, or is suspected of having a cancer.
  • the cancer can be a solid tumor.
  • the cancer can be a hematological cancer.
  • the anti-cancer therapy can comprise chemotherapy, radiation therapy, immunotherapy, a targeted therapy, or surgery.
  • the disclosed methods may further comprise one or more of the steps of: (i) obtaining the sample from the subject (e.g., a subject suspected of having or determined to have cancer), (ii) extracting nucleic acid molecules (e.g., a mixture of tumor nucleic acid molecules and non-tumor nucleic acid molecules) from the sample, (iii) ligating one or more adapters to the nucleic acid molecules extracted from the sample (e.g., one or more amplification primers, flow cell adaptor sequences, substrate adapter sequences, or sample index sequences), (iv) performing a methylation conversion reaction to convert, e.g., non-methylated cytosine to uracil, (v) amplifying the nucleic acid molecules (e.g., using a polymerase chain reaction (PCR) amplification technique, a non-PCR amplification technique, or an isothermal amplification technique), (vi) capturing nucleic acid molecules from the amplified
  • PCR polymerase
  • the report comprises output from the methods described herein. In some instances, all or a 1 portion of the report may be displayed in the graphical user interface of an online or webbased healthcare portal. In some instances, the report is transmitted via a computer network or peer-to-peer connection.
  • the sample may comprise a tissue biopsy sample, a liquid biopsy sample, or a normal control.
  • the sample may be a liquid biopsy sample and may comprise blood, plasma, cerebrospinal fluid, sputum, stool, urine, or saliva.
  • the sample may be a liquid biopsy sample and may comprise circulating tumor cells (CTCs).
  • the sample may be a liquid biopsy sample and may comprise cell-free DNA (cfDNA).
  • the cell-free DNA (cfDNA), or a portion thereof, may comprise circulating tumor DNA (ctDNA).
  • the liquid biopsy sample may comprise a combination of cell-free DNA (cfDNA) and circulating tumor DNA (ctDNA).
  • the nucleic acid molecules extracted from a sample may comprise a mixture of tumor nucleic acid molecules and non-tumor nucleic acid molecules.
  • the tumor nucleic acid molecules may be derived from a tumor portion of a heterogeneous tissue biopsy sample, and the non-tumor nucleic acid molecules may be derived from a normal portion of the heterogeneous tissue biopsy sample.
  • the sample may comprise a liquid biopsy sample, and the tumor nucleic acid molecules may be derived from a circulating tumor DNA (ctDNA) fraction of the liquid biopsy sample while the non-tumor nucleic acid molecules may be derived from a non-tumor, cell-free DNA (cfDNA) fraction of the liquid biopsy sample.
  • ctDNA circulating tumor DNA
  • the disclosed methods for methylation sequencing may be used to diagnose (or as part of a diagnosis of) the presence of disease or other condition (e.g., cancer, genetic disorders (such as Down Syndrome and Fragile X), neurological disorders, or any other disease type where detection of variants, e.g., copy number alternations, are relevant to diagnosing, treating, or predicting said disease) in a subject (e.g., a patient).
  • disease or other condition e.g., cancer, genetic disorders (such as Down Syndrome and Fragile X), neurological disorders, or any other disease type where detection of variants, e.g., copy number alternations, are relevant to diagnosing, treating, or predicting said disease
  • a subject e.g., a patient
  • the disclosed methods may be applicable to diagnosis of any of a variety of cancers as described elsewhere herein.
  • the disclosed methods for methylation sequencing may be used to predict genetic disorders in fetal DNA. (e.g., for invasive or non-invasive prenatal testing), such as, but not limited to, the methods described in Tsui, D.W.Y. et al., Chimerism, 2010, 1 ( 1) :30-35.
  • sequence read data obtained by sequencing fetal DNA extracted from samples obtained using invasive amniocentesis, chorionic villus sampling (cVS), or fetal umbilical cord sampling techniques, or obtained using non-invasive sampling of cell- free DNA (cfDNA) samples (which comprises a mix of maternal cfDNA and fetal cfDNA), may be processed according to the disclosed methods to identify variants, e.g., copy number alterations, associated with, e.g., Down Syndrome (trisomy 21), trisomy 18, trisomy 13, and extra or missing copies of the X and Y chromosomes.
  • variants e.g., copy number alterations, associated with, e.g., Down Syndrome (trisomy 21), trisomy 18, trisomy 13, and extra or missing copies of the X and Y chromosomes.
  • the disclosed methods for methylation sequencing may be used to select a subject (e.g., a patient) for a clinical trial based on the nucleic acid sequence determined for one or more gene loci.
  • patient selection for clinical trials based on, e.g., identification of a methylation signature at one or more gene loci may accelerate the development of targeted therapies and improve the healthcare outcomes for treatment decisions.
  • the disclosed methods for methylation sequencing may be used to select an appropriate therapy or treatment (e.g., an anti-cancer therapy or anti-cancer treatment) for a subject.
  • an appropriate therapy or treatment e.g., an anti-cancer therapy or anti-cancer treatment
  • the anti-cancer therapy or treatment may comprise use of a poly (ADP-ribose) polymerase inhibitor (PARPi), a platinum compound, chemotherapy, radiation therapy, a targeted therapy, an immunotherapy, a neoantigen-based therapy, surgery, or any combination thereof.
  • PARPi poly (ADP-ribose) polymerase inhibitor
  • the anti-cancer target therapy or treatment may comprise a targeted anti-cancer therapy or treatment (e.g., a monoclonal antibody-based therapy, an enzyme inhibitor-based therapy, an antibody-drug conjugate therapy, a hormone therapy, and/or a targeted radiotherapy) that targets specific molecules required for cancer cell growth, division, and spreading.
  • a targeted anti-cancer therapy or treatment e.g., a monoclonal antibody-based therapy, an enzyme inhibitor-based therapy, an antibody-drug conjugate therapy, a hormone therapy, and/or a targeted radiotherapy
  • the targeted anti-cancer therapy or treatment may comprise abemaciclib (Verzenio), abiraterone acetate (Zytiga), acalabrutinib (Calquence), ado-trastuzumab emtansine (Kadcyla), afatinib dimaleate (Gilotrif), alectinib (Alecensa), alemtuzumab (Campath), alitretinoin (Panretin), alpelisib (Piqray), amivantamab-vmjw (Rybrevant), anastrozole (Arimidex), apalutamide (Erleada), asciminib hydrochloride (Scemblix), atezolizumab (Tecentriq), avapritinib (Ayvakit), avelumab (Bavencio), axicabtagene ciloleucel (Yescarta),
  • the anti-cancer therapy or treatment may comprise an immunotherapy (e.g., a cancer treatment that acts by stimulating the immune system to fight cancer).
  • the immunotherapy can be, for example, an immune system modulator (e.g., a cytokine, such as an interferon or interleukin), an immune checkpoint inhibitor (such as an anti-PD-1 or anti-PD-Ll antibody), a T-cell transfer therapy (e.g., a tumor infiltrating lymphocyte (TIL) therapy in lymphocytes extracted from a patient’s tumor are selected for their ability to recognize tumor cells and propagated prior to reintroduction into the patient, or a CAR T-cell therapy in which a patient’s T-cells are modified to express the CAR protein prior to reintroduction into the patient), a monoclonal antibody-based therapy (e.g., a monoclonal antibody that binds to cell surface markers on cancer cells to facilitate recognition by the immune system), or a cancer treatment
  • an immune system modulator e
  • the anti-cancer therapy or treatment may comprise a neoantigenbased therapy.
  • neoantigen-based therapies include T-cell receptor (TCR) engineered T-cell (TCR-T) therapies, chimeric antigen receptor T-cell (CAR-T) therapies, TCR bispecific antibody therapies, and cancer vaccines.
  • TCR-T therapies are produced by genetically engineering a patient’s T-cells to express T-cell receptors that are specific to neoantigens of interest, and then infusing them back into the patient.
  • CAR-T therapies are produced by genetically engineering a patient’s T-cells to express chimeric antigen receptor molecules which contain an intracellular signaling and co-signaling domain as well as an extracellular antigen-binding domain; CAR-T therapies don’t always rely on neoantigen presentation, but can be designed to be directed towards neoantigens.
  • TCR bispecific antibody therapies are small, engineered antibody molecules that comprise a neoantigen-specific TCR on one end and a CD3-directed single-chain variable fragment on the other end.
  • Cancer vaccines can include RNA molecules, DNA molecules, peptides, or a combination thereof that are designed to boost the immune system’s ability to find and destroy neoantigen-presenting cells.
  • the disclosed methods for methylation sequencing may be used in treating a disease (e.g., a cancer) in a subject.
  • a disease e.g., a cancer
  • an effective amount of an anti-cancer therapy or anti-cancer treatment may be administered to the subject.
  • the disclosed methods for methylation sequencing may be used for monitoring disease progression or recurrence (e.g., cancer or tumor progression or recurrence) in a subject.
  • the methods may be used to determine a methylation signature in a first sample obtained from the subject at a first time point, and used to determine a methylation signature in a second sample obtained from the subject at a second time point, where comparison of the first determination of the methylation signature and the second determination of the methylation signature allows one to monitor disease progression or recurrence.
  • the first time point is chosen before the subject has been administered a therapy or treatment
  • the second time point is chosen after the subject has been administered the therapy or treatment.
  • the disclosed methods may be used for adjusting a therapy or treatment (e.g., an anti-cancer treatment or anti-cancer therapy) for a subject, e.g., by adjusting a treatment dose and/or selecting a different treatment in response to a change in the determination of the methylation signature.
  • a therapy or treatment e.g., an anti-cancer treatment or anti-cancer therapy
  • the methylation signature determined using the disclosed methods may be used as a prognostic or diagnostic indicator associated with the sample.
  • the prognostic or diagnostic indicator may comprise an indicator of the presence of a disease (e.g., cancer) in the sample, an indicator of the probability that a disease (e.g., cancer) is present in the sample, an indicator of the probability that the subject from which the sample was derived will develop a disease (e.g., cancer) (z.e., a risk factor), or an indicator of the likelihood that the subject from which the sample was derived will respond to a particular therapy or treatment.
  • the disclosed methods for methylation sequencing may be implemented as part of a genomic profiling process that comprises identification of the presence of variant sequences at one or more gene loci in a sample derived from a subject as part of detecting, monitoring, predicting a risk factor, or selecting a treatment for a particular disease, e.g., cancer.
  • the variant panel selected for genomic profiling may comprise the detection of variant sequences at a selected set of gene loci.
  • the variant panel selected for genomic profiling may comprise detection of variant sequences at a number of gene loci through comprehensive genomic profiling (CGP), which is a nextgeneration sequencing (NGS) approach used to assess hundreds of genes (including relevant cancer biomarkers) in a single assay.
  • CGP comprehensive genomic profiling
  • NGS nextgeneration sequencing
  • Inclusion of the disclosed methods for nucleic acid sequencing as part of a genomic profiling process can improve the validity of, e.g., disease detection calls and treatment decisions, made on the basis of the genomic profile by, for example, independently confirming the presence of a methylation signature in a given patient sample.
  • a genomic profile may comprise information on the presence of genes (or variant sequences thereof), copy number variations, epigenetic traits, proteins (or modifications thereof), and/or other biomarkers in an individual’s genome and/or proteome, as well as information on the individual’s corresponding phenotypic traits and the interaction between genetic or genomic traits, phenotypic traits, and environmental factors.
  • a genomic profile for the subject may comprise results from a comprehensive genomic profiling (CGP) test, a nucleic acid sequencing-based test, a gene expression profiling test, a cancer hotspot panel test, a DNA methylation test, a DNA fragmentation test, an RNA fragmentation test, or any combination thereof.
  • CGP genomic profiling
  • the method can further include administering or applying a treatment or therapy e.g., an anti-cancer agent, anti-cancer treatment, or anti-cancer therapy) to the subject based on the generated genomic profile.
  • a treatment or therapy e.g., an anti-cancer agent, anti-cancer treatment, or anti-cancer therapy
  • An anti-cancer agent or anti-cancer treatment may refer to a compound that is effective in the treatment of cancer cells.
  • anti-cancer agents or anti-cancer therapies include, but not limited to, alkylating agents, antimetabolites, natural products, hormones, chemotherapy, radiation therapy, immunotherapy, surgery, or a therapy configured to target a defect in a specific cell signaling pathway, e.g., a defect in a DNA mismatch repair (MMR) pathway.
  • MMR DNA mismatch repair
  • the disclosed methods and systems may be used with any of a variety of samples (also referred to herein as specimens) comprising nucleic acids (e.g., DNA or RNA) that are collected from a subject (e.g.. a patient).
  • samples also referred to herein as specimens
  • nucleic acids e.g., DNA or RNA
  • a sample examples include, but are not limited to, a tumor sample, a tissue sample, a biopsy sample e.g., a tissue biopsy, a liquid biopsy, or both), a blood sample (e.g., a peripheral whole blood sample), a blood plasma sample, a blood serum sample, a lymph sample, a saliva sample, a sputum sample, a urine sample, a gynecological fluid sample, a circulating tumor cell (CTC) sample, a cerebral spinal fluid (CSF) sample, a pericardial fluid sample, a pleural fluid sample, an ascites (peritoneal fluid) sample, a feces (or stool) sample, or other body fluid, secretion, and/or excretion sample (or cell sample derived therefrom).
  • the sample may be frozen sample or a formalin-fixed paraffin-embedded (FFPE) sample.
  • FFPE formalin-fixed paraffin-embedded
  • the sample may be collected by tissue resection (e.g., surgical resection), needle biopsy, bone marrow biopsy, bone marrow aspiration, skin biopsy, endoscopic biopsy, fine needle aspiration, oral swab, nasal swab, vaginal swab or a cytology smear, scrapings, washings or lavages (such as a ductal lavage or bronchoalveolar lavage), etc.
  • tissue resection e.g., surgical resection
  • needle biopsy e.g., bone marrow biopsy, bone marrow aspiration, skin biopsy, endoscopic biopsy, fine needle aspiration, oral swab, nasal swab, vaginal swab or a cytology smear
  • fine needle aspiration e.g., oral swab, nasal swab, vaginal swab or a cytology smear
  • scrapings e.
  • the sample is a liquid biopsy sample, and may comprise, e.g., whole blood, blood plasma, blood serum, urine, stool, sputum, saliva, or cerebrospinal fluid.
  • the sample may be a liquid biopsy sample and may comprise circulating tumor cells (CTCs).
  • the sample may be a liquid biopsy sample and may comprise cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), or any combination thereof.
  • the sample may comprise one or more premalignant or malignant cells.
  • Premalignant refers to a cell or tissue that is not yet malignant but is poised to become malignant.
  • the sample may be acquired from a solid tumor, a soft tissue tumor, or a metastatic lesion.
  • the sample may be acquired from a hematologic malignancy or pre-malignancy.
  • the sample may comprise a tissue or cells from a surgical margin.
  • the sample may comprise tumor-infiltrating lymphocytes.
  • the sample may comprise one or more non-malignant cells.
  • the sample may be, or is part of, a primary tumor or a metastasis (e.g., a metastasis biopsy sample).
  • the sample may be obtained from a site (e.g., a tumor site) with the highest percentage of tumor (e.g., tumor cells) as compared to adjacent sites (e.g., sites adjacent to the tumor).
  • the sample may be obtained from a site (e.g., a tumor site) with the largest tumor focus (e.g., the largest number of tumor cells as visualized under a microscope) as compared to adjacent sites (e.g., sites adjacent to the tumor).
  • the disclosed methods may further comprise analyzing a primary control (e.g., a normal tissue sample). In some instances, the disclosed methods may further comprise determining if a primary control is available and, if so, isolating a control nucleic acid (e.g., DNA) from said primary control. In some instances, the sample may comprise any normal control (e.g., a normal adjacent tissue (NAT)) if no primary control is available. In some instances, the sample may be or may comprise histologically normal tissue. In some instances, the method includes evaluating a sample, e.g., a histologically normal sample (e.g., from a surgical tissue margin) using the methods described herein.
  • a primary control e.g., a normal tissue sample.
  • the disclosed methods may further comprise determining if a primary control is available and, if so, isolating a control nucleic acid (e.g., DNA) from said primary control.
  • the sample may comprise any normal control (e.g.,
  • the disclosed methods may further comprise acquiring a sub-sample enriched for non-tumor cells, e.g., by macro-dissecting non-tumor tissue from said NAT in a sample not accompanied by a primary control. In some instances, the disclosed methods may further comprise determining that no primary control and no NAT is available, and marking said sample for analysis without a matched control.
  • samples obtained from histologically normal tissues may still comprise a genetic alteration such as a variant sequence as described herein.
  • the methods may thus further comprise re-classifying a sample based on the presence of the detected genetic alteration.
  • multiple samples e.g., from different subjects are processed simultaneously.
  • tissue samples e.g., solid tissue samples, soft tissue samples, metastatic lesions, or liquid biopsy samples.
  • tissues include, but are not limited to, connective tissue, muscle tissue, nervous tissue, epithelial tissue, and blood.
  • Tissue samples may be collected from any of the organs within an animal or human body.
  • human organs include, but are not limited to, the brain, heart, lungs, liver, kidneys, pancreas, spleen, thyroid, mammary glands, uterus, prostate, large intestine, small intestine, bladder, bone, skin, etc.
  • the nucleic acids extracted from the sample may comprise deoxyribonucleic acid (DNA) molecules.
  • DNA DNA that may be suitable for analysis by the disclosed methods include, but are not limited to, genomic DNA or fragments thereof, mitochondrial DNA or fragments thereof, cell-free DNA (cfDNA), and circulating tumor DNA (ctDNA).
  • Cell-free DNA (cfDNA) is comprised of fragments of DNA that are released from normal and/or cancerous cells during apoptosis and necrosis, and circulate in the blood stream and/or accumulate in other bodily fluids.
  • Circulating tumor DNA ctDNA is comprised of fragments of DNA that are released from cancerous cells and tumors that circulate in the blood stream and/or accumulate in other bodily fluids.
  • DNA is extracted from nucleated cells from the sample.
  • a sample may have a low nucleated cellularity, e.g., when the sample is comprised mainly of erythrocytes, lesional cells that contain excessive cytoplasm, or tissue with fibrosis.
  • a sample with low nucleated cellularity may require more, e.g., greater, tissue volume for DNA extraction.
  • the nucleic acids extracted from the sample may comprise ribonucleic acid (RNA) molecules.
  • RNA ribonucleic acid
  • examples of RNA that may be suitable for analysis by the disclosed methods include, but are not limited to, total cellular RNA, total cellular RNA after depletion of certain abundant RNA sequences (e.g., ribosomal RNAs), cell-free RNA (cfRNA), messenger RNA (mRNA) or fragments thereof, the poly(A)-tailed mRNA fraction of the total RNA, ribosomal RNA (rRNA) or fragments thereof, transfer RNA (tRNA) or fragments thereof, and mitochondrial RNA or fragments thereof.
  • ribosomal RNAs e.g., ribosomal RNAs
  • cfRNA cell-free RNA
  • mRNA messenger RNA
  • rRNA transfer RNA
  • tRNA transfer RNA
  • RNA may be extracted from the sample and converted to complementary DNA (cDNA) using, e.g., a reverse transcription reaction.
  • cDNA complementary DNA
  • the cDNA is produced by random-primed cDNA synthesis methods.
  • the cDNA synthesis is initiated at the poly (A) tail of mature mRNAs by priming with oligo(dT)-containing oligonucleotides. Methods for depletion, poly(A) enrichment, and cDNA synthesis are well known to those of skill in the art.
  • the sample may comprise a tumor content (e.g., comprising tumor cells or tumor cell nuclei), or a non-tumor content (e.g., immune cells, fibroblasts, and other non-tumor cells).
  • the tumor content of the sample may constitute a sample metric.
  • the sample may comprise a tumor content of at least 5-50%, 10- 40%, 15-25%, or 20-30% tumor cell nuclei.
  • the sample may comprise a tumor content of at least 5%, at least 10%, at least 20%, at least 30%, at least 40%, or at least 50% tumor cell nuclei.
  • the percent tumor cell nuclei (e.g., sample fraction) is determined (e.g., calculated) by dividing the number of tumor cells in the sample by the total number of all cells within the sample that have nuclei.
  • a different tumor content calculation may be required due to the presence of hepatocytes having nuclei with twice, or more than twice, the DNA content of other, e.g., non-hepatocyte, somatic cell nuclei.
  • the sensitivity of detection of a genetic alteration e.g., a variant sequence, or a determination of, e.g., micro satellite instability, may depend on the tumor content of the sample. For example, a sample having a lower tumor content can result in lower sensitivity of detection for a given size sample.
  • the sample comprises nucleic acid (e.g., DNA, RNA (or a cDNA derived from the RNA), or both), e.g., from a tumor or from normal tissue.
  • nucleic acid e.g., DNA, RNA (or a cDNA derived from the RNA), or both
  • the sample may further comprise a non-nucleic acid component, e.g., cells, protein, carbohydrate, or lipid, e.g., from the tumor or normal tissue.
  • the sample is obtained (e.g., collected) from a subject (e.g., patient) with a condition or disease (e.g., a hyperproliferative disease or a non-cancer indication) or suspected of having the condition or disease.
  • a condition or disease e.g., a hyperproliferative disease or a non-cancer indication
  • the hyperproliferative disease is a cancer.
  • the cancer is a solid tumor or a metastatic form thereof.
  • the cancer is a hematological cancer, e.g., a leukemia or lymphoma.
  • the subject has a cancer or is at risk of having a cancer.
  • the subject has a genetic predisposition to a cancer (e.g., having a genetic mutation that increases his or her baseline risk for developing a cancer).
  • the subject has been exposed to an environmental perturbation (e.g., radiation or a chemical) that increases his or her risk for developing a cancer.
  • the subject is in need of being monitored for development of a cancer.
  • the subject is in need of being monitored for cancer progression or regression, e.g., after being treated with an anti-cancer therapy (or anti-cancer treatment).
  • the subject is in need of being monitored for relapse of cancer.
  • the subject is in need of being monitored for minimum residual disease (MRD).
  • the subject has been, or is being treated, for cancer.
  • the subject has not been treated with an anti-cancer therapy (or anti-cancer treatment).
  • the subject e.g., a patient
  • a post-targeted therapy sample e.g., specimen
  • the post-targeted therapy sample is a sample obtained after the completion of the targeted therapy.
  • the patient has not been previously treated with a targeted therapy.
  • the sample comprises a resection, e.g., an original resection, or a resection following recurrence (e.g., following a disease recurrence post- therapy).
  • the sample is acquired from a subject having a cancer.
  • exemplary cancers include, but are not limited to, B cell cancer (e.g., multiple myeloma), melanomas, breast cancer, lung cancer (such as non-small cell lung carcinoma or NSCLC), bronchus cancer, colorectal cancer, prostate cancer, pancreatic cancer, stomach cancer, ovarian cancer, urinary bladder cancer, brain or central nervous system cancer, peripheral nervous system cancer, esophageal cancer, cervical cancer, uterine or endometrial cancer, cancer of the oral cavity or pharynx, liver cancer, kidney cancer, testicular cancer, biliary tract cancer, small bowel or appendix cancer, salivary gland cancer, thyroid gland cancer, adrenal gland cancer, osteosarcoma, chondrosarcoma, cancer of hematological tissues, adenocarcinomas, inflammatory myofibroblastic tumors, gastrointestinal stromal tumor (GIST), colon cancer, multiple myeloma (MM),
  • B cell cancer
  • the cancer comprises acute lymphoblastic leukemia (Philadelphia chromosome positive), acute lymphoblastic leukemia (precursor B-cell), acute myeloid leukemia (FLT3+), acute myeloid leukemia (with an IDH2 mutation), anaplastic large cell lymphoma, basal cell carcinoma, B-cell chronic lymphocytic leukemia, bladder cancer, breast cancer (HER2 overexpressed/amplified), breast cancer (HER2+), breast cancer (HR+, HER2- ), cervical cancer, cholangiocarcinoma, chronic lymphocytic leukemia, chronic lymphocytic leukemia (with 17p deletion), chronic myelogenous leukemia, chronic myelogenous leukemia (Philadelphia chromosome positive), classical Hodgkin lymphoma, colorectal cancer, colorectal cancer (dMMR and MSI-H), colorectal cancer (KRAS wild type), cryopyrin- associated periodic syndrome,
  • the cancer is a hematologic malignancy (or premaligancy).
  • a hematologic malignancy refers to a tumor of the hematopoietic or lymphoid tissues, e.g., a tumor that affects blood, bone marrow, or lymph nodes.
  • Exemplary hematologic malignancies include, but are not limited to, leukemia (e.g., acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), chronic myelogenous leukemia (CML), hairy cell leukemia, acute monocytic leukemia (AMoL), chronic myelomonocytic leukemia (CMML), juvenile myelomonocytic leukemia (JMML), or large granular lymphocytic leukemia), lymphoma (e.g., AIDS-related lymphoma, cutaneous T-cell lymphoma, Hodgkin lymphoma (e.g., classical Hodgkin lymphoma or nodular lymphocyte-predominant Hodgkin lymphoma), mycosis fungoides, non-Hodgkin lymphoma (e.g., B-cell non-Hodgkin lymphoma (e
  • DNA or RNA may be extracted from tissue samples, biopsy samples, blood samples, or other bodily fluid samples using any of a variety of techniques known to those of skill in the art (see, e.g., Example 1 of International Patent Application Publication No. WO 2012/092426; Tan, et al. (2009), “DNA, RNA, and Protein Extraction: The Past and The Present”, J. Biomed. Biotech. 2009:574398; the technical literature for the Maxwell® 16 LEV Blood DNA Kit (Promega Corporation, Madison, WI); and the Maxwell 16 Buccal Swab LEV DNA Purification Kit Technical Manual (Promega Literature #TM333, January 1, 2011, Promega Corporation, Madison, WI)). Protocols for RNA isolation are disclosed in, e.g., the Maxwell® 16 Total RNA Purification Kit Technical Bulletin (Promega Literature #TB351, August 2009, Promega Corporation, Madison, WI).
  • a typical DNA extraction procedure for example, comprises (i) collection of the fluid sample, cell sample, or tissue sample from which DNA is to be extracted, (ii) disruption of cell membranes (z.e., cell lysis), if necessary, to release DNA and other cytoplasmic components, (iii) treatment of the fluid sample or lysed sample with a concentrated salt solution to precipitate proteins, lipids, and RNA, followed by centrifugation to separate out the precipitated proteins, lipids, and RNA, and (iv) purification of DNA from the supernatant to remove detergents, proteins, salts, or other reagents used during the cell membrane lysis step.
  • Disruption of cell membranes may be performed using a variety of mechanical shear (e.g., by passing through a Erench press or fine needle) or ultrasonic disruption techniques.
  • the cell lysis step often comprises the use of detergents and surfactants to solubilize lipids the cellular and nuclear membranes.
  • the lysis step may further comprise use of proteases to break down protein, and/or the use of an RNase for digestion of RNA in the sample.
  • cellular and histone proteins bound to the DNA may be removed either by adding a protease or by having precipitated the proteins with sodium or ammonium acetate, or through extraction with a phenol-chloroform mixture prior to a DNA precipitation step.
  • DNA may be extracted using any of a variety of suitable commercial DNA extraction and purification kits. Examples include, but are not limited to, the QIAamp (for isolation of genomic DNA from human samples) and DNAeasy (for isolation of genomic DNA from animal or plant samples) kits from Qiagen (Germantown, MD) or the Maxwell® and ReliaPrepTM series of kits from Promega (Madison, WI).
  • the sample may comprise a formalin-fixed (also known as formaldehyde-fixed, or paraformaldehyde-fixed), paraffin-embedded (FFPE) tissue preparation.
  • FFPE formalin-fixed
  • the FFPE sample may be a tissue sample embedded in a matrix, e.g., an FFPE block.
  • nucleic acids e.g., DNA
  • Methods to isolate nucleic acids (e.g., DNA) from formaldehyde- or paraformaldehyde-fixed, paraffin-embedded (FFPE) tissues are disclosed in, e.g., Cronin, et al., (2004) Am J Pathol. 164(l):35-42; Masuda, et al., (1999) Nucleic Acids Res.
  • the RecoverAllTM Total Nucleic Acid Isolation Kit uses xylene at elevated temperatures to solubilize paraffin-embedded samples and a glass-fiber filter to capture nucleic acids.
  • the Maxwell® 16 FFPE Plus LEV DNA Purification Kit is used with the Maxwell® 16 Instrument for purification of genomic DNA from 1 to 10 pm sections of FFPE tissue. DNA is purified using silica-clad paramagnetic particles (PMPs), and eluted in low elution volume.
  • PMPs silica-clad paramagnetic particles
  • the E.Z.N.A.® FFPE DNA Kit uses a spin column and buffer system for isolation of genomic DNA.
  • QIAamp® DNA FFPE Tissue Kit uses QIAamp® DNA Micro technology for purification of genomic and mitochondrial DNA.
  • the disclosed methods may further comprise determining or acquiring a yield value for the nucleic acid extracted from the sample and comparing the determined value to a reference value. For example, if the determined or acquired value is less than the reference value, the nucleic acids may be amplified prior to proceeding with library construction. In some instances, the disclosed methods may further comprise determining or acquiring a value for the size (or average size) of nucleic acid fragments in the sample, and comparing the determined or acquired value to a reference value, e.g., a size (or average size) of at least 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 base pairs (bps).
  • a reference value e.g., a size (or average size) of at least 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 base pairs (bps).
  • the nucleic acids are typically dissolved in a slightly alkaline buffer, e.g., Tris-EDTA (TE) buffer, or in ultra-pure water.
  • the isolated nucleic acids e.g., genomic DNA
  • genomic DNA can be fragmented by physical shearing methods, enzymatic cleavage methods, chemical cleavage methods, and other methods known to those of skill in the art. Methods for DNA shearing are described in Example 4 in International Patent Application Publication No. WO 2012/092426. In some instances, alternatives to DNA shearing methods can be used to avoid a ligation step during library preparation.
  • the nucleic acids isolated from the sample may be used to construct a library (e.g., a nucleic acid library as described herein).
  • the nucleic acids are fragmented using any of the methods described above, optionally subjected to repair of chain end damage, and optionally ligated to synthetic adapters, primers, and/or barcodes (e.g., amplification primers, sequencing adapters, flow cell adapters, substrate adapters, sample barcodes or indexes, and/or unique molecular identifier sequences), size-selected (e.g., by preparative gel electrophoresis), and/or amplified (e.g., using PCR, a non-PCR amplification technique, or an isothermal amplification technique).
  • synthetic adapters, primers, and/or barcodes e.g., amplification primers, sequencing adapters, flow cell adapters, substrate adapters, sample barcodes or indexes, and/or unique molecular identifier sequences
  • the fragmented and adapter-ligated group of nucleic acids is used without explicit size selection or amplification prior to hybridization-based selection of target sequences.
  • the nucleic acid is amplified by any of a variety of specific or non-specific nucleic acid amplification methods known to those of skill in the art.
  • the nucleic acids are amplified, e.g., by a whole-genome amplification method such as random-primed strand-displacement amplification. Examples of nucleic acid library preparation techniques for next-generation sequencing are described in, e.g., van Dijk, et al. (2014), Exp. Cell Research 322:12 - 20, and Illumina’s genomic DNA sample preparation kit.
  • the resulting nucleic acid library may contain all or substantially all of the complexity of the genome.
  • the term “substantially all” in this context refers to the possibility that there can in practice be some unwanted loss of genome complexity during the initial steps of the procedure.
  • the methods described herein also are useful in cases where the nucleic acid library comprises a portion of the genome, e.g., where the complexity of the genome is reduced by design. In some instances, any selected portion of the genome can be used with a method described herein. For example, in certain embodiments, the entire exome or a subset thereof is isolated.
  • the library may include at least 95%, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, 10%, or 5% of the genomic DNA.
  • the library may consist of cDNA copies of genomic DNA that includes copies of at least 95%, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, 10%, or 5% of the genomic DNA.
  • the amount of nucleic acid used to generate the nucleic acid library may be less than 5 micrograms, less than 1 microgram, less than 500 ng, less than 200 ng, less than 100 ng, less than 50 ng, less than 10 ng, less than 5 ng, or less than 1 ng.
  • a library (e.g., a nucleic acid library) includes a collection of nucleic acid molecules.
  • the nucleic acid molecules of the library can include a target nucleic acid molecule (e.g., a tumor nucleic acid molecule, a reference nucleic acid molecule and/or a control nucleic acid molecule; also referred to herein as a first, second and/or third nucleic acid molecule, respectively).
  • the nucleic acid molecules of the library can be from a single subject or individual.
  • a library can comprise nucleic acid molecules derived from more than one subject (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30 or more subjects).
  • two or more libraries from different subjects can be combined to form a library having nucleic acid molecules from more than one subject (where the nucleic acid molecules derived from each subject are optionally ligated to a unique sample barcode corresponding to a specific subject).
  • the subject is a human having, or at risk of having, a cancer or tumor.
  • the library may comprise one or more subgenomic intervals.
  • a subgenomic interval can be a single nucleotide position, e.g., a nucleotide position for which a variant at the position is associated (positively or negatively) with a tumor phenotype.
  • a subgenomic interval comprises more than one nucleotide position. Such instances include sequences of at least 2, 5, 10, 50, 100, 150, 250, or more than 250 nucleotide positions in length.
  • Subgenomic intervals can comprise, e.g., one or more entire genes (or portions thereof), one or more exons or coding sequences (or portions thereof), one or more introns (or portion thereof), one or more micro satellite region (or portions thereof), or any combination thereof.
  • a subgenomic interval can comprise all or a part of a fragment of a naturally occurring nucleic acid molecule, e.g., a genomic DNA molecule.
  • a subgenomic interval can correspond to a fragment of genomic DNA which is subjected to a sequencing reaction.
  • a subgenomic interval is a continuous sequence from a genomic source.
  • a subgenomic interval includes sequences that are not contiguous in the genome, e.g., subgenomic intervals in cDNA can include exon-exon junctions formed as a result of splicing.
  • the subgenomic interval comprises a tumor nucleic acid molecule.
  • the subgenomic interval comprises a non-tumor nucleic acid molecule.
  • the methods described herein can be used in combination with, or as part of, a method for evaluating a plurality or set of subject intervals (e.g., target sequences), e.g., from a set of genomic loci (e.g., gene loci or fragments thereof), as described herein.
  • a plurality or set of subject intervals e.g., target sequences
  • genomic loci e.g., gene loci or fragments thereof
  • the set of genomic loci evaluated by the disclosed methods comprises a plurality of, e.g., genes, which in mutant form, are associated with an effect on cell division, growth or survival, or are associated with a cancer, e.g., a cancer described herein.
  • the set of gene loci evaluated by the disclosed methods comprises 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, at least 10, at least 20, at least 30, at least 40, at least 50, at least 60, at least 70, at least 80, at least 90, at least 100, or more than 100 gene loci.
  • the selected gene loci may include subject intervals comprising non-coding sequences, coding sequences, intragenic regions, or intergenic regions of the subject genome.
  • the subject intervals can include a non-coding sequence or fragment thereof (e.g., a promoter sequence, enhancer sequence, 5’ untranslated region (5’ UTR), 3’ untranslated region (3’ UTR), or a fragment thereof), a coding sequence of fragment thereof, an exon sequence or fragment thereof, an intron sequence or a fragment thereof.
  • the methods described herein may comprise contacting a nucleic acid library with a plurality of target capture reagents in order to select and capture a plurality of specific target sequences (e.g., gene sequences or fragments thereof) for analysis.
  • a target capture reagent i.e., a molecule which can bind to and thereby allow capture of a target molecule
  • a target capture reagent is used to select the subject intervals to be analyzed.
  • a target capture reagent can be a bait molecule, e.g., a nucleic acid molecule (e.g., a DNA molecule or RNA molecule) which can hybridize to (z.e., is complementary to) a target molecule, and thereby allows capture of the target nucleic acid.
  • the target capture reagent e.g., a bait molecule (or bait sequence)
  • the target nucleic acid is a genomic DNA molecule, an RNA molecule, a cDNA molecule derived from an RNA molecule, a micro satellite DNA sequence, and the like.
  • the target capture reagent is suitable for solution-phase hybridization to the target. In some instances, the target capture reagent is suitable for solidphase hybridization to the target. In some instances, the target capture reagent is suitable for both solution-phase and solid-phase hybridization to the target.
  • the design and construction of target capture reagents is described in more detail in, e.g., International Patent Application Publication No. WO 2020/236941, the entire content of which is incorporated herein by reference.
  • the methods described herein provide for optimized sequencing of a large number of genomic loci (e.g., genes or gene products (e.g., mRNA), micro satellite loci, etc.) from samples (e.g., cancerous tissue specimens, liquid biopsy samples, and the like) from one or more subjects by the appropriate selection of target capture reagents to select the target nucleic acid molecules to be sequenced.
  • a target capture reagent may hybridize to a specific target locus, e.g., a specific target gene locus or fragment thereof.
  • a target capture reagent may hybridize to a specific group of target loci, e.g., a specific group of gene loci or fragments thereof.
  • a plurality of target capture reagents comprising a mix of target- specific and/or group- specific target capture reagents may be used.
  • the number of target capture reagents (e.g., bait molecules) in the plurality of target capture reagents (e.g., a bait set) contacted with a nucleic acid library to capture a plurality of target sequences for nucleic acid sequencing is greater than 10, greater than 50, greater than 100, greater than 200, greater than 300, greater than 400, greater than 500, greater than 600, greater than 700, greater than 800, greater than 900, greater than 1,000, greater than 1,250, greater than 1,500, greater than 1,750, greater than 2,000, greater than 3,000, greater than 4,000, greater than 5,000, greater than 10,000, greater than 25,000, or greater than 50,000.
  • the overall length of the target capture reagent sequence can be between about 70 nucleotides and 1000 nucleotides. In one instance, the target capture reagent length is between about 100 and 300 nucleotides, 110 and 200 nucleotides, or 120 and 170 nucleotides, in length. In addition to those mentioned above, intermediate oligonucleotide lengths of about 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 300, 400, 500, 600, 700, 800, and 900 nucleotides in length can be used in the methods described herein. In some embodiments, oligonucleotides of about 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, or 230 bases can be used.
  • each target capture reagent sequence can include: (i) a targetspecific capture sequence (e.g., a gene locus or micro satellite locus-specific complementary sequence), (ii) an adapter, primer, barcode, and/or unique molecular identifier sequence, and (iii) universal tails on one or both ends.
  • a targetspecific capture sequence e.g., a gene locus or micro satellite locus-specific complementary sequence
  • an adapter, primer, barcode, and/or unique molecular identifier sequence e.g., a gene locus or micro satellite locus-specific complementary sequence
  • universal tails e.g., a targetspecific capture sequence
  • target capture reagent can refer to the target- specific target capture sequence or to the entire target capture reagent oligonucleotide including the target- specific target capture sequence.
  • the target-specific capture sequences in the target capture reagents are between about 40 nucleotides and 1000 nucleotides in length. In some instances, the target- specific capture sequence is between about 70 nucleotides and 300 nucleotides in length. In some instances, the target- specific sequence is between about 100 nucleotides and 200 nucleotides in length. In yet other instances, the target- specific sequence is between about 120 nucleotides and 170 nucleotides in length, typically 120 nucleotides in length.
  • target-specific sequences of about 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 300, 400, 500, 600, 700, 800, and 900 nucleotides in length, as well as target- specific sequences of lengths between the above-mentioned lengths.
  • the target capture reagent may be designed to select a subject interval containing one or more rearrangements, e.g., an intron containing a genomic rearrangement.
  • the target capture reagent is designed such that repetitive sequences are masked to increase the selection efficiency.
  • complementary target capture reagents can be designed to recognize the juncture sequence to increase the selection efficiency.
  • the disclosed methods may comprise the use of target capture reagents designed to capture two or more different target categories, each category having a different target capture reagent design strategy.
  • the hybridization-based capture methods and target capture reagent compositions disclosed herein may provide for the capture and homogeneous coverage of a set of target sequences, while minimizing coverage of genomic sequences outside of the targeted set of sequences.
  • the target sequences may include the entire exome of genomic DNA or a selected subset thereof.
  • the target sequences may include, e.g., a large chromosomal region (e.g., a whole chromosome arm).
  • the methods and compositions disclosed herein provide different target capture reagents for achieving different sequencing depths and patterns of coverage for complex sets of target nucleic acid sequences.
  • DNA molecules are used as target capture reagent sequences, although RNA molecules can also be used.
  • a DNA molecule target capture reagent can be single stranded DNA (ssDNA) or double-stranded DNA (dsDNA).
  • ssDNA single stranded DNA
  • dsDNA double-stranded DNA
  • an RNA-DNA duplex is more stable than a DNA-DNA duplex and therefore provides for potentially better capture of nucleic acids.
  • the disclosed methods comprise providing a selected set of nucleic acid molecules (e.g., a library catch) captured from one or more nucleic acid libraries.
  • the method may comprise: providing one or a plurality of nucleic acid libraries, each comprising a plurality of nucleic acid molecules (e.g., a plurality of target nucleic acid molecules and/or reference nucleic acid molecules) extracted from one or more samples from one or more subjects; contacting the one or a plurality of libraries (e.g., in a solution-based hybridization reaction) with one, two, three, four, five, or more than five pluralities of target capture reagents (e.g., oligonucleotide target capture reagents) to form a hybridization mixture comprising a plurality of target capture reagent/nucleic acid molecule hybrids; separating the plurality of target capture reagent/nucleic acid molecule hybrids from said hybridization mixture, e.g., by
  • the disclosed methods may further comprise amplifying the library catch (e.g., by performing PCR). In other instances, the library catch is not amplified.
  • the target capture reagents can be part of a kit which can optionally comprise instructions, standards, buffers or enzymes or other reagents.
  • the methods disclosed herein may include the step of contacting the library (e.g., the nucleic acid library) with a plurality of target capture reagents to provide a selected library target nucleic acid sequences (z.e., the library catch).
  • the contacting step can be effected in, e.g., solution-based hybridization.
  • the method includes repeating the hybridization step for one or more additional rounds of solution-based hybridization.
  • the method further includes subjecting the library catch to one or more additional rounds of solution-based hybridization with the same or a different collection of target capture reagents.
  • the contacting step is effected using a solid support, e.g., an array.
  • a solid support e.g., an array.
  • Suitable solid supports for hybridization are described in, e.g., Albert, T.J. et al. (2007) Nat. Methods 4(1 l):903-5; Hodges, E. et al. (2007) Nat. Genet. 39(12): 1522-7; and Okou, D.T. et al. (2007) Nat. Methods 4(11):907-9, the contents of which are incorporated herein by reference in their entireties.
  • Hybridization methods that can be adapted for use in the methods herein are described in the art, e.g., as described in International Patent Application Publication No. WO 2012/092426. Methods for hybridizing target capture reagents to a plurality of target nucleic acids are described in more detail in, e.g., International Patent Application Publication No. WO 2020/236941, the entire content of which is incorporated herein by reference.
  • the methods and systems disclosed herein can be used in combination with, or as part of, a method or system for sequencing nucleic acids (e.g., a next-generation sequencing system) to generate a plurality of sequence reads that overlap one or more gene loci within a subgenomic interval in the sample and thereby determine, e.g., gene allele sequences at a plurality of gene loci.
  • a method or system for sequencing nucleic acids e.g., a next-generation sequencing system
  • next-generation sequencing may also be referred to as “massively parallel sequencing” (or “MPS”), and refers to any sequencing method that determines the nucleotide sequence of either individual nucleic acid molecules (e.g., as in single molecule sequencing) or clonally expanded proxies for individual nucleic acid molecules in a high throughput fashion (e.g., wherein greater than 10 3 , 10 4 , 10 5 or more than 10 5 molecules are sequenced simultaneously).
  • Next-generation sequencing methods are known in the art, and are described in, e.g., Metzker, M. (2010) Nature Biotechnology Reviews 11:31-46, which is incorporated herein by reference.
  • the sequencing may comprise, for example, whole genome sequencing (WGS), whole exome sequencing, targeted sequencing, or direct sequencing.
  • WGS whole genome sequencing
  • sequencing may be performed using, e.g., Sanger sequencing.
  • the sequencing may comprise a paired-end sequencing technique that allows both ends of a fragment to be sequenced and generates high-quality, alignable sequence data for detection of, e.g., genomic rearrangements, repetitive sequence elements, gene fusions, and novel transcripts.
  • sequencing platforms such as the Roche/454 Genome Sequencer (GS) FLX System, Illumina/Solexa Genome Analyzer (GA), Illumina’s HiSeq® 2500, HiSeq® 3000, HiSeq® 4000 and NovaSeq® 6000 Sequencing Systems, Life/APG’s Support Oligonucleotide Ligation Detection (SOLiD) system, Polonator’s G.007 system, Helicos BioSciences’ HeliScope Gene Sequencing system, or Pacific Biosciences’ PacBio® RS platform.
  • sequencing may comprise Illumina MiSeqTM sequencing.
  • sequencing may comprise Illumina HiSeq® sequencing.
  • sequencing may comprise Illumina NovaSeq® sequencing. Optimized methods for sequencing a large number of target genomic loci in nucleic acids extracted from a sample are described in more detail in, e.g., International Patent Application Publication No. WO 2020/236941, the entire content of which is incorporated herein by reference.
  • the disclosed methods comprise one or more of the steps of: (a) acquiring a library comprising a plurality of normal and/or tumor nucleic acid molecules from a sample; (b) simultaneously or sequentially contacting the library with one, two, three, four, five, or more than five pluralities of target capture reagents under conditions that allow hybridization of the target capture reagents to the target nucleic acid molecules, thereby providing a selected set of captured normal and/or tumor nucleic acid molecules (i.e., a library catch); (c) separating the selected subset of the nucleic acid molecules e.g., the library catch) from the hybridization mixture, e.g.
  • sequence reads e.g., sequence reads
  • subject intervals e.g., one or more target sequences
  • sequence reads may comprise a mutation (or alteration), e.g., a variant sequence comprising a somatic mutation or germline mutation
  • aligning said sequence reads using an alignment method as described elsewhere herein and/or assigning a nucleotide value for a nucleotide position in the subject interval (e.g., calling a mutation using, e.g., a Bayesian method or other method described herein) from one or more sequence reads of the plurality.
  • acquiring sequence reads for one or more subject intervals may comprise sequencing at least 1, at least 5, at least 10, at least 20, at least 30, at least 40, at least 50, at least 100, at least 150, at least 200, at least 250, at least 300, at least 350, at least 400, at least 450, at least 500, at least 550, at least 600, at least 650, at least 700, at least 750, at least 800, at least 850, at least 900, at least 950, at least 1,000, at least 1,250, at least 1,500, at least 1,750, at least 2,000, at least 2,250, at least 2,500, at least 2,750, at least 3,000, at least 3,500, at least 4,000, at least 4,500, or at least 5,000 loci, e.g., genomic loci, gene loci, micro satellite loci, etc.
  • acquiring a sequence read for one or more subject intervals may comprise sequencing a subject interval for any number of loci within the range described in this paragraph, e.g., genomic loci, gene loci
  • acquiring a sequence read for one or more subject intervals comprises sequencing a subject interval with a sequencing method that provides a sequence read length (or average sequence read length) of at least 20 bases, at least 30 bases, at least 40 bases, at least 50 bases, at least 60 bases, at least 70 bases, at least 80 bases, at least 90 bases, at least 100 bases, at least 120 bases, at least 140 bases, at least 160 bases, at least 180 bases, at least 200 bases, at least 220 bases, at least 240 bases, at least 260 bases, at least 280 bases, at least 300 bases, at least 320 bases, at least 340 bases, at least 360 bases, at least 380 bases, or at least 400 bases.
  • a sequencing method that provides a sequence read length (or average sequence read length) of at least 20 bases, at least 30 bases, at least 40 bases, at least 50 bases, at least 60 bases, at least 70 bases, at least 80 bases, at least 90 bases, at least 100 bases, at least 120 bases, at least 140 bases, at least 160 bases, at least 180 bases, at
  • acquiring a sequence read for the one or more subject intervals may comprise sequencing a subject interval with a sequencing method that provides a sequence read length (or average sequence read length) of any number of bases within the range described in this paragraph, e.g., a sequence read length (or average sequence read length) of 56 bases.
  • acquiring a sequence read for one or more subject intervals may comprise sequencing with at least lOOx or more coverage (or depth) on average.
  • acquiring a sequence read for one or more subject intervals may comprise sequencing with at least lOOx, at least 15Ox, at least 200x, at least 250x, at least 5OOx, at least 750x, at least l,OOOx, at least 1,500 x, at least 2,000x, at least 2,500x, at least 3,000x, at least 3,500x, at least 4,000x, at least 4,500x, at least 5,000x, at least 5,500x, or at least 6,000x or more coverage (or depth) on average.
  • acquiring a sequence read for one or more subject intervals may comprise sequencing with an average coverage (or depth) having any value within the range of values described in this paragraph, e.g., at least 160x.
  • acquiring a read for the one or more subject intervals comprises sequencing with an average sequencing depth having any value ranging from at least lOOx to at least 6,000x for greater than about 90%, 92%, 94%, 95%, 96%, 97%, 98%, or 99% of the gene loci sequenced.
  • acquiring a read for the subject interval comprises sequencing with an average sequencing depth of at least 125x for at least 99% of the gene loci sequenced.
  • acquiring a read for the subject interval comprises sequencing with an average sequencing depth of at least 4,100x for at least 95% of the gene loci sequenced.
  • the relative abundance of a nucleic acid species in the library can be estimated by counting the relative number of occurrences of their cognate sequences (e.g., the number of sequence reads for a given cognate sequence) in the data generated by the sequencing experiment.
  • the disclosed methods and systems provide nucleotide sequences for a set of subject intervals (e.g., gene loci), as described herein.
  • the sequences are provided without using a method that includes a matched normal control (e.g., a wild-type control) and/or a matched tumor control (e.g., primary versus metastatic).
  • the level of sequencing depth as used herein refers to the number of reads (e.g., unique reads) obtained after detection and removal of duplicate reads (e.g., PCR duplicate reads).
  • duplicate reads are evaluated, e.g., to support detection of copy number alteration (CNAs).
  • Alignment is the process of matching a read with a location, e.g., a genomic location or locus.
  • NGS reads may be aligned to a known reference sequence (e.g., a wild-type sequence).
  • NGS reads may be assembled de novo. Methods of sequence alignment for NGS reads are described in, e.g., Trapnell, C. and Salzberg, S.L. Nature Biotech., 2009, 27:455-457. Examples of de novo sequence assemblies are described in, e.g., Warren R., et al., Bioinformatics, 2007, 23:500-501; Butler, J.
  • Misalignment e.g., the placement of base-pairs from a short read at incorrect locations in the genome
  • misalignment of reads due to sequence context can lead to reduction in sensitivity of mutation detection
  • sequence context e.g., the presence of repetitive sequence
  • reads for the alternate allele may be shifted off the histogram peak of alternate allele reads.
  • sequence context e.g., the presence of repetitive sequence
  • Other examples of sequence context that may cause misalignment include short-tandem repeats, interspersed repeats, low complexity regions, insertions - deletions (indels), and paralogs.
  • misalignment may introduce artifactual reads of “mutated” alleles by placing reads of actual reference genome base sequences at the wrong location. Because mutation-calling algorithms for multigene analysis should be sensitive to even low-abundance mutations, sequence misalignments may increase false positive discovery rates and/or reduce specificity.
  • the methods and systems disclosed herein may integrate the use of multiple, individually-tuned, alignment methods or algorithms to optimize base-calling performance in sequencing methods, particularly in methods that rely on massively parallel sequencing (MPS) of a large number of diverse genetic events at a large number of diverse genomic loci.
  • the disclosed methods and systems may comprise the use of one or more global alignment algorithms.
  • the disclosed methods and systems may comprise the use of one or more local alignment algorithms. Examples of alignment algorithms that may be used include, but are not limited to, the Burrows-Wheeler Alignment (BWA) software bundle (see, e.g., Li, et al.
  • BWA Burrows-Wheeler Alignment
  • the methods and systems disclosed herein may also comprise the use of a sequence assembly algorithm, e.g., the Arachne sequence assembly algorithm (see, e.g., Batzoglou, et al. (2002), “ARACHNE: A Whole-Genome Shotgun Assembler”, Genome Res. 12:177-189).
  • a sequence assembly algorithm e.g., the Arachne sequence assembly algorithm (see, e.g., Batzoglou, et al. (2002), “ARACHNE: A Whole-Genome Shotgun Assembler”, Genome Res. 12:177-189).
  • the alignment method used to analyze sequence reads is not individually customized or tuned for detection of different variants (e.g., point mutations, insertions, deletions, and the like) at different genomic loci.
  • different alignment methods are used to analyze reads that are individually customized or tuned for detection of at least a subset of the different variants detected at different genomic loci.
  • different alignment methods are used to analyze reads that are individually customized or tuned to detect each different variant at different genomic loci.
  • tuning can be a function of one or more of: (i) the genetic locus (e.g., gene loci, micro satellite locus, or other subject interval) being sequenced, (ii) the tumor type associated with the sample, (iii) the variant being sequenced, or (iv) a characteristic of the sample or the subject.
  • the genetic locus e.g., gene loci, micro satellite locus, or other subject interval
  • the tumor type associated with the sample e.g., tumor type associated with the sample
  • the variant e.g., the variant being sequenced
  • a characteristic of the sample or the subject e.g., tuning can be a function of one or more of: (i) the genetic locus (e.g., gene loci, micro satellite locus, or other subject interval) being sequenced, (ii) the tumor type associated with the sample, (iii) the variant being sequenced, or (iv) a characteristic of the sample or the subject.
  • the method includes the use of an alignment method optimized for rearrangements in combination with other alignment methods optimized for subject intervals not associated with rearrangements.
  • the methods disclosed herein allow for the rapid and efficient alignment of troublesome reads, e.g., a read having a rearrangement.
  • a read for a subject interval comprises a nucleotide position with a rearrangement, e.g., a translocation
  • the method can comprise using an alignment method that is appropriately tuned and that includes: (i) selecting a rearrangement reference sequence for alignment with a read, wherein said rearrangement reference sequence aligns with a rearrangement (in some instances, the reference sequence is not identical to the genomic rearrangement); and (ii) comparing, e.g., aligning, a read with said rearrangement reference sequence.
  • a method of analyzing a sample can comprise: (i) performing a comparison (e.g., an alignment comparison) of a read using a first set of parameters (e.g., using a first mapping algorithm, or by comparison with a first reference sequence), and determining if said read meets a first alignment criterion (e.g., the read can be aligned with said first reference sequence, e.g., with less than a specific number of mismatches); (ii) if said read fails to meet the first alignment criterion, performing a second alignment comparison using a second set of parameters, (e.g., using a second mapping algorithm, or by comparison with a second reference sequence); and (iii) optionally, determining if said read meets said second criterion (e.g., the read can be
  • the alignment of sequence reads in the disclosed methods may be combined with a mutation calling method as described elsewhere herein.
  • reduced sensitivity for detecting actual mutations may be addressed by evaluating the quality of alignments (manually or in an automated fashion) around expected mutation sites in the genes or genomic loci (e.g., gene loci) being analyzed.
  • the sites to be evaluated can be obtained from databases of the human genome (e.g., the HG19 human reference genome) or cancer mutations (e.g., COSMIC).
  • Regions that are identified as problematic can be remedied with the use of an algorithm selected to give better performance in the relevant sequence context, e.g., by alignment optimization (or re-alignment) using slower, but more accurate alignment algorithms such as Smith-Waterman alignment.
  • customized alignment approaches may be created by, e.g., adjustment of maximum difference mismatch penalty parameters for genes with a high likelihood of containing substitutions; adjusting specific mismatch penalty parameters based on specific mutation types that are common in certain tumor types (e.g. C ⁇ T in melanoma); or adjusting specific mismatch penalty parameters based on specific mutation types that are common in certain sample types (e.g. substitutions that are common in FFPE).
  • Reduced specificity (increased false positive rate) in the evaluated subject intervals due to misalignment can be assessed by manual or automated examination of all mutation calls in the sequencing data. Those regions found to be prone to spurious mutation calls due to misalignment can be subjected to alignment remedies as discussed above. In cases where no algorithmic remedy is found possible, “mutations” from the problem regions can be classified or screened out from the panel of targeted loci.
  • the methods may include the use of an alignment method optimized for aligning sequence reads for DNA that has been converted using, e.g., a bisulfite reaction, to convert unmethylated cytosine residues to uracil (which is interpreted as a thymine in sequencing results).
  • sequence reads may be aligned to two genomes in silico, e.g., converted and unconverted versions of the reference genome, using such alignment tools. Methylation occurs primarily at CpG sites, but may also occur less frequently at non-CpG sites (e.g., CHG or CHH sites).
  • the sequence read data may be obtained using a nucleic acid sequencing method comprising the use of a bisulfite- or enzymatic-conversion reaction (e.g., during library preparation) to convert non-methylated cytosine to uracil (see, e.g., Li, el al. (2011), “DNA Methylation Detection: Bisulfite Genomic Sequencing Analysis”, Methods Mol. Biol. 791:11-21).
  • sequence read data may be obtained using a nucleic acid sequencing method comprising the use of alternative chemical and/or enzymatic reactions (e.g., during library preparation) to convert non-methylated cytosine to uracil (or to convert methylated cytosine to dihydrouracil).
  • enzymatic deamination of nonmethylated cytosine using APOBEC to form uracil can be performed using, e.g., the Enzymatic Methyl-seq Kit from New England BioLabs (Ipswich, MA) which uses prior treatment with ten-eleven translocation methylcytosine dioxygenase 2 (TET2) to oxidize 5mC and 5hmC, thereby providing greater protection of the methylated cytosine from deamination by APOBEC).
  • TERT2 ten-eleven translocation methylcytosine dioxygenase 2
  • sequence read data may be obtained using a nucleic acid sequencing method comprising the use of Methylated DNA Immunoprecipitation (MeDIP).
  • MeDIP Methylated DNA Immunoprecipitation
  • Examples of alignment tools optimized for aligning sequence reads for converted DNA include, but are not limited to, NovoAlign (Novocraft Technologies, Selangor, Malaysia), and the Bismark tool (Krueger, et al. (2011), “Bismark: A Flexible Aligner and Methylation Caller for Bisulfite-Seq Applications”, Bioinformatics 27(11): 1571- 1572).
  • Base calling refers to the raw output of a sequencing device, e.g., the determined sequence of nucleotides in an oligonucleotide molecule.
  • Mutation calling refers to the process of selecting a nucleotide value, e.g., A, G, T, or C, for a given nucleotide position being sequenced. Typically, the sequence reads (or base calling) for a position will provide more than one value, e.g., some reads will indicate a T and some will indicate a G.
  • Mutation calling is the process of assigning a correct nucleotide value, e.g., one of those values, to the sequence.
  • mutant calling it can be applied to assign a nucleotide value to any nucleotide position, e.g., positions corresponding to mutant alleles, wild-type alleles, alleles that have not been characterized as either mutant or wild-type, or to positions not characterized by variability.
  • the disclosed methods may comprise the use of customized or tuned mutation calling algorithms or parameters thereof to optimize performance when applied to sequencing data, particularly in methods that rely on massively parallel sequencing (MPS) of a large number of diverse genetic events at a large number of diverse genomic loci (e.g., gene loci, microsatellite regions, etc.) in samples, e.g., samples from a subject having cancer.
  • MPS massively parallel sequencing
  • optimization of mutation calling is described in the art, e.g., as set out in International Patent Application Publication No. WO 2012/092426.
  • Methods for mutation calling can include one or more of the following: making independent calls based on the information at each position in the reference sequence (e.g., examining the sequence reads; examining the base calls and quality scores; calculating the probability of observed bases and quality scores given a potential genotype; and assigning genotypes (e.g., using Bayes’ rule)); removing false positives (e.g., using depth thresholds to reject SNPs with read depth much lower or higher than expected; local realignment to remove false positives due to small indels); and performing linkage disequilibrium (LD)/imputation- based analysis to refine the calls.
  • making independent calls based on the information at each position in the reference sequence e.g., examining the sequence reads; examining the base calls and quality scores; calculating the probability of observed bases and quality scores given a potential genotype; and assigning genotypes (e.g., using Bayes’ rule)
  • removing false positives e.g., using depth thresholds to reject SNP
  • Equations used to calculate the genotype likelihood associated with a specific genotype and position are described in, e.g., Li, H. and Durbin, R. Bioinformatics, 2010; 26(5): 589-95.
  • the prior expectation for a particular mutation in a certain cancer type can be used when evaluating samples from that cancer type.
  • Such likelihood can be derived from public databases of cancer mutations, e.g., Catalogue of Somatic Mutation in Cancer (COSMIC), HGMD (Human Gene Mutation Database), The SNP Consortium, Breast Cancer Mutation Data Base (BIC), and Breast Cancer Gene Database (BCGD).
  • Examples of LD/imputation based analysis are described in, e.g., Browning, B.L. and Yu, Z. Am. J. Hum. Genet. 2009, 85(6):847-61.
  • Examples of low-coverage SNP calling methods are described in, e.g., Li, Y., et al., Annu. Rev. Genomics Hum. Genet. 2009, 10:387- 406.
  • detection of substitutions can be performed using a mutation calling method (e.g., a Bayesian mutation calling method) which is applied to each base in each of the subject intervals, e.g., exons of a gene or other locus to be evaluated, where presence of alternate alleles is observed.
  • a mutation calling method e.g., a Bayesian mutation calling method
  • This method will compare the probability of observing the read data in the presence of a mutation with the probability of observing the read data in the presence of base-calling error alone. Mutations can be called if this comparison is sufficiently strongly supportive of the presence of a mutation.
  • An advantage of a Bayesian mutation detection approach is that the comparison of the probability of the presence of a mutation with the probability of base-calling error alone can be weighted by a prior expectation of the presence of a mutation at the site. If some reads of an alternate allele are observed at a frequently mutated site for the given cancer type, then presence of a mutation may be confidently called even if the amount of evidence of mutation does not meet the usual thresholds. This flexibility can then be used to increase detection sensitivity for even rarer mutations/lower purity samples, or to make the test more robust to decreases in read coverage.
  • the likelihood of a random base-pair in the genome being mutated in cancer is ⁇ le-6.
  • the likelihood of specific mutations occurring at many sites in, for example, a typical multigenic cancer genome panel can be orders of magnitude higher. These likelihoods can be derived from public databases of cancer mutations (e.g., COSMIC).
  • Indel calling is a process of finding bases in the sequencing data that differ from the reference sequence by insertion or deletion, typically including an associated confidence score or statistical evidence metric.
  • Methods of indel calling can include the steps of identifying candidate indels, calculating genotype likelihood through local re-alignment, and performing LD-based genotype inference and calling.
  • a Bayesian approach is used to obtain potential indel candidates, and then these candidates are tested together with the reference sequence in a Bayesian framework.
  • Methods for generating indel calls and individual-level genotype likelihoods include, e.g., the Dindel algorithm (Albers, C.A., et al., Genome Res. 2011;21(6):961-73).
  • the Bayesian EM algorithm can be used to analyze the reads, make initial indel calls, and generate genotype likelihoods for each candidate indel, followed by imputation of genotypes using, e.g., QCALL (Le S.Q. and Durbin R. Genome Res. 2011 ;21(6):952-60).
  • Parameters, such as prior expectations of observing the indel can be adjusted e.g., increased or decreased), based on the size or location of the indels.
  • the mutation calling method used to analyze sequence reads is not individually customized or fine-tuned for detection of different mutations at different genomic loci.
  • different mutation calling methods are used that are individually customized or fine-tuned for at least a subset of the different mutations detected at different genomic loci.
  • different mutation calling methods are used that are individually customized or fine-tuned for each different mutant detected at each different genomic loci.
  • the customization or tuning can be based on one or more of the factors described herein, e.g., the type of cancer in a sample, the gene or locus in which the subject interval to be sequenced is located, or the variant to be sequenced. This selection or use of mutation calling methods individually customized or fine-tuned for a number of subject intervals to be sequenced allows for optimization of speed, sensitivity and specificity of mutation calling.
  • a nucleotide value is assigned for a nucleotide position in each of X unique subject intervals using a unique mutation calling method, and X is at least 2, at least 3, at least 4, at least 5, at least 10, at least 15, at least 20, at least 30, at least 40, at least 50, at least 60, at least 70, at least 80, at least 90, at least 100, at least 200, at least 300, at least 400, at least 500, at least 1000, at least 1500, at least 2000, at least 2500, at least 3000, at least 3500, at least 4000, at least 4500, at least 5000, or greater.
  • the calling methods can differ, and thereby be unique, e.g., by relying on different Bayesian prior values.
  • assigning said nucleotide value is a function of a value which is or represents the prior (e.g., literature) expectation of observing a read showing a variant, e.g., a mutation, at said nucleotide position in a tumor of type.
  • the method comprises assigning a nucleotide value e.g., calling a mutation) for at least 10, 20, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1,000 nucleotide positions, wherein each assignment is a function of a unique value (as opposed to the value for the other assignments) which is or represents the prior (e.g., literature) expectation of observing a read showing a variant, e.g., a mutation, at said nucleotide position in a tumor of type.
  • a nucleotide value e.g., calling a mutation
  • each assignment is a function of a unique value (as opposed to the value for the other assignments) which is or represents the prior (e.g., literature) expectation of observing a read showing a variant, e.g., a mutation, at said nucleotide position in a tumor of type.
  • assigning said nucleotide value is a function of a set of values which represent the probabilities of observing a read showing said variant at said nucleotide position if the variant is present in the sample at a specified frequency (e.g., 1%, 5%, 10%, etc.) and/or if the variant is absent (e.g., observed in the reads due to base-calling error alone).
  • the mutation calling methods described herein can include the following: (a) acquiring, for a nucleotide position in each of said X subject intervals: (i) a first value which is or represents the prior (e.g., literature) expectation of observing a read showing a variant, e.g., a mutation, at said nucleotide position in a tumor of type X; and (ii) a second set of values which represent the probabilities of observing a read showing said variant at said nucleotide position if the variant is present in the sample at a frequency (e.g., 1%, 5%, 10%, etc.) and/or if the variant is absent (e.g., observed in the reads due to basecalling error alone); and (b) responsive to said values, assigning a nucleotide value (e.g., calling a mutation) from said reads for each of said nucleotide positions by weighing, e.g., by a Baye
  • the methods described herein may comprise the use of a methylation status calling method, e.g., to call the methylation status of the CpG sites based on the sequence reads and fragments (complementary pairs of forward and reverse sequence reads) derived from DNA that has been subjected to a chemical or enzymatic conversion reaction, e.g., to convert unmethylated cytosine residues to uracil (which is interpreted as a thymine in sequencing results).
  • a methylation status calling method include, but are not limited to, the Bismark tool (Krueger, et al.
  • Example 1 Comparison of DNA sequence read yields from enzymatic- and bisulfite-based methyl-sequencing methods
  • FIG. 1 depicts a non-limiting example of DNA sequence read yield data for enzymatic- and bisulfite-based methyl-sequencing methods.
  • Vertical bars 102 to the left of the dashed line depict data for reads derived from an enzymatic-based methyl-sequencing method.
  • Vertical bars 104 to the right of the dashed line depict data for reads derived from a bisulfite-based methyl-sequencing method.
  • the y-axis depicts the percentage of sequencing reads identified for each sample index in a sequencing library that passed a quality control filter associated with the sequencing platform.
  • the x-axis depicts the index number and is a discrete categorical quantity.
  • vertical bars 102 indicate that fewer reads obtained using an enzymatic conversion reaction protocol pass the quality control filter (e.g., an internal quality control filter based on a ratio of brightest base signal intensity divided by the sum of the brightest and second brightest base signal intensities; clusters of reads pass the filter if no more than 1 base call has a signal intensity ratio of below 0.6 in the first 25 sequencing cycles; clusters that fail to pass the filter are removed from image analysis results) relative to reads obtained using a bisulfite conversion reaction protocol (vertical bars 104).
  • the quality control filter e.g., an internal quality control filter based on a ratio of brightest base signal intensity divided by the sum of the brightest and second brightest base signal intensities; clusters of reads pass the filter if no more than 1 base call has a signal intensity ratio of below 0.6 in the first 25 sequencing cycles; clusters that fail to pass the filter are removed from image analysis results
  • enzymatic-based methyl-sequencing methods appear to provide lower yields than bisulfit
  • FIG. 2 - FIG. 4 depict non-limiting examples of primer and primer binding site sequences used for some sequencing protocols, such as, but not limited to, protocols run on next generation sequencing (NGS) sequencing platforms, in this case, an Illumina® sequencer. Sequences 202 and 204 in FIG. 2 depict the Read 1 and Read 2 primers that are commonly used for NGS sequencing platforms.
  • NGS next generation sequencing
  • FIG. 3 depicts sequence 202 in a schematic illustrating the binding between a primer comprising sequence 202 and a library molecule incorporating a conventional sequencing adapter comprising the primer binding site subsequence 302 and an insert 306 e.g., a template nucleic acid sequence of interest), e.g., as may occur in a clonally-amplified cluster in a flow cell for an NGS sequencing platform.
  • a conventional sequencing adapter comprising the primer binding site subsequence 302 and an insert 306 e.g., a template nucleic acid sequence of interest
  • Erroneous conversion of 5-methylcytosine in a “stubby adapter” used for methylation sequencing may occur at any of a variety of cytosine positions within the stubby adapter sequence, e.g., at the cytosine located proximally to the 3’ end (TCT) of the primer binding site sequence 202, thereby resulting in a TTT sequence.
  • Downstream PCR amplification will then synthesize a complementary strand 304 which includes a complementary AAA subsequence, as indicated in the figure (circled), and weakens the binding interaction between the library molecule and the sequencing primer.
  • FIG. 4 depicts a similar schematic to that shown in FIG. 3, except that sequence 204 is depicted instead of sequence 202.
  • a primer comprising sequence 204 is bound to a library molecule comprising the primer binding subsequence 402 and an insert 404.
  • erroneous conversion of 5-methylcytosine in a “stubby adapter” used for methylation sequencing may occur at the various cytosine positions within the stubby adapter sequence, e.g., at the cytosine located proximally to the 3’ end (TCT) of the primer binding site sequence 204, thereby resulting in a TTT sequence.
  • TTT 3’ end
  • FIG. 5 depicts a non-limiting schematic illustrating the biochemical mechanism by which modified cytosines can be protected from conversion to uracil / thymine.
  • FIG. 5 illustrates the use of enzymes TET2 and T4-PGT to convert 5-methylcytosine to a modified cytosine, such as 5-hydroxymethylcytosine, 5-formylcytosine, 5-carobxycytosine, and/or 5- (D-glucosyl)oxymethylcytosine.
  • the modified cytosines (in the case of the schematic, 5-(D- glucosyl)oxymethylcytosine and 5-carobxycytosine) are not readily deaminated by a deaminating enzyme such as Apolipoprotein B mRNA Editing Catalytic Polypeptide-like (APOBEC) enzymes/proteins, and as a result, the modified cytosines remain as modified cytosines, and are protected from conversion to uracil / thymine (e.g., the uracils are replaced with thymines via e.g a polymerase chain reactions (PCR) process.
  • a deaminating enzyme such as Apolipoprotein B mRNA Editing Catalytic Polypeptide-like (APOBEC) enzymes/proteins
  • FIGS. 6A-C depict non-limiting schematic illustrations of a workflow by which nucleic acids extracted from a biological sample can be processed to create a nucleic acid library for methylation sequencing.
  • FIG. 6A depicts a non-limiting schematic illustration of a process 600A for extracting and purifying nucleic acids, e.g., DNA, from a sample.
  • the cells in a tissue sample are disrupted by any of a variety of techniques known to those of skill in the art including, but not limited to, addition of detergents and/or cell lysis reagents, sonication, mechanical (e.g., French press) disruption, etc.
  • DNA may be separated from proteins and other cellular debris, e.g., by addition of a protease and/or filtration.
  • the DNA may be precipitated, e.g., by the addition of ice-cold ethanol or isopropanol.
  • the DNA may be optionally sheared (e.g., using a method such as sonication) to a length of about 200-500 bp if it was derived from a tissue sample.
  • the DNA may be purified, e.g., by rinsing with alcohol and/or the use of chromatographic techniques.
  • the quantity and quality of the purified DNA may be assessed, e.g., using optical density measurements, gel electrophoresis, and/or capillary electrophoresis techniques.
  • FIG. 6B provides a non-limiting schematic illustration of a process 600B for performing end-repair and tailing reactions on extracted and purified DNA.
  • an end repair reaction such as a blunt ligation, addition of bases to the 3’ ends of DNA fragments, and/or other single- stranded DNA library preparation steps.
  • the 3’ ends of the nucleic acids may be subjected to a tailing reaction, e.g., resulting in the addition of dT, dC, dG, or dA tails, which can prevent the formation of concatemers during subsequent ligation reactions.
  • the end-repaired nucleic acid (DNA) fragments may then be ligated to adapters that comprise, e.g., sequencing primer binding sites and/or binding sequences (used to hybridize library molecules to a sequencing flow cell).
  • adapters may be added to DNA fragments during amplification (e.g., PCR amplification) without using a ligation step.
  • FIG. 6C provides a non-limiting schematic illustration of a process 600C for performing enzymatic conversion of cytosines in a DNA sample and performing methylation sequencing.
  • TET2 and/or T4-PGT enzymes can be introduced to the end-repaired DNA fragments so that methylated cytosine bases of the nucleic acids are further modified and protected during subsequent exposure to deaminating enzymes (step 604C), such as APOBEC enzymes/proteins (e.g., APOBEC3A).
  • APOBEC3A deaminating enzyme in this example was provided to deaminate non-modified cytosines, which converts the cytosines to uracil bases.
  • the APOBEC3A should fail to convert the modified (protected) cytosines to uracil.
  • the nucleic acids are then subjected to a nucleic acid amplification reaction, such as, but not limited to, a polymerase chain reaction (PCR), during which uracils are replaced by thymines.
  • a nucleic acid amplification reaction such as, but not limited to, a polymerase chain reaction (PCR)
  • PCR polymerase chain reaction
  • the amplified nucleic acid library molecules are then sequenced using a sequencing platform, such as, but not limited to, an NGS sequencing platform.
  • FIG. 7 depicts a non-limiting example of data illustrating the effectiveness with which various modifications to cytosine protect the cytosine from conversion to uracil / thymine upon treatment with a sequencing workflow comprising the use of deaminating enzymes or bisulfite.
  • Primer extension was used to synthesize a "genomic strand" that incorporates a specific modified cytosine residue that should be protected from enzymatic (APOBEC) conversion.
  • APOBEC enzymatic
  • SNP filtered error rate quantifies the rate of mismatches between the sequence reads and the reference genome, specifically in regions that are not known to have cancer associated SNPs.
  • the y-axis depicts the observed single nucleotide polymorphism (SNP) filtered error rates for different modified cytosines (indicated on the x axis).
  • Vertical bar 702 represents the SNP filtered error rate observed for conventional whole genome sequencing, and is quantified as a rate of 0.0055.
  • Vertical bar 704 represents the SNP filtered error rate for 5-methylcytosine (5mC), and is quantified as a rate of 0.012.
  • Vertical bar 706 represents the SNP filtered error rates for 5- hydroxymethylcytosine (5hmC), and is quantified as a rate of 0.0067.
  • FIG. 8 depicts a non-limiting example of typical adapter sequences provided for use in preparing double-stranded DNA libraries for methylation sequencing.
  • the methylated cytosine included in the last three nucleotide residues (TCT) at the 3’ end of the 5mC modified adapter has an approximately 5% chance of erroneous conversion to thymine.
  • Example 4 Modified adapter sequences for improving methyl-seq sequencing efficiency
  • FIG. 9, FIG. 10, and FIG. 11 depict non-limiting examples of sequences for custom methylation adapters with incorporated 5hmC nucleotides.
  • the adapter sequences shown in FIG. 9 incorporate 5hmC for the three cytosines closest to the 5’ end of the upper strand (bases 902, 904, 906), and for the three cytosines closest to the 3’ end of the lower, complementary strand (bases 908, 910, 912).
  • the remaining cytosine positions shown in this example consist of 5mC.
  • all or a portion of the cytosines in the adapter sequence may comprise 5hmC or another modified cytosine for which the erroneous conversion rate by deaminating enzymes is lower than that for 5mC.
  • the adapter sequences shown in FIG. 10 incorporate 5hmC for cytosines that reside in several nucleotide residue positions (bases 1002 and 1004 on the upper strand, and bases 1006, 1008, and 1010). Again, the remaining cytosine positions in this example consist of 5mC, but in some instances, could also be replaced by 5hmC or other protected forms of cytosine.
  • the adapter sequences shown in FIG. 11 incorporate 5hmC at a single position 1102. The remaining cytosine positions in this example consist of 5mC, but in some instances, could also be replaced by 5hmC or other protected forms of cytosine.
  • FIG. 12 provides a non-limiting example of data that illustrates the improvement in the number of sequence reads passing filter that were observed using the custom 5-hydroxy- methylated cytosine adapters (modified sequencing adapters 1 and 2) shown in FIG. 9 and FIG. 10 to perform enzymatic conversion (in this example Enzymatic Methyl-seq (EM- seqTM) Kit, New England BioLabs, Ipswich, MA) and methylation sequencing.
  • FIG. 12 provides a box plot of the percentage of sequence reads identified that pass the quality filter per sample index, for methylation sequencing performed using different adapter sequences or conversion reactions.
  • Box 1202 represents the percentage of reads passing filter data for the enzymatic-based methylation sequencing protocol using an adapter comprising standard 5mC nucleotides.
  • Box 1204 represents the data for a bisulfite-based methylation sequencing protocol (EZ DNA Methylation, Zymo Research, Irvine, CA).
  • Box 1206 represents the data obtained using the enzymatic -based methylation sequencing protocol in combination with the modified sequencing adapter incorporating six 5hmC nucleotides (modified sequencing adapter 1), as indicated in FIG. 9.
  • Box 1208 represents the data obtained when the enzymatic-based methylation sequencing protocol was used in combination with the modified adapter sequences comprising 5hmC nucleotides at the five nucleotide positions indicated in FIG. 10 (modified sequencing adapter 2).
  • Substituting the 5hmC adapters for the conventional 5mC adapter in the enzymatic methylation sequencing protocol (1206 and 1208) yielded higher percentages of high-quality sequence reads compared to use of the conventional 5mC adapter (1202) under otherwise identical conditions.
  • the percentage of reads passing the quality filter for the 5hmC-incorporated adapters is similar to the percentage of reads passing the quality filter for the bisulfite methylation sequencing protocol (1204).
  • Table 1 The relative improvements in yields of quality sequence reads
  • Example 5 -Modified adapters provide improved yields of quality sequence reads
  • FIG. 13 provides a non-limiting schematic illustration of an alternative assay used for testing the effectiveness of the disclosed modified sequencing adapters comprising 5hmC nucleotides in reducing the erroneous conversion of cytosine to uracil / thymine in enzymatic methylation sequencing methods.
  • the assay comprises the steps of ligating either the standard methylation sequencing adapters (e.g., the p5 and p7 adapters with all Cs methylated, as indicated by strands 1302 and 1304 in the figure) or modified sequencing adapters as described herein to double-stranded template DNA sequences, followed by primer extension using 5mC or 5hmC to generate a methylated copy (z.e., a 5mC or 5hmC copy of the genomic strand, as shown by strand 1308, which is complementary to the template strand 1306). Cytosine conversion comprising the use of a deaminating enzyme is then performed, which results in the conversion of applicable cytosines in the methylation workflow (or methylation) strand.
  • the standard methylation sequencing adapters e.g., the p5 and p7 adapters with all Cs methylated, as indicated by strands 1302 and 1304 in the figure
  • modified sequencing adapters as described herein to double-stranded template DNA sequence
  • FIG. 14 and FIG. 15 provide schematic illustrations that further describe the process by which the assay described in FIG. 13 is performed to generate genomic and methylation strands from the same sample.
  • the adapter sequences e.g., the standard 5mC “stubby” methylation sequencing adapter sequences
  • a ligation cleanup step is performed prior to performing linear amplification during which the DNA is denatured and a Q5 polymerase incorporates 5hmCs and standard A, T, and G nucleotides to form the “genomic strand”, i.e., the strand that comprises only 5hmC nucleotides at cytosine positions and will not undergo erroneous conversion.
  • the other strand i.e. the “methylation strand”, still comprises the original adapter sequence comprising 5mC, which has an approximately 5% chance of undergoing an erroneous conversion (mutation) to uracil
  • “stubby” adaptor sequences that have a 5hmC at the Read 1 sequencing primer binding site were ligated to the double-stranded DNA inserts, where the 5hmC blocks erroneous conversion. After performing the ligation and cleanup steps, the molecules undergo linear amplification. As a result of using the custom 5hmC adapter sequences, which prove better protected from erroneous conversion of 5mC to uracil / thymine, relative to 5mC. As a result, the only real difference between the genomic and methylation strands following linear amplification is that the methylation strand retains the 5hmC.
  • FIG. 16 depicts a non-limiting example of percent sequence read passing filter data obtained using the assay as described in FIG. 13.
  • the nucleotide sequences between the two corresponding strands z.e., the genomic and methylation workflow strands generated in the same library from the same sample
  • the box plot depicted in FIG. 16 plots the percentage of sequence reads passing the quality filter per sample index for the genomic (gen) and methylation workflow (methyl) strands as obtained using either the standard methyl-seq adapter sequences or a modified 5hmC adapter sequence (modified sequencing adapter 1; FIG. 9) as described herein.
  • Boxes 1602 and 1604 summarize the percent sequence read data obtained using the standard methyl-seq adapter sequences.
  • Boxes 1606 and 1608 summarize the percent sequence read data obtained using the custom 5hmC adapter sequences.
  • a comparison between boxes 1602 and 1604 reveals a 21.4% difference in the percentage of reads passing filter between the genomic and methylation strands when using the standard methyl-seq adapter sequences.
  • comparison of boxes 1606 and 1608 indicate that the difference in percentage of sequence reads passing filter was much smaller (11.6%) when using the custom 5hmC adapter sequences.
  • FIG. 17 provides a plot of the ratio of the percentage sequence reads passing filter data obtained for the genomic and methylation strands using the standard methyation sequencing adapter sequences (1702), and using the custom 5hmC adapter sequences(1704). A ratio of one would indicate that an equal number of sequence reads pass the quality filter for the genomic and methylation strands.
  • the data obtained using the custom 5hmC adapter sequences (1704) is closer to the ideal ratio of one than that obtained using the standard methyl sequencing adapters (1702).
  • a sequencing adapter comprising an oligonucleotide sequence that comprises at least one modified base, wherein the at least one modified base is not 5-methylcytosine, and wherein a rate of conversion of the at least one modified base to uracil when contacted with a deaminating enzyme or enzyme combination is less than that of 5-methylcytosine.
  • sequencing adapter of any one of clauses 1 to 11, wherein the sequencing adapter comprises two complementary oligonucleotide sequences, each comprising at least four cytosines, and wherein three cytosines closest to a 3’ end or a 5’ end in at least one of the two complementary oligonucleotide sequences are modified cytosines.
  • oligonucleotide sequence comprises at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 contiguous nucleotides selected from the sequence 5’ AAT GAT ACG GCG ACC ACC GA 3’ (SEQ ID NO: 1) or its complement.
  • oligonucleotide sequence comprises at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 contiguous nucleotides selected from the sequence 5’ CAA GCA GAA GAC GGC ATA CGA GAT 3’ (SEQ ID NO: 2) or its complement.
  • oligonucleotide sequence comprises at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, or 33 contiguous nucleotides selected from the sequence 5’ ACA CTC TTT CCC TAC ACG ACG CTC TTC CGA TCT 3’ (SEQ ID NO: 3) or its complement.
  • oligonucleotide sequence comprises at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, or 34 contiguous nucleotides selected from the sequence 5’ GTG ACT GGA GTT CAG ACG TGT GCT CTT CCG ATC T 3’ (SEQ ID NO: 4) or its complement.
  • a method for performing nucleic acid sequencing comprising: a) providing a plurality of nucleic acid molecules obtained from a sample from a subject; b) performing an enzymatic ligation of one or more of the sequencing adapters of any one of claims 1 to 18 onto the plurality of nucleic acid molecules; c) sequencing, by a sequencer, the ligated nucleic acid molecules to obtain a plurality of sequence reads derived from the sample; and d) receiving, at one or more processors, sequence read data for the plurality of sequence reads derived from the sample.
  • nucleic acid sequencing comprises a whole genome sequencing, whole exome sequencing, or targeted sequencing method.
  • nucleic acid sequencing comprises a methylation sequencing method.
  • nucleic acid amplification reaction comprises a polymerase chain reaction.
  • nucleic acid amplification reaction comprises a rolling circle amplification reaction.
  • next- generation sequencer comprises a cyclic array sequencer, a nanopore sequencer, or a single mode waveguide sequencer.
  • a method comprising: providing a plurality of nucleic acid molecules obtained from a sample from a subject; ligating one or more sequencing adapters onto one or more nucleic acid molecules from the plurality of nucleic acid molecules, wherein the one or more sequencing adapters comprise an oligonucleotide sequence comprising at least one modified cytosine, wherein the at least one modified cytosine is not 5-methylcytosine, and wherein a rate of conversion of the at least one modified cytosine to uracil when contacted with a deaminating enzyme is less than that of 5-methylcytosine; amplifying the one or more ligated nucleic acid molecules from the plurality of nucleic acid molecules; capturing amplified nucleic acid molecules from the amplified nucleic acid molecules; sequencing, by a sequencer, the captured nucleic acid molecules to obtain a plurality of sequence reads that represent the captured nucleic acid molecules; receiving, at
  • the cancer is a B cell cancer (multiple myeloma), a melanoma, breast cancer, lung cancer, bronchus cancer, colorectal cancer, prostate cancer, pancreatic cancer, stomach cancer, ovarian cancer, urinary bladder cancer, brain cancer, central nervous system cancer, peripheral nervous system cancer, esophageal cancer, cervical cancer, uterine cancer, endometrial cancer, cancer of an oral cavity, cancer of a pharynx, liver cancer, kidney cancer, testicular cancer, biliary tract cancer, small bowel cancer, appendix cancer, salivary gland cancer, thyroid gland cancer, adrenal gland cancer, osteosarcoma, chondrosarcoma, a cancer of hematological tissue, an adenocarcinoma, an inflammatory myofibroblastic tumor, a gastrointestinal stromal tumor (GIST), colon cancer, multiple myeloma (MM), myelodysplastic syndrome (MDS), mye
  • MDS myelodysplastic syndrome
  • the cancer comprises acute lymphoblastic leukemia (Philadelphia chromosome positive), acute lymphoblastic leukemia (precursor B-cell), acute myeloid leukemia (FLT3+), acute myeloid leukemia (with an IDH2 mutation), anaplastic large cell lymphoma, basal cell carcinoma, B-cell chronic lymphocytic leukemia, bladder cancer, breast cancer (HER2 overexpressed/amplified), breast cancer (HER2+), breast cancer (HR+, HER2-), cervical cancer, cholangiocarcinoma, chronic lymphocytic leukemia, chronic lymphocytic leukemia (with 17p deletion), chronic myelogenous leukemia, chronic myelogenous leukemia (Philadelphia chromosome positive), classical Hodgkin lymphoma, colorectal cancer, colorectal cancer (dMMR/MSLH), colorectal cancer (KRAS wild type), cryopyr
  • the targeted anti-cancer therapy comprises abemaciclib (Verzenio), abiraterone acetate (Zytiga), acalabrutinib (Calquence), ado-trastuzumab emtansine (Kadcyla), afatinib dimaleate (Gilotrif), aldesleukin (Proleukin), alectinib (Alecensa), alemtuzumab (Campath), alitretinoin (Panretin), alpelisib (Piqray), amivantamab- vmjw (Rybrevant), anastrozole (Arimidex), apalutamide (Erleada), asciminib hydrochloride (Scemblix), atezolizumab (Tecentriq), avapritinib (Ayvakit), avelumab (Bavencio), axicab
  • the sample is a liquid biopsy sample and comprises blood, plasma, cerebrospinal fluid, sputum, stool, urine, or saliva.
  • the sample is a liquid biopsy sample and comprises cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), or any combination thereof.
  • cfDNA cell-free DNA
  • ctDNA circulating tumor DNA
  • the tumor nucleic acid molecules are derived from a tumor portion of a heterogeneous tissue biopsy sample, and the non-tumor nucleic acid molecules are derived from a normal portion of the heterogeneous tissue biopsy sample.
  • the sample comprises a liquid biopsy sample, and wherein the tumor nucleic acid molecules are derived from a circulating tumor DNA (ctDNA) fraction of the liquid biopsy sample, and the non-tumor nucleic acid molecules are derived from a non-tumor, cell-free DNA (cfDNA) fraction of the liquid biopsy sample.
  • ctDNA circulating tumor DNA
  • cfDNA non-tumor, cell-free DNA
  • the one or more bait molecules comprise one or more nucleic acid molecules, each comprising a region that is complementary to a region of a captured nucleic acid molecule.
  • amplifying nucleic acid molecules comprises performing a polymerase chain reaction (PCR) amplification technique, a non- PCR amplification technique, or an isothermal amplification technique.
  • PCR polymerase chain reaction
  • the one or more gene loci comprises between 10 and 20 loci, between 10 and 40 loci, between 10 and 60 loci, between 10 and 80 loci, between 10 and 100 loci, between 10 and 150 loci, between 10 and 200 loci, between 10 and 250 loci, between 10 and 300 loci, between 10 and 350 loci, between 10 and 400 loci, between 10 and 450 loci, between 10 and 500 loci, between 20 and 40 loci, between 20 and 60 loci, between 20 and 80 loci, between 20 and 100 loci, between 20 and 150 loci, between 20 and 200 loci, between 20 and 250 loci, between 20 and 300 loci, between 20 and 350 loci, between 20 and 400 loci, between 20 and 500 loci, between 40 and 60 loci, between 40 and 80 loci, between 40 and 100 loci, between 40 and 150 loci, between 40 and 200 loci, between 40 and 250 loci, between 40 and 300 loci, between 40 and 350 loci, between 40 and 400 loci, between 20 and 500 loci, between 40 and 60 loci,
  • the one or more gene loci comprise ABL1, ACVR1B, AKT1, AKT2, AKT3, ALK, ALOX12B, AMER1, APC, AR, ARAF, ARFRP1, ARID1A, ASXL1, ATM, ATR, ATRX, AURKA, AURKB, AXIN1, AXL, BAP1, BARD1, BCL2, BCL2L1, BCL2L2, BCL6, BCOR, BCORL1, BCR, BRAF, BRCA1, BRCA2, BRD4, BRIP1, BTG1, BTG2, BTK, CALR, CARD11, CASP8, CBFB, CBL, CCND1, CCND2, CCND3, CCNE1, CD22, CD274, CD70, CD74, CD79A, CD79B, CDC73, CDH1, CDK12, CDK4, CDK6, CDK8, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CDKN2
  • a method for diagnosing a disease comprising: diagnosing that a subject has the disease based on a determination of a methylation signature for a sample from the subject, wherein the methylation signature is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to the method of any one of clauses 19 to 74.
  • a method of selecting an anti-cancer therapy comprising: responsive to determining a methylation signature for a sample from a subject, selecting an anti-cancer therapy for the subject, wherein the methylation signature is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to the method of any one of clauses 19 to 74.
  • a method of treating a cancer in a subject comprising: responsive to determining a methylation signature for a sample from the subject, administering an effective amount of an anti-cancer therapy to the subject, wherein the methylation signature is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to the method of any one of clauses 19 to 74.
  • a method for monitoring cancer progression or recurrence in a subject comprising: determining a first methylation signature in a first sample obtained from the subject at a first time point, wherein the first methylation signature is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to the method of any one of clauses 19 to 74; determining a second methylation signature in a second sample obtained from the subject at a second time point; and comparing the first methylation signature to the second methylation signature, thereby monitoring the cancer progression or recurrence.

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Abstract

A sequencing adapter and methods for performing nucleic acid sequencing comprising the sequencing adapter are described. The sequencing adapter may comprise, for example, an oligonucleotide sequence comprising at least one modified base, wherein a rate of conversion of the at least one modified base to uracil when contacted with a deaminating enzyme or enzyme combination is less than that of 5-methylcytosine.

Description

SEQUENCING ADAPTERS FOR METHYLATION SEQUENCING
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application claims the priority benefit of United States Provisional Patent Application Serial No. 63/466,524, filed May 15, 2023, the contents of which are incorporated herein by reference in their entirety.
REFERENCE TO AN ELECTRONIC SEQUENCE LISTING
[0002] The contents of the electronic sequence listing (197102013840SEQLIST.xml; 81,823 bytes; and Date of Creation: May 10, 2024) is herein incorporated by reference in its entirety.
FIELD OF THE INVENTION
[0003] The present disclosure relates generally to sequencing adapters, and methods and systems for their use in performing nucleic acid sequencing and determining a methylation state associated with one or more nucleotides in nucleic acid molecules. More specifically, the present disclosure relates to sequencing adapters for performing methylation sequencing and determining a methylation signature therefrom.
BACKGROUND
[0004] The term “methylation sequencing” refers to a family of related nucleic acid sequencing techniques that can be used to identify methylated and non-methylated cytosines in nucleic acid sequences. Some methylation sequencing methods include library preparation steps that comprise the addition of enzymes that convert non-methylated cytosines to thymine, while preserving the states of methylated cytosines. The use of such enzymes in methylation sequencing methods confers advantages over other approaches but can, however, be problematic in terms of, e.g., unexpectedly low sequence read yields. Improved compositions and methods are thus needed for performing enzymatic conversion-based methylation sequencing. The present disclosure addresses these needs.
BRIEF SUMMARY OF THE INVENTION
[0005] Disclosed herein are sequencing adapter compositions (and associated methods and systems) configured for use in performing methylation sequencing. Existing sequencing adapters include 5-methylcytosine (5mC) within the adaptor sequences to prevent unwanted conversion of the cytosines in the adaptor sequences while performing conversion of non- methylated cytosines. Many DNA modifying enzymes, including those used for methylation sequencing, have sequence- specific biases. Disclosed herein are studies that demonstrate the erroneous conversion of 5mC into uracil in enzymatic methylation sequencing workflows, and that indicate how sequencing read depth and coverage output could be affected if these erroneous conversion events occur in the adapter sequences. Also disclosed herein are modified sequencing adapters that mitigate erroneous cytosine conversion in the adapter sequences and provide for higher sequence read yields and improved sequencing performance when performing enzymatic conversion-based methylation sequencing.
[0006] The sequencing adapter compositions described herein comprise modified nucleobases (e.g., alternatives to 5mC) that are better protected from erroneous conversion to uracil when subjected to enzymatic conversion-based methylation sequencing protocols.
Examples of modified cytosines that are better protected from erroneous conversion include, but are not limited to, 5-hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, 5- formylcytosine, or 5-carboxycytosine. The modified cytosines (and other modified nucleobases) incorporated into the sequencing adapters disclosed herein exhibit reduced erroneous conversion to uracil compared to that for 5 -methylcytosine. By eliminating or minimizing erroneous conversion, the disclosed sequencing adapter compositions and methods incorporating their use enable improved sequencing performance for detection of methylation states and determining methylation signatures in nucleic acid molecules using enzymatic conversion-based methylation sequencing protocols.
[0007] Disclosed herein is a sequencing adapter comprising an oligonucleotide sequence that comprises at least one modified base, wherein the at least one modified base is not 5- methylcytosine, and wherein a rate of conversion of the at least one modified base to uracil when contacted with a deaminating enzyme or enzyme combination is less than that of 5- methylcytosine. In some embodiments, the modified base is inosine, 5-nitroindole, N4-ethyl- deoxycytidine, 5-propynylcytosine, 5-vinylcytosine, 5-ethynylcytosine, pyrrolo- deoxycytidine, or propynyl-deoxy cytidine. In some embodiments, the modified base is a modified cytosine.
[0008] In any of the embodiments herein, the at least one modified cytosine can be 5- hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, 5-formylcytosine, 5- carboxycytosine, or a combination thereof. In any of the embodiments herein, the at least one modified cytosine can be 5-hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, or a combination thereof. In any of the embodiments herein, the at least one modified cytosine can be 5 -hydroxy methylcytosine.
[0009] In any of the embodiments herein, the oligonucleotide sequence can comprise 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 modified bases. In any of the embodiments herein, the oligonucleotide sequence can comprise at least four cytosines, and the three cytosines closest to the 3’ end of the oligonucleotide sequence can be modified cytosines. In any of the embodiments herein, all or substantially all of the cytosines of the oligonucleotide sequence can be modified cytosines. In any of the embodiments herein, all or substantially all of the cytosines of the oligonucleotide sequence can be 5-hydroxymethy Icy to sines. In any of the embodiments herein, the sequencing adapter can comprise two complementary oligonucleotide sequences, each comprising at least four cytosines, and the three cytosines closest to a 3’ end or a 5’ end in at least one of the two complementary oligonucleotide sequences can be modified cytosines.
[0010] In any of the embodiments herein, the deaminating enzyme can be an APOBEC enzyme. In any of the embodiments herein, the oligonucleotide sequence can be between about 20 and 100 nucleotides in length. In any of the embodiments herein, the oligonucleotide sequence can comprise at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 contiguous nucleotides selected from the sequence 5’ A AT GAT ACG GCG ACC ACC GA 3’ (SEQ ID NO: 1) or its complement. In any of the embodiments herein, the oligonucleotide sequence can comprise at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 contiguous nucleotides selected from the sequence 5’ CAA GCA GAA GAC GGC ATA CGA GAT 3’ (SEQ ID NO: 2) or its complement. In any of the embodiments herein, the oligonucleotide sequence can comprise at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, or 33 contiguous nucleotides selected from the sequence 5’ AC A CTC TTT CCC TAC ACG ACG CTC TTC CGA TCT 3’ (SEQ ID NO: 3) or its complement. In any of the embodiments herein, the oligonucleotide sequence can comprise at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, or 34 contiguous nucleotides selected from the sequence 5’ GTG ACT GGA GTT CAG ACG TGT GCT CTT CCG ATC T 3’ (SEQ ID NO: 4) or its complement.
[0011] Also disclosed is a method for performing nucleic acid sequencing, comprising: a) providing a plurality of nucleic acid molecules obtained from a sample from a subject; b) performing an enzymatic ligation of one or more of any of the sequencing adapters described herein onto the plurality of nucleic acid molecules; c) sequencing, by a sequencer, the ligated nucleic acid molecules to obtain a plurality of sequence reads derived from the sample; and d) receiving, at one or more processors, sequence read data for the plurality of sequence reads derived from the sample.
[0012] In some embodiments, the enzymatic ligation can comprise single- stranded ligation. In some embodiments, the enzymatic ligation can comprise double-stranded ligation. In any of the embodiments herein, the nucleic acid sequencing may comprise a whole genome sequencing, whole exome sequencing, or targeted sequencing method. In any of the embodiments herein, the nucleic acid sequencing can comprise a methylation sequencing method. In any of the embodiments herein, the methylation sequencing method can comprise an enzymatic cytosine conversion step.
[0013] In any of the embodiments herein, the sample can comprise a tissue sample or a buffy coat sample. In some embodiments, the methods disclosed can further comprise shearing nucleic acids extracted from the sample to provide the plurality of nucleic acid molecules. In any of the embodiments herein, the methods disclosed can further comprise performing an end repair reaction on the plurality of nucleic acid molecules prior to performing the enzymatic ligation. In any of the embodiments herein, the methods disclosed can further comprise performing an A-tailing reaction on the plurality of nucleic acid molecules prior to performing the enzymatic ligation. In any of the embodiments herein, the methods disclosed can further comprise contacting the ligated nucleic acid molecules with a TET2 enzyme to oxidize 5-methyl-cytosine (5mC) or 5-hydroxymethyl-cytosine (5hmC) to 5-carboxycytosine (5caC) prior to performing the sequencing step. In any of the embodiments herein, the methods disclosed can further comprise contacting the ligated nucleic acid molecules with a combination of TET2 and T4-PGT enzymes to convert 5-methyl-cytosine (5mC) or 5- hydroxymethyl-cytosine (5hmC) to 5-(D-glucosyl)oxymethyl-cytosine prior to performing the sequencing step.
[0014] In any of the embodiments herein, the methods disclosed can further comprise contacting the ligated nucleic acid molecules with an APOBEC enzyme to convert cytosines to uracil prior to performing the sequencing step.
[0015] In any of the embodiments herein, the methods disclosed can further comprise performing a nucleic acid amplification reaction to generate amplified nucleic acid molecules prior to performing the sequencing step. In some embodiments, the nucleic acid amplification reaction can comprise a polymerase chain reaction. In some embodiments, the nucleic acid amplification reaction comprises a rolling circle amplification reaction.
[0016] In any of the embodiments herein, the methods disclosed can further comprise capturing a subset of nucleic acid molecules from the amplified nucleic acid molecules prior to performing the sequencing step. In any of the embodiments herein, the sequencer is a nextgeneration sequencer. In some embodiments herein, the next-generation sequencer comprises a cyclic array sequencer, a nanopore sequencer, or a single mode waveguide sequencer. In any of the embodiments herein, the methods disclosed can further comprise determining a methylation status for each of a plurality of genomic loci based on the sequence read data.
[0017] In any of the embodiments herein, the methods disclosed can further comprise diagnosing or confirming a diagnosis of disease in the subject based at least in part on a variant or a methylation signature identified in the sequence read data. In some embodiments, the variant can comprise a single nucleotide variant or a copy number alteration. In any of the embodiments herein, the methods disclosed can further comprise detecting minimum residual disease in the subject based on the sequence read data. In any of the embodiments herein, the disease can be cancer.
[0018] Disclosed herein is a method comprising: providing a plurality of nucleic acid molecules obtained from a sample from a subject; ligating one or more sequencing adapters onto one or more nucleic acid molecules from the plurality of nucleic acid molecules, wherein the one or more sequencing adapters can comprise an oligonucleotide sequence comprising at least one modified cytosine, wherein the at least one modified cytosine is not 5- methylcytosine, and wherein a rate of conversion of the at least one modified cytosine to uracil when contacted with a deaminating enzyme is less than that of 5-methylcytosine; amplifying the one or more ligated nucleic acid molecules from the plurality of nucleic acid molecules; capturing amplified nucleic acid molecules from the amplified nucleic acid molecules; sequencing, by a sequencer, the captured nucleic acid molecules to obtain a plurality of sequence reads that represent the captured nucleic acid molecules; receiving, at one or more processors, sequence read data for the plurality of sequence reads; and determining, using the one or more processors, a methylation status for each of a plurality of genomic loci based on the sequence read data. [0019] In some of the embodiments herein, the method may further comprise identifying one or more variant sequences based on the sequence read data. In some embodiments, the subject is suspected of having or is determined to have cancer.
[0020] In some embodiments, the cancer is a B cell cancer (multiple myeloma), a melanoma, breast cancer, lung cancer, bronchus cancer, colorectal cancer, prostate cancer, pancreatic cancer, stomach cancer, ovarian cancer, urinary bladder cancer, brain cancer, central nervous system cancer, peripheral nervous system cancer, esophageal cancer, cervical cancer, uterine cancer, endometrial cancer, cancer of an oral cavity, cancer of a pharynx, liver cancer, kidney cancer, testicular cancer, biliary tract cancer, small bowel cancer, appendix cancer, salivary gland cancer, thyroid gland cancer, adrenal gland cancer, osteosarcoma, chondrosarcoma, a cancer of hematological tissue, an adenocarcinoma, an inflammatory myofibroblastic tumor, a gastrointestinal stromal tumor (GIST), colon cancer, multiple myeloma (MM), myelodysplastic syndrome (MDS), myeloproliferative disorder (MPD), acute lymphocytic leukemia (ALL), acute myelocytic leukemia (AML), chronic myelocytic leukemia (CML), chronic lymphocytic leukemia (CLL), polycythemia Vera, Hodgkin lymphoma, non-Hodgkin lymphoma (NHL), soft-tissue sarcoma, fibrosarcoma, myxosarcoma, liposarcoma, osteogenic sarcoma, chordoma, angiosarcoma, endotheliosarcoma, lymphangiosarcoma, lymphangioendotheliosarcoma, synovioma, mesothelioma, Ewing’s tumor, leiomyosarcoma, rhabdomyosarcoma, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary carcinoma, papillary adenocarcinomas, medullary carcinoma, bronchogenic carcinoma, renal cell carcinoma, hepatoma, bile duct carcinoma, choriocarcinoma, seminoma, embryonal carcinoma, Wilms’ tumor, bladder carcinoma, epithelial carcinoma, glioma, astrocytoma, medulloblastoma, craniopharyngioma, ependymoma, pinealoma, hemangioblastoma, acoustic neuroma, oligodendroglioma, meningioma, neuroblastoma, retinoblastoma, follicular lymphoma, diffuse large B-cell lymphoma, mantle cell lymphoma, hepatocellular carcinoma, thyroid cancer, gastric cancer, head and neck cancer, small cell cancer, essential thrombocythemia, agnogenic myeloid metaplasia, hypereosinophilic syndrome, systemic mastocytosis, familiar hypereosinophilia, chronic eosinophilic leukemia, neuroendocrine cancers, or a carcinoid tumor.
[0021] In some embodiments, the cancer comprises acute lymphoblastic leukemia (Philadelphia chromosome positive), acute lymphoblastic leukemia (precursor B-cell), acute myeloid leukemia (FLT3+), acute myeloid leukemia (with an IDH2 mutation), anaplastic large cell lymphoma, basal cell carcinoma, B-cell chronic lymphocytic leukemia, bladder cancer, breast cancer (HER2 overexpressed/amplified), breast cancer (HER2+), breast cancer (HR+, HER2-), cervical cancer, cholangiocarcinoma, chronic lymphocytic leukemia, chronic lymphocytic leukemia (with 17p deletion), chronic myelogenous leukemia, chronic myelogenous leukemia (Philadelphia chromosome positive), classical Hodgkin lymphoma, colorectal cancer, colorectal cancer (dMMR/MSI-H), colorectal cancer (KRAS wild type), cryopyrin-associated periodic syndrome, a cutaneous T-cell lymphoma, dermatofibrosarcoma protuberans, a diffuse large B-cell lymphoma, fallopian tube cancer, a follicular B-cell nonHodgkin lymphoma, a follicular lymphoma, gastric cancer, gastric cancer (HER2+), gastroesophageal junction (GEJ) adenocarcinoma, a gastrointestinal stromal tumor, a gastrointestinal stromal tumor (KIT+), a giant cell tumor of the bone, a glioblastoma, granulomatosis with polyangiitis, a head and neck squamous cell carcinoma, a hepatocellular carcinoma, Hodgkin lymphoma, juvenile idiopathic arthritis, lupus erythematosus, a mantle cell lymphoma, medullary thyroid cancer, melanoma, a melanoma with a BRAF V600 mutation, a melanoma with a BRAF V600E or V600K mutation, Merkel cell carcinoma, multicentric Castleman’s disease, multiple hematologic malignancies including Philadelphia chromosome-positive ALL and CML, multiple myeloma, myelofibrosis, a non-Hodgkin’s lymphoma, a nonresectable subependymal giant cell astrocytoma associated with tuberous sclerosis, a non-small cell lung cancer, a non-small cell lung cancer (ALK+), a non-small cell lung cancer (PD-L1+), a non-small cell lung cancer (with ALK fusion or ROS1 gene alteration), a non-small cell lung cancer (with BRAF V600E mutation), a non-small cell lung cancer (with an EGFR exon 19 deletion or exon 21 substitution (L858R) mutations), a non- small cell lung cancer (with an EGFR T790M mutation), ovarian cancer, ovarian cancer (with a BRCA mutation), pancreatic cancer, a pancreatic, gastrointestinal, or lung origin neuroendocrine tumor, a pediatric neuroblastoma, a peripheral T-cell lymphoma, peritoneal cancer, prostate cancer, a renal cell carcinoma, rheumatoid arthritis, a small lymphocytic lymphoma, a soft tissue sarcoma, a solid tumor (MSI-H/dMMR), a squamous cell cancer of the head and neck, a squamous non-small cell lung cancer, thyroid cancer, a thyroid carcinoma, urothelial cancer, a urothelial carcinoma, or Waldenstrom’s macroglobulinemia.
[0022] In some embodiments, the method may further comprise treating the subject with an anti-cancer therapy. In some embodiments, the anti-cancer therapy comprises a targeted anticancer therapy. In some embodiments, the targeted anti-cancer therapy comprises abemaciclib (Verzenio), abiraterone acetate (Zytiga), acalabrutinib (Calquence), ado- trastuzumab emtansine (Kadcyla), afatinib dimaleate (Gilotrif), aldesleukin (Proleukin), alectinib (Alecensa), alemtuzumab (Campath), alitretinoin (Panretin), alpelisib (Piqray), amivantamab-vmjw (Rybrevant), anastrozole (Arimidex), apalutamide (Erleada), asciminib hydrochloride (Scemblix), atezolizumab (Tecentriq), avapritinib (Ayvakit), avelumab (Bavencio), axicabtagene ciloleucel (Yescarta), axitinib (Inlyta), belantamab mafodotin-blmf (Blenrep), belimumab (Benlysta), belinostat (Beleodaq), belzutifan (Welireg), bevacizumab (Avastin), bexarotene (Targretin), binimetinib (Mektovi), blinatumomab (Blincyto), bortezomib (Velcade), bosutinib (Bosulif), brentuximab vedotin (Adcetris), brexucabtagene autoleucel (Tecartus), brigatinib (Alunbrig), cabazitaxel (Jevtana), cabozantinib (Cabometyx), cabozantinib (Cabometyx, Cometriq), canakinumab (Haris), capmatinib hydrochloride (Tabrecta), carfilzomib (Kyprolis), cemiplimab-rwlc (Libtayo), ceritinib (LDK378/Zykadia), cetuximab (Erbitux), cobimetinib (Cotellic), copanlisib hydrochloride (Aliqopa), crizotinib (Xalkori), dabrafenib (Tafinlar), dacomitinib (Vizimpro), daratumumab (Darzalex), daratumumab and hyaluronidase-fihj (Darzalex Faspro), darolutamide (Nubeqa), dasatinib (Sprycel), denileukin diftitox (Ontak), denosumab (Xgeva), dinutuximab (Unituxin), dostarlimab-gxly (Jemperli), durvalumab (Imfinzi), duvelisib (Copiktra), elotuzumab (Empliciti), enasidenib mesylate (Idhifa), encorafenib (Braftovi), enfortumab vedotin-ejfv (Padcev), entrectinib (Rozlytrek), enzalutamide (Xtandi), erdafitinib (Balversa), erlotinib (Tarceva), everolimus (Afinitor), exemestane (Aromasin), fam-trastuzumab deruxtecan-nxki (Enhertu), fedratinib hydrochloride (Inrebic), fulvestrant (Faslodex), gefitinib (Iressa), gemtuzumab ozogamicin (Mylotarg), gilteritinib (Xospata), glasdegib maleate (Daurismo), hyaluronidase-zzxf (Phesgo), ibrutinib (Imbruvica), ibritumomab tiuxetan (Zevalin), idecabtagene vicleucel (Abecma), idelalisib (Zydelig), imatinib mesylate (Gleevec), infigratinib phosphate (Truseltiq), inotuzumab ozogamicin (Besponsa), iobenguane 1131 (Azedra), ipilimumab (Yervoy), isatuximab-irfc (Sarclisa), ivosidenib (Tibsovo), ixazomib citrate (Ninlaro), lanreotide acetate (Somatuline Depot), lapatinib (Tykerb), larotrectinib sulfate (Vitrakvi), lenvatinib mesylate (Lenvima), letrozole (Femara), lisocabtagene maraleucel (Breyanzi), loncastuximab tesirine-lpyl (Zynlonta), lorlatinib (Lorbrena), lutetium Lu 177-dotatate (Lutathera), margetuximab-cmkb (Margenza), midostaurin (Rydapt), mobocertinib succinate (Exkivity), mogamulizumab-kpkc (Poteligeo), moxetumomab pasudotox-tdfk (Lumoxiti), naxitamab-gqgk (Danyelza), necitumumab (Portrazza), neratinib maleate (Nerlynx), nilotinib (Tasigna), niraparib tosylate monohydrate (Zejula), nivolumab (Opdivo), obinutuzumab (Gazyva), ofatumumab (Arzerra), olaparib (Lynparza), olaratumab (Lartruvo), osimertinib (Tagrisso), palbociclib (Ibrance), panitumumab (Vectibix), panobinostat (Farydak), pazopanib (Votrient), pembrolizumab (Keytruda), pemigatinib (Pemazyre), pertuzumab (Perjeta), pexidartinib hydrochloride (Turalio), polatuzumab vedotin-piiq (Polivy), ponatinib hydrochloride (Iclusig), pralatrexate (Folotyn), pralsetinib (Gavreto), radium 223 dichloride (Xofigo), ramucirumab (Cyramza), regorafenib (Stivarga), ribociclib (Kisqali), ripretinib (Qinlock), rituximab (Rituxan), rituximab and hyaluronidase human (Rituxan Hycela), romidepsin (Istodax), rucaparib camsylate (Rubraca), ruxolitinib phosphate (Jakafi), sacituzumab govitecan-hziy (Trodelvy), seliciclib, selinexor (Xpovio), selpercatinib (Retevmo), selumetinib sulfate (Koselugo), siltuximab (Sylvant), sipuleucel-T (Provenge), sirolimus protein-bound particles (Fyarro), sonidegib (Odomzo), sorafenib (Nexavar), sotorasib (Lumakras), sunitinib (Sutent), tafasitamab-cxix (Monjuvi), tagraxofusp-erzs (Elzonris), talazoparib tosylate (Talzenna), tamoxifen (Nolvadex), tazemetostat hydrobromide (Tazverik), tebentafusp-tebn (Kimmtrak), temsirolimus (Torisel), tepotinib hydrochloride (Tepmetko), tisagenlecleucel (Kymriah), tisotumab vedotin-tftv (Tivdak), tocilizumab (Actemra), tofacitinib (Xeljanz), tositumomab (Bexxar), trametinib (Mekinist), trastuzumab (Herceptin), tretinoin (Vesanoid), tivozanib hydrochloride (Fotivda), toremifene (Fareston), tucatinib (Tukysa), umbralisib tosylate (Ukoniq), vandetanib (Caprelsa), vemurafenib (Zelboraf), venetoclax (Venclexta), vismodegib (Erivedge), vorinostat (Zolinza), zanubrutinib (Brukinsa), ziv-aflibercept (Zaltrap), or any combination thereof.
[0023] In some embodiments, the method may further comprise obtaining the sample from the subject. In some embodiments, the sample comprises a tissue biopsy sample, a liquid biopsy sample, or a normal control. In some embodiments, the sample is a liquid biopsy sample and comprises blood, plasma, cerebrospinal fluid, sputum, stool, urine, or saliva. In some embodiments, the sample is a liquid biopsy sample and comprises circulating tumor cells (CTCs). In some embodiments, the sample is a liquid biopsy sample and comprises cell- free DNA (cfDNA), circulating tumor DNA (ctDNA), or any combination thereof. In some embodiments, the plurality of nucleic acid molecules comprises a mixture of tumor nucleic acid molecules and non-tumor nucleic acid molecules. In some embodiments, the tumor nucleic acid molecules are derived from a tumor portion of a heterogeneous tissue biopsy sample, and the non-tumor nucleic acid molecules are derived from a normal portion of the heterogeneous tissue biopsy sample. In some embodiments, the sample comprises a liquid biopsy sample, and wherein the tumor nucleic acid molecules are derived from a circulating tumor DNA (ctDNA) fraction of the liquid biopsy sample, and the non-tumor nucleic acid molecules are derived from a non-tumor, cell-free DNA (cfDNA) fraction of the liquid biopsy sample.
[0024] In any of the embodiments herein, the one or more adapters comprise amplification primers, flow cell adaptor sequences, substrate adapter sequences, or sample index sequences. In any of the embodiments herein, the captured nucleic acid molecules may be captured from the amplified nucleic acid molecules by hybridization to one or more bait molecules. In some embodiments, the one or more bait molecules comprise one or more nucleic acid molecules, each comprising a region that is complementary to a region of a captured nucleic acid molecule. In some embodiments, amplifying nucleic acid molecules comprises performing a polymerase chain reaction (PCR) amplification technique, a non- PCR amplification technique, or an isothermal amplification technique. In some embodiments, the sequencing comprises use of a massively parallel sequencing (MPS) technique, whole genome sequencing (WGS), whole exome sequencing, targeted sequencing, direct sequencing, or Sanger sequencing technique. In some embodiments, the sequencing comprises massively parallel sequencing, and the massively parallel sequencing technique comprises next generation sequencing (NGS). In some embodiments, the sequencer comprises a next generation sequencer.
[0025] In any of the embodiments herein, one or more of the plurality of sequencing reads may overlap one or more gene loci within one or more subgenomic intervals in the sample. In some embodiments, the one or more gene loci comprises between 10 and 20 loci, between 10 and 40 loci, between 10 and 60 loci, between 10 and 80 loci, between 10 and 100 loci, between 10 and 150 loci, between 10 and 200 loci, between 10 and 250 loci, between 10 and 300 loci, between 10 and 350 loci, between 10 and 400 loci, between 10 and 450 loci, between 10 and 500 loci, between 20 and 40 loci, between 20 and 60 loci, between 20 and 80 loci, between 20 and 100 loci, between 20 and 150 loci, between 20 and 200 loci, between 20 and 250 loci, between 20 and 300 loci, between 20 and 350 loci, between 20 and 400 loci, between 20 and 500 loci, between 40 and 60 loci, between 40 and 80 loci, between 40 and 100 loci, between 40 and 150 loci, between 40 and 200 loci, between 40 and 250 loci, between 40 and 300 loci, between 40 and 350 loci, between 40 and 400 loci, between 40 and 500 loci, between 60 and 80 loci, between 60 and 100 loci, between 60 and 150 loci, between 60 and 200 loci, between 60 and 250 loci, between 60 and 300 loci, between 60 and 350 loci, between 60 and 400 loci, between 60 and 500 loci, between 80 and 100 loci, between 80 and 150 loci, between 80 and 200 loci, between 80 and 250 loci, between 80 and 300 loci, between 80 and 350 loci, between 80 and 400 loci, between 80 and 500 loci, between 100 and 150 loci, between 100 and 200 loci, between 100 and 250 loci, between 100 and 300 loci, between 100 and 350 loci, between 100 and 400 loci, between 100 and 500 loci, between 150 and 200 loci, between 150 and 250 loci, between 150 and 300 loci, between 150 and 350 loci, between 150 and 400 loci, between 150 and 500 loci, between 200 and 250 loci, between 200 and 300 loci, between 200 and 350 loci, between 200 and 400 loci, between 200 and 500 loci, between 250 and 300 loci, between 250 and 350 loci, between 250 and 400 loci, between 250 and 500 loci, between 300 and 350 loci, between 300 and 400 loci, between 300 and 500 loci, between 350 and 400 loci, between 350 and 500 loci, or between 400 and 500 loci.
[0026] In some embodiments, the one or more gene loci may comprise ABL1, ACVR1B, AKT1, AKT2, AKT3, ALK, ALOX12B, AMER1, APC, AR, ARAF, ARFRP1, ARID1A, ASXL1, ATM, ATR, ATRX, AURKA, AURKB, AXIN1, AXL, BAP1, BARD1, BCL2, BCL2L1, BCL2L2, BCL6, BCOR, BCORL1, BCR, BRAF, BRCA1, BRCA2, BRD4, BRIP1, BTG1, BTG2, BTK, CALR, CARD11, CASP8, CBFB, CBL, CCND1, CCND2, CCND3, CCNE1, CD22, CD274, CD70, CD74, CD79A, CD79B, CDC73, CDH1, CDK12, CDK4, CDK6, CDK8, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CDKN2C, CEBPA, CHEK1, CHEK2, CIC, CREBBP, CRKL, CSF1R, CSF3R, CTCF, CTNNA1, CTNNB1, CUL3, CUL4A, CXCR4, CYP17A1, DAXX, DDR1, DDR2, DIS3, DNMT3A, DOT1L, EED, EGFR, EMSY (Cl lorf30), EP300, EPHA3, EPHB1, EPHB4, ERBB2, ERBB3, ERBB4, ERCC4, ERG, ERRFI1, ESRI, ETV4, ETV5, ETV6, EWSR1, EZH2, EZR, FAM46C, FANCA, FANCC, FANCG, FANCL, FAS, FBXW7, FGF10, FGF12, FGF14, FGF19, FGF23, FGF3, FGF4, FGF6, FGFR1, FGFR2, FGFR3, FGFR4, FH, FLCN, FLT1, FLT3, FOXL2, FUBP1, GABRA6, GATA3, GATA4, GATA6, GID4 (C17orf39), GNA11, GNA13, GNAQ, GNAS, GRM3, GSK3B, H3F3A, HDAC1, HGF, HNF1A, HRAS, HSD3B1, ID3, IDH1, IDH2, IGF1R, IKBKE, IKZF1, INPP4B, IRF2, IRF4, IRS2, JAK1, JAK2, JAK3, JUN, KDM5A, KDM5C, KDM6A, KDR, KEAP1, KEL, KIT, KLHL6, KMT2A (MLL), KMT2D (MLL2), KRAS, LTK, LYN, MAF, MAP2K1, MAP2K2, MAP2K4, MAP3K1, MAP3K13, MAPK1, MCL1, MDM2, MDM4, MED12, MEF2B, MEN1, MERTK, MET, MITF, MKNK1, MLH1, MPL, MRE11A, MSH2, MSH3, MSH6, MST1R, MTAP, MTOR, MUTYH, MYB, MYC, MYCL, MYCN, MYD88, NBN, NF1, NF2, NFE2L2, NFKBIA, NKX2-1, NOTCH1, NOTCH2, NOTCH3, NPM1, NRAS, NT5C2, NTRK1, NTRK2, NTRK3, NUTM1, P2RY8, PALB2, PARK2, PARP1, PARP2, PARP3, PAX5, PBRM1, PDCD1, PDCD1LG2, PDGFRA, PDGFRB, PDK1, PIK3C2B, PIK3C2G, PIK3CA, PIK3CB, PIK3R1, PIM1, PMS2, POLDI, POLE, PPARG, PPP2R1A, PPP2R2A, PRDM1, PRKAR1A, PRKCI, PTCHI, PTEN, PTPN11, PTPRO, QKI, RAC1, RAD21, RAD51, RAD51B, RAD51C, RAD51D, RAD52, RAD54L, RAFI, RARA, RBI, RBM10, REL, RET, RICTOR, RNF43, ROS1, RPTOR, RSPO2, SDC4, SDHA, SDHB, SDHC, SDHD, SETD2, SF3B1, SGK1, SLC34A2, SMAD2, SMAD4, SMARCA4, SMARCB1, SMO, SNCAIP, SOCS1, SOX2, SOX9, SPEN, SPOP, SRC, STAG2, STAT3, STK11, SUFU, SYK, TBX3, TEK, TERC, TERT, TET2, TGFBR2, TIPARP, TMPRSS2, TNFAIP3, TNFRSF14, TP53, TSC1, TSC2, TYRO3, U2AF1, VEGFA, VHL, WHSCI, WHSC1L1, WT1, XPO1, XRCC2, ZNF217, ZNF703, or any combination thereof.
[0027] In some embodiments, the one or more gene loci may comprise ABL, ALK, ALL, B4GALNT1, BAFF, BCL2, BRAF, BRCA, BTK, CD19, CD20, CD3, CD30, CD319, CD38, CD52, CDK4, CDK6, CML, CRACC, CS1, CTLA-4, dMMR, EGFR, ERBB1, ERBB2, FGFR1-3, FLT3, GD2, HDAC, HER1, HER2, HR, IDH2, IL-ip, IL-6, IL-6R, JAK1, JAK2, JAK3, KIT, KRAS, MEK, MET, MSI-H, mTOR, PARP, PD-1, PDGFR, PDGFRa, PDGFRP, PD-L1, PI3K5, PIGF, PTCH, RAF, RANKL, RET, ROS1, SLAMF7, VEGF, VEGFA, VEGFB, or any combination thereof.
[0028] In any of the embodiments herein, the method may further comprise generating, by the one or more processors, a report indicating the methylation status determined for each of the plurality of genomic loci. In some embodiments, the method may further comprise transmitting the report to a healthcare provider. In some embodiments, the report is transmitted via a computer network or a peer-to-peer connection.
[0029] Disclosed herein is a method for diagnosing a disease, the method comprising: diagnosing that a subject has the disease based on a determination of a methylation signature for a sample from the subject, wherein the methylation signature can be determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to any of the embodiments herein.
[0030] Disclosed herein is a method of selecting an anti-cancer therapy, the method comprising: responsive to determining the methylation signature for a sample from a subject, selecting an anti-cancer therapy for the subject, wherein the methylation signature is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to any of the embodiments herein. [0031] Disclosed herein is a method of treating a cancer in a subject, comprising: responsive to determining the methylation signature for a sample from the subject, administering an effective amount of an anti-cancer therapy to the subject, wherein the methylation signature is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to any of the embodiments herein.
[0032] Disclosed herein is a method for monitoring cancer progression or recurrence in a subject, the method comprising: determining a first methylation signature in a first sample obtained from the subject at a first time point, wherein the first methylation signature is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to any of the embodiments herein; determining a second methylation signature in a second sample obtained from the subject at a second time point; and comparing the first methylation signature to the second methylation signature, thereby monitoring the cancer progression or recurrence. In some embodiments, the second methylation signature for the second sample is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to any of the embodiments disclosed herein.
[0033] The methods disclosed herein can further comprise selecting an anti-cancer therapy for the subject in response to the cancer progression. The methods disclosed herein can further comprise administering an anti-cancer therapy to the subject in response to the cancer progression. The methods disclosed herein can further comprise adjusting an anti-cancer therapy for the subject in response to the cancer progression. The methods disclosed herein can further comprise adjusting a dosage of the anti-cancer therapy or selecting a different anti-cancer therapy in response to the cancer progression.
[0034] In some embodiments, the methods disclosed herein can further comprise administering the adjusted anti-cancer therapy to the subject. In any of the embodiments herein, the first time point is before the subject has been administered an anti-cancer therapy, and wherein the second time point is after the subject has been administered the anti-cancer therapy. In any of the embodiments herein, the subject has a cancer, and can be at risk of having a cancer, is being routine tested for cancer, or is suspected of having a cancer. In any of the embodiments herein, the cancer can be a solid tumor. In any of the embodiments herein, the cancer can be a hematological cancer. In any of the embodiments herein, the anti- cancer therapy can comprise chemotherapy, radiation therapy, immunotherapy, a targeted therapy, or surgery.
INCORPORATION BY REFERENCE
[0035] All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference in their entirety to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated be incorporated by reference in its entirety. In the event of a conflict between a term herein and a term in an incorporated reference, the term herein controls.
BRIEF DESCRIPTION OF THE DRAWINGS
[0036] Various aspects of the disclosed methods, devices, and systems are set forth with particularity in the appended claims. A better understanding of the features and advantages of the disclosed methods, devices, and systems will be obtained by reference to the following detailed description of illustrative embodiments and the accompanying drawings, of which:
[0037] FIG. 1 depicts a non-limiting example of data that illustrates a histogram depicting the percentage of sequence reads passing a quality filter, in accordance with some instances of the present disclosure.
[0038] FIG. 2 depicts a non-limiting example of schematics that illustrate primer sequences (ACACTCTTTCCCTACACGACGCTCTTCCGATCT (SEQ ID NO: 3);
GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT (SEQ ID NO: 4)), in accordance with some instances of the present disclosure.
[0039] FIG. 3 depicts a non-limiting example of schematics that illustrate primer sequences (ACACTCTTTCCCTACACGACGCTCTTCCGATCT (SEQ ID NO: 3)) and their complementary sequences (AGATCGGAAGAGCGTCGAGTAGGGAAAGAGTGT (SEQ ID NO: 5); AAATCGGAAAAACGTCGAGTAGGGAAAGAGTGT (SEQ ID NO: 6)), in accordance with some instances of the present disclosure.
[0040] FIG. 4 depicts a non-limiting example of schematics that illustrate primer sequences (GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT (SEQ ID NO: 4) and their complementary sequences (AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC (SEQ ID NO: 7); AAATCGGAAAAACACACGTCTGAACTCCAGTCAC (SEQ ID NO: 8)), in accordance with some instances of the present disclosure. [0041] FIG. 5 depicts a non-limiting example of schematics that illustrates a potential mechanism of action of 5mC modifications, in accordance with some instances of the present disclosure.
[0042] FIGS. 6A-C depict non-limiting examples of schematics that illustrate the steps of a workflow for processing DNA, in accordance with some instances of the present disclosure. FIG. 6A: non-limiting schematic illustration of a process for extracting and purifying DNA from a sample. FIG. 6B: non-limiting schematic illustration of a process for performing endrepair and tailing reactions on extracted and purified DNA. FIG. 6C: non-limiting schematic illustration of a process for performing enzymatic conversion of cytosines in a DNA sample and performing methylation sequencing.
[0043] FIG. 7 depicts a non-limiting example of data that illustrates the SNP filtered error rate for different sequencing workflows, in accordance with some instances of the present disclosure.
[0044] FIG. 8 depicts a non-limiting example of typical adapter sequences provided for use in preparing double-stranded DNA libraries for methylation sequencing, in accordance with some instances of the present disclosure.
(ACACTCTTTCCCTACACGACGCTCTTCCGATCT (SEQ ID NO: 3); GATCGGAAGAGCACACGTCTGAACTCCAGTC (SEQ ID NO: 9))
[0045] FIG. 9 depicts a non-limiting example of a modified sequencing adaptor for performing methylation sequencing that comprises incorporated 5hmC nucleotide residues, in accordance with some instances of the present disclosure.
GAT[5hmC]GGAAGAG[5hmC]A[5hmC]A[5mC]GT[5mC]TGAA[5mC]T[5mC][5mC]AG T[5mC] (SEQ ID NO: 10);
A[5mC]A[5mC]T[5mC]TTT[5mC][5mC][5mC]TA[5mC]A[5mC]GA[5mC]G[5mC]T[5mC] TT[5hmC][5hmC]GAT[5hmC]T (SEQ ID NO: 11))
[0046] FIG. 10 depicts a non-limiting example of a modified sequencing adaptor for performing methylation sequencing that comprises incorporated 5hmC nucleotide residues, in accordance with some instances of the present disclosure.
(GAT[5hmC]GGAAGAG[5mC]A[5mC]A[5mC]GT[5hmC]TGAA[5mC]T[5mC][5mC]AGT [5mC] (SEQ ID NO: 12);
A[5mC]A[5mC]T[5mC]TTT[5mC][5mC][5mC]TA[5mC]A[5mC]GA[5mC]G[5hmC]T[5hm C]TT[5mC][5mC]GAT[5hmC]T (SEQ ID NO: 13)) [0047] FIG. 11 depicts a non-limiting example of a modified sequencing adaptor for performing methylation sequencing that comprises a single incorporated 5hmC nucleotide residue.
(GAT[5mC]GGAAGAG[5mC]A[5mC]A[5mC]GT[5mC]TGAA[5mC]T[5mC][5mC]AGT[5 mC] (SEQ ID NO: 22);
A[5mC]A[5mC]T[5mC]TTT[5mC][5mC][5mC]TA[5mC]A[5mC]GA[5mC]G[5mC]T[5mC] TT[5mC][5mC]GAT [5hmC]T (SEQ ID NO: 14))
[0048] FIG. 12 depicts a non-limiting example of data that illustrates the percentage of reads passing a quality filter, for various sequencing platforms and adapter sequences, in accordance with some instances of the present disclosure.
[0049] FIG. 13 depicts a non-limiting example of schematics that illustrates an assay for validating the effects of modified cytosines, in accordance with some instances of the present disclosure.
[0050] FIG. 14 depicts a non-limiting example of schematics that illustrates an assay for validating the effects of modified cytosines, in accordance with some instances of the present disclosure.
(A[5mC]A[5mC]T[5mC]TTT[5mC][5mC][5mC]TA[5mC]A[5mC]GA[5mC][G/T][5mC]T[5 mC]TT[5mC][5mC]GA[T/G][5mC]T (SEQ ID NO: 15);
GAT[5mC]GGAAGAG[5mC]A[5mC]A[5mC]G[T/G][5mC]TGAA[5mC]T[5mC][5mC]AG T[5mC] (SEQ ID NO: 16);
[G/T][5hmC]T[5hmC]TT[5hmC][5hmC]GA[T/G][5hmC]TNNNNNNNNNNNNNNAGAT[ 5hmC]GGAAGAG[5hmC]GT[5hmC]GTGTAGGGAAAGAGTGT (SEQ ID NO: 17);
A[5mC]A[5mC]T[5mC]TTT[5mC][5mC][5mC]TA[5mC]A[5mC]GA[5mC][G/T][5mC]T[5 mC]TT[5mC][5mC]GA[T/G][5mC]TNNNNNNNNNNNNNNAGAT[5mC]GGAAGAG[5m C]A[5mC]A[5mC]G[T/G][5mC]TGAA[5mC]T[5mC][5mC]AGT[5mC] (SEQ ID NO: 18))
[0051] FIG. 15 depicts a non-limiting example of schematics that illustrates an assay for validating the effects of modified cytosines, in accordance with some instances of the present disclosure.
(A[5mC]A[5mC]T[5mC]TTT[5mC][5mC][5mC]TA[5mC]A[5mC]GA[5mC][G/T][5hmC]T[ 5hmC]TT[5mC][5mC]GA[T/G][5hmC]T (SEQ ID NO: 19);
GAT[5hmC]GGAAGAG[5mC]A[5mC]A[5mC]G[T/G][5hmC]TGAA[5mC]T[5mC][5mC]A GT[5mC] (SEQ ID NO: 20); [G/T][5hmC]T[5hmC]TT[5hmC][5hmC]GA[T/G][5hmC]TNNNNNNNNNNNNNNAGAT[ 5hmC]GGAAGAG[5hmC]GT[5hmC]GTGTAGGGAAAGAGTGT (SEQ ID NO: 17); A[5mC]A[5mC]T[5mC]TTT[5mC][5mC][5mC]TA[5mC]A[5mC]GA[5mC]N[5hmC]T[5hm C]TT[5mC][5mC]GAN[5hmC]TNNNNNNNNNNNNNNAGAT[5hmC]GGAAGAG[5mC] A[5mC]A[5mC]GN[5hmC]TGAA[5mC]T[5mC][5mC]AGT[5mC] (SEQ ID NO: 21)
[0052] FIG. 16 depicts a non-limiting example of data that illustrates the percentage of reads passing a quality filter, for various sequencing methods and adapter sequences, in accordance with some instances of the present disclosure.
[0053] FIG. 17 depicts a non-limiting example of data that illustrates a ratio of the percentage sequence reads passing filter, for various sequencing methods, in accordance with some instances of the present disclosure.
DETAILED DESCRIPTION
[0054] The present disclosure describes novel sequencing adapters. The disclosed sequencing adapters feature an oligonucleotide sequence that contains at least one modified base (e.g., a modified cytosine), where at least one modified base is not 5-methylcytosine, and where the rate of conversion of at least one modified base to uracil, when contacted by a deaminating enzyme, is less than the corresponding rate of conversion of 5-methylcytosine (5mC). The at least one modified base can include, for example, inosine, 5-nitroindole, N4-ethyl- deoxycytidine, 5-propynylcytosine, 5-vinylcytosine, 5-ethynylcytosine, pyrrolo- deoxycytidine, propynyl-deoxycytidine, 5-hydroxymethylcytosine, 5-(D- glucosyl)oxymethylcytosine, 5-formylcytosine, 5-carboxycytosine, or any combination of the above.
[0055] Some methylation sequencing methods use protective enzymes (e.g. tet methylcytosine dioxygenase 2 (TET2) and/or a glycosylase) to shield methylated cytosines from deaminating enzymes (e.g. apolipoprotein B mRNA editing enzyme catalytic polypeptide (APOBEC)), so the methylated cytosines are not converted into uracil. In theory, this protection is configured to be efficient for most methylated cytosines, including 5mC. In other words, the TET2 and/or glycosylase enzymes are expected to protect 5mC from being deaminated into cytosine/uracil. In practice, however, the protective enzymes do not act efficiently on certain methylated cytosines, such as 5mC. This poor protecting of 5mC from deamination appears especially prevalent in the context of certain nucleotide sequence motifs. Such poor protection from deamination can affect the 5-methylcytosines of sequencing adapters used in methylation sequencing methods. Failure to protect 5-methylcytosines of sequencing adapters from unintended deamination results in the unprotected 5- methylcytosines deaminating — that is, effectively mutating — into uracil, which can abrogate the complementary binding between the sequencing adapter and flow cell adapters and/or sequencing primers. The expected C-G hybridization between the adapter and the flow cell adapters or sequencing primers will have mutated into a non-hybridizing U-G / T-G pairing, if the protective enzymes fail to prevent the conversion of 5-methylcytosine into uracil. [0056] The present disclosure describes a sequencing adapter having a composition that is more resilient to the erroneous conversion of 5-methlycytosine to uracil. The sequencing adapter described herein uses at least one modified base (e.g., a modified base that is not 5mC) that exhibits reduced erroneous conversion to uracil, relative to 5-methylcytosine. By being more resilient to the erroneous conversion effects of deaminating enzymes, the sequencing adapters described herein exhibit improvements in retaining their expected nucleic acid sequence, and accordingly, can better hybridize to their target adapter and/or corresponding primer sequences. The sequencing adapters described herein as a result provide improvements to the read depth and/or coverage of genome sequences achieved when applied to enzymatic conversion-based methylation sequencing methods. Moreover, the sequencing adapters described herein may provide improvements to not only methylation sequencing methods, but also to general technologies comprising the use of deaminating enzymes.
[0057] Disclosed herein is a sequencing adapter comprising an oligonucleotide sequencing comprising at least one modified base, wherein the at least one modified cytosine is not 5- methylcytosine, and wherein a rate of conversion of the at least one modified cytosine to uracil when contacted with a deaminating enzyme or enzyme combination is less than that of 5-methylcytosine. The at least one modified base can be inosine, 5-nitroindole, N4-ethyl- deoxycytidine, 5-propynylcytosine, 5-vinylcytosine, 5-ethynylcytosine, pyrrolo- deoxycytidine, or propynyl-deoxy cytidine. The at least one modified base can be a modified cytosine. The modified cytosine of the sequencing adapter can be, for example, 5- hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, 5-formylcytosine, 5- carboxycytosine, or a combination thereof. Definitions
[0058] Unless otherwise defined, all of the technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art in the field to which this disclosure belongs.
[0059] As used in this specification and the appended claims, the singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise. Any reference to “or” herein is intended to encompass “and/or” unless otherwise stated.
[0060] ‘ ‘About” and “approximately” shall generally mean an acceptable degree of error for the quantity measured given the nature or precision of the measurements. Exemplary degrees of error are within 20 percent (%), typically, within 10%, and more typically, within 5% of a given value or range of values.
[0061] As used herein, the terms "comprising" (and any form or variant of comprising, such as "comprise" and "comprises"), "having" (and any form or variant of having, such as "have" and "has"), "including" (and any form or variant of including, such as "includes" and "include"), or "containing" (and any form or variant of containing, such as "contains" and "contain"), are inclusive or open-ended and do not exclude additional, un-recited additives, components, integers, elements, or method steps.
[0062] The section headings used herein are for organizational purposes only and are not to be construed as limiting the subject matter described. The description is presented to enable one of ordinary skill in the art to make and use the invention, and is provided in the context of a patent application and its requirements.
[0063] As used herein, the terms “individual,” “patient,” or “subject” are used interchangeably and refer to any single animal, e.g., a mammal (including such non-human animals as, for example, dogs, cats, horses, rabbits, zoo animals, cows, pigs, sheep, and non- human primates) for which treatment is desired. In particular embodiments, the individual, patient, or subject herein is a human.
[0064] The terms “cancer” and “tumor” are used interchangeably herein. These terms refer to the presence of cells possessing characteristics typical of cancer-causing cells, such as uncontrolled proliferation, immortality, metastatic potential, rapid growth and proliferation rate, and certain characteristic morphological features. Cancer cells are often in the form of a tumor, but such cells can exist alone within an animal, or can be a non-tumorigenic cancer cell, such as a leukemia cell. These terms include a solid tumor, a soft tissue tumor, or a metastatic lesion. As used herein, the term “cancer” includes premalignant, as well as malignant cancers.
[0065] As used herein, “treatment” (and grammatical variations thereof such as “treat” or “treating”) refers to clinical intervention (e.g., administration of an anti-cancer agent or anticancer therapy) in an attempt to alter the natural course of the individual being treated, and can be performed either for prophylaxis or during the course of clinical pathology. Desirable effects of treatment include, but are not limited to, preventing occurrence or recurrence of disease, alleviation of symptoms, diminishment of any direct or indirect pathological consequences of the disease, preventing metastasis, decreasing the rate of disease progression, amelioration or palliation of the disease state, and remission or improved prognosis.
[0066] As used herein, the term “subgenomic interval” (or “subgenomic sequence interval”) refers to a portion of a genomic sequence.
[0067] As used herein, the term "subject interval" refers to a subgenomic interval or an expressed subgenomic interval (e.g., the transcribed sequence of a subgenomic interval).
[0068] As used herein, the terms “variant sequence” or “variant” are used interchangeably and refer to a modified nucleic acid sequence relative to a corresponding “normal” or “wildtype” sequence. In some instances, a variant sequence may be a “short variant sequence” (or “short variant”), i.e., a variant sequence of less than about 50 base pairs in length.
[0069] The terms “allele frequency” and “allele fraction” are used interchangeably herein and refer to the fraction of sequence reads corresponding to a particular allele relative to the total number of sequence reads for a genomic locus.
[0070] The terms “variant allele frequency” and “variant allele fraction” are used interchangeably herein and refer to the fraction of sequence reads corresponding to a particular variant allele relative to the total number of sequence reads for a genomic locus.
[0071] The term “sequencing adapter” as used herein refers to a short oligonucleotide sequence that may be ligated to template DNA fragments in preparation for performing nucleic acid sequencing, and that may be configured to enable template DNA fragments from a sequencing library to bind to complementary flow cell adapter sequences and/or may comprise sequencing primer binding sites. [0072] The terms “modified” or “protected” are used interchangeably herein, and when used to describe a nucleobase (e.g., cytosine) herein, refer to a nucleobase (e.g., cytosine) comprising a chemical modification that protects the base from deamination by a combination of enzymes (e.g., glycosylase and/or TET2 and APOBEC). For example, the terms “modified cytosine” or “protected cytosine” can refer to a cytosine comprising 5- methylcytosine, 5-hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, 5- formylcytosine, or 5-carboxycytosine. The terms “modified” or “protected” when used to describe a base herein, imply that the base exhibits reduced erroneous conversion to uracil when contacted with a deaminating enzyme (or combination of enzymes) than an “unprotected” base.
Sequencing adapters for performing methylation sequencing
[0073] The modified sequencing adapters configured for methylation sequencing, as described herein, comprise at least one modified cytosine that possesses a rate of conversion to uracil that is less than that of 5-methylcytosine, when in the presence of deaminating enzymes. Examples of modified cytosines that exhibit a rate of conversion to uracil by deaminating enzymes that is less than that of 5-methylcytosine and that can be incorporated into the disclosed adapter sequences include, but are not limited to, 5-hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, 5-formylcytosine, or 5-carboxycytosine, and any combination of the aforementioned. 5-hydroxymethylcytosine can be generated from 5- methylcytosine via a ten-eleven translocation (TET) enzyme, and 5-formylcytosine can be generated from 5-hydroxymethylcytosine, also via the TET enzyme. Similarly, 5- carboxycytosine can be generated from 5-formylcytosine via the TET enzyme. The modified cytosines that are derived from the activity of the TET enzyme on 5-methylcytosine are inefficiently converted into uracil by deaminating enzymes, like APOBEC. Given their inefficient conversion into uracil via deamination, these modified cytosines may be included in sequencing adapters for methylation sequencing in place of 5-methylcytosine such that the modified cytosines of the sequencing adapters exhibit reduced erroneous conversion to uracil uracil when used in any technology comprising the application of deaminating enzymes including, but not limited to, methylation sequencing methods. The erroneous conversion of 5-methylcytosine into uracil can be unusually prevalent if the 5-methylcytosine is located in certain nucleotide subsequences. Consequently, adapter sequences comprising such problematic nucleotide subsequences may especially benefit from the inclusion of modified cytosine bases. [0074] In some aspects, disclosed herein are sequencing adapter comprising an oligonucleotide sequence comprising at least one modified cytosine, where a rate of conversion of the at least one modified cytosine to uracil when contacted with a deaminating enzyme is less than that of 5-methylcytosine.
[0075] In some instances, the at least one modified cytosine can be located at any position within the oligonucleotide sequence, e.g., at or in close proximity to the 5’ end or the 3’ end of the adapter sequence, or at a position somewhere in between.
[0076] In any of the instances herein, the at least one modified cytosine incorporated into the disclosed modified sequencing adapters can be 5-hydroxymethylcytosine, 5-(D- glucosyl)oxymethylcytosine, 5-formylcytosine, 5-carboxycytosine, or a combination thereof. In any of the instances herein, the at least one modified cytosine can be 5- hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, or a combination thereof. In any of the instances herein, the at least one modified cytosine can be 5-hydroxymethylcytosine.
[0077] The at least one modified cytosine incorporated into the disclosed modified sequencing adapters can be generated via chemical synthesis, or can be isolated and extracted via biotechnological methods.
[0078] In some instances herein, the oligonucleotide sequence can comprise at least four cytosines, and the three cytosines closest to the 3’ end of the oligonucleotide sequence can be modified cytosines. In any of the instances herein, the cytosines of the oligonucleotide sequence can all be modified cytosines. In any of the instances herein, the sequencing adapter can comprise two complementary oligonucleotide sequences, each comprising at least four cytosines, and the three cytosines closest to a 3’ end or a 5’ end in at least one of the two complementary oligonucleotide sequences can be modified cytosines.
[0079] In any of the instances herein, the deaminating enzyme can be an APOBEC enzyme.
[0080] In any of the instances herein, the oligonucleotide sequence can be between about 20 and 100 nucleotides in length.
[0081] The oligonucleotide sequence can be about 20 nucleotides, 25 nucleotides, 30 nucleotides, 35 nucleotides, 40 nucleotides, 45 nucleotides, 50 nucleotides, 55 nucleotides, 60 nucleotides, 65 nucleotides, 70 nucleotides, 75 nucleotides, 80 nucleotides, 85 nucleotides, 90 nucleotides, 95 nucleotides, or 100 nucleotides in length. In some instances, the oligonucleotide sequence can have a length corresponding to any value within the range of 20 nucleotides to 100 nucleotides.
[0082] In any of the instances herein, the oligonucleotide sequence can comprise at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 contiguous nucleotides selected from the sequence 5’ AAT GAT ACG GCG ACC ACC GA 3’ (SEQ ID NO: 1) or its complement. In any of the instances herein, the oligonucleotide sequence can comprise at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 contiguous nucleotides selected from the sequence 5’ CAA GCA GAA GAC GGC ATA CGA GAT 3’ (SEQ ID NO: 2) or its complement. In any of the instances herein, the oligonucleotide sequence can comprise at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, or 33 contiguous nucleotides selected from the sequence 5’ ACA CTC TTT CCC TAC ACG ACG CTC TTC CGA TCT 3’ (SEQ ID NO: 3) or its complement. In any of the instances herein, the oligonucleotide sequence can comprise at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, or 34 contiguous nucleotides selected from the sequence 5’ GTG ACT GGA GTT CAG ACG TGT GCT CTT CCG ATC T 3’ (SEQ ID NO: 4) or its complement.
[0083] In any of the instances herein, disclosed is a method for performing nucleic acid sequencing, comprising: a) providing a plurality of nucleic acid molecules obtained from a sample from a subject; b) performing an enzymatic ligation of one or more of the sequence adapters of any one of claims 1 to 14 onto the plurality of nucleic acid molecules; c) sequencing, by a sequencer, the ligated nucleic acid molecules to obtain a plurality of sequence reads derived from the sample; and d) receiving, at one or more processors, sequence read data for the plurality of sequence reads derived from the sample.
[0084] In some instances, the enzymatic ligation can comprise single- stranded ligation. In some instances, the enzymatic ligation can comprise double-stranded ligation.
[0085] In any of the instances herein, the nucleic acid sequencing can comprise a methylation sequencing method. In any of the instances herein, the methylation sequencing method can comprise an enzymatic cytosine conversion step.
[0086] The methylation sequencing method can comprise a PCR-based detection assay, a quantitative PCR-based detection assay, a digital droplet PCR-based detection assay, a methylation- specific PCR-based detection assay, a methylation- specific selection assay, such as immunoprecipitation of methylated DNA, or a microarray-based DNA methylation profiling assay.
[0087] In any of the instances herein, the sample can comprise a tissue sample or a buffy coat sample.
[0088] In some instances, the methods disclosed can further comprise shearing nucleic acids extracted from the sample to provide the plurality of nucleic acid molecules.
[0089] In any of the instances herein, the methods disclosed can further comprise performing an end repair reaction on the plurality of nucleic acid molecules prior to performing the enzymatic ligation. In any of the instances herein, the methods disclosed can further comprise performing an A-tailing reaction on the plurality of nucleic acid molecules prior to performing the enzymatic ligation.
[0090] The end repair reaction and/or the A-tailing reaction can be performed as part of sequencing library preparation, or any other protocol that configures or optimizes nucleic acid molecules for a methylation sequencing method. The end repair reactions can also comprise blunt ligations without any 3’ tailing, the addition of an indeterminate length of bases on the 3’ end, and/or a ligation-free addition of adapters during PCR. In the case of the A-tailing reaction, terminal deoxytransferase can be used to add an oligo-A tail rather than a single A tail.
[0091] In any of the instances herein, the methods disclosed can further comprise contacting the ligated nucleic acid molecules with a TET2 enzyme to oxidize 5-methyl-cytosine (5mC) or 5-hydroxymethyl-cytosine (5hmC) to 5-carboxycytosine (5caC) prior to performing the sequencing step. In any of the instances herein, the methods disclosed can further comprise contacting the ligated nucleic acid molecules with a combination of TET2 and T4-PGT enzymes to convert 5-methyl-cytosine (5mC) or 5-hydroxymethyl-cytosine (5hmC) to 5-(D- glucosyl)oxymethyl-cytosine prior to performing the sequencing step.
[0092] In any of the instances herein, the methods disclosed can further comprise contacting the ligated nucleic acid molecules with an APOBEC enzyme to convert cytosines to uracil prior to performing the sequencing step.
[0093] In any of the instances herein, the methods disclosed can further comprise performing a nucleic acid amplification reaction to generate amplified nucleic acid molecules prior to performing the sequencing step. In some instances, the nucleic acid amplification reaction can comprise a polymerase chain reaction.
[0094] In any of the instances herein, the methods disclosed can further comprise capturing a subset of nucleic acid molecules from the amplified nucleic acid molecules prior to performing the sequencing step. In any of the instances herein, the sequencing can be performed using a next-generation sequencer.
[0095] In any of the instances herein, the methods disclosed can further comprise determining a methylation status for each of a plurality of genomic loci based on the sequence read data.
[0096] In any of the instances herein, the methods disclosed can further comprise diagnosing or confirming a diagnosis of disease in the subject based on a variant or a methylation signature identified in the sequence read data. In some instances, the variant can comprise a single nucleotide variant or a copy number alteration. In any of the instances herein, the methods disclosed can further comprise detecting minimum residual disease in the subject based on the sequence read data. In any of the instances herein, the disease can be cancer.
[0097] Disclosed herein is a method comprising: providing a plurality of nucleic acid molecules obtained from a sample from a subject; ligating one or more sequencing adapters onto one or more nucleic acid molecules from the plurality of nucleic acid molecules, wherein the one or more sequencing adapters can comprise an oligonucleotide sequence comprising at least one modified cytosine, wherein a rate of conversion of the at least one modified cytosine to uracil when contacted with a deaminating enzyme is less than that of 5- methylcytosine; amplifying the one or more ligated nucleic acid molecules from the plurality of nucleic acid molecules; capturing amplified nucleic acid molecules from the amplified nucleic acid molecules; sequencing, by a sequencer, the captured nucleic acid molecules to obtain a plurality of sequence reads that represent the captured nucleic acid molecules; receiving, at one or more processors, sequence read data for the plurality of sequence reads; identifying, using the one or more processors, one or more variant sequences based on the sequence read data; categorizing, using the one or more processors, the one or more variant sequences according to one or more characteristics associated with at least one of a structural feature or a functional effect.
[0098] Disclosed herein is a method for diagnosing a disease, the method comprising: diagnosing that a subject has the disease based on a determination of a methylation signature for a sample from the subject, wherein the methylation signature can be determined according to any of the instances herein.
[0099] Disclosed herein is a method of selecting an anti-cancer therapy, the method comprising: responsive to determining the methylation signature for a sample from a subject, selecting an anti-cancer therapy for the subject, wherein the methylation signature is determined according to any of the instances herein.
[0100] Disclosed herein is a method of treating a cancer in a subject, comprising: responsive to determining the methylation signature for a sample from the subject, administering an effective amount of an anti-cancer therapy to the subject, wherein the methylation signature is determined according to any of the instances herein.
[0101] Disclosed herein is a method for monitoring cancer progression or recurrence in a subject, the method comprising: determining a first methylation signature in a first sample obtained from the subject at a first time point according to any of the instances herein; determining a second methylation signature in a second sample obtained from the subject at a second time point; and comparing the first methylation signature to the second methylation signature, thereby monitoring the cancer progression or recurrence. In some instances, the second methylation signature for the second sample is determined according to the instances disclosed herein.
[0102] The methods disclosed herein can further comprise selecting an anti-cancer therapy for the subject in response to the cancer progression. The methods disclosed herein can further comprise administering an anti-cancer therapy to the subject in response to the cancer progression. The methods disclosed herein can further comprise adjusting an anti-cancer therapy for the subject in response to the cancer progression. The methods disclosed herein can further comprise adjusting a dosage of the anti-cancer therapy or selecting a different anti-cancer therapy in response to the cancer progression.
[0103] In some instances, the methods disclosed herein can further comprise administering the adjusted anti-cancer therapy to the subject. In any of the instances herein, the first time point is before the subject has been administered an anti-cancer therapy, and wherein the second time point is after the subject has been administered the anti-cancer therapy. In any of the instances herein, the subject has a cancer, and can be at risk of having a cancer, is being routine tested for cancer, or is suspected of having a cancer. In any of the instances herein, the cancer can be a solid tumor. In any of the instances herein, the cancer can be a hematological cancer. In any of the instances herein, the anti-cancer therapy can comprise chemotherapy, radiation therapy, immunotherapy, a targeted therapy, or surgery.
Methods of Use
[0104] In some instances, the disclosed methods may further comprise one or more of the steps of: (i) obtaining the sample from the subject (e.g., a subject suspected of having or determined to have cancer), (ii) extracting nucleic acid molecules (e.g., a mixture of tumor nucleic acid molecules and non-tumor nucleic acid molecules) from the sample, (iii) ligating one or more adapters to the nucleic acid molecules extracted from the sample (e.g., one or more amplification primers, flow cell adaptor sequences, substrate adapter sequences, or sample index sequences), (iv) performing a methylation conversion reaction to convert, e.g., non-methylated cytosine to uracil, (v) amplifying the nucleic acid molecules (e.g., using a polymerase chain reaction (PCR) amplification technique, a non-PCR amplification technique, or an isothermal amplification technique), (vi) capturing nucleic acid molecules from the amplified nucleic acid molecules (e.g., by hybridization to one or more bait molecules, where the bait molecules each comprise one or more nucleic acid molecules that each comprising a region that is complementary to a region of a captured nucleic acid molecule), (vii) sequencing the nucleic acid molecules extracted from the sample (or library proxies derived therefrom) using, e.g., a next-generation (massively parallel) sequencing technique, a whole genome sequencing (WGS) technique, a whole exome sequencing technique, a targeted sequencing technique, a direct sequencing technique, or a Sanger sequencing technique) using, e.g., a next-generation (massively parallel) sequencer, (viii) combining the nucleic acid sequence data (including, e.g., variant data, copy number data, methylation status data, etc., of the sequenced nucleic acid molecules) with other biomarker data modalities including, but not limited to, proteomics-based biomarker data (e.g., the detection of specific polypeptides, such as proteins) or fragmentomics-based biomarker data (e.g., the detection of certain attributes related to nucleic acid fragments, such as fragment size or the sequences of fragment ends), to determine, for example, the presence of ctDNA in the sample and/or to determine a diagnostic, prognostic, and/or treatment response prediction for the subject, and (ix) generating, displaying, transmitting, and/or delivering a report (e.g., an electronic, web-based, or paper report) to the subject (or patient), a caregiver, a healthcare provider, a physician, an oncologist, an electronic medical record system, a hospital, a clinic, a third-party payer, an insurance company, or a government office. In some instances, the report comprises output from the methods described herein. In some instances, all or a 1 portion of the report may be displayed in the graphical user interface of an online or webbased healthcare portal. In some instances, the report is transmitted via a computer network or peer-to-peer connection.
[0105] The disclosed methods may be used with any of a variety of samples. For example, in some instances, the sample may comprise a tissue biopsy sample, a liquid biopsy sample, or a normal control. In some instances, the sample may be a liquid biopsy sample and may comprise blood, plasma, cerebrospinal fluid, sputum, stool, urine, or saliva. In some instances, the sample may be a liquid biopsy sample and may comprise circulating tumor cells (CTCs). In some instances, the sample may be a liquid biopsy sample and may comprise cell-free DNA (cfDNA). In some instances, the cell-free DNA (cfDNA), or a portion thereof, may comprise circulating tumor DNA (ctDNA). In some instances, the liquid biopsy sample may comprise a combination of cell-free DNA (cfDNA) and circulating tumor DNA (ctDNA).
[0106] In some instances, the nucleic acid molecules extracted from a sample may comprise a mixture of tumor nucleic acid molecules and non-tumor nucleic acid molecules. In some instances, the tumor nucleic acid molecules may be derived from a tumor portion of a heterogeneous tissue biopsy sample, and the non-tumor nucleic acid molecules may be derived from a normal portion of the heterogeneous tissue biopsy sample. In some instances, the sample may comprise a liquid biopsy sample, and the tumor nucleic acid molecules may be derived from a circulating tumor DNA (ctDNA) fraction of the liquid biopsy sample while the non-tumor nucleic acid molecules may be derived from a non-tumor, cell-free DNA (cfDNA) fraction of the liquid biopsy sample.
[0107] In some instances, the disclosed methods for methylation sequencing may be used to diagnose (or as part of a diagnosis of) the presence of disease or other condition (e.g., cancer, genetic disorders (such as Down Syndrome and Fragile X), neurological disorders, or any other disease type where detection of variants, e.g., copy number alternations, are relevant to diagnosing, treating, or predicting said disease) in a subject (e.g., a patient). In some instances, the disclosed methods may be applicable to diagnosis of any of a variety of cancers as described elsewhere herein.
[0108] In some instances, the disclosed methods for methylation sequencing may be used to predict genetic disorders in fetal DNA. (e.g., for invasive or non-invasive prenatal testing), such as, but not limited to, the methods described in Tsui, D.W.Y. et al., Chimerism, 2010, 1 ( 1) :30-35. For example, sequence read data obtained by sequencing fetal DNA extracted from samples obtained using invasive amniocentesis, chorionic villus sampling (cVS), or fetal umbilical cord sampling techniques, or obtained using non-invasive sampling of cell- free DNA (cfDNA) samples (which comprises a mix of maternal cfDNA and fetal cfDNA), may be processed according to the disclosed methods to identify variants, e.g., copy number alterations, associated with, e.g., Down Syndrome (trisomy 21), trisomy 18, trisomy 13, and extra or missing copies of the X and Y chromosomes.
[0109] In some instances, the disclosed methods for methylation sequencing may be used to select a subject (e.g., a patient) for a clinical trial based on the nucleic acid sequence determined for one or more gene loci. In some instances, patient selection for clinical trials based on, e.g., identification of a methylation signature at one or more gene loci, may accelerate the development of targeted therapies and improve the healthcare outcomes for treatment decisions.
[0110] In some instances, the disclosed methods for methylation sequencing may be used to select an appropriate therapy or treatment (e.g., an anti-cancer therapy or anti-cancer treatment) for a subject. In some instances, for example, the anti-cancer therapy or treatment may comprise use of a poly (ADP-ribose) polymerase inhibitor (PARPi), a platinum compound, chemotherapy, radiation therapy, a targeted therapy, an immunotherapy, a neoantigen-based therapy, surgery, or any combination thereof.
[0111] In some instances, the anti-cancer target therapy or treatment may comprise a targeted anti-cancer therapy or treatment (e.g., a monoclonal antibody-based therapy, an enzyme inhibitor-based therapy, an antibody-drug conjugate therapy, a hormone therapy, and/or a targeted radiotherapy) that targets specific molecules required for cancer cell growth, division, and spreading. In some instances, the targeted anti-cancer therapy or treatment may comprise abemaciclib (Verzenio), abiraterone acetate (Zytiga), acalabrutinib (Calquence), ado-trastuzumab emtansine (Kadcyla), afatinib dimaleate (Gilotrif), alectinib (Alecensa), alemtuzumab (Campath), alitretinoin (Panretin), alpelisib (Piqray), amivantamab-vmjw (Rybrevant), anastrozole (Arimidex), apalutamide (Erleada), asciminib hydrochloride (Scemblix), atezolizumab (Tecentriq), avapritinib (Ayvakit), avelumab (Bavencio), axicabtagene ciloleucel (Yescarta), axitinib (Inlyta), belantamab mafodotin-blmf (Blenrep), belimumab (Benlysta), belinostat (Beleodaq), belzutifan (Welireg), bevacizumab (Avastin), bexarotene (Targretin), binimetinib (Mektovi), blinatumomab (Blincyto), bortezomib (Velcade), bosutinib (Bosulif), brentuximab vedotin (Adcetris), brexucabtagene autoleucel (Tecartus), brigatinib (Alunbrig), cabazitaxel (Jevtana), cabozantinib (Cabometyx), cabozantinib (Cabometyx, Cometriq), canakinumab (Haris), capmatinib hydrochloride (Tabrecta), carfilzomib (Kyprolis), cemiplimab-rwlc (Libtayo), ceritinib (LDK378/Zykadia), cetuximab (Erbitux), cobimetinib (Cotellic), crizotinib (Xalkori), dabrafenib (Tafinlar), dacomitinib (Vizimpro), daratumumab (Darzalex), daratumumab and hyaluronidase-fihj (Darzalex Faspro), darolutamide (Nubeqa), dasatinib (Sprycel), denileukin diftitox (Ontak), denosumab (Xgeva), dinutuximab (Unituxin), dostarlimab-gxly (Jemperli), durvalumab (Imfinzi), duvelisib (Copiktra), elotuzumab (Empliciti), enasidenib mesylate (Idhifa), encorafenib (Braftovi), enfortumab vedotin-ejfv (Padcev), entrectinib (Rozlytrek), enzalutamide (Xtandi), erdafitinib (Balversa), erlotinib (Tarceva), everolimus (Afinitor), exemestane (Aromasin), fam-trastuzumab deruxtecan-nxki (Enhertu), fedratinib hydrochloride (Inrebic), fulvestrant (Faslodex), gefitinib (Iressa), gemtuzumab ozogamicin (Mylotarg), gilteritinib (Xospata), glasdegib maleate (Daurismo), hyaluronidase-zzxf (Phesgo), ibrutinib (Imbruvica), ibritumomab tiuxetan (Zevalin), idecabtagene vicleucel (Abecma), idelalisib (Zydelig), imatinib mesylate (Gleevec), infigratinib phosphate (Truseltiq), inotuzumab ozogamicin (Besponsa), ipilimumab (Yervoy), isatuximab-irfc (Sarclisa), ivosidenib (Tibsovo), ixazomib citrate (Ninlaro), lanreotide acetate (Somatuline Depot), lapatinib (Tykerb), larotrectinib sulfate (Vitrakvi), lenvatinib mesylate (Lenvima), letrozole (Femara), lisocabtagene maraleucel (Breyanzi), loncastuximab tesirine-lpyl (Zynlonta), lorlatinib (Lorbrena), lutetium Lu 177-dotatate (Lutathera), margetuximab-cmkb (Margenza), midostaurin (Rydapt), mobocertinib succinate (Exkivity), mogamulizumab-kpkc (Poteligeo), moxetumomab pasudotox-tdfk (Lumoxiti), naxitamab-gqgk (Danyelza), necitumumab (Portrazza), neratinib maleate (Nerlynx), nilotinib (Tasigna), niraparib tosylate monohydrate (Zejula), nivolumab (Opdivo), obinutuzumab (Gazyva), ofatumumab (Arzerra), olaparib (Lynparza), olaratumab (Lartruvo), osimertinib (Tagrisso), palbociclib (Ibrance), panitumumab (Vectibix), pazopanib (Votrient), pembrolizumab (Keytruda), pemigatinib (Pemazyre), pertuzumab (Perjeta), pexidartinib hydrochloride (Turalio), polatuzumab vedotin-piiq (Polivy), ponatinib hydrochloride (Iclusig), pralatrexate (Folotyn), pralsetinib (Gavreto), radium 223 dichloride (Xofigo), ramucirumab (Cyramza), regorafenib (Stivarga), ribociclib (Kisqali), ripretinib (Qinlock), rituximab (Rituxan), rituximab and hyaluronidase human (Rituxan Hycela), romidepsin (Istodax), rucaparib camsylate (Rubraca), ruxolitinib phosphate (Jakafi), sacituzumab govitecan-hziy (Trodelvy), seliciclib, selinexor (Xpovio), selpercatinib (Retevmo), selumetinib sulfate (Koselugo), siltuximab (Sylvant), sirolimus protein-bound particles (Fyarro), sonidegib (Odomzo), sorafenib (Nexavar), sotorasib (Lumakras), sunitinib (Sutent), tafasitamab-cxix (Monjuvi), tagraxofusp-erzs (Elzonris), talazoparib tosylate (Talzenna), tamoxifen (Nolvadex), tazemetostat hydrobromide (Tazverik), tebentafusp-tebn (Kimmtrak), temsirolimus (Torisel), tepotinib hydrochloride (Tepmetko), tisagenlecleucel (Kymriah), tisotumab vedotin-tftv (Tivdak), tocilizumab (Actemra), tofacitinib (Xeljanz), tositumomab (Bexxar), trametinib (Mekinist), trastuzumab (Herceptin), tretinoin (Vesanoid), tivozanib hydrochloride (Fotivda), toremifene (Fareston), tucatinib (Tukysa), umbralisib tosylate (Ukoniq), vandetanib (Caprelsa), vemurafenib (Zelboraf), venetoclax (Venclexta), vismodegib (Erivedge), vorinostat (Zolinza), zanubrutinib (Brukinsa), ziv-aflibercept (Zaltrap), or any combination thereof.
[0112] In some instances, the anti-cancer therapy or treatment may comprise an immunotherapy (e.g., a cancer treatment that acts by stimulating the immune system to fight cancer). In some instances, the immunotherapy can be, for example, an immune system modulator (e.g., a cytokine, such as an interferon or interleukin), an immune checkpoint inhibitor (such as an anti-PD-1 or anti-PD-Ll antibody), a T-cell transfer therapy (e.g., a tumor infiltrating lymphocyte (TIL) therapy in lymphocytes extracted from a patient’s tumor are selected for their ability to recognize tumor cells and propagated prior to reintroduction into the patient, or a CAR T-cell therapy in which a patient’s T-cells are modified to express the CAR protein prior to reintroduction into the patient), a monoclonal antibody-based therapy (e.g., a monoclonal antibody that binds to cell surface markers on cancer cells to facilitate recognition by the immune system), or a cancer treatment vaccine (e.g., a vaccine based on tumor cells, tumor-associated neoantigens, or dendritic cells, etc., that stimulates the immune system to fight cancer).
[0113] In some instances, the anti-cancer therapy or treatment may comprise a neoantigenbased therapy. Non-limiting examples of neoantigen-based therapies include T-cell receptor (TCR) engineered T-cell (TCR-T) therapies, chimeric antigen receptor T-cell (CAR-T) therapies, TCR bispecific antibody therapies, and cancer vaccines. TCR-T therapies are produced by genetically engineering a patient’s T-cells to express T-cell receptors that are specific to neoantigens of interest, and then infusing them back into the patient. CAR-T therapies are produced by genetically engineering a patient’s T-cells to express chimeric antigen receptor molecules which contain an intracellular signaling and co-signaling domain as well as an extracellular antigen-binding domain; CAR-T therapies don’t always rely on neoantigen presentation, but can be designed to be directed towards neoantigens. TCR bispecific antibody therapies are small, engineered antibody molecules that comprise a neoantigen-specific TCR on one end and a CD3-directed single-chain variable fragment on the other end. Cancer vaccines can include RNA molecules, DNA molecules, peptides, or a combination thereof that are designed to boost the immune system’s ability to find and destroy neoantigen-presenting cells.
[0114] In some instances, the disclosed methods for methylation sequencing may be used in treating a disease (e.g., a cancer) in a subject. For example, in response to determining a methylation signature using any of the methods disclosed herein, an effective amount of an anti-cancer therapy or anti-cancer treatment may be administered to the subject.
[0115] In some instances, the disclosed methods for methylation sequencing may be used for monitoring disease progression or recurrence (e.g., cancer or tumor progression or recurrence) in a subject. For example, in some instances, the methods may be used to determine a methylation signature in a first sample obtained from the subject at a first time point, and used to determine a methylation signature in a second sample obtained from the subject at a second time point, where comparison of the first determination of the methylation signature and the second determination of the methylation signature allows one to monitor disease progression or recurrence. In some instances, the first time point is chosen before the subject has been administered a therapy or treatment, and the second time point is chosen after the subject has been administered the therapy or treatment.
[0116] In some instances, the disclosed methods may be used for adjusting a therapy or treatment (e.g., an anti-cancer treatment or anti-cancer therapy) for a subject, e.g., by adjusting a treatment dose and/or selecting a different treatment in response to a change in the determination of the methylation signature.
[0117] In some instances, the methylation signature determined using the disclosed methods may be used as a prognostic or diagnostic indicator associated with the sample. For example, in some instances, the prognostic or diagnostic indicator may comprise an indicator of the presence of a disease (e.g., cancer) in the sample, an indicator of the probability that a disease (e.g., cancer) is present in the sample, an indicator of the probability that the subject from which the sample was derived will develop a disease (e.g., cancer) (z.e., a risk factor), or an indicator of the likelihood that the subject from which the sample was derived will respond to a particular therapy or treatment. [0118] In some instances, the disclosed methods for methylation sequencing may be implemented as part of a genomic profiling process that comprises identification of the presence of variant sequences at one or more gene loci in a sample derived from a subject as part of detecting, monitoring, predicting a risk factor, or selecting a treatment for a particular disease, e.g., cancer. In some instances, the variant panel selected for genomic profiling may comprise the detection of variant sequences at a selected set of gene loci. In some instances, the variant panel selected for genomic profiling may comprise detection of variant sequences at a number of gene loci through comprehensive genomic profiling (CGP), which is a nextgeneration sequencing (NGS) approach used to assess hundreds of genes (including relevant cancer biomarkers) in a single assay. Inclusion of the disclosed methods for nucleic acid sequencing as part of a genomic profiling process (or inclusion of the output from the disclosed methods for nucleic acid sequencing as part of the genomic profile of the subject) can improve the validity of, e.g., disease detection calls and treatment decisions, made on the basis of the genomic profile by, for example, independently confirming the presence of a methylation signature in a given patient sample.
[0119] In some instances, a genomic profile may comprise information on the presence of genes (or variant sequences thereof), copy number variations, epigenetic traits, proteins (or modifications thereof), and/or other biomarkers in an individual’s genome and/or proteome, as well as information on the individual’s corresponding phenotypic traits and the interaction between genetic or genomic traits, phenotypic traits, and environmental factors.
[0120] In some instances, a genomic profile for the subject may comprise results from a comprehensive genomic profiling (CGP) test, a nucleic acid sequencing-based test, a gene expression profiling test, a cancer hotspot panel test, a DNA methylation test, a DNA fragmentation test, an RNA fragmentation test, or any combination thereof.
[0121] In some instances, the method can further include administering or applying a treatment or therapy e.g., an anti-cancer agent, anti-cancer treatment, or anti-cancer therapy) to the subject based on the generated genomic profile. An anti-cancer agent or anti-cancer treatment may refer to a compound that is effective in the treatment of cancer cells.
Examples of anti-cancer agents or anti-cancer therapies include, but not limited to, alkylating agents, antimetabolites, natural products, hormones, chemotherapy, radiation therapy, immunotherapy, surgery, or a therapy configured to target a defect in a specific cell signaling pathway, e.g., a defect in a DNA mismatch repair (MMR) pathway. Samples
[0122] The disclosed methods and systems may be used with any of a variety of samples (also referred to herein as specimens) comprising nucleic acids (e.g., DNA or RNA) that are collected from a subject (e.g.. a patient). Examples of a sample include, but are not limited to, a tumor sample, a tissue sample, a biopsy sample e.g., a tissue biopsy, a liquid biopsy, or both), a blood sample (e.g., a peripheral whole blood sample), a blood plasma sample, a blood serum sample, a lymph sample, a saliva sample, a sputum sample, a urine sample, a gynecological fluid sample, a circulating tumor cell (CTC) sample, a cerebral spinal fluid (CSF) sample, a pericardial fluid sample, a pleural fluid sample, an ascites (peritoneal fluid) sample, a feces (or stool) sample, or other body fluid, secretion, and/or excretion sample (or cell sample derived therefrom). In certain instances, the sample may be frozen sample or a formalin-fixed paraffin-embedded (FFPE) sample.
[0123] In some instances, the sample may be collected by tissue resection (e.g., surgical resection), needle biopsy, bone marrow biopsy, bone marrow aspiration, skin biopsy, endoscopic biopsy, fine needle aspiration, oral swab, nasal swab, vaginal swab or a cytology smear, scrapings, washings or lavages (such as a ductal lavage or bronchoalveolar lavage), etc.
[0124] In some instances, the sample is a liquid biopsy sample, and may comprise, e.g., whole blood, blood plasma, blood serum, urine, stool, sputum, saliva, or cerebrospinal fluid. In some instances, the sample may be a liquid biopsy sample and may comprise circulating tumor cells (CTCs). In some instances, the sample may be a liquid biopsy sample and may comprise cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), or any combination thereof.
[0125] In some instances, the sample may comprise one or more premalignant or malignant cells. Premalignant, as used herein, refers to a cell or tissue that is not yet malignant but is poised to become malignant. In certain instances, the sample may be acquired from a solid tumor, a soft tissue tumor, or a metastatic lesion. In certain instances, the sample may be acquired from a hematologic malignancy or pre-malignancy. In other instances, the sample may comprise a tissue or cells from a surgical margin. In certain instances, the sample may comprise tumor-infiltrating lymphocytes. In some instances, the sample may comprise one or more non-malignant cells. In some instances, the sample may be, or is part of, a primary tumor or a metastasis (e.g., a metastasis biopsy sample). In some instances, the sample may be obtained from a site (e.g., a tumor site) with the highest percentage of tumor (e.g., tumor cells) as compared to adjacent sites (e.g., sites adjacent to the tumor). In some instances, the sample may be obtained from a site (e.g., a tumor site) with the largest tumor focus (e.g., the largest number of tumor cells as visualized under a microscope) as compared to adjacent sites (e.g., sites adjacent to the tumor).
[0126] In some instances, the disclosed methods may further comprise analyzing a primary control (e.g., a normal tissue sample). In some instances, the disclosed methods may further comprise determining if a primary control is available and, if so, isolating a control nucleic acid (e.g., DNA) from said primary control. In some instances, the sample may comprise any normal control (e.g., a normal adjacent tissue (NAT)) if no primary control is available. In some instances, the sample may be or may comprise histologically normal tissue. In some instances, the method includes evaluating a sample, e.g., a histologically normal sample (e.g., from a surgical tissue margin) using the methods described herein. In some instances, the disclosed methods may further comprise acquiring a sub-sample enriched for non-tumor cells, e.g., by macro-dissecting non-tumor tissue from said NAT in a sample not accompanied by a primary control. In some instances, the disclosed methods may further comprise determining that no primary control and no NAT is available, and marking said sample for analysis without a matched control.
[0127] In some instances, samples obtained from histologically normal tissues (e.g., otherwise histologically normal surgical tissue margins) may still comprise a genetic alteration such as a variant sequence as described herein. The methods may thus further comprise re-classifying a sample based on the presence of the detected genetic alteration. In some instances, multiple samples (e.g., from different subjects) are processed simultaneously.
[0128] The disclosed methods and systems may be applied to the analysis of nucleic acids extracted from any of variety of tissue samples (or disease states thereof), e.g., solid tissue samples, soft tissue samples, metastatic lesions, or liquid biopsy samples. Examples of tissues include, but are not limited to, connective tissue, muscle tissue, nervous tissue, epithelial tissue, and blood. Tissue samples may be collected from any of the organs within an animal or human body. Examples of human organs include, but are not limited to, the brain, heart, lungs, liver, kidneys, pancreas, spleen, thyroid, mammary glands, uterus, prostate, large intestine, small intestine, bladder, bone, skin, etc. [0129] In some instances, the nucleic acids extracted from the sample may comprise deoxyribonucleic acid (DNA) molecules. Examples of DNA that may be suitable for analysis by the disclosed methods include, but are not limited to, genomic DNA or fragments thereof, mitochondrial DNA or fragments thereof, cell-free DNA (cfDNA), and circulating tumor DNA (ctDNA). Cell-free DNA (cfDNA) is comprised of fragments of DNA that are released from normal and/or cancerous cells during apoptosis and necrosis, and circulate in the blood stream and/or accumulate in other bodily fluids. Circulating tumor DNA (ctDNA) is comprised of fragments of DNA that are released from cancerous cells and tumors that circulate in the blood stream and/or accumulate in other bodily fluids.
[0130] In some instances, DNA is extracted from nucleated cells from the sample. In some instances, a sample may have a low nucleated cellularity, e.g., when the sample is comprised mainly of erythrocytes, lesional cells that contain excessive cytoplasm, or tissue with fibrosis. In some instances, a sample with low nucleated cellularity may require more, e.g., greater, tissue volume for DNA extraction.
[0131] In some instances, the nucleic acids extracted from the sample may comprise ribonucleic acid (RNA) molecules. Examples of RNA that may be suitable for analysis by the disclosed methods include, but are not limited to, total cellular RNA, total cellular RNA after depletion of certain abundant RNA sequences (e.g., ribosomal RNAs), cell-free RNA (cfRNA), messenger RNA (mRNA) or fragments thereof, the poly(A)-tailed mRNA fraction of the total RNA, ribosomal RNA (rRNA) or fragments thereof, transfer RNA (tRNA) or fragments thereof, and mitochondrial RNA or fragments thereof. In some instances, RNA may be extracted from the sample and converted to complementary DNA (cDNA) using, e.g., a reverse transcription reaction. In some instances, the cDNA is produced by random-primed cDNA synthesis methods. In other instances, the cDNA synthesis is initiated at the poly (A) tail of mature mRNAs by priming with oligo(dT)-containing oligonucleotides. Methods for depletion, poly(A) enrichment, and cDNA synthesis are well known to those of skill in the art.
[0132] In some instances, the sample may comprise a tumor content (e.g., comprising tumor cells or tumor cell nuclei), or a non-tumor content (e.g., immune cells, fibroblasts, and other non-tumor cells). In some instances, the tumor content of the sample may constitute a sample metric. In some instances, the sample may comprise a tumor content of at least 5-50%, 10- 40%, 15-25%, or 20-30% tumor cell nuclei. In some instances, the sample may comprise a tumor content of at least 5%, at least 10%, at least 20%, at least 30%, at least 40%, or at least 50% tumor cell nuclei. In some instances, the percent tumor cell nuclei (e.g., sample fraction) is determined (e.g., calculated) by dividing the number of tumor cells in the sample by the total number of all cells within the sample that have nuclei. In some instances, for example when the sample is a liver sample comprising hepatocytes, a different tumor content calculation may be required due to the presence of hepatocytes having nuclei with twice, or more than twice, the DNA content of other, e.g., non-hepatocyte, somatic cell nuclei. In some instances, the sensitivity of detection of a genetic alteration, e.g., a variant sequence, or a determination of, e.g., micro satellite instability, may depend on the tumor content of the sample. For example, a sample having a lower tumor content can result in lower sensitivity of detection for a given size sample.
[0133] In some instances, as noted above, the sample comprises nucleic acid (e.g., DNA, RNA (or a cDNA derived from the RNA), or both), e.g., from a tumor or from normal tissue. In certain instances, the sample may further comprise a non-nucleic acid component, e.g., cells, protein, carbohydrate, or lipid, e.g., from the tumor or normal tissue.
Subjects
[0134] In some instances, the sample is obtained (e.g., collected) from a subject (e.g., patient) with a condition or disease (e.g., a hyperproliferative disease or a non-cancer indication) or suspected of having the condition or disease. In some instances, the hyperproliferative disease is a cancer. In some instances, the cancer is a solid tumor or a metastatic form thereof. In some instances, the cancer is a hematological cancer, e.g., a leukemia or lymphoma.
[0135] In some instances, the subject has a cancer or is at risk of having a cancer. For example, in some instances, the subject has a genetic predisposition to a cancer (e.g., having a genetic mutation that increases his or her baseline risk for developing a cancer). In some instances, the subject has been exposed to an environmental perturbation (e.g., radiation or a chemical) that increases his or her risk for developing a cancer. In some instances, the subject is in need of being monitored for development of a cancer. In some instances, the subject is in need of being monitored for cancer progression or regression, e.g., after being treated with an anti-cancer therapy (or anti-cancer treatment). In some instances, the subject is in need of being monitored for relapse of cancer. In some instances, the subject is in need of being monitored for minimum residual disease (MRD). In some instances, the subject has been, or is being treated, for cancer. In some instances, the subject has not been treated with an anti-cancer therapy (or anti-cancer treatment).
[0136] In some instances, the subject (e.g., a patient) is being treated, or has been previously treated, with one or more targeted therapies. In some instances, e.g., for a patient who has been previously treated with a targeted therapy, a post-targeted therapy sample (e.g., specimen) is obtained (e.g., collected). In some instances, the post-targeted therapy sample is a sample obtained after the completion of the targeted therapy.
[0137] In some instances, the patient has not been previously treated with a targeted therapy. In some instances, e.g., for a patient who has not been previously treated with a targeted therapy, the sample comprises a resection, e.g., an original resection, or a resection following recurrence (e.g., following a disease recurrence post- therapy).
Cancers
[0138] In some instances, the sample is acquired from a subject having a cancer. Exemplary cancers include, but are not limited to, B cell cancer (e.g., multiple myeloma), melanomas, breast cancer, lung cancer (such as non-small cell lung carcinoma or NSCLC), bronchus cancer, colorectal cancer, prostate cancer, pancreatic cancer, stomach cancer, ovarian cancer, urinary bladder cancer, brain or central nervous system cancer, peripheral nervous system cancer, esophageal cancer, cervical cancer, uterine or endometrial cancer, cancer of the oral cavity or pharynx, liver cancer, kidney cancer, testicular cancer, biliary tract cancer, small bowel or appendix cancer, salivary gland cancer, thyroid gland cancer, adrenal gland cancer, osteosarcoma, chondrosarcoma, cancer of hematological tissues, adenocarcinomas, inflammatory myofibroblastic tumors, gastrointestinal stromal tumor (GIST), colon cancer, multiple myeloma (MM), myelodysplastic syndrome (MDS), myeloproliferative disorder (MPD), acute lymphocytic leukemia (ALL), acute myelocytic leukemia (AML), chronic myelocytic leukemia (CML), chronic lymphocytic leukemia (CLL), polycythemia Vera, Hodgkin lymphoma, non-Hodgkin lymphoma (NHL), soft-tissue sarcoma, fibrosarcoma, myxosarcoma, liposarcoma, osteogenic sarcoma, chordoma, angiosarcoma, endotheliosarcoma, lymphangiosarcoma, lymphangioendotheliosarcoma, synovioma, mesothelioma, Ewing's tumor, leiomyosarcoma, rhabdomyosarcoma, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary carcinoma, papillary adenocarcinomas, medullary carcinoma, bronchogenic carcinoma, renal cell carcinoma, hepatoma, bile duct carcinoma, choriocarcinoma, seminoma, embryonal carcinoma, Wilms' tumor, bladder carcinoma, epithelial carcinoma, glioma, astrocytoma, medulloblastoma, craniopharyngioma, ependymoma, pinealoma, hemangioblastoma, acoustic neuroma, oligodendroglioma, meningioma, neuroblastoma, retinoblastoma, follicular lymphoma, diffuse large B-cell lymphoma, mantle cell lymphoma, hepatocellular carcinoma, thyroid cancer, gastric cancer, head and neck cancer, small cell cancers, essential thrombocythemia, agnogenic myeloid metaplasia, hypereosinophilic syndrome, systemic mastocytosis, familiar hypereosinophilia, chronic eosinophilic leukemia, neuroendocrine cancers, carcinoid tumors, and the like.
[0139] In some instances, the cancer comprises acute lymphoblastic leukemia (Philadelphia chromosome positive), acute lymphoblastic leukemia (precursor B-cell), acute myeloid leukemia (FLT3+), acute myeloid leukemia (with an IDH2 mutation), anaplastic large cell lymphoma, basal cell carcinoma, B-cell chronic lymphocytic leukemia, bladder cancer, breast cancer (HER2 overexpressed/amplified), breast cancer (HER2+), breast cancer (HR+, HER2- ), cervical cancer, cholangiocarcinoma, chronic lymphocytic leukemia, chronic lymphocytic leukemia (with 17p deletion), chronic myelogenous leukemia, chronic myelogenous leukemia (Philadelphia chromosome positive), classical Hodgkin lymphoma, colorectal cancer, colorectal cancer (dMMR and MSI-H), colorectal cancer (KRAS wild type), cryopyrin- associated periodic syndrome, a cutaneous T-cell lymphoma, dermatofibrosarcoma protuberans, a diffuse large B-cell lymphoma, fallopian tube cancer, a follicular B-cell nonHodgkin lymphoma, a follicular lymphoma, gastric cancer, gastric cancer (HER2+), a gastroesophageal junction (GEJ) adenocarcinoma, a gastrointestinal stromal tumor, a gastrointestinal stromal tumor (KIT+), a giant cell tumor of the bone, a glioblastoma, granulomatosis with polyangiitis, a head and neck squamous cell carcinoma, a hepatocellular carcinoma, Hodgkin lymphoma, juvenile idiopathic arthritis, lupus erythematosus, a mantle cell lymphoma, medullary thyroid cancer, melanoma, a melanoma with a BRAF V600 mutation, a melanoma with a BRAF V600E or V600K mutation, Merkel cell carcinoma, multicentric Castleman's disease, multiple hematologic malignancies including Philadelphia chromosome-positive ALL and CML, multiple myeloma, myelofibrosis, a non-Hodgkin’s lymphoma, a nonresectable subependymal giant cell astrocytoma associated with tuberous sclerosis, a non-small cell lung cancer, a non-small cell lung cancer (ALK+), a non-small cell lung cancer (PD-L1+), a non-small cell lung cancer (with ALK fusion or ROS1 gene alteration), a non-small cell lung cancer (with BRAF V600E mutation), a non-small cell lung cancer (with an EGFR exon 19 deletion or exon 21 substitution (L858R) mutations), a non- small cell lung cancer (with an EGFR T790M mutation), ovarian cancer, ovarian cancer (with a BRCA mutation), pancreatic cancer, a pancreatic, gastrointestinal, or lung origin neuroendocrine tumor, a pediatric neuroblastoma, a peripheral T-cell lymphoma, peritoneal cancer, prostate cancer, a renal cell carcinoma, rheumatoid arthritis, a small lymphocytic lymphoma, a soft tissue sarcoma, a solid tumor (MSI-H/dMMR), a squamous cell cancer of the head and neck, a squamous non-small cell lung cancer, thyroid cancer, a thyroid carcinoma, urothelial cancer, a urothelial carcinoma, or Waldenstrom's macroglobulinemia.
[0140] In some instances, the cancer is a hematologic malignancy (or premaligancy). As used herein, a hematologic malignancy refers to a tumor of the hematopoietic or lymphoid tissues, e.g., a tumor that affects blood, bone marrow, or lymph nodes. Exemplary hematologic malignancies include, but are not limited to, leukemia (e.g., acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), chronic myelogenous leukemia (CML), hairy cell leukemia, acute monocytic leukemia (AMoL), chronic myelomonocytic leukemia (CMML), juvenile myelomonocytic leukemia (JMML), or large granular lymphocytic leukemia), lymphoma (e.g., AIDS-related lymphoma, cutaneous T-cell lymphoma, Hodgkin lymphoma (e.g., classical Hodgkin lymphoma or nodular lymphocyte-predominant Hodgkin lymphoma), mycosis fungoides, non-Hodgkin lymphoma (e.g., B-cell non-Hodgkin lymphoma (e.g., Burkitt lymphoma, small lymphocytic lymphoma (CLL/SLL), diffuse large B-cell lymphoma, follicular lymphoma, immunoblastic large cell lymphoma, precursor B -lymphoblastic lymphoma, or mantle cell lymphoma) or T-cell non- Hodgkin lymphoma (mycosis fungoides, anaplastic large cell lymphoma, or precursor T- lymphoblastic lymphoma)), primary central nervous system lymphoma, Sezary syndrome, Waldenstrom macroglobulinemia), chronic myeloproliferative neoplasm, Langerhans cell histiocytosis, multiple myeloma/plasma cell neoplasm, myelodysplastic syndrome, or myelodysplastic/myeloproliferative neoplasm.
Nucleic acid extraction and processing
[0141] DNA or RNA may be extracted from tissue samples, biopsy samples, blood samples, or other bodily fluid samples using any of a variety of techniques known to those of skill in the art (see, e.g., Example 1 of International Patent Application Publication No. WO 2012/092426; Tan, et al. (2009), “DNA, RNA, and Protein Extraction: The Past and The Present”, J. Biomed. Biotech. 2009:574398; the technical literature for the Maxwell® 16 LEV Blood DNA Kit (Promega Corporation, Madison, WI); and the Maxwell 16 Buccal Swab LEV DNA Purification Kit Technical Manual (Promega Literature #TM333, January 1, 2011, Promega Corporation, Madison, WI)). Protocols for RNA isolation are disclosed in, e.g., the Maxwell® 16 Total RNA Purification Kit Technical Bulletin (Promega Literature #TB351, August 2009, Promega Corporation, Madison, WI).
[0142] A typical DNA extraction procedure, for example, comprises (i) collection of the fluid sample, cell sample, or tissue sample from which DNA is to be extracted, (ii) disruption of cell membranes (z.e., cell lysis), if necessary, to release DNA and other cytoplasmic components, (iii) treatment of the fluid sample or lysed sample with a concentrated salt solution to precipitate proteins, lipids, and RNA, followed by centrifugation to separate out the precipitated proteins, lipids, and RNA, and (iv) purification of DNA from the supernatant to remove detergents, proteins, salts, or other reagents used during the cell membrane lysis step.
[0143] Disruption of cell membranes may be performed using a variety of mechanical shear (e.g., by passing through a Erench press or fine needle) or ultrasonic disruption techniques. The cell lysis step often comprises the use of detergents and surfactants to solubilize lipids the cellular and nuclear membranes. In some instances, the lysis step may further comprise use of proteases to break down protein, and/or the use of an RNase for digestion of RNA in the sample.
[0144] Examples of suitable techniques for DNA purification include, but are not limited to,
(i) precipitation in ice-cold ethanol or isopropanol, followed by centrifugation (precipitation of DNA may be enhanced by increasing ionic strength, e.g., by addition of sodium acetate),
(ii) phenol-chloroform extraction, followed by centrifugation to separate the aqueous phase containing the nucleic acid from the organic phase containing denatured protein, and (iii) solid phase chromatography where the nucleic acids adsorb to the solid phase (e.g., silica or other) depending on the pH and salt concentration of the buffer.
[0145] In some instances, cellular and histone proteins bound to the DNA may be removed either by adding a protease or by having precipitated the proteins with sodium or ammonium acetate, or through extraction with a phenol-chloroform mixture prior to a DNA precipitation step.
[0146] In some instances, DNA may be extracted using any of a variety of suitable commercial DNA extraction and purification kits. Examples include, but are not limited to, the QIAamp (for isolation of genomic DNA from human samples) and DNAeasy (for isolation of genomic DNA from animal or plant samples) kits from Qiagen (Germantown, MD) or the Maxwell® and ReliaPrep™ series of kits from Promega (Madison, WI).
[0147] As noted above, in some instances the sample may comprise a formalin-fixed (also known as formaldehyde-fixed, or paraformaldehyde-fixed), paraffin-embedded (FFPE) tissue preparation. For example, the FFPE sample may be a tissue sample embedded in a matrix, e.g., an FFPE block. Methods to isolate nucleic acids (e.g., DNA) from formaldehyde- or paraformaldehyde-fixed, paraffin-embedded (FFPE) tissues are disclosed in, e.g., Cronin, et al., (2004) Am J Pathol. 164(l):35-42; Masuda, et al., (1999) Nucleic Acids Res.
27(22): 4436-4443; Specht, et al., (2001) Am J Pathol. 158(2):419-429; the Ambion RecoverAll™ Total Nucleic Acid Isolation Protocol (Ambion, Cat. No. AM1975, September 2008); the Maxwell® 16 FFPE Plus LEV DNA Purification Kit Technical Manual (Promega Literature #TM349, February 2011); the E.Z.N.A.® FFPE DNA Kit Handbook (OMEGA bio- tek, Norcross, GA, product numbers D3399-00, D3399-01, and D3399-02, June 2009); and the QIAamp® DNA FFPE Tissue Handbook (Qiagen, Cat. No. 37625, October 2007). For example, the RecoverAll™ Total Nucleic Acid Isolation Kit uses xylene at elevated temperatures to solubilize paraffin-embedded samples and a glass-fiber filter to capture nucleic acids. The Maxwell® 16 FFPE Plus LEV DNA Purification Kit is used with the Maxwell® 16 Instrument for purification of genomic DNA from 1 to 10 pm sections of FFPE tissue. DNA is purified using silica-clad paramagnetic particles (PMPs), and eluted in low elution volume. The E.Z.N.A.® FFPE DNA Kit uses a spin column and buffer system for isolation of genomic DNA. QIAamp® DNA FFPE Tissue Kit uses QIAamp® DNA Micro technology for purification of genomic and mitochondrial DNA.
[0148] In some instances, the disclosed methods may further comprise determining or acquiring a yield value for the nucleic acid extracted from the sample and comparing the determined value to a reference value. For example, if the determined or acquired value is less than the reference value, the nucleic acids may be amplified prior to proceeding with library construction. In some instances, the disclosed methods may further comprise determining or acquiring a value for the size (or average size) of nucleic acid fragments in the sample, and comparing the determined or acquired value to a reference value, e.g., a size (or average size) of at least 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 base pairs (bps). In some instances, one or more parameters described herein may be adjusted or selected in response to this determination. [0149] After isolation, the nucleic acids are typically dissolved in a slightly alkaline buffer, e.g., Tris-EDTA (TE) buffer, or in ultra-pure water. In some instances, the isolated nucleic acids (e.g., genomic DNA) may be fragmented or sheared by using any of a variety of techniques known to those of skill in the art. For example, genomic DNA can be fragmented by physical shearing methods, enzymatic cleavage methods, chemical cleavage methods, and other methods known to those of skill in the art. Methods for DNA shearing are described in Example 4 in International Patent Application Publication No. WO 2012/092426. In some instances, alternatives to DNA shearing methods can be used to avoid a ligation step during library preparation.
Library preparation
[0150] In some instances, the nucleic acids isolated from the sample may be used to construct a library (e.g., a nucleic acid library as described herein). In some instances, the nucleic acids are fragmented using any of the methods described above, optionally subjected to repair of chain end damage, and optionally ligated to synthetic adapters, primers, and/or barcodes (e.g., amplification primers, sequencing adapters, flow cell adapters, substrate adapters, sample barcodes or indexes, and/or unique molecular identifier sequences), size-selected (e.g., by preparative gel electrophoresis), and/or amplified (e.g., using PCR, a non-PCR amplification technique, or an isothermal amplification technique). In some instances, the fragmented and adapter-ligated group of nucleic acids is used without explicit size selection or amplification prior to hybridization-based selection of target sequences. In some instances, the nucleic acid is amplified by any of a variety of specific or non-specific nucleic acid amplification methods known to those of skill in the art. In some instances, the nucleic acids are amplified, e.g., by a whole-genome amplification method such as random-primed strand-displacement amplification. Examples of nucleic acid library preparation techniques for next-generation sequencing are described in, e.g., van Dijk, et al. (2014), Exp. Cell Research 322:12 - 20, and Illumina’s genomic DNA sample preparation kit.
[0151] In some instances, the resulting nucleic acid library may contain all or substantially all of the complexity of the genome. The term “substantially all” in this context refers to the possibility that there can in practice be some unwanted loss of genome complexity during the initial steps of the procedure. The methods described herein also are useful in cases where the nucleic acid library comprises a portion of the genome, e.g., where the complexity of the genome is reduced by design. In some instances, any selected portion of the genome can be used with a method described herein. For example, in certain embodiments, the entire exome or a subset thereof is isolated. In some instances, the library may include at least 95%, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, 10%, or 5% of the genomic DNA. In some instances, the library may consist of cDNA copies of genomic DNA that includes copies of at least 95%, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, 10%, or 5% of the genomic DNA. In certain instances, the amount of nucleic acid used to generate the nucleic acid library may be less than 5 micrograms, less than 1 microgram, less than 500 ng, less than 200 ng, less than 100 ng, less than 50 ng, less than 10 ng, less than 5 ng, or less than 1 ng.
[0152] In some instances, a library (e.g., a nucleic acid library) includes a collection of nucleic acid molecules. As described herein, the nucleic acid molecules of the library can include a target nucleic acid molecule (e.g., a tumor nucleic acid molecule, a reference nucleic acid molecule and/or a control nucleic acid molecule; also referred to herein as a first, second and/or third nucleic acid molecule, respectively). The nucleic acid molecules of the library can be from a single subject or individual. In some instances, a library can comprise nucleic acid molecules derived from more than one subject (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30 or more subjects). For example, two or more libraries from different subjects can be combined to form a library having nucleic acid molecules from more than one subject (where the nucleic acid molecules derived from each subject are optionally ligated to a unique sample barcode corresponding to a specific subject). In some instances, the subject is a human having, or at risk of having, a cancer or tumor.
[0153] In some instances, the library (or a portion thereof) may comprise one or more subgenomic intervals. In some instances, a subgenomic interval can be a single nucleotide position, e.g., a nucleotide position for which a variant at the position is associated (positively or negatively) with a tumor phenotype. In some instances, a subgenomic interval comprises more than one nucleotide position. Such instances include sequences of at least 2, 5, 10, 50, 100, 150, 250, or more than 250 nucleotide positions in length. Subgenomic intervals can comprise, e.g., one or more entire genes (or portions thereof), one or more exons or coding sequences (or portions thereof), one or more introns (or portion thereof), one or more micro satellite region (or portions thereof), or any combination thereof. A subgenomic interval can comprise all or a part of a fragment of a naturally occurring nucleic acid molecule, e.g., a genomic DNA molecule. For example, a subgenomic interval can correspond to a fragment of genomic DNA which is subjected to a sequencing reaction. In some instances, a subgenomic interval is a continuous sequence from a genomic source. In some instances, a subgenomic interval includes sequences that are not contiguous in the genome, e.g., subgenomic intervals in cDNA can include exon-exon junctions formed as a result of splicing. In some instances, the subgenomic interval comprises a tumor nucleic acid molecule. In some instances, the subgenomic interval comprises a non-tumor nucleic acid molecule.
Targeting gene loci for analysis
[0154] The methods described herein can be used in combination with, or as part of, a method for evaluating a plurality or set of subject intervals (e.g., target sequences), e.g., from a set of genomic loci (e.g., gene loci or fragments thereof), as described herein.
[0155] In some instances, the set of genomic loci evaluated by the disclosed methods comprises a plurality of, e.g., genes, which in mutant form, are associated with an effect on cell division, growth or survival, or are associated with a cancer, e.g., a cancer described herein.
[0156] In some instances, the set of gene loci evaluated by the disclosed methods comprises 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, at least 10, at least 20, at least 30, at least 40, at least 50, at least 60, at least 70, at least 80, at least 90, at least 100, or more than 100 gene loci.
[0157] In some instances, the selected gene loci (also referred to herein as target gene loci or target sequences), or fragments thereof, may include subject intervals comprising non-coding sequences, coding sequences, intragenic regions, or intergenic regions of the subject genome. For example, the subject intervals can include a non-coding sequence or fragment thereof (e.g., a promoter sequence, enhancer sequence, 5’ untranslated region (5’ UTR), 3’ untranslated region (3’ UTR), or a fragment thereof), a coding sequence of fragment thereof, an exon sequence or fragment thereof, an intron sequence or a fragment thereof.
Target capture reagents
[0158] The methods described herein may comprise contacting a nucleic acid library with a plurality of target capture reagents in order to select and capture a plurality of specific target sequences (e.g., gene sequences or fragments thereof) for analysis. In some instances, a target capture reagent (i.e., a molecule which can bind to and thereby allow capture of a target molecule) is used to select the subject intervals to be analyzed. For example, a target capture reagent can be a bait molecule, e.g., a nucleic acid molecule (e.g., a DNA molecule or RNA molecule) which can hybridize to (z.e., is complementary to) a target molecule, and thereby allows capture of the target nucleic acid. In some instances, the target capture reagent, e.g., a bait molecule (or bait sequence), is a capture oligonucleotide (or capture probe). In some instances, the target nucleic acid is a genomic DNA molecule, an RNA molecule, a cDNA molecule derived from an RNA molecule, a micro satellite DNA sequence, and the like. In some instances, the target capture reagent is suitable for solution-phase hybridization to the target. In some instances, the target capture reagent is suitable for solidphase hybridization to the target. In some instances, the target capture reagent is suitable for both solution-phase and solid-phase hybridization to the target. The design and construction of target capture reagents is described in more detail in, e.g., International Patent Application Publication No. WO 2020/236941, the entire content of which is incorporated herein by reference.
[0159] The methods described herein provide for optimized sequencing of a large number of genomic loci (e.g., genes or gene products (e.g., mRNA), micro satellite loci, etc.) from samples (e.g., cancerous tissue specimens, liquid biopsy samples, and the like) from one or more subjects by the appropriate selection of target capture reagents to select the target nucleic acid molecules to be sequenced. In some instances, a target capture reagent may hybridize to a specific target locus, e.g., a specific target gene locus or fragment thereof. In some instances, a target capture reagent may hybridize to a specific group of target loci, e.g., a specific group of gene loci or fragments thereof. In some instances, a plurality of target capture reagents comprising a mix of target- specific and/or group- specific target capture reagents may be used.
[0160] In some instances, the number of target capture reagents (e.g., bait molecules) in the plurality of target capture reagents (e.g., a bait set) contacted with a nucleic acid library to capture a plurality of target sequences for nucleic acid sequencing is greater than 10, greater than 50, greater than 100, greater than 200, greater than 300, greater than 400, greater than 500, greater than 600, greater than 700, greater than 800, greater than 900, greater than 1,000, greater than 1,250, greater than 1,500, greater than 1,750, greater than 2,000, greater than 3,000, greater than 4,000, greater than 5,000, greater than 10,000, greater than 25,000, or greater than 50,000.
[0161] In some instances, the overall length of the target capture reagent sequence can be between about 70 nucleotides and 1000 nucleotides. In one instance, the target capture reagent length is between about 100 and 300 nucleotides, 110 and 200 nucleotides, or 120 and 170 nucleotides, in length. In addition to those mentioned above, intermediate oligonucleotide lengths of about 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 300, 400, 500, 600, 700, 800, and 900 nucleotides in length can be used in the methods described herein. In some embodiments, oligonucleotides of about 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, or 230 bases can be used.
[0162] In some instances, each target capture reagent sequence can include: (i) a targetspecific capture sequence (e.g., a gene locus or micro satellite locus-specific complementary sequence), (ii) an adapter, primer, barcode, and/or unique molecular identifier sequence, and (iii) universal tails on one or both ends. As used herein, the term "target capture reagent" can refer to the target- specific target capture sequence or to the entire target capture reagent oligonucleotide including the target- specific target capture sequence.
[0163] In some instances, the target- specific capture sequences in the target capture reagents are between about 40 nucleotides and 1000 nucleotides in length. In some instances, the target- specific capture sequence is between about 70 nucleotides and 300 nucleotides in length. In some instances, the target- specific sequence is between about 100 nucleotides and 200 nucleotides in length. In yet other instances, the target- specific sequence is between about 120 nucleotides and 170 nucleotides in length, typically 120 nucleotides in length. Intermediate lengths in addition to those mentioned above also can be used in the methods described herein, such as target- specific sequences of about 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 300, 400, 500, 600, 700, 800, and 900 nucleotides in length, as well as target- specific sequences of lengths between the above-mentioned lengths.
[0164] In some instances, the target capture reagent may be designed to select a subject interval containing one or more rearrangements, e.g., an intron containing a genomic rearrangement. In such instances, the target capture reagent is designed such that repetitive sequences are masked to increase the selection efficiency. In those instances where the rearrangement has a known juncture sequence, complementary target capture reagents can be designed to recognize the juncture sequence to increase the selection efficiency.
[0165] In some instances, the disclosed methods may comprise the use of target capture reagents designed to capture two or more different target categories, each category having a different target capture reagent design strategy. In some instances, the hybridization-based capture methods and target capture reagent compositions disclosed herein may provide for the capture and homogeneous coverage of a set of target sequences, while minimizing coverage of genomic sequences outside of the targeted set of sequences. In some instances, the target sequences may include the entire exome of genomic DNA or a selected subset thereof. In some instances, the target sequences may include, e.g., a large chromosomal region (e.g., a whole chromosome arm). The methods and compositions disclosed herein provide different target capture reagents for achieving different sequencing depths and patterns of coverage for complex sets of target nucleic acid sequences.
[0166] Typically, DNA molecules are used as target capture reagent sequences, although RNA molecules can also be used. In some instances, a DNA molecule target capture reagent can be single stranded DNA (ssDNA) or double-stranded DNA (dsDNA). In some instances, an RNA-DNA duplex is more stable than a DNA-DNA duplex and therefore provides for potentially better capture of nucleic acids.
[0167] In some instances, the disclosed methods comprise providing a selected set of nucleic acid molecules (e.g., a library catch) captured from one or more nucleic acid libraries. For example, the method may comprise: providing one or a plurality of nucleic acid libraries, each comprising a plurality of nucleic acid molecules (e.g., a plurality of target nucleic acid molecules and/or reference nucleic acid molecules) extracted from one or more samples from one or more subjects; contacting the one or a plurality of libraries (e.g., in a solution-based hybridization reaction) with one, two, three, four, five, or more than five pluralities of target capture reagents (e.g., oligonucleotide target capture reagents) to form a hybridization mixture comprising a plurality of target capture reagent/nucleic acid molecule hybrids; separating the plurality of target capture reagent/nucleic acid molecule hybrids from said hybridization mixture, e.g., by contacting said hybridization mixture with a binding entity that allows for separation of said plurality of target capture reagent/nucleic acid molecule hybrids from the hybridization mixture, thereby providing a library catch (e.g., a selected or enriched subgroup of nucleic acid molecules from the one or a plurality of libraries).
[0168] In some instances, the disclosed methods may further comprise amplifying the library catch (e.g., by performing PCR). In other instances, the library catch is not amplified.
[0169] In some instances, the target capture reagents can be part of a kit which can optionally comprise instructions, standards, buffers or enzymes or other reagents. Hybridization conditions
[0170] As noted above, the methods disclosed herein may include the step of contacting the library (e.g., the nucleic acid library) with a plurality of target capture reagents to provide a selected library target nucleic acid sequences (z.e., the library catch). The contacting step can be effected in, e.g., solution-based hybridization. In some instances, the method includes repeating the hybridization step for one or more additional rounds of solution-based hybridization. In some instances, the method further includes subjecting the library catch to one or more additional rounds of solution-based hybridization with the same or a different collection of target capture reagents.
[0171] In some instances, the contacting step is effected using a solid support, e.g., an array. Suitable solid supports for hybridization are described in, e.g., Albert, T.J. et al. (2007) Nat. Methods 4(1 l):903-5; Hodges, E. et al. (2007) Nat. Genet. 39(12): 1522-7; and Okou, D.T. et al. (2007) Nat. Methods 4(11):907-9, the contents of which are incorporated herein by reference in their entireties.
[0172] Hybridization methods that can be adapted for use in the methods herein are described in the art, e.g., as described in International Patent Application Publication No. WO 2012/092426. Methods for hybridizing target capture reagents to a plurality of target nucleic acids are described in more detail in, e.g., International Patent Application Publication No. WO 2020/236941, the entire content of which is incorporated herein by reference.
Sequencing methods
[0173] The methods and systems disclosed herein can be used in combination with, or as part of, a method or system for sequencing nucleic acids (e.g., a next-generation sequencing system) to generate a plurality of sequence reads that overlap one or more gene loci within a subgenomic interval in the sample and thereby determine, e.g., gene allele sequences at a plurality of gene loci. “Next-generation sequencing” (or “NGS”) as used herein may also be referred to as “massively parallel sequencing” (or “MPS”), and refers to any sequencing method that determines the nucleotide sequence of either individual nucleic acid molecules (e.g., as in single molecule sequencing) or clonally expanded proxies for individual nucleic acid molecules in a high throughput fashion (e.g., wherein greater than 103, 104, 105 or more than 105 molecules are sequenced simultaneously). [0174] Next-generation sequencing methods are known in the art, and are described in, e.g., Metzker, M. (2010) Nature Biotechnology Reviews 11:31-46, which is incorporated herein by reference. Other examples of sequencing methods suitable for use when implementing the methods and systems disclosed herein are described in, e.g., International Patent Application Publication No. WO 2012/092426. In some instances, the sequencing may comprise, for example, whole genome sequencing (WGS), whole exome sequencing, targeted sequencing, or direct sequencing. In some instances, sequencing may be performed using, e.g., Sanger sequencing. In some instances, the sequencing may comprise a paired-end sequencing technique that allows both ends of a fragment to be sequenced and generates high-quality, alignable sequence data for detection of, e.g., genomic rearrangements, repetitive sequence elements, gene fusions, and novel transcripts.
[0175] The disclosed methods and systems may be implemented using sequencing platforms such as the Roche/454 Genome Sequencer (GS) FLX System, Illumina/Solexa Genome Analyzer (GA), Illumina’s HiSeq® 2500, HiSeq® 3000, HiSeq® 4000 and NovaSeq® 6000 Sequencing Systems, Life/APG’s Support Oligonucleotide Ligation Detection (SOLiD) system, Polonator’s G.007 system, Helicos BioSciences’ HeliScope Gene Sequencing system, or Pacific Biosciences’ PacBio® RS platform. In some instances, sequencing may comprise Illumina MiSeq™ sequencing. In some instances, sequencing may comprise Illumina HiSeq® sequencing. In some instances, sequencing may comprise Illumina NovaSeq® sequencing. Optimized methods for sequencing a large number of target genomic loci in nucleic acids extracted from a sample are described in more detail in, e.g., International Patent Application Publication No. WO 2020/236941, the entire content of which is incorporated herein by reference.
[0176] In certain instances, the disclosed methods comprise one or more of the steps of: (a) acquiring a library comprising a plurality of normal and/or tumor nucleic acid molecules from a sample; (b) simultaneously or sequentially contacting the library with one, two, three, four, five, or more than five pluralities of target capture reagents under conditions that allow hybridization of the target capture reagents to the target nucleic acid molecules, thereby providing a selected set of captured normal and/or tumor nucleic acid molecules (i.e., a library catch); (c) separating the selected subset of the nucleic acid molecules e.g., the library catch) from the hybridization mixture, e.g. , by contacting the hybridization mixture with a binding entity that allows for separation of the target capture reagent/nucleic acid molecule hybrids from the hybridization mixture, (d) sequencing the library catch to acquiring a plurality of reads (e.g., sequence reads) that overlap one or more subject intervals (e.g., one or more target sequences) from said library catch that may comprise a mutation (or alteration), e.g., a variant sequence comprising a somatic mutation or germline mutation; (e) aligning said sequence reads using an alignment method as described elsewhere herein; and/or (f) assigning a nucleotide value for a nucleotide position in the subject interval (e.g., calling a mutation using, e.g., a Bayesian method or other method described herein) from one or more sequence reads of the plurality.
[0177] In some instances, acquiring sequence reads for one or more subject intervals may comprise sequencing at least 1, at least 5, at least 10, at least 20, at least 30, at least 40, at least 50, at least 100, at least 150, at least 200, at least 250, at least 300, at least 350, at least 400, at least 450, at least 500, at least 550, at least 600, at least 650, at least 700, at least 750, at least 800, at least 850, at least 900, at least 950, at least 1,000, at least 1,250, at least 1,500, at least 1,750, at least 2,000, at least 2,250, at least 2,500, at least 2,750, at least 3,000, at least 3,500, at least 4,000, at least 4,500, or at least 5,000 loci, e.g., genomic loci, gene loci, micro satellite loci, etc. In some instances, acquiring a sequence read for one or more subject intervals may comprise sequencing a subject interval for any number of loci within the range described in this paragraph, e.g., for at least 2,850 gene loci.
[0178] In some instances, acquiring a sequence read for one or more subject intervals comprises sequencing a subject interval with a sequencing method that provides a sequence read length (or average sequence read length) of at least 20 bases, at least 30 bases, at least 40 bases, at least 50 bases, at least 60 bases, at least 70 bases, at least 80 bases, at least 90 bases, at least 100 bases, at least 120 bases, at least 140 bases, at least 160 bases, at least 180 bases, at least 200 bases, at least 220 bases, at least 240 bases, at least 260 bases, at least 280 bases, at least 300 bases, at least 320 bases, at least 340 bases, at least 360 bases, at least 380 bases, or at least 400 bases. In some instances, acquiring a sequence read for the one or more subject intervals may comprise sequencing a subject interval with a sequencing method that provides a sequence read length (or average sequence read length) of any number of bases within the range described in this paragraph, e.g., a sequence read length (or average sequence read length) of 56 bases.
[0179] In some instances, acquiring a sequence read for one or more subject intervals may comprise sequencing with at least lOOx or more coverage (or depth) on average. In some instances, acquiring a sequence read for one or more subject intervals may comprise sequencing with at least lOOx, at least 15Ox, at least 200x, at least 250x, at least 5OOx, at least 750x, at least l,OOOx, at least 1,500 x, at least 2,000x, at least 2,500x, at least 3,000x, at least 3,500x, at least 4,000x, at least 4,500x, at least 5,000x, at least 5,500x, or at least 6,000x or more coverage (or depth) on average. In some instances, acquiring a sequence read for one or more subject intervals may comprise sequencing with an average coverage (or depth) having any value within the range of values described in this paragraph, e.g., at least 160x.
[0180] In some instances, acquiring a read for the one or more subject intervals comprises sequencing with an average sequencing depth having any value ranging from at least lOOx to at least 6,000x for greater than about 90%, 92%, 94%, 95%, 96%, 97%, 98%, or 99% of the gene loci sequenced. For example, in some instances acquiring a read for the subject interval comprises sequencing with an average sequencing depth of at least 125x for at least 99% of the gene loci sequenced. As another example, in some instances acquiring a read for the subject interval comprises sequencing with an average sequencing depth of at least 4,100x for at least 95% of the gene loci sequenced.
[0181] In some instances, the relative abundance of a nucleic acid species in the library can be estimated by counting the relative number of occurrences of their cognate sequences (e.g., the number of sequence reads for a given cognate sequence) in the data generated by the sequencing experiment.
[0182] In some instances, the disclosed methods and systems provide nucleotide sequences for a set of subject intervals (e.g., gene loci), as described herein. In certain instances, the sequences are provided without using a method that includes a matched normal control (e.g., a wild-type control) and/or a matched tumor control (e.g., primary versus metastatic).
[0183] In some instances, the level of sequencing depth as used herein (e.g., an X-fold level of sequencing depth) refers to the number of reads (e.g., unique reads) obtained after detection and removal of duplicate reads (e.g., PCR duplicate reads). In other instances, duplicate reads are evaluated, e.g., to support detection of copy number alteration (CNAs).
Alignment
[0184] Alignment is the process of matching a read with a location, e.g., a genomic location or locus. In some instances, NGS reads may be aligned to a known reference sequence (e.g., a wild-type sequence). In some instances, NGS reads may be assembled de novo. Methods of sequence alignment for NGS reads are described in, e.g., Trapnell, C. and Salzberg, S.L. Nature Biotech., 2009, 27:455-457. Examples of de novo sequence assemblies are described in, e.g., Warren R., et al., Bioinformatics, 2007, 23:500-501; Butler, J. et al., Genome Res., 2008, 18:810-820; and Zerbino, D.R. and Birney, E., Genome Res., 2008, 18:821-829. Optimization of sequence alignment is described in the art, e.g., as set out in International Patent Application Publication No. WO 2012/092426. Additional description of sequence alignment methods is provided in, e.g., International Patent Application Publication No. WO 2020/236941, the entire content of which is incorporated herein by reference.
[0185] Misalignment (e.g., the placement of base-pairs from a short read at incorrect locations in the genome), e.g., misalignment of reads due to sequence context (e.g., the presence of repetitive sequence) around an actual cancer mutation can lead to reduction in sensitivity of mutation detection, can lead to a reduction in sensitivity of mutation detection, as reads for the alternate allele may be shifted off the histogram peak of alternate allele reads. Other examples of sequence context that may cause misalignment include short-tandem repeats, interspersed repeats, low complexity regions, insertions - deletions (indels), and paralogs. If the problematic sequence context occurs where no actual mutation is present, misalignment may introduce artifactual reads of “mutated” alleles by placing reads of actual reference genome base sequences at the wrong location. Because mutation-calling algorithms for multigene analysis should be sensitive to even low-abundance mutations, sequence misalignments may increase false positive discovery rates and/or reduce specificity.
[0186] In some instances, the methods and systems disclosed herein may integrate the use of multiple, individually-tuned, alignment methods or algorithms to optimize base-calling performance in sequencing methods, particularly in methods that rely on massively parallel sequencing (MPS) of a large number of diverse genetic events at a large number of diverse genomic loci. In some instances, the disclosed methods and systems may comprise the use of one or more global alignment algorithms. In some instances, the disclosed methods and systems may comprise the use of one or more local alignment algorithms. Examples of alignment algorithms that may be used include, but are not limited to, the Burrows-Wheeler Alignment (BWA) software bundle (see, e.g., Li, et al. (2009), “Fast and Accurate Short Read Alignment with Burrows-Wheeler Transform”, Bioinformatics 25:1754-60; Li, et al. (2010), Fast and Accurate Long-Read Alignment with Burrows-Wheeler Transform”, Bioinformatics epub. PMID: 20080505), the Smith-Waterman algorithm (see, e.g., Smith, et al. (1981), "Identification of Common Molecular Subsequences", J. Molecular Biology 147(1): 195-197), the Striped Smith-Waterman algorithm (see, e.g., Farrar (2007), “Striped Smith-Waterman Speeds Database Searches Six Times Over Other SIMD Implementations”, Bioinformatics 23(2): 156- 161), the Needleman- Wunsch algorithm (Needleman, et al. (1970) "A General Method Applicable to the Search for Similarities in the Amino Acid Sequence of Two Proteins", J. Molecular Biology 48(3):443-53), or any combination thereof.
[0187] In some instances, the methods and systems disclosed herein may also comprise the use of a sequence assembly algorithm, e.g., the Arachne sequence assembly algorithm (see, e.g., Batzoglou, et al. (2002), “ARACHNE: A Whole-Genome Shotgun Assembler”, Genome Res. 12:177-189).
[0188] In some instances, the alignment method used to analyze sequence reads is not individually customized or tuned for detection of different variants (e.g., point mutations, insertions, deletions, and the like) at different genomic loci. In some instances, different alignment methods are used to analyze reads that are individually customized or tuned for detection of at least a subset of the different variants detected at different genomic loci. In some instances, different alignment methods are used to analyze reads that are individually customized or tuned to detect each different variant at different genomic loci. In some instances, tuning can be a function of one or more of: (i) the genetic locus (e.g., gene loci, micro satellite locus, or other subject interval) being sequenced, (ii) the tumor type associated with the sample, (iii) the variant being sequenced, or (iv) a characteristic of the sample or the subject. The selection or use of alignment conditions that are individually tuned to a number of specific subject intervals to be sequenced allows optimization of speed, sensitivity, and specificity. The method is particularly effective when the alignment of reads for a relatively large number of diverse subject intervals are optimized.
[0189] In some instances, the method includes the use of an alignment method optimized for rearrangements in combination with other alignment methods optimized for subject intervals not associated with rearrangements.
[0190] In some instances, the methods disclosed herein further comprise selecting or using an alignment method for analyzing, e.g., aligning, a sequence read, wherein said alignment method is a function of, is selected responsive to, or is optimized for, one or more of: (i) tumor type, e.g., the tumor type in the sample; (ii) the location (e.g., a gene locus) of the subject interval being sequenced; (iii) the type of variant (e.g., a point mutation, insertion, deletion, substitution, copy number variation (CNV), rearrangement, or fusion) in the subject interval being sequenced; (iv) the site (e.g., nucleotide position) being analyzed; (v) the type of sample (e.g., a sample described herein); and/or (vi) adjacent sequence(s) in or near the subject interval being evaluated (e.g., according to the expected propensity thereof for misalignment of the subject interval due to, e.g., the presence of repeated sequences in or near the subject interval).
[0191] In some instances, the methods disclosed herein allow for the rapid and efficient alignment of troublesome reads, e.g., a read having a rearrangement. Thus, in some instances where a read for a subject interval comprises a nucleotide position with a rearrangement, e.g., a translocation, the method can comprise using an alignment method that is appropriately tuned and that includes: (i) selecting a rearrangement reference sequence for alignment with a read, wherein said rearrangement reference sequence aligns with a rearrangement (in some instances, the reference sequence is not identical to the genomic rearrangement); and (ii) comparing, e.g., aligning, a read with said rearrangement reference sequence.
[0192] In some instances, alternative methods may be used to align troublesome reads. These methods are particularly effective when the alignment of reads for a relatively large number of diverse subject intervals is optimized. By way of example, a method of analyzing a sample can comprise: (i) performing a comparison (e.g., an alignment comparison) of a read using a first set of parameters (e.g., using a first mapping algorithm, or by comparison with a first reference sequence), and determining if said read meets a first alignment criterion (e.g., the read can be aligned with said first reference sequence, e.g., with less than a specific number of mismatches); (ii) if said read fails to meet the first alignment criterion, performing a second alignment comparison using a second set of parameters, (e.g., using a second mapping algorithm, or by comparison with a second reference sequence); and (iii) optionally, determining if said read meets said second criterion (e.g., the read can be aligned with said second reference sequence, e.g., with less than a specific number of mismatches), wherein said second set of parameters comprises use of, e.g., said second reference sequence, which, compared with said first set of parameters, is more likely to result in an alignment with a read for a variant (e.g., a rearrangement, insertion, deletion, or translocation).
[0193] In some instances, the alignment of sequence reads in the disclosed methods may be combined with a mutation calling method as described elsewhere herein. As discussed herein, reduced sensitivity for detecting actual mutations may be addressed by evaluating the quality of alignments (manually or in an automated fashion) around expected mutation sites in the genes or genomic loci (e.g., gene loci) being analyzed. In some instances, the sites to be evaluated can be obtained from databases of the human genome (e.g., the HG19 human reference genome) or cancer mutations (e.g., COSMIC). Regions that are identified as problematic can be remedied with the use of an algorithm selected to give better performance in the relevant sequence context, e.g., by alignment optimization (or re-alignment) using slower, but more accurate alignment algorithms such as Smith-Waterman alignment. In cases where general alignment algorithms cannot remedy the problem, customized alignment approaches may be created by, e.g., adjustment of maximum difference mismatch penalty parameters for genes with a high likelihood of containing substitutions; adjusting specific mismatch penalty parameters based on specific mutation types that are common in certain tumor types (e.g. C~^T in melanoma); or adjusting specific mismatch penalty parameters based on specific mutation types that are common in certain sample types (e.g. substitutions that are common in FFPE).
[0194] Reduced specificity (increased false positive rate) in the evaluated subject intervals due to misalignment can be assessed by manual or automated examination of all mutation calls in the sequencing data. Those regions found to be prone to spurious mutation calls due to misalignment can be subjected to alignment remedies as discussed above. In cases where no algorithmic remedy is found possible, “mutations” from the problem regions can be classified or screened out from the panel of targeted loci.
Alignment of Methyl-Seq Sequence Reads
[0195] In some instances, the methods may include the use of an alignment method optimized for aligning sequence reads for DNA that has been converted using, e.g., a bisulfite reaction, to convert unmethylated cytosine residues to uracil (which is interpreted as a thymine in sequencing results). In some instances, sequence reads may be aligned to two genomes in silico, e.g., converted and unconverted versions of the reference genome, using such alignment tools. Methylation occurs primarily at CpG sites, but may also occur less frequently at non-CpG sites (e.g., CHG or CHH sites).
[0196] In some instances, the sequence read data may be obtained using a nucleic acid sequencing method comprising the use of a bisulfite- or enzymatic-conversion reaction (e.g., during library preparation) to convert non-methylated cytosine to uracil (see, e.g., Li, el al. (2011), “DNA Methylation Detection: Bisulfite Genomic Sequencing Analysis”, Methods Mol. Biol. 791:11-21). [0197] In some instances, the sequence read data may be obtained using a nucleic acid sequencing method comprising the use of alternative chemical and/or enzymatic reactions (e.g., during library preparation) to convert non-methylated cytosine to uracil (or to convert methylated cytosine to dihydrouracil). For example, enzymatic deamination of nonmethylated cytosine using APOBEC to form uracil can be performed using, e.g., the Enzymatic Methyl-seq Kit from New England BioLabs (Ipswich, MA) which uses prior treatment with ten-eleven translocation methylcytosine dioxygenase 2 (TET2) to oxidize 5mC and 5hmC, thereby providing greater protection of the methylated cytosine from deamination by APOBEC). Liu, et al. (2019) recently described a bisulfite-free and base- level-resolution sequencing-based method, TET-Assisted Pyridine borane Sequencing (TAPS), for detection of 5mC and 5hmC. The method combines ten-eleven translocation methylcytosine dioxygenase (TET)-mediated oxidation of 5mC and 5hmC to 5- carboxylcytosine (5caC) with pyridine borane reduction of 5caC to dihydrouracil (DHU). Subsequent PCR amplification converts DHU to thymine, thereby enabling conversion of methylated cytosines to thymine (Liu, et al. (2019), “Bisulfite-Free Direct Detection of 5- Methylcytosine and 5-Hydroxymethylcytosine at Base Resolution”, Nature Biotechnology, vol. 37, pp. 424-429).
[0198] In some instances, the sequence read data may be obtained using a nucleic acid sequencing method comprising the use of Methylated DNA Immunoprecipitation (MeDIP).
[0199] Examples of alignment tools optimized for aligning sequence reads for converted DNA include, but are not limited to, NovoAlign (Novocraft Technologies, Selangor, Malaysia), and the Bismark tool (Krueger, et al. (2011), “Bismark: A Flexible Aligner and Methylation Caller for Bisulfite-Seq Applications”, Bioinformatics 27(11): 1571- 1572).
Mutation calling
[0200] Base calling refers to the raw output of a sequencing device, e.g., the determined sequence of nucleotides in an oligonucleotide molecule. Mutation calling refers to the process of selecting a nucleotide value, e.g., A, G, T, or C, for a given nucleotide position being sequenced. Typically, the sequence reads (or base calling) for a position will provide more than one value, e.g., some reads will indicate a T and some will indicate a G. Mutation calling is the process of assigning a correct nucleotide value, e.g., one of those values, to the sequence. Although it is referred to as “mutation” calling, it can be applied to assign a nucleotide value to any nucleotide position, e.g., positions corresponding to mutant alleles, wild-type alleles, alleles that have not been characterized as either mutant or wild-type, or to positions not characterized by variability.
[0201] In some instances, the disclosed methods may comprise the use of customized or tuned mutation calling algorithms or parameters thereof to optimize performance when applied to sequencing data, particularly in methods that rely on massively parallel sequencing (MPS) of a large number of diverse genetic events at a large number of diverse genomic loci (e.g., gene loci, microsatellite regions, etc.) in samples, e.g., samples from a subject having cancer. Optimization of mutation calling is described in the art, e.g., as set out in International Patent Application Publication No. WO 2012/092426.
[0202] Methods for mutation calling can include one or more of the following: making independent calls based on the information at each position in the reference sequence (e.g., examining the sequence reads; examining the base calls and quality scores; calculating the probability of observed bases and quality scores given a potential genotype; and assigning genotypes (e.g., using Bayes’ rule)); removing false positives (e.g., using depth thresholds to reject SNPs with read depth much lower or higher than expected; local realignment to remove false positives due to small indels); and performing linkage disequilibrium (LD)/imputation- based analysis to refine the calls.
[0203] Equations used to calculate the genotype likelihood associated with a specific genotype and position are described in, e.g., Li, H. and Durbin, R. Bioinformatics, 2010; 26(5): 589-95. The prior expectation for a particular mutation in a certain cancer type can be used when evaluating samples from that cancer type. Such likelihood can be derived from public databases of cancer mutations, e.g., Catalogue of Somatic Mutation in Cancer (COSMIC), HGMD (Human Gene Mutation Database), The SNP Consortium, Breast Cancer Mutation Data Base (BIC), and Breast Cancer Gene Database (BCGD).
[0204] Examples of LD/imputation based analysis are described in, e.g., Browning, B.L. and Yu, Z. Am. J. Hum. Genet. 2009, 85(6):847-61. Examples of low-coverage SNP calling methods are described in, e.g., Li, Y., et al., Annu. Rev. Genomics Hum. Genet. 2009, 10:387- 406.
[0205] After alignment, detection of substitutions can be performed using a mutation calling method (e.g., a Bayesian mutation calling method) which is applied to each base in each of the subject intervals, e.g., exons of a gene or other locus to be evaluated, where presence of alternate alleles is observed. This method will compare the probability of observing the read data in the presence of a mutation with the probability of observing the read data in the presence of base-calling error alone. Mutations can be called if this comparison is sufficiently strongly supportive of the presence of a mutation.
[0206] An advantage of a Bayesian mutation detection approach is that the comparison of the probability of the presence of a mutation with the probability of base-calling error alone can be weighted by a prior expectation of the presence of a mutation at the site. If some reads of an alternate allele are observed at a frequently mutated site for the given cancer type, then presence of a mutation may be confidently called even if the amount of evidence of mutation does not meet the usual thresholds. This flexibility can then be used to increase detection sensitivity for even rarer mutations/lower purity samples, or to make the test more robust to decreases in read coverage. The likelihood of a random base-pair in the genome being mutated in cancer is ~le-6. The likelihood of specific mutations occurring at many sites in, for example, a typical multigenic cancer genome panel can be orders of magnitude higher. These likelihoods can be derived from public databases of cancer mutations (e.g., COSMIC).
[0207] Indel calling is a process of finding bases in the sequencing data that differ from the reference sequence by insertion or deletion, typically including an associated confidence score or statistical evidence metric. Methods of indel calling can include the steps of identifying candidate indels, calculating genotype likelihood through local re-alignment, and performing LD-based genotype inference and calling. Typically, a Bayesian approach is used to obtain potential indel candidates, and then these candidates are tested together with the reference sequence in a Bayesian framework.
[0208] Algorithms to generate candidate indels are described in, e.g., McKenna, A., et al., Genome Res. 2010; 20(9): 1297-303; Ye, K., et al., Bioinformatics, 2009; 25(21):2865-71; Lunter, G., and Goodson, M., Genome Res. 2011; 21(6):936-9; and Li, H., et al. (2009), Bioinformatics 25(16):2078-9.
[0209] Methods for generating indel calls and individual-level genotype likelihoods include, e.g., the Dindel algorithm (Albers, C.A., et al., Genome Res. 2011;21(6):961-73). For example, the Bayesian EM algorithm can be used to analyze the reads, make initial indel calls, and generate genotype likelihoods for each candidate indel, followed by imputation of genotypes using, e.g., QCALL (Le S.Q. and Durbin R. Genome Res. 2011 ;21(6):952-60). Parameters, such as prior expectations of observing the indel can be adjusted e.g., increased or decreased), based on the size or location of the indels. [0210] Methods have been developed that address limited deviations from allele frequencies of 50% or 100% for the analysis of cancer DNA. (see, e.g., SNVMix -Bioinformatics. 2010 March 15; 26(6): 730-736.) Methods disclosed herein, however, allow consideration of the possibility of the presence of a mutant allele at frequencies (or allele fractions) ranging from 1% to 100% (z.e., allele fractions ranging from 0.01 to 1.0), and especially at levels lower than 50%. This approach is particularly important for the detection of mutations in, for example, low-purity FFPE samples of natural (multi-clonal) tumor DNA.
[0211] In some instances, the mutation calling method used to analyze sequence reads is not individually customized or fine-tuned for detection of different mutations at different genomic loci. In some instances, different mutation calling methods are used that are individually customized or fine-tuned for at least a subset of the different mutations detected at different genomic loci. In some instances, different mutation calling methods are used that are individually customized or fine-tuned for each different mutant detected at each different genomic loci. The customization or tuning can be based on one or more of the factors described herein, e.g., the type of cancer in a sample, the gene or locus in which the subject interval to be sequenced is located, or the variant to be sequenced. This selection or use of mutation calling methods individually customized or fine-tuned for a number of subject intervals to be sequenced allows for optimization of speed, sensitivity and specificity of mutation calling.
[0212] In some instances, a nucleotide value is assigned for a nucleotide position in each of X unique subject intervals using a unique mutation calling method, and X is at least 2, at least 3, at least 4, at least 5, at least 10, at least 15, at least 20, at least 30, at least 40, at least 50, at least 60, at least 70, at least 80, at least 90, at least 100, at least 200, at least 300, at least 400, at least 500, at least 1000, at least 1500, at least 2000, at least 2500, at least 3000, at least 3500, at least 4000, at least 4500, at least 5000, or greater. The calling methods can differ, and thereby be unique, e.g., by relying on different Bayesian prior values.
[0213] In some instances, assigning said nucleotide value is a function of a value which is or represents the prior (e.g., literature) expectation of observing a read showing a variant, e.g., a mutation, at said nucleotide position in a tumor of type.
[0214] In some instances, the method comprises assigning a nucleotide value e.g., calling a mutation) for at least 10, 20, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1,000 nucleotide positions, wherein each assignment is a function of a unique value (as opposed to the value for the other assignments) which is or represents the prior (e.g., literature) expectation of observing a read showing a variant, e.g., a mutation, at said nucleotide position in a tumor of type.
[0215] In some instances, assigning said nucleotide value is a function of a set of values which represent the probabilities of observing a read showing said variant at said nucleotide position if the variant is present in the sample at a specified frequency (e.g., 1%, 5%, 10%, etc.) and/or if the variant is absent (e.g., observed in the reads due to base-calling error alone).
[0216] In some instances, the mutation calling methods described herein can include the following: (a) acquiring, for a nucleotide position in each of said X subject intervals: (i) a first value which is or represents the prior (e.g., literature) expectation of observing a read showing a variant, e.g., a mutation, at said nucleotide position in a tumor of type X; and (ii) a second set of values which represent the probabilities of observing a read showing said variant at said nucleotide position if the variant is present in the sample at a frequency (e.g., 1%, 5%, 10%, etc.) and/or if the variant is absent (e.g., observed in the reads due to basecalling error alone); and (b) responsive to said values, assigning a nucleotide value (e.g., calling a mutation) from said reads for each of said nucleotide positions by weighing, e.g., by a Bayesian method described herein, the comparison among the values in the second set using the first value (e.g., computing the posterior probability of the presence of a mutation), thereby analyzing said sample.
[0217] Additional description of exemplary nucleic acid sequencing methods, mutation calling methods, and methods for analysis of genetic variants is provided in, e.g., U.S. Patent No. 9,340,830, U.S. Patent No. 9,792,403, U.S. Patent No. 11,136,619, U.S. Patent No. 11,118,213, and International Patent Application Publication No. WO 2020/236941, the entire contents of each of which is incorporated herein by reference.
Methylation Status Calling
[0218] In some instances, the methods described herein may comprise the use of a methylation status calling method, e.g., to call the methylation status of the CpG sites based on the sequence reads and fragments (complementary pairs of forward and reverse sequence reads) derived from DNA that has been subjected to a chemical or enzymatic conversion reaction, e.g., to convert unmethylated cytosine residues to uracil (which is interpreted as a thymine in sequencing results). Examples of such methylation status calling tools include, but are not limited to, the Bismark tool (Krueger, et al. (2011), “Bismark: A Flexible Aligner and Methylation Caller for Bisulfite-Seq Applications”, Bioinformatics 27(11): 1571-1572), TARGOMICS (Garinet, et al. (2017), “Calling Chromosome Alterations, DNA Methylation Statuses, and Mutations in Tumors by Simple Targeted Next-Generation Sequencing - A Solution for Transferring Integrated Pangenomic Studies into Routine Practice?”, J. Molecular Diagnostics 19(5):776-787), Bicycle (Grana, et al. (2018) “Bicycle: A Bioinformatics Pipeline to Analyze Bisulfite Sequencing Data”, Bioinformatics 34(8): 1414- 5), SMAP (Gao, et al. (2015), “SMAP: A Streamlined Methylation Analysis Pipeline for Bisulfite Sequencing”, Gigascience 4:29), and MeDUSA (Wilson, et al. (2016), “Computational Analysis and Integration of MeDIP-Seq Methylome Data”, in: Kulski JK, editor, Next Generation Sequencing: Advances, Applications and Challenges. Rijeka: InTech, p. 153-69). See also, Rauluseviciute, et al. (2019), “DNA Methylation Data by Sequencing: Experimental Approaches and Recommendations for Tools and Pipelines for Data Analysis”, Clinical Epigenetics 11:193.
EXAMPLES
Example 1 -Comparison of DNA sequence read yields from enzymatic- and bisulfite-based methyl-sequencing methods
[0219] FIG. 1 depicts a non-limiting example of DNA sequence read yield data for enzymatic- and bisulfite-based methyl-sequencing methods. Vertical bars 102 to the left of the dashed line depict data for reads derived from an enzymatic-based methyl-sequencing method. Vertical bars 104 to the right of the dashed line depict data for reads derived from a bisulfite-based methyl-sequencing method. The y-axis depicts the percentage of sequencing reads identified for each sample index in a sequencing library that passed a quality control filter associated with the sequencing platform. The x-axis depicts the index number and is a discrete categorical quantity. As can be seen, vertical bars 102 indicate that fewer reads obtained using an enzymatic conversion reaction protocol pass the quality control filter (e.g., an internal quality control filter based on a ratio of brightest base signal intensity divided by the sum of the brightest and second brightest base signal intensities; clusters of reads pass the filter if no more than 1 base call has a signal intensity ratio of below 0.6 in the first 25 sequencing cycles; clusters that fail to pass the filter are removed from image analysis results) relative to reads obtained using a bisulfite conversion reaction protocol (vertical bars 104). In other words, enzymatic-based methyl-sequencing methods appear to provide lower yields than bisulfite-based methyl- sequencing methods. This may be due to, e.g., reduced binding of sequencing primers to the sequencing primer binding sites during the sequencing process due to erroneous conversion of 5mC residues in the sequencing adapter by APOBEC, thereby resulting in base-pairing mismatches.
Example 2 -Erroneous cytosine conversion and. its impact on adapter binding interactions
[0220] FIG. 2 - FIG. 4 depict non-limiting examples of primer and primer binding site sequences used for some sequencing protocols, such as, but not limited to, protocols run on next generation sequencing (NGS) sequencing platforms, in this case, an Illumina® sequencer. Sequences 202 and 204 in FIG. 2 depict the Read 1 and Read 2 primers that are commonly used for NGS sequencing platforms.
[0221] FIG. 3 depicts sequence 202 in a schematic illustrating the binding between a primer comprising sequence 202 and a library molecule incorporating a conventional sequencing adapter comprising the primer binding site subsequence 302 and an insert 306 e.g., a template nucleic acid sequence of interest), e.g., as may occur in a clonally-amplified cluster in a flow cell for an NGS sequencing platform. Erroneous conversion of 5-methylcytosine in a “stubby adapter” used for methylation sequencing may occur at any of a variety of cytosine positions within the stubby adapter sequence, e.g., at the cytosine located proximally to the 3’ end (TCT) of the primer binding site sequence 202, thereby resulting in a TTT sequence. Downstream PCR amplification will then synthesize a complementary strand 304 which includes a complementary AAA subsequence, as indicated in the figure (circled), and weakens the binding interaction between the library molecule and the sequencing primer.
[0222] FIG. 4 depicts a similar schematic to that shown in FIG. 3, except that sequence 204 is depicted instead of sequence 202. A primer comprising sequence 204 is bound to a library molecule comprising the primer binding subsequence 402 and an insert 404. Again, erroneous conversion of 5-methylcytosine in a “stubby adapter” used for methylation sequencing may occur at the various cytosine positions within the stubby adapter sequence, e.g., at the cytosine located proximally to the 3’ end (TCT) of the primer binding site sequence 204, thereby resulting in a TTT sequence. Downstream PCR amplification will then synthesize a complementary strand 404 which includes a complementary AAA subsequence, as indicated in the figure (circled) , and weakens the binding interaction between the library molecule and the sequencing primer. [0223] FIG. 5 depicts a non-limiting schematic illustrating the biochemical mechanism by which modified cytosines can be protected from conversion to uracil / thymine. FIG. 5 illustrates the use of enzymes TET2 and T4-PGT to convert 5-methylcytosine to a modified cytosine, such as 5-hydroxymethylcytosine, 5-formylcytosine, 5-carobxycytosine, and/or 5- (D-glucosyl)oxymethylcytosine. The modified cytosines (in the case of the schematic, 5-(D- glucosyl)oxymethylcytosine and 5-carobxycytosine) are not readily deaminated by a deaminating enzyme such as Apolipoprotein B mRNA Editing Catalytic Polypeptide-like (APOBEC) enzymes/proteins, and as a result, the modified cytosines remain as modified cytosines, and are protected from conversion to uracil / thymine (e.g., the uracils are replaced with thymines via e.g a polymerase chain reactions (PCR) process.
[0224] FIGS. 6A-C depict non-limiting schematic illustrations of a workflow by which nucleic acids extracted from a biological sample can be processed to create a nucleic acid library for methylation sequencing. FIG. 6A depicts a non-limiting schematic illustration of a process 600A for extracting and purifying nucleic acids, e.g., DNA, from a sample. At step 602A, the cells in a tissue sample are disrupted by any of a variety of techniques known to those of skill in the art including, but not limited to, addition of detergents and/or cell lysis reagents, sonication, mechanical (e.g., French press) disruption, etc. In some instances, e.g., in the case of some liquid biopsy samples, cells may simply be removed (e.g., by centrifugation) and a cell disruption step may not be required. At step 604A, DNA may be separated from proteins and other cellular debris, e.g., by addition of a protease and/or filtration. At step 606A, the DNA may be precipitated, e.g., by the addition of ice-cold ethanol or isopropanol. At step 608A, the DNA may be optionally sheared (e.g., using a method such as sonication) to a length of about 200-500 bp if it was derived from a tissue sample. At step 610A, the DNA may be purified, e.g., by rinsing with alcohol and/or the use of chromatographic techniques. At step 612A, the quantity and quality of the purified DNA may be assessed, e.g., using optical density measurements, gel electrophoresis, and/or capillary electrophoresis techniques.
[0225] The sheared nucleic acids may then be subjected to an end repair reaction and/or tailing reaction. FIG. 6B provides a non-limiting schematic illustration of a process 600B for performing end-repair and tailing reactions on extracted and purified DNA. For example, at step 602B, an end repair reaction, such as a blunt ligation, addition of bases to the 3’ ends of DNA fragments, and/or other single- stranded DNA library preparation steps. At step 604B, the 3’ ends of the nucleic acids may be subjected to a tailing reaction, e.g., resulting in the addition of dT, dC, dG, or dA tails, which can prevent the formation of concatemers during subsequent ligation reactions. At step 606B, the end-repaired nucleic acid (DNA) fragments may then be ligated to adapters that comprise, e.g., sequencing primer binding sites and/or binding sequences (used to hybridize library molecules to a sequencing flow cell). In some instances, adapters may be added to DNA fragments during amplification (e.g., PCR amplification) without using a ligation step.
[0226] FIG. 6C provides a non-limiting schematic illustration of a process 600C for performing enzymatic conversion of cytosines in a DNA sample and performing methylation sequencing. At step 602C, for example, TET2 and/or T4-PGT enzymes can be introduced to the end-repaired DNA fragments so that methylated cytosine bases of the nucleic acids are further modified and protected during subsequent exposure to deaminating enzymes (step 604C), such as APOBEC enzymes/proteins (e.g., APOBEC3A). The APOBEC3A deaminating enzyme in this example, was provided to deaminate non-modified cytosines, which converts the cytosines to uracil bases. In contrast, the APOBEC3A should fail to convert the modified (protected) cytosines to uracil. At step 606C, the nucleic acids are then subjected to a nucleic acid amplification reaction, such as, but not limited to, a polymerase chain reaction (PCR), during which uracils are replaced by thymines. At step 608C, the amplified nucleic acid library molecules are then sequenced using a sequencing platform, such as, but not limited to, an NGS sequencing platform.
Example 3 -Erroneous cytosine conversion rates for different modified cytosines in adapter sequences
[0227] FIG. 7 depicts a non-limiting example of data illustrating the effectiveness with which various modifications to cytosine protect the cytosine from conversion to uracil / thymine upon treatment with a sequencing workflow comprising the use of deaminating enzymes or bisulfite. Primer extension was used to synthesize a "genomic strand" that incorporates a specific modified cytosine residue that should be protected from enzymatic (APOBEC) conversion. Following the primer extension step, the "genomic strands" were then converted via EM-Seq™ (New England BioLabs, Ipswich, MA). Any erroneous conversion events were detected as an increase in the SNP filtered error rate (filtered error rate quantifies the rate of mismatches between the sequence reads and the reference genome, specifically in regions that are not known to have cancer associated SNPs). The y-axis depicts the observed single nucleotide polymorphism (SNP) filtered error rates for different modified cytosines (indicated on the x axis). Vertical bar 702 represents the SNP filtered error rate observed for conventional whole genome sequencing, and is quantified as a rate of 0.0055. Vertical bar 704 represents the SNP filtered error rate for 5-methylcytosine (5mC), and is quantified as a rate of 0.012. Vertical bar 706 represents the SNP filtered error rates for 5- hydroxymethylcytosine (5hmC), and is quantified as a rate of 0.0067.
[0228] FIG. 8 depicts a non-limiting example of typical adapter sequences provided for use in preparing double-stranded DNA libraries for methylation sequencing. The methylated cytosine included in the last three nucleotide residues (TCT) at the 3’ end of the 5mC modified adapter has an approximately 5% chance of erroneous conversion to thymine.
Example 4 -Modified adapter sequences for improving methyl-seq sequencing efficiency
[0229] FIG. 9, FIG. 10, and FIG. 11 depict non-limiting examples of sequences for custom methylation adapters with incorporated 5hmC nucleotides. The adapter sequences shown in FIG. 9 (modified sequencing adapter 1) incorporate 5hmC for the three cytosines closest to the 5’ end of the upper strand (bases 902, 904, 906), and for the three cytosines closest to the 3’ end of the lower, complementary strand (bases 908, 910, 912). The remaining cytosine positions shown in this example consist of 5mC. In some instances, all or a portion of the cytosines in the adapter sequence may comprise 5hmC or another modified cytosine for which the erroneous conversion rate by deaminating enzymes is lower than that for 5mC. The adapter sequences shown in FIG. 10 (modified sequencing adapter 2) incorporate 5hmC for cytosines that reside in several nucleotide residue positions (bases 1002 and 1004 on the upper strand, and bases 1006, 1008, and 1010). Again, the remaining cytosine positions in this example consist of 5mC, but in some instances, could also be replaced by 5hmC or other protected forms of cytosine. The adapter sequences shown in FIG. 11 (modified sequencing adapter 3) incorporate 5hmC at a single position 1102. The remaining cytosine positions in this example consist of 5mC, but in some instances, could also be replaced by 5hmC or other protected forms of cytosine.
[0230] FIG. 12 provides a non-limiting example of data that illustrates the improvement in the number of sequence reads passing filter that were observed using the custom 5-hydroxy- methylated cytosine adapters (modified sequencing adapters 1 and 2) shown in FIG. 9 and FIG. 10 to perform enzymatic conversion (in this example Enzymatic Methyl-seq (EM- seq™) Kit, New England BioLabs, Ipswich, MA) and methylation sequencing. FIG. 12 provides a box plot of the percentage of sequence reads identified that pass the quality filter per sample index, for methylation sequencing performed using different adapter sequences or conversion reactions. The y-axis represents the percentage of reads identified passing the quality filter per index, whereas the x-axis represents different methylation sequencing protocols. Significance was based on a student's t-test: t=2.30600, alpha = 0.05. Box 1202 represents the percentage of reads passing filter data for the enzymatic-based methylation sequencing protocol using an adapter comprising standard 5mC nucleotides. Box 1204 represents the data for a bisulfite-based methylation sequencing protocol (EZ DNA Methylation, Zymo Research, Irvine, CA). Box 1206 represents the data obtained using the enzymatic -based methylation sequencing protocol in combination with the modified sequencing adapter incorporating six 5hmC nucleotides (modified sequencing adapter 1), as indicated in FIG. 9. Box 1208 represents the data obtained when the enzymatic-based methylation sequencing protocol was used in combination with the modified adapter sequences comprising 5hmC nucleotides at the five nucleotide positions indicated in FIG. 10 (modified sequencing adapter 2). Substituting the 5hmC adapters for the conventional 5mC adapter in the enzymatic methylation sequencing protocol (1206 and 1208) yielded higher percentages of high-quality sequence reads compared to use of the conventional 5mC adapter (1202) under otherwise identical conditions. The percentage of reads passing the quality filter for the 5hmC-incorporated adapters is similar to the percentage of reads passing the quality filter for the bisulfite methylation sequencing protocol (1204). The relative improvements in yields of quality sequence reads are summarized in Table 1.
Table 1. Percent difference in yield of quality sequence reads.
Figure imgf000068_0001
Figure imgf000069_0001
Example 5 -Modified adapters provide improved yields of quality sequence reads
[0231] FIG. 13 provides a non-limiting schematic illustration of an alternative assay used for testing the effectiveness of the disclosed modified sequencing adapters comprising 5hmC nucleotides in reducing the erroneous conversion of cytosine to uracil / thymine in enzymatic methylation sequencing methods. As illustrated, the assay comprises the steps of ligating either the standard methylation sequencing adapters (e.g., the p5 and p7 adapters with all Cs methylated, as indicated by strands 1302 and 1304 in the figure) or modified sequencing adapters as described herein to double-stranded template DNA sequences, followed by primer extension using 5mC or 5hmC to generate a methylated copy (z.e., a 5mC or 5hmC copy of the genomic strand, as shown by strand 1308, which is complementary to the template strand 1306). Cytosine conversion comprising the use of a deaminating enzyme is then performed, which results in the conversion of applicable cytosines in the methylation workflow (or methylation) strand.
[0232] FIG. 14 and FIG. 15 provide schematic illustrations that further describe the process by which the assay described in FIG. 13 is performed to generate genomic and methylation strands from the same sample. As depicted in FIG. 14, the adapter sequences (e.g., the standard 5mC “stubby” methylation sequencing adapter sequences) are ligated to doublestranded DNA inserts, and a ligation cleanup step is performed prior to performing linear amplification during which the DNA is denatured and a Q5 polymerase incorporates 5hmCs and standard A, T, and G nucleotides to form the “genomic strand”, i.e., the strand that comprises only 5hmC nucleotides at cytosine positions and will not undergo erroneous conversion. The other strand, i.e. the “methylation strand”, still comprises the original adapter sequence comprising 5mC, which has an approximately 5% chance of undergoing an erroneous conversion (mutation) to uracil / thymine.
[0233] In FIG. 15, “stubby” adaptor sequences that have a 5hmC at the Read 1 sequencing primer binding site were ligated to the double-stranded DNA inserts, where the 5hmC blocks erroneous conversion. After performing the ligation and cleanup steps, the molecules undergo linear amplification. As a result of using the custom 5hmC adapter sequences, which prove better protected from erroneous conversion of 5mC to uracil / thymine, relative to 5mC. As a result, the only real difference between the genomic and methylation strands following linear amplification is that the methylation strand retains the 5hmC.
[0234] FIG. 16 depicts a non-limiting example of percent sequence read passing filter data obtained using the assay as described in FIG. 13. In the case that not a single modified cytosine was erroneously converted, the nucleotide sequences between the two corresponding strands (z.e., the genomic and methylation workflow strands generated in the same library from the same sample) should be identical. The box plot depicted in FIG. 16 plots the percentage of sequence reads passing the quality filter per sample index for the genomic (gen) and methylation workflow (methyl) strands as obtained using either the standard methyl-seq adapter sequences or a modified 5hmC adapter sequence (modified sequencing adapter 1; FIG. 9) as described herein. Boxes 1602 and 1604 summarize the percent sequence read data obtained using the standard methyl-seq adapter sequences. Boxes 1606 and 1608 summarize the percent sequence read data obtained using the custom 5hmC adapter sequences. A comparison between boxes 1602 and 1604 reveals a 21.4% difference in the percentage of reads passing filter between the genomic and methylation strands when using the standard methyl-seq adapter sequences. In contrast, comparison of boxes 1606 and 1608 indicate that the difference in percentage of sequence reads passing filter was much smaller (11.6%) when using the custom 5hmC adapter sequences.
[0235] FIG. 17 provides a plot of the ratio of the percentage sequence reads passing filter data obtained for the genomic and methylation strands using the standard methyation sequencing adapter sequences (1702), and using the custom 5hmC adapter sequences(1704). A ratio of one would indicate that an equal number of sequence reads pass the quality filter for the genomic and methylation strands. The data obtained using the custom 5hmC adapter sequences (1704) is closer to the ideal ratio of one than that obtained using the standard methyl sequencing adapters (1702).
[0236] Collectively, the data presented in FIG. 12, FIG. 16, and FIG. 17 is indicative that replacement of 5mCs with 5hmCs in modified methyl-seq adapter sequences increases the number of sequence reads passing the quality filter. These results were confirmed using two different orthogonal tests: assessment of the percentage of reads passing the quality filter in matched libraries (FIG. 12), and in a single workflow assay that generated genomic and methylated strands in the same library from the same sample (FIGS. 14 and 15). The potential for error reduction and reduced data loss make this an important improvement for methylation workflows.
EXEMPLARY IMPLEMENTATIONS
[0237] Exemplary implementations of the methods and systems described herein include:
1. A sequencing adapter comprising an oligonucleotide sequence that comprises at least one modified base, wherein the at least one modified base is not 5-methylcytosine, and wherein a rate of conversion of the at least one modified base to uracil when contacted with a deaminating enzyme or enzyme combination is less than that of 5-methylcytosine.
2. The sequencing adaptor of clause 1, wherein the modified base is inosine, 5-nitroindole, N4-ethyl-deoxycytidine, 5-propynylcytosine, 5-vinylcytosine, 5-ethynylcytosine, pyrrolo- deoxycytidine, or propynyl-deoxy cytidine.
3. The sequencing adaptor of clause 1, wherein the modified base is a modified cytosine.
4. The sequencing adapter of clause 3, wherein at least one modified cytosine is located within a specified subsequence or at one or more specified positions within the oligonucleotide sequence.
5. The sequencing adapter of clause 1 or clause 3, wherein the at least one modified cytosine is 5-hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, 5-formylcytosine, 5- carboxycytosine, or a combination thereof.
6. The sequencing adapter of clause 1 or clause 3, wherein the at least one modified cytosine is 5-hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, or a combination thereof.
7. The sequencing adapter of clause 1 or clause 3, wherein the at least one modified cytosine is 5-hydroxymethylcytosine.
8. The sequencing adapter of any one of clauses 1 to 7, wherein the oligonucleotide sequence comprises 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 modified bases.
9. The sequencing adapter of any one of clauses 1 to 8, wherein the oligonucleotide sequence comprises at least four cytosines, and wherein three cytosines closest to the 3’ end of the oligonucleotide sequence are modified cytosines.
10. The sequencing adapter of any of clauses 1 to 9, wherein all or substantially all of the cytosines of the oligonucleotide sequence are modified cytosines. 11. The sequencing adapter of any of clauses 1 to 10, wherein all or substantially all of the cytosines of the oligonucleotide sequence are 5-hydroxymethylcytosines.
12. The sequencing adapter of any one of clauses 1 to 11, wherein the sequencing adapter comprises two complementary oligonucleotide sequences, each comprising at least four cytosines, and wherein three cytosines closest to a 3’ end or a 5’ end in at least one of the two complementary oligonucleotide sequences are modified cytosines.
13. The sequencing adapter of any one of clauses 1 to 12, wherein the deaminating enzyme is an APOB EC enzyme.
14. The sequencing adapter of any one of clauses 1 to 13, wherein the oligonucleotide sequence is between about 20 and 100 nucleotides in length.
15. The sequencing adapter of any one of clauses 1 to 14, wherein the oligonucleotide sequence comprises at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 contiguous nucleotides selected from the sequence 5’ AAT GAT ACG GCG ACC ACC GA 3’ (SEQ ID NO: 1) or its complement.
16. The sequencing adapter of any one of clauses 1 to 14, wherein the oligonucleotide sequence comprises at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 contiguous nucleotides selected from the sequence 5’ CAA GCA GAA GAC GGC ATA CGA GAT 3’ (SEQ ID NO: 2) or its complement.
17. The sequencing adapter of any of clauses 1 to 14, wherein the oligonucleotide sequence comprises at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, or 33 contiguous nucleotides selected from the sequence 5’ ACA CTC TTT CCC TAC ACG ACG CTC TTC CGA TCT 3’ (SEQ ID NO: 3) or its complement.
18. The sequencing adapter of any of clauses 1 to 14, wherein the oligonucleotide sequence comprises at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, or 34 contiguous nucleotides selected from the sequence 5’ GTG ACT GGA GTT CAG ACG TGT GCT CTT CCG ATC T 3’ (SEQ ID NO: 4) or its complement.
19. A method for performing nucleic acid sequencing, comprising: a) providing a plurality of nucleic acid molecules obtained from a sample from a subject; b) performing an enzymatic ligation of one or more of the sequencing adapters of any one of claims 1 to 18 onto the plurality of nucleic acid molecules; c) sequencing, by a sequencer, the ligated nucleic acid molecules to obtain a plurality of sequence reads derived from the sample; and d) receiving, at one or more processors, sequence read data for the plurality of sequence reads derived from the sample.
20. The method of clause 19, wherein the enzymatic ligation comprises single- stranded ligation.
21. The method of clause 19, wherein the enzymatic ligation comprises double-stranded ligation.
22. The method of any of clauses 19 to 21, wherein the nucleic acid sequencing comprises a whole genome sequencing, whole exome sequencing, or targeted sequencing method.
23. The method of any of clauses claim 19 to 22, wherein the nucleic acid sequencing comprises a methylation sequencing method.
24. The method of any of clauses 19 to 23, wherein the methylation sequencing method comprises an enzymatic cytosine conversion step.
25. The method of any of clauses 19 to 24, wherein the sample comprises a tissue sample or a buffy coat sample.
26. The method of clause 25, further comprising shearing nucleic acids extracted from the sample to provide the plurality of nucleic acid molecules.
27. The method of any one of clauses 19 to 26, further comprising performing an end repair reaction on the plurality of nucleic acid molecules prior to performing the enzymatic ligation.
28. The method of any one of clauses 19 to 27, further comprising performing an A-tailing reaction on the plurality of nucleic acid molecules prior to performing the enzymatic ligation.
29. The method of any one of clauses 19 to 28, further comprising contacting the ligated nucleic acid molecules with a TET2 enzyme to oxidize 5-methyl-cytosine (5mC) or 5- hydroxymethyl-cytosine (5hmC) to 5-carboxycytosine (5caC) prior to performing the sequencing step.
30. The method of any one of clauses 19 to 29, further comprising contacting the ligated nucleic acid molecules with a combination of TET2 and T4-PGT enzymes to convert 5- methyl-cytosine (5mC) or 5-hydroxymethyl-cytosine (5hmC) to 5-(D-glucosyl)oxymethyl- cytosine prior to performing the sequencing step.
31. The method of clause 29 or clause 30, further comprising contacting the ligated nucleic acid molecules with an APOBEC enzyme to convert cytosines to uracil prior to performing the sequencing step.
32. The method of any one of clauses 19 to 31, further comprising performing a nucleic acid amplification reaction to generate amplified nucleic acid molecules prior to performing the sequencing step.
33. The method of clause 32, wherein the nucleic acid amplification reaction comprises a polymerase chain reaction.
34. The method of clause 32, wherein the nucleic acid amplification reaction comprises a rolling circle amplification reaction.
35. The method of any one of clauses 19 to 34, further comprising capturing a subset of nucleic acid molecules from the amplified nucleic acid molecules prior to performing the sequencing step.
36. The method of any one of clauses 19 to 35, wherein the sequencer is a next-generation sequencer.
37. The method of clause 36, wherein the next- generation sequencer comprises a cyclic array sequencer, a nanopore sequencer, or a single mode waveguide sequencer.
38. The method of any one of clauses 19 to 37, further comprising determining a methylation status for each of a plurality of genomic loci based on the sequence read data.
39. The method of any one of clauses 19 to 38, further comprising diagnosing or confirming a diagnosis of disease in the subject based at least in part on a variant or a methylation signature identified in the sequence read data.
40. The method of clause 39, wherein the variant comprises a single nucleotide variant or a copy number alteration.
41. The method of any one of clauses 19 to 40, further comprising detecting minimum residual disease in the subject based on the sequence read data.
42. The method of clause 40 or clause 41, wherein the disease is cancer. 43. A method comprising: providing a plurality of nucleic acid molecules obtained from a sample from a subject; ligating one or more sequencing adapters onto one or more nucleic acid molecules from the plurality of nucleic acid molecules, wherein the one or more sequencing adapters comprise an oligonucleotide sequence comprising at least one modified cytosine, wherein the at least one modified cytosine is not 5-methylcytosine, and wherein a rate of conversion of the at least one modified cytosine to uracil when contacted with a deaminating enzyme is less than that of 5-methylcytosine; amplifying the one or more ligated nucleic acid molecules from the plurality of nucleic acid molecules; capturing amplified nucleic acid molecules from the amplified nucleic acid molecules; sequencing, by a sequencer, the captured nucleic acid molecules to obtain a plurality of sequence reads that represent the captured nucleic acid molecules; receiving, at one or more processors, sequence read data for the plurality of sequence reads; and determining, using the one or more processors, a methylation status for each of a plurality of genomic loci based on the sequence read data.
44. The method of clause 43, further comprising identifying one or more variant sequences based on the sequence read data.
45. The method of clause 43 or clause 44, wherein the subject is being screened for cancer.
46. The method of clause 43 or clause 44, wherein the subject is suspected of having cancer.
47. The method of clause 43 or clause 44, wherein the subject is determined to have cancer.
48. The method of any one of clauses 45 to 47, wherein the cancer is a B cell cancer (multiple myeloma), a melanoma, breast cancer, lung cancer, bronchus cancer, colorectal cancer, prostate cancer, pancreatic cancer, stomach cancer, ovarian cancer, urinary bladder cancer, brain cancer, central nervous system cancer, peripheral nervous system cancer, esophageal cancer, cervical cancer, uterine cancer, endometrial cancer, cancer of an oral cavity, cancer of a pharynx, liver cancer, kidney cancer, testicular cancer, biliary tract cancer, small bowel cancer, appendix cancer, salivary gland cancer, thyroid gland cancer, adrenal gland cancer, osteosarcoma, chondrosarcoma, a cancer of hematological tissue, an adenocarcinoma, an inflammatory myofibroblastic tumor, a gastrointestinal stromal tumor (GIST), colon cancer, multiple myeloma (MM), myelodysplastic syndrome (MDS), myeloproliferative disorder (MPD), acute lymphocytic leukemia (ALL), acute myelocytic leukemia (AML), chronic myelocytic leukemia (CML), chronic lymphocytic leukemia (CLL), polycythemia Vera, Hodgkin lymphoma, non-Hodgkin lymphoma (NHL), soft-tissue sarcoma, fibrosarcoma, myxosarcoma, liposarcoma, osteogenic sarcoma, chordoma, angiosarcoma, endotheliosarcoma, lymphangiosarcoma, lymphangioendotheliosarcoma, synovioma, mesothelioma, Ewing's tumor, leiomyosarcoma, rhabdomyosarcoma, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary carcinoma, papillary adenocarcinomas, medullary carcinoma, bronchogenic carcinoma, renal cell carcinoma, hepatoma, bile duct carcinoma, choriocarcinoma, seminoma, embryonal carcinoma, Wilms' tumor, bladder carcinoma, epithelial carcinoma, glioma, astrocytoma, medulloblastoma, craniopharyngioma, ependymoma, pinealoma, hemangioblastoma, acoustic neuroma, oligodendroglioma, meningioma, neuroblastoma, retinoblastoma, follicular lymphoma, diffuse large B-cell lymphoma, mantle cell lymphoma, hepatocellular carcinoma, thyroid cancer, gastric cancer, head and neck cancer, small cell cancer, essential thrombocythemia, agnogenic myeloid metaplasia, hypereosinophilic syndrome, systemic mastocytosis, familiar hypereosinophilia, chronic eosinophilic leukemia, neuroendocrine cancers, or a carcinoid tumor.
49. The method of any one of clauses 45 to 47, wherein the cancer comprises acute lymphoblastic leukemia (Philadelphia chromosome positive), acute lymphoblastic leukemia (precursor B-cell), acute myeloid leukemia (FLT3+), acute myeloid leukemia (with an IDH2 mutation), anaplastic large cell lymphoma, basal cell carcinoma, B-cell chronic lymphocytic leukemia, bladder cancer, breast cancer (HER2 overexpressed/amplified), breast cancer (HER2+), breast cancer (HR+, HER2-), cervical cancer, cholangiocarcinoma, chronic lymphocytic leukemia, chronic lymphocytic leukemia (with 17p deletion), chronic myelogenous leukemia, chronic myelogenous leukemia (Philadelphia chromosome positive), classical Hodgkin lymphoma, colorectal cancer, colorectal cancer (dMMR/MSLH), colorectal cancer (KRAS wild type), cryopyrin-associated periodic syndrome, a cutaneous T- cell lymphoma, dermatofibrosarcoma protuberans, a diffuse large B-cell lymphoma, fallopian tube cancer, a follicular B-cell non-Hodgkin lymphoma, a follicular lymphoma, gastric cancer, gastric cancer (HER2+), gastroesophageal junction (GEJ) adenocarcinoma, a gastrointestinal stromal tumor, a gastrointestinal stromal tumor (KIT+), a giant cell tumor of the bone, a glioblastoma, granulomatosis with polyangiitis, a head and neck squamous cell carcinoma, a hepatocellular carcinoma, Hodgkin lymphoma, juvenile idiopathic arthritis, lupus erythematosus, a mantle cell lymphoma, medullary thyroid cancer, melanoma, a melanoma with a BRAF V600 mutation, a melanoma with a BRAF V600E or V600K mutation, Merkel cell carcinoma, multicentric Castleman's disease, multiple hematologic malignancies including Philadelphia chromosome-positive ALL and CML, multiple myeloma, myelofibrosis, a non-Hodgkin’s lymphoma, a nonresectable subependymal giant cell astrocytoma associated with tuberous sclerosis, a non-small cell lung cancer, a non-small cell lung cancer (ALK+), a non-small cell lung cancer (PD-L1+), a non-small cell lung cancer (with ALK fusion or ROS1 gene alteration), a non-small cell lung cancer (with BRAF V600E mutation), a non-small cell lung cancer (with an EGFR exon 19 deletion or exon 21 substitution (L858R) mutations), a non-small cell lung cancer (with an EGFR T790M mutation), ovarian cancer, ovarian cancer (with a BRCA mutation), pancreatic cancer, a pancreatic, gastrointestinal, or lung origin neuroendocrine tumor, a pediatric neuroblastoma, a peripheral T-cell lymphoma, peritoneal cancer, prostate cancer, a renal cell carcinoma, rheumatoid arthritis, a small lymphocytic lymphoma, a soft tissue sarcoma, a solid tumor (MSLH/dMMR), a squamous cell cancer of the head and neck, a squamous non-small cell lung cancer, thyroid cancer, a thyroid carcinoma, urothelial cancer, a urothelial carcinoma, or Waldenstrom's macroglobulinemia.
50. The method of any one of clauses 45 to 47, further comprising treating the subject with an anti-cancer therapy.
51. The method of clause 50, wherein the anti-cancer therapy comprises a targeted anticancer therapy.
52. The method of clause 51, wherein the targeted anti-cancer therapy comprises abemaciclib (Verzenio), abiraterone acetate (Zytiga), acalabrutinib (Calquence), ado-trastuzumab emtansine (Kadcyla), afatinib dimaleate (Gilotrif), aldesleukin (Proleukin), alectinib (Alecensa), alemtuzumab (Campath), alitretinoin (Panretin), alpelisib (Piqray), amivantamab- vmjw (Rybrevant), anastrozole (Arimidex), apalutamide (Erleada), asciminib hydrochloride (Scemblix), atezolizumab (Tecentriq), avapritinib (Ayvakit), avelumab (Bavencio), axicabtagene ciloleucel (Yescarta), axitinib (Inlyta), belantamab mafodotin-blmf (Blenrep), belimumab (Benlysta), belinostat (Beleodaq), belzutifan (Welireg), bevacizumab (Avastin), bexarotene (Targretin), binimetinib (Mektovi), blinatumomab (Blincyto), bortezomib (Velcade), bosutinib (Bosulif), brentuximab vedotin (Adcetris), brexucabtagene autoleucel (Tecartus), brigatinib (Alunbrig), cabazitaxel (Jevtana), cabozantinib (Cabometyx), cabozantinib (Cabometyx, Cometriq), canakinumab (Haris), capmatinib hydrochloride (Tabrecta), carfilzomib (Kyprolis), cemiplimab-rwlc (Libtayo), ceritinib (LDK378/Zykadia), cetuximab (Erbitux), cobimetinib (Cotellic), copanlisib hydrochloride (Aliqopa), crizotinib (Xalkori), dabrafenib (Tafinlar), dacomitinib (Vizimpro), daratumumab (Darzalex), daratumumab and hyaluronidase-fihj (Darzalex Faspro), darolutamide (Nubeqa), dasatinib (Sprycel), denileukin diftitox (Ontak), denosumab (Xgeva), dinutuximab (Unituxin), dostarlimab-gxly (Jemperli), durvalumab (Imfinzi), duvelisib (Copiktra), elotuzumab (Empliciti), enasidenib mesylate (Idhifa), encorafenib (Braftovi), enfortumab vedotin-ejfv (Padcev), entrectinib (Rozlytrek), enzalutamide (Xtandi), erdafitinib (Balversa), erlotinib (Tarceva), everolimus (Afinitor), exemestane (Aromasin), fam-trastuzumab deruxtecan-nxki (Enhertu), fedratinib hydrochloride (Inrebic), fulvestrant (Faslodex), gefitinib (Iressa), gemtuzumab ozogamicin (Mylotarg), gilteritinib (Xospata), glasdegib maleate (Daurismo), hyaluronidase-zzxf (Phesgo), ibrutinib (Imbruvica), ibritumomab tiuxetan (Zevalin), idecabtagene vicleucel (Abecma), idelalisib (Zydelig), imatinib mesylate (Gleevec), infigratinib phosphate (Truseltiq), inotuzumab ozogamicin (Besponsa), iobenguane 1131 (Azedra), ipilimumab (Yervoy), isatuximab-irfc (Sarclisa), ivosidenib (Tibsovo), ixazomib citrate (Ninlaro), lanreotide acetate (Somatuline Depot), lapatinib (Tykerb), larotrectinib sulfate (Vitrakvi), lenvatinib mesylate (Lenvima), letrozole (Femara), lisocabtagene maraleucel (Breyanzi), loncastuximab tesirine-lpyl (Zynlonta), lorlatinib (Lorbrena), lutetium Lu 177-dotatate (Lutathera), margetuximab-cmkb (Margenza), midostaurin (Rydapt), mobocertinib succinate (Exkivity), mogamulizumab-kpkc (Poteligeo), moxetumomab pasudotox-tdfk (Lumoxiti), naxitamab-gqgk (Danyelza), necitumumab (Portrazza), neratinib maleate (Nerlynx), nilotinib (Tasigna), niraparib tosylate monohydrate (Zejula), nivolumab (Opdivo), obinutuzumab (Gazyva), ofatumumab (Arzerra), olaparib (Lynparza), olaratumab (Lartruvo), osimertinib (Tagrisso), palbociclib (Ibrance), panitumumab (Vectibix), panobinostat (Farydak), pazopanib (Votrient), pembrolizumab (Keytruda), pemigatinib (Pemazyre), pertuzumab (Perjeta), pexidartinib hydrochloride (Turalio), polatuzumab vedotin-piiq (Polivy), ponatinib hydrochloride (Iclusig), pralatrexate (Folotyn), pralsetinib (Gavreto), radium 223 dichloride (Xofigo), ramucirumab (Cyramza), regorafenib (Stivarga), ribociclib (Kisqali), ripretinib (Qinlock), rituximab (Rituxan), rituximab and hyaluronidase human (Rituxan Hycela), romidepsin (Istodax), rucaparib camsylate (Rubraca), ruxolitinib phosphate (Jakafi), sacituzumab govitecan-hziy (Trodelvy), seliciclib, selinexor (Xpovio), selpercatinib (Retevmo), selumetinib sulfate (Koselugo), siltuximab (Sylvant), sipuleucel-T (Provenge), sirolimus protein-bound particles (Fyarro), sonidegib (Odomzo), sorafenib (Nexavar), sotorasib (Lumakras), sunitinib (Sutent), tafasitamab-cxix (Monjuvi), tagraxofusp-erzs (Elzonris), talazoparib tosylate (Talzenna), tamoxifen (Nolvadex), tazemetostat hydrobromide (Tazverik), tebentafusp-tebn (Kimmtrak), temsirolimus (Torisel), tepotinib hydrochloride (Tepmetko), tisagenlecleucel (Kymriah), tisotumab vedotin-tftv (Tivdak), tocilizumab (Actemra), tofacitinib (Xeljanz), tositumomab (Bexxar), trametinib (Mekinist), trastuzumab (Herceptin), tretinoin (Vesanoid), tivozanib hydrochloride (Fotivda), toremifene (Fareston), tucatinib (Tukysa), umbralisib tosylate (Ukoniq), vandetanib (Caprelsa), vemurafenib (Zelboraf), venetoclax (Venclexta), vismodegib (Erivedge), vorinostat (Zolinza), zanubrutinib (Brukinsa), ziv-aflibercept (Zaltrap), or any combination thereof.
53. The method of any one of clauses 43 to 52, further comprising obtaining the sample from the subject.
54. The method of any one of clauses 43 to 53, wherein the sample comprises a tissue biopsy sample, a liquid biopsy sample, or a normal control.
55. The method of clause 54, wherein the sample is a liquid biopsy sample and comprises blood, plasma, cerebrospinal fluid, sputum, stool, urine, or saliva.
56. The method of clause 54, wherein the sample is a liquid biopsy sample and comprises circulating tumor cells (CTCs).
57. The method of clause 54, wherein the sample is a liquid biopsy sample and comprises cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), or any combination thereof.
58. The method of any one of clauses 43 to 57, wherein the plurality of nucleic acid molecules comprises a mixture of tumor nucleic acid molecules and non-tumor nucleic acid molecules.
59. The method of clause 58, wherein the tumor nucleic acid molecules are derived from a tumor portion of a heterogeneous tissue biopsy sample, and the non-tumor nucleic acid molecules are derived from a normal portion of the heterogeneous tissue biopsy sample. 60. The method of clause 58, wherein the sample comprises a liquid biopsy sample, and wherein the tumor nucleic acid molecules are derived from a circulating tumor DNA (ctDNA) fraction of the liquid biopsy sample, and the non-tumor nucleic acid molecules are derived from a non-tumor, cell-free DNA (cfDNA) fraction of the liquid biopsy sample.
61. The method of any one of clauses 43 to 60, wherein the one or more adapters comprise amplification primers, flow cell adaptor sequences, substrate adapter sequences, or sample index sequences.
62. The method of any one of clauses 43 to 61, wherein the captured nucleic acid molecules are captured from the amplified nucleic acid molecules by hybridization to one or more bait molecules.
63. The method of clause 62, wherein the one or more bait molecules comprise one or more nucleic acid molecules, each comprising a region that is complementary to a region of a captured nucleic acid molecule.
64. The method of any one of clauses 43 to 63, wherein amplifying nucleic acid molecules comprises performing a polymerase chain reaction (PCR) amplification technique, a non- PCR amplification technique, or an isothermal amplification technique.
65. The method of any one of clauses 43 to 64, wherein the sequencing comprises use of a massively parallel sequencing (MPS) technique, whole genome sequencing (WGS), whole exome sequencing, targeted sequencing, direct sequencing, or Sanger sequencing technique.
66. The method of clause 65, wherein the sequencing comprises massively parallel sequencing, and the massively parallel sequencing technique comprises next generation sequencing (NGS).
67. The method of any one of clauses 43 to 66, wherein the sequencer comprises a next generation sequencer.
68. The method of any one of clauses 43 to 67, wherein one or more of the plurality of sequencing reads overlap one or more gene loci within one or more subgenomic intervals in the sample.
69. The method of clause 68, wherein the one or more gene loci comprises between 10 and 20 loci, between 10 and 40 loci, between 10 and 60 loci, between 10 and 80 loci, between 10 and 100 loci, between 10 and 150 loci, between 10 and 200 loci, between 10 and 250 loci, between 10 and 300 loci, between 10 and 350 loci, between 10 and 400 loci, between 10 and 450 loci, between 10 and 500 loci, between 20 and 40 loci, between 20 and 60 loci, between 20 and 80 loci, between 20 and 100 loci, between 20 and 150 loci, between 20 and 200 loci, between 20 and 250 loci, between 20 and 300 loci, between 20 and 350 loci, between 20 and 400 loci, between 20 and 500 loci, between 40 and 60 loci, between 40 and 80 loci, between 40 and 100 loci, between 40 and 150 loci, between 40 and 200 loci, between 40 and 250 loci, between 40 and 300 loci, between 40 and 350 loci, between 40 and 400 loci, between 40 and 500 loci, between 60 and 80 loci, between 60 and 100 loci, between 60 and 150 loci, between 60 and 200 loci, between 60 and 250 loci, between 60 and 300 loci, between 60 and 350 loci, between 60 and 400 loci, between 60 and 500 loci, between 80 and 100 loci, between 80 and 150 loci, between 80 and 200 loci, between 80 and 250 loci, between 80 and 300 loci, between 80 and 350 loci, between 80 and 400 loci, between 80 and 500 loci, between 100 and 150 loci, between 100 and 200 loci, between 100 and 250 loci, between 100 and 300 loci, between 100 and 350 loci, between 100 and 400 loci, between 100 and 500 loci, between 150 and 200 loci, between 150 and 250 loci, between 150 and 300 loci, between 150 and 350 loci, between 150 and 400 loci, between 150 and 500 loci, between 200 and 250 loci, between 200 and 300 loci, between 200 and 350 loci, between 200 and 400 loci, between 200 and 500 loci, between 250 and 300 loci, between 250 and 350 loci, between 250 and 400 loci, between 250 and 500 loci, between 300 and 350 loci, between 300 and 400 loci, between 300 and 500 loci, between 350 and 400 loci, between 350 and 500 loci, or between 400 and 500 loci.
70. The method of clause 68 or clause 69, wherein the one or more gene loci comprise ABL1, ACVR1B, AKT1, AKT2, AKT3, ALK, ALOX12B, AMER1, APC, AR, ARAF, ARFRP1, ARID1A, ASXL1, ATM, ATR, ATRX, AURKA, AURKB, AXIN1, AXL, BAP1, BARD1, BCL2, BCL2L1, BCL2L2, BCL6, BCOR, BCORL1, BCR, BRAF, BRCA1, BRCA2, BRD4, BRIP1, BTG1, BTG2, BTK, CALR, CARD11, CASP8, CBFB, CBL, CCND1, CCND2, CCND3, CCNE1, CD22, CD274, CD70, CD74, CD79A, CD79B, CDC73, CDH1, CDK12, CDK4, CDK6, CDK8, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CDKN2C, CEBPA, CHEK1, CHEK2, CIC, CREBBP, CRKL, CSF1R, CSF3R, CTCF, CTNNA1, CTNNB1, CUL3, CUL4A, CXCR4, CYP17A1, DAXX, DDR1, DDR2, DIS3, DNMT3A, DOT1L, EED, EGFR, EMSY (Cl lorf30), EP300, EPHA3, EPHB1, EPHB4, ERBB2, ERBB3, ERBB4, ERCC4, ERG, ERRFI1, ESRI, ETV4, ETV5, ETV6, EWSR1, EZH2, EZR, FAM46C, FANCA, FANCC, FANCG, FANCL, FAS, FBXW7, FGF10, FGF12, FGF14, FGF19, FGF23, FGF3, FGF4, FGF6, FGFR1, FGFR2, FGFR3, FGFR4, FH, FLCN, FLT1, FLT3, F0XL2, FUBP1, GABRA6, GATA3, GATA4, GATA6, GID4 (C17orf39), GNA11, GNA13, GNAQ, GNAS, GRM3, GSK3B, H3F3A, HDAC1, HGF, HNF1A, HRAS, HSD3B1, ID3, IDH1, IDH2, IGF1R, IKBKE, IKZF1, INPP4B, IRF2, IRF4, IRS2, JAK1, JAK2, JAK3, JUN, KDM5A, KDM5C, KDM6A, KDR, KEAP1, KEL, KIT, KLHL6, KMT2A (MLL), KMT2D (MLL2), KRAS, LTK, LYN, MAF, MAP2K1, MAP2K2, MAP2K4, MAP3K1, MAP3K13, MAPK1, MCL1, MDM2, MDM4, MED12, MEF2B, MEN1, MERTK, MET, MITF, MKNK1, MLH1, MPL, MRE11A, MSH2, MSH3, MSH6, MST1R, MTAP, MTOR, MUTYH, MYB, MYC, MYCL, MYCN, MYD88, NBN, NF1, NF2, NFE2L2, NFKBIA, NKX2-1, NOTCH1, NOTCH2, NOTCH3, NPM1, NRAS, NT5C2, NTRK1, NTRK2, NTRK3, NUTM1, P2RY8, PALB2, PARK2, PARP1, PARP2, PARP3, PAX5, PBRM1, PDCD1, PDCD1LG2, PDGFRA, PDGFRB, PDK1, PIK3C2B, PIK3C2G, PIK3CA, PIK3CB, PIK3R1, PIM1, PMS2, POLDI, POLE, PPARG, PPP2R1A, PPP2R2A, PRDM1, PRKAR1A, PRKCI, PTCHI, PTEN, PTPN11, PTPRO, QKI, RAC1, RAD21, RAD51, RAD51B, RAD51C, RAD51D, RAD52, RAD54L, RAFI, RARA, RBI, RBM10, REL, RET, RICTOR, RNF43, ROS1, RPTOR, RSPO2, SDC4, SDHA, SDHB, SDHC, SDHD, SETD2, SF3B1, SGK1, SLC34A2, SMAD2, SMAD4, SMARCA4, SMARCB1, SMO, SNCAIP, SOCS1, SOX2, SOX9, SPEN, SPOP, SRC, STAG2, STAT3, STK11, SUFU, SYK, TBX3, TEK, TERC, TERT, TET2, TGFBR2, TIPARP, TMPRSS2, TNFAIP3, TNFRSF14, TP53, TSC1, TSC2, TYRO3, U2AF1, VEGFA, VHL, WHSCI, WHSC1L1, WT1, XPO1, XRCC2, ZNF217, ZNF703, or any combination thereof.
71. The method of clause 68 or clause 69, wherein the one or more gene loci comprise ABL, ALK, ALL, B4GALNT1, BAFF, BCL2, BRAF, BRCA, BTK, CD19, CD20, CD3, CD30, CD319, CD38, CD52, CDK4, CDK6, CML, CRACC, CS1, CTLA-4, dMMR, EGFR, ERBB1, ERBB2, FGFR1-3, FLT3, GD2, HDAC, HER1, HER2, HR, IDH2, IL-ip, IL-6, IL- 6R, JAK1, JAK2, JAK3, KIT, KRAS, MEK, MET, MSI-H, mTOR, PARP, PD-1, PDGFR, PDGFRa, PDGFRP, PD-L1, PI3K5, PIGF, PTCH, RAF, RANKL, RET, ROS1, SLAMF7, VEGF, VEGFA, VEGFB, or any combination thereof.
72. The method of any one of clauses 43 to 71, further comprising generating, by the one or more processors, a report indicating the methylation status determined for each of the plurality of genomic loci.
73. The method of clause 72, further comprising transmitting the report to a healthcare provider. 74. The method of clause 73, wherein the report is transmitted via a computer network or a peer-to-peer connection.
75. A method for diagnosing a disease, the method comprising: diagnosing that a subject has the disease based on a determination of a methylation signature for a sample from the subject, wherein the methylation signature is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to the method of any one of clauses 19 to 74.
76. A method of selecting an anti-cancer therapy, the method comprising: responsive to determining a methylation signature for a sample from a subject, selecting an anti-cancer therapy for the subject, wherein the methylation signature is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to the method of any one of clauses 19 to 74.
77. A method of treating a cancer in a subject, comprising: responsive to determining a methylation signature for a sample from the subject, administering an effective amount of an anti-cancer therapy to the subject, wherein the methylation signature is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to the method of any one of clauses 19 to 74.
78. A method for monitoring cancer progression or recurrence in a subject, the method comprising: determining a first methylation signature in a first sample obtained from the subject at a first time point, wherein the first methylation signature is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to the method of any one of clauses 19 to 74; determining a second methylation signature in a second sample obtained from the subject at a second time point; and comparing the first methylation signature to the second methylation signature, thereby monitoring the cancer progression or recurrence.
79. The method of clause 78, wherein the second methylation signature for the second sample is determined based on the sequence read data generated, or the methylation status determined for each of a plurality of genomic loci, according to the method of any one of clauses 19 to 74. 80. The method of clause 78 or clause 79, further comprising selecting an anti-cancer therapy for the subject in response to the cancer progression.
81. The method of clause 78 or clause 79, further comprising administering an anti-cancer therapy to the subject in response to the cancer progression.
82. The method of clause 78 or clause 79, further comprising adjusting an anti-cancer therapy for the subject in response to the cancer progression.
83. The method of any one of clauses 80 to 82, further comprising adjusting a dosage of the anti-cancer therapy or selecting a different anti-cancer therapy in response to the cancer progression.
84. The method of clause 83, further comprising administering the adjusted anti-cancer therapy to the subject.
85. The method of any one of clauses 78 to 84, wherein the first time point is before the subject has been administered an anti-cancer therapy, and wherein the second time point is after the subject has been administered the anti-cancer therapy.
86. The method of any one of clauses 78 to 85, wherein the subject has a cancer, is at risk of having a cancer, is being routine tested for cancer, or is suspected of having a cancer.
87. The method of any one of clauses 78 to 86, wherein the cancer is a solid tumor.
88. The method of any one of clauses 78 to 87, wherein the cancer is a hematological cancer.
89. The method of any one of clauses 80 to 88, wherein the anti-cancer therapy comprises chemotherapy, radiation therapy, immunotherapy, hormone therapy, a targeted therapy, or surgery.
[0238] It should be understood from the foregoing that, while particular implementations of the disclosed methods and systems have been illustrated and described, various modifications can be made thereto and are contemplated herein. It is also not intended that the invention be limited by the specific examples provided within the specification. While the invention has been described with reference to the aforementioned specification, the descriptions and illustrations of the preferable embodiments herein are not meant to be construed in a limiting sense. Furthermore, it shall be understood that all aspects of the invention are not limited to the specific depictions, configurations or relative proportions set forth herein which depend upon a variety of conditions and variables. Various modifications in form and detail of the embodiments of the invention will be apparent to a person skilled in the art. It is therefore contemplated that the invention shall also cover any such modifications, variations and equivalents.

Claims

CLAIMS What is claimed is:
1. A sequencing adapter comprising an oligonucleotide sequence that comprises at least one modified base, wherein the at least one modified base is not 5-methylcytosine, and wherein a rate of conversion of the at least one modified base to uracil when contacted with a deaminating enzyme or enzyme combination is less than that of 5-methylcytosine.
2. The sequencing adaptor of claim 1, wherein the at least one modified base comprises inosine, 5-nitroindole, N4-ethyl-deoxycytidine, 5-propynylcytosine, 5-vinylcytosine, 5- ethynylcytosine, pyrrolo-deoxycytidine, or propynyl-deoxycytidine.
3. The sequencing adaptor of claim 1, wherein the at least one modified base comprises a modified cytosine.
4. The sequencing adapter of claim 1, wherein the at least one modified cytosine comprises 5- hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, 5-formylcytosine, 5- carboxycytosine, or a combination thereof.
5. The sequencing adapter of claim 1, wherein the at least one modified cytosine comprises 5- hydroxymethylcytosine, 5-(D-glucosyl)oxymethylcytosine, or a combination thereof.
6. The sequencing adapter of claim 1, wherein the at least one modified cytosine comprises 5- hydroxymethylcytosine.
7. The sequencing adapter of claim 1, wherein the oligonucleotide sequence comprises 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 modified bases.
8. The sequencing adapter of claim 1, wherein the oligonucleotide sequence comprises at least four cytosines, and wherein three cytosines closest to the 3’ end of the oligonucleotide sequence are modified cytosines.
9. The sequencing adapter of claim 1, wherein all or substantially all of the cytosines of the oligonucleotide sequence are modified cytosines.
10. The sequencing adapter of claim 1, wherein the sequencing adapter comprises two complementary oligonucleotide sequences, each comprising at least four cytosines, and wherein three cytosines closest to a 3’ end or a 5’ end in at least one of the two complementary oligonucleotide sequences are modified cytosines.
11. The sequencing adapter of claim 1, wherein the deaminating enzyme is an APOBEC enzyme.
12. The sequencing adapter of claim 1, wherein the oligonucleotide sequence comprises at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 contiguous nucleotides selected from the sequence 5’ AAT GAT ACG GCG ACC ACC GA 3’ (SEQ ID NO: 1) or its complement.
13. The sequencing adapter of claim 1, wherein the oligonucleotide sequence comprises at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 contiguous nucleotides selected from the sequence 5’ CAA GCA GAA GAC GGC ATA CGA GAT 3’ (SEQ ID NO: 2) or its complement.
14. The sequencing adapter of claim 1, wherein the oligonucleotide sequence comprises at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, or 33 contiguous nucleotides selected from the sequence 5’ ACA CTC TTT CCC TAC ACG ACG CTC TTC CGA TCT 3’ (SEQ ID NO: 3) or its complement.
15. The sequencing adapter of claim 1, wherein the oligonucleotide sequence comprises at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, or 34 contiguous nucleotides selected from the sequence 5’ GTG ACT GGA GTT CAG ACG TGT GCT CTT CCG ATC T 3’ (SEQ ID NO: 4) or its complement.
16. A method for performing nucleic acid sequencing, comprising: a) providing a plurality of nucleic acid molecules obtained from a sample from a subject; b) performing an enzymatic ligation of one or more of the sequencing adapters of claim 1 onto the plurality of nucleic acid molecules; c) sequencing, by a sequencer, the ligated nucleic acid molecules to obtain a plurality of sequence reads derived from the sample; and d) receiving, at one or more processors, sequence read data for the plurality of sequence reads derived from the sample.
17. The method of claim 16, wherein the enzymatic ligation comprises single- stranded ligation.
18. The method of claim 16, wherein the enzymatic ligation comprises double-stranded ligation.
19. The method of claim 16, wherein the nucleic acid sequencing comprises a methylation sequencing method.
20. The method of claim 19, wherein the methylation sequencing method comprises an enzymatic cytosine conversion step.
21. The method of claim 16, further comprising performing an end repair reaction on the plurality of nucleic acid molecules prior to performing the enzymatic ligation.
22. The method of claim 16, further comprising performing an A-tailing reaction on the plurality of nucleic acid molecules prior to performing the enzymatic ligation.
23. The method of claim 16, further comprising contacting the ligated nucleic acid molecules with a TET2 enzyme to oxidize 5-methyl-cytosine (5mC) or 5-hydroxymethyl-cytosine (5hmC) to 5-carboxycytosine (5caC) prior to performing the sequencing step.
24. The method of claim 16, further comprising contacting the ligated nucleic acid molecules with a combination of TET2 and T4-PGT enzymes to convert 5-methyl-cytosine (5mC) or 5- hydroxymethyl-cytosine (5hmC) to 5-(D-glucosyl)oxymethyl-cytosine prior to performing the sequencing step.
25. The method of claim 16, further comprising contacting the ligated nucleic acid molecules with an APOBEC enzyme to convert cytosines to uracil prior to performing the sequencing step.
26. The method of claim 16, further comprising determining a methylation status for each of a plurality of genomic loci based on the sequence read data.
27. The method of claim 16, further comprising diagnosing or confirming a diagnosis of disease in the subject based at least in part on a variant or a methylation signature identified in the sequence read data.
28. The method of claim 16, further comprising detecting minimum residual disease in the subject based on the sequence read data.
29. The method of claim 28, wherein the disease is cancer.
30. A method comprising: providing a plurality of nucleic acid molecules obtained from a sample from a subject; ligating one or more sequencing adapters onto one or more nucleic acid molecules from the plurality of nucleic acid molecules, wherein the one or more sequencing adapters comprise an oligonucleotide sequence comprising at least one modified cytosine, wherein the at least one modified cytosine is not 5-methylcytosine, and wherein a rate of conversion of the at least one modified cytosine to uracil when contacted with a deaminating enzyme is less than that of 5-methylcytosine; amplifying the one or more ligated nucleic acid molecules from the plurality of nucleic acid molecules; capturing amplified nucleic acid molecules from the amplified nucleic acid molecules; sequencing, by a sequencer, the captured nucleic acid molecules to obtain a plurality of sequence reads that represent the captured nucleic acid molecules; receiving, at one or more processors, sequence read data for the plurality of sequence reads; and determining, using the one or more processors, a methylation status for each of a plurality of genomic loci based on the sequence read data.
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