Methods and compositions for quantifying immune cell DNA

Abstract

Provided herein is a DNA analysis method for detecting and quantifying the type of immune cell from which DNA originates.Also provided herein is a method for determining the likelihood that a subject has a disease or condition, such as cancer.The method herein provides an approach for quantifying the level of circulating cell-free DNA (cfDNA) derived from different immune cell types based on DNA methylation data generated by dividing DNA based on the degree of methylation and performing next-generation DNA sequencing.

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit of priority to U.S. Provisional Application No. 63 / 166,200, filed March 25, 2021, which is incorporated by reference herein in its entirety for any purpose.

[0002] FIELD OF THEINVENTION The present disclosure provides methods and compositions related to analyzing DNA that naturally exists in immune cells, such as cell-free DNA.In some embodiments, DNA is derived from a subject that has or is suspected to have disease or disorder, such as cancer.In some embodiments, the immune cell type that DNA originates from is identified and quantified. [Background technology]

[0003] Introduction and Executive Summary Invasive diagnostic procedures, including biopsies, are commonly used to detect or diagnose cancer, ulcers, liver disease, infections, transplant rejection, and other diseases and disorders, in which analysis of cells or tissues from potential disease sites are analyzed for relevant traits. Detection of diseases and disorders based on analysis of bodily fluids, such as blood ("liquid biopsy"), is an attractive alternative. Liquid biopsies are non-invasive and may require only blood sampling. However, in the case of recovery of nucleic acids from such fluids in an analyzable form, the amount of nucleic acids released into bodily fluids is low and variable, so developing accurate and sensitive methods for analyzing liquid biopsy materials has been a challenge. For example, it is difficult to detect the presence of circulating tumor DNA (ctDNA) from early cancers due to its low abundance.

[0004] An alternative or complementary approach is to detect signals related to the secondary effect of the presence of disease, for example, cancer. One such signal of secondary effect is the signal from immune response to tumor development. In the presence of tumor cells, immune cells proliferate, differentiate, and potentially turn over at a faster rate than in healthy subjects. Such phenomena can lead to increased shedding of immune cell DNA into the bloodstream. Thus, secondary immune signals can be useful for detecting disease or disorder, for example, cancer, with improved sensitivity, at least in some circumstances.

[0005] Furthermore, quantification of different blood cell types provides important information about the overall health of a subject in addition to information about disease states. The ability to distinguish between different cell types, including closely related cell types, can be important for distinguishing between different types of diseases and disorders. Several studies have reported that cfDNA in plasma is mainly derived from blood cells (myeloid cells) in normal conditions. However, in disease states, cfDNA from immune cell types can be elevated, which can be used as an indicator of disease. In some genomic regions, DNA methylation signatures in different immune cell types are distinguishable from myeloid cells and other immune cell types. Existing methods, such as complete blood counts and microarray-based profiling of differentially methylated regions of cfDNA, allow the detection of many cell types, but do not distinguish between certain types of immune cells, such as naive lymphocytes and activated lymphocytes, and therefore do not provide important information about the state of a subject's immune system. Summary of the Invention [Means for solving the problem]

[0006] The method herein provides an approach for quantifying the level of circulating cell-free DNA (cfDNA) from different immune cell types based on DNA methylation data generated by distributing DNA based on the degree of methylation and performing next-generation DNA sequencing. In some embodiments, the method herein uses methyl-binding assays to profile genomic regions that are differentially methylated between specific immune cell types and other blood cells, as well as the methylation status of cfDNA fragments from these regions, facilitating quantification of the presence of one or more specific immune cell types. Applications of this approach include cancer detection by detecting tumor-induced immune cell proliferation.

[0007] The methods herein can also provide combined information regarding other DNA mutations and modifications, including but not limited to sequence mutations.

[0008] The present disclosure aims to meet the need for improved analysis of DNA originating from different immune cell types, including rare immune cell types, such as activated lymphocytes and naive lymphocytes. Improved differentiation of immune cell types over existing methods that do not distinguish between immune cell types, such as complete blood count (CBC) or methods based on DNA methylation, allows for more accurate detection (diagnosis) of disorders and therefore improved treatment. Accordingly, the following exemplary embodiments are provided.

[0009] Embodiment 1 A method for analyzing cfDNA in a sample, comprising: a) sequencing the cfDNA to determine methylation levels for a set of epigenetic target regions comprising a plurality of target regions comprising DNA sequences that are differentially methylated in a plurality of immune cell types; and b) determining the amount of each of a plurality of immune cell types from which the cfDNA originates based on the methylation level, the plurality of immune cell types comprising: i. Naive and activated lymphocytes; ii. monocytes and macrophages; or iii. Myelocytes, neutrophils, and eosinophils Including steps A method comprising:

[0010] Embodiment 2. A method for analyzing cfDNA in a sample, comprising: a) capturing at least one set of epigenetic target regions from the cfDNA or subsample thereof, comprising contacting the cfDNA or subsample thereof with target-specific probes specific for the at least one set of epigenetic target regions, the set of epigenetic target regions comprising target regions that comprise DNA sequences that are differentially methylated in a plurality of immune cell types; b) determining a methylation level for said target region; and c) determining the amount of each of the plurality of immune cell types from which the DNA originates, the plurality of immune cell types comprising: i. Naive and activated lymphocytes; ii. monocytes and macrophages; or iii. Myelocytes, neutrophils, and eosinophils Including steps A method comprising:

[0011] Embodiment 3. A method for analyzing cfDNA in a sample, comprising: a) sequencing the cfDNA to determine methylation levels for a set of epigenetic target regions comprising a plurality of hypomethylated variable target regions that comprise DNA sequences that are differentially hypomethylated in a plurality of immune cell types; and b) determining the amount of each of a plurality of immune cell types from which the cfDNA originates based on the methylation level. A method comprising:

[0012] Embodiment 4 A method for analyzing cfDNA in a sample, comprising: a) capturing at least one set of epigenetic target regions from the cfDNA or subsample thereof, comprising contacting the cfDNA or subsample thereof with target-specific probes specific for the at least one set of epigenetic target regions, wherein the set of epigenetic target regions comprises hypomethylated variable target regions comprising DNA sequences that are differentially hypomethylated in a plurality of immune cell types; b) determining a methylation level for said target region; and c) determining the amount of each of said plurality of immune cell types from which said DNA originates. A method comprising:

[0013] Embodiment 5. A method for analyzing DNA in a sample, comprising: a) partitioning the sample into a plurality of aliquots by contacting the DNA with an agent that recognizes modified cytosines in the DNA, the plurality comprising a first aliquot and a second aliquot, the first aliquot comprising a greater proportion of DNA having modified cytosines than the second aliquot; b) sequencing DNA from one or more of said plurality of aliquots; and c) detecting the level of the DNA sequence to determine the amount of each of a plurality of immune cell types from which the DNA originates, the plurality of immune cell types comprising: i. Naive and activated lymphocytes; ii. monocytes and macrophages; or iii. Myelocytes, neutrophils, and eosinophils Including steps A method comprising:

[0014] Embodiment 6 A method for analyzing DNA in a sample, comprising: a) partitioning the sample into a plurality of aliquots by contacting the DNA with an agent that recognizes modified cytosines in the DNA, the plurality comprising a first aliquot and a second aliquot, the first aliquot comprising a greater proportion of DNA having modified cytosines than the second aliquot; b) capturing at least one set of epigenetic target regions of DNA from at least one of said first and second subsamples, comprising contacting said DNA with target-specific probes specific for said at least one set of epigenetic target regions, said target regions of said set of epigenetic target regions comprising DNA sequences that are differentially methylated in a plurality of immune cell types, said plurality of immune cell types comprising: iv. Naive and activated lymphocytes; v. Monocytes and macrophages; or vi. Myelocytes, neutrophils, and eosinophils Including, vii. thereby providing captured DNA; and c) sequencing the captured DNA to determine the level of each of a plurality of immune cell types from which the DNA originates. A method comprising:

[0015] Embodiment 7 A method for analyzing DNA in a sample, comprising the steps of: a) partitioning the sample into a plurality of aliquots by contacting the DNA with an agent that recognizes modified cytosines in the DNA, the plurality comprising a first aliquot and a second aliquot, the first aliquot comprising a greater proportion of DNA having modified cytosines than the second aliquot; b) capturing at least one set of epigenetic target regions of DNA from at least one of said first and second sub-samples, wherein the at least one set of epigenetic target regions comprises a set of hypomethylated variable target regions, thereby providing captured DNA; c) sequencing the captured DNA; and d) detecting the level of the captured DNA sequences and determining the level of each of a plurality of immune cell types from which the DNA originates. A method comprising:

[0016] Embodiment 8. A method for analyzing DNA in a sample, comprising: a) partitioning the sample into a plurality of aliquots by contacting the DNA with an agent that recognizes modified cytosines in the DNA, the plurality comprising a first aliquot and a second aliquot, the first aliquot comprising a greater proportion of DNA having modified cytosines than the second aliquot; b) capturing at least one set of epigenetic target regions of DNA from at least one of the first and second subsamples, comprising contacting the DNA with target-specific probes specific for the at least one set of epigenetic target regions, wherein the target regions of the set of epigenetic target regions comprise DNA sequences that are hypomethylated in a plurality of immune cell types, thereby providing captured DNA; and c) sequencing the captured DNA A method comprising:

[0017] Embodiment 9. The method of embodiment 5 or 7, comprising capturing at least one set of epigenetic target regions of DNA from at least one of the first and second subsamples, wherein the target regions of the set of epigenetic target regions comprise DNA sequences that are differentially methylated in multiple immune cell types, and wherein the capturing step is performed before the sequencing step.

[0018]

[0023] Embodiment 10. The method of any one of the preceding embodiments, wherein said set of epigenetic target regions comprises a set of hypermethylated variable target regions and a set of hypomethylated variable target regions.

[0019] Embodiment 11. The method of any one of the preceding embodiments, wherein the multiple immune cell types comprise naive lymphocytes and activated lymphocytes.

[0020] Embodiment 12. The method of the immediately preceding embodiment, wherein said multiple immune cell types comprise naive T cells, naive B cells, effector CD4 T cells, effector CD8 T cells, Treg cells, plasma cells, and memory cells.

[0021] Embodiment 13. The method of the immediately preceding embodiment, wherein said effector CD4 T cells comprise effector memory CD4 T cells and central memory CD4 T cells, and said effector CD8 T cells comprise effector memory CD8 T cells and central memory CD8 T cells.

[0022] Embodiment 14. The method of any one of the preceding embodiments, wherein the multiple immune cell types include monocytes and macrophages.

[0023] Embodiment 15. The method of any one of the preceding embodiments, wherein the multiple immune cell types comprise myeloid cells, neutrophils, and eosinophils.

[0024] Embodiment 16. The method of any one of the immediately preceding embodiments, wherein said multiple immune cell types comprise metamyelocytes.

[0025] Embodiment 17. The method of any one of the preceding embodiments, wherein the multiple immune cell types comprise natural killer (NK) cells.

[0026] Embodiment 18. The method of any one of the preceding embodiments, wherein the level of each of the plurality of immune cell types is determined relative to the level of total blood cells.

[0027] Embodiment 19. The method of any one of the preceding embodiments, wherein the sample is a blood sample.

[0028] Embodiment 20. The method of any one of the preceding embodiments, wherein the sample is a plasma sample.

[0029] Embodiment 21. The method of any one of the preceding embodiments, wherein the sample is obtained from a tissue sample.

[0030] Embodiment 22. The method of the immediately preceding embodiment, wherein said tissue sample is a biopsy, fine needle aspirate, or a formalin-fixed, paraffin-embedded tissue sample.

[0031] Embodiment 23. The method of any one of the preceding embodiments, wherein the DNA comprises cell-free DNA (cfDNA).

[0032] Embodiment 24. The method of any one of embodiments 5 to 23, wherein the DNA comprises DNA isolated from intact cells naturally present in the sample.

[0033] Embodiment 25. The method of any one of the preceding embodiments, comprising determining a ratio of levels or amounts of immune cell types based on the determined levels or amounts of the plurality of immune cell types.

[0034] Embodiment 26. The method of the immediately preceding embodiment, wherein the numerators in the ratio comprise levels or amounts of neutrophils, monocytes, or both neutrophils and monocytes.

[0035]

[0046] Embodiment 27. The method of embodiment 25 or 26, wherein the denominator of the ratio comprises the level or amount of T cells, B cells, NK cells, or total lymphocytes.

[0036] Embodiment 28. The method of any one of embodiments 25-27, wherein the numerator of the ratio comprises a neutrophil level or amount and the denominator of the ratio comprises a total lymphocyte level or amount.

[0037] Embodiment 29. The method of any one of embodiments 25-27, wherein the numerator of the ratio comprises the level or amount of monocytes and the denominator of the ratio comprises the level or amount of T cells.

[0038]

[0023] Embodiment 30. The method of any one of the preceding embodiments, comprising determining the frequency of turnover of at least one of said plurality of immune cell types.

[0039] Embodiment 31. The method of the immediately preceding embodiment, wherein said turnover comprises proliferation.

[0040]

[0081] Embodiment 32. The method of embodiment 30, wherein the turnover comprises apoptosis.

[0041] Embodiment 33. The method of any one of the preceding embodiments, comprising determining the level of at least one cell type other than the immune cell type from which the DNA originated.

[0042] Embodiment 34. The method of the immediately preceding embodiment, comprising capturing at least one set of epigenetic target regions that comprise sequence-independent differences in target regions in DNA originating from a cell type other than an immune cell type compared to the same target regions in DNA originating from all other cell types in the sample or subsample.

[0043] Embodiment 35. The method of embodiment 33 or 34, wherein said other than an immune cell type is not a blood cell type.

[0044] Embodiment 36. The method of the immediately preceding embodiment, wherein said cell type other than an immune cell type is colorectal, lung, breast, prostate, skin, stomach, bladder, liver, ovary, pancreas, squamous, salivary gland, larynx, hypopharynx, nose, paranasal sinuses, nasopharynx, or kidney.

[0045] Embodiment 37. The method of any one of the preceding embodiments, wherein the sample is obtained from a subject.

[0046] Embodiment 38. The method of the immediately preceding embodiment, comprising determining the likelihood that the subject has cancer or precancer.

[0047] Embodiment 39. The method of the immediately preceding embodiment, comprising determining the likelihood that the subject has cancer.

[0048] Embodiment 40. The method of the immediately preceding embodiment, wherein the cancer is an immune cell type cancer.

[0049] Embodiment 41 The method of the immediately preceding embodiment, wherein the cancer is a lymphocytic cancer.

[0050] Embodiment 42. The method of the immediately preceding embodiment, wherein the cancer is leukemia, lymphoma, or myeloma.

[0051] Embodiment 43. The method of any one of embodiments 38-40, wherein the cancer is a myeloid cancer.

[0052]

[0046] Embodiment 44: The method of embodiment 38 or 39, wherein the cancer is a cancer of a cell or tissue type other than an immune cell type.

[0053] Embodiment 45. The method of any one of embodiments 38, 39, or 44, wherein the cancer or precancer is a cancer or precancer other than a hematological cancer or precancer, or the cancer or precancer is a solid tumor cancer, and optionally the solid tumor cancer is a carcinoma or sarcoma.

[0054] Embodiment 46. The method of embodiment 44 or 45, wherein the cancer is colorectal cancer, lung cancer, breast cancer, prostate cancer, skin cancer, gastric cancer, bladder cancer, liver cancer, ovarian cancer, pancreatic cancer, head and neck cancer, or renal cancer.

[0055] Embodiment 46.1 The method of embodiment 46, wherein the cancer is colorectal cancer.

[0056] Embodiment 46.2 The method of embodiment 46, wherein the cancer is lung cancer.

[0057] Embodiment 46.3 The method of embodiment 46, wherein the cancer is breast cancer.

[0058] Embodiment 46.4 The method of embodiment 46, wherein the cancer is prostate cancer.

[0059] Embodiment 46.5 The method of embodiment 46, wherein the cancer is skin cancer.

[0060] Embodiment 46.6 The method of embodiment 46, wherein the cancer is gastric cancer.

[0061] Embodiment 46.7 The method of embodiment 46, wherein the cancer is bladder cancer.

[0062] Embodiment 46.8 The method of embodiment 46, wherein the cancer is liver cancer.

[0063] Embodiment 46.9 The method of embodiment 46, wherein the cancer is ovarian cancer.

[0064] Embodiment 46.10 The method of embodiment 46, wherein the cancer is pancreatic cancer.

[0065] Embodiment 46.11 The method of embodiment 46, wherein the cancer is head and neck cancer.

[0066] Embodiment 46.12 The method of embodiment 46, wherein the cancer is renal cancer.

[0067]

[0047] Embodiment 47. The method of embodiment 38, comprising determining the likelihood that the subject has a precancer.

[0068] Embodiment 48. The method of the immediately preceding embodiment, wherein the precancer is an adenoma.

[0069] Embodiment 49. The method of the immediately preceding embodiment, wherein the adenoma is an advanced adenoma.

[0070] Embodiment 50. The method of any one of embodiments 47-49, wherein the precancer is colorectal precancer, lung precancer, breast precancer, prostate precancer, skin precancer, gastric precancer, bladder precancer, liver precancer, ovarian precancer, pancreatic precancer, head and neck precancer, or renal precancer.

[0071] Embodiment 51. The method of any one of embodiments 37 to 50, comprising determining the likelihood that the subject has an infection.

[0072] Embodiment 52. The method of any one of embodiments 37-51, comprising determining the likelihood that the subject has graft rejection.

[0073]

[0046] Embodiment 53. The method of any one of embodiments 38-52, wherein the step of determining the amount of each of the plurality of immune cell types or the step of sequencing comprises generating a plurality of sequencing reads, and the method further comprises the steps of mapping the plurality of sequence reads to one or more reference sequences to generate mapped sequence reads, and processing the mapped sequence reads to determine the likelihood that the subject has cancer, precancer, an infection, or transplant rejection.

[0074] Embodiment 54. The method of any one of the preceding embodiments, wherein the sample is obtained from a subject who has previously been diagnosed with cancer and has undergone one or more previous cancer treatments, optionally wherein the sample is obtained at one or more preselected time points after said one or more previous cancer treatments.

[0075] Embodiment 55. The method of the immediately preceding embodiment, further comprising determining a cancer recurrence score, optionally wherein the subject's cancer recurrence status is determined to be at risk of cancer recurrence if the Cancer Recurrence Score is determined to be at or above a pre-defined threshold, or the subject's cancer recurrence status is determined to be at lower risk of cancer recurrence if the Cancer Recurrence Score is below the pre-defined threshold.

[0076] Embodiment 56. The method of the immediately preceding embodiment, further comprising comparing the subject's cancer recurrence score to a pre-defined cancer recurrence threshold, wherein the subject is classified as being a candidate for subsequent cancer treatment if the cancer recurrence score is above the cancer recurrence threshold, and as not being a candidate for subsequent cancer treatment if the cancer recurrence score is below the cancer recurrence threshold.

[0077]

[0046] Embodiment 57. The method of any one of embodiments 2, 4, 6, or 8-56, wherein the capturing step comprises capturing a sequence variable target region.

[0078] Embodiment 57.1 The method of embodiment 57, wherein the sequence variable target region comprises a single nucleotide mutation compared to the reference sequence.

[0079] Embodiment 57.2 The method of embodiment 57 or 57.1, wherein the sequence variable target region comprises an indel compared to the reference sequence.

[0080]

[0023] Embodiment 58. The method of the immediately preceding embodiment, wherein said capturing step comprises contacting said DNA with a target specific probe specific for said at least one set of epigenetic target regions and a target specific probe specific for said sequence variable target region.

[0081] Embodiment 59. The method of any one of embodiments 5 to 58, wherein the modified cytosine is a methylcytosine.

[0082] Embodiment 60. The method of any one of embodiments 5 to 58, wherein said agent that recognizes a modified cytosine is a methyl-binding agent.

[0083] Embodiment 61. The method of the immediately preceding embodiment, wherein the methyl-binding reagent is an antibody.

[0084]

[0081] Embodiment 62. The method of embodiment 60, wherein the agent that recognizes a modified cytosine is a methyl-binding protein or comprises a methyl-binding domain.

[0085] Embodiment 63. The method of any one of embodiments 60 to 62, wherein the methyl-binding reagent specifically recognizes 5-methylcytosine.

[0086] Embodiment 64. The method of any one of embodiments 60 to 63, wherein the methyl-binding reagent is immobilized on a solid support.

[0087]

[0046] Embodiment 65. The method of any one of embodiments 5 to 64, wherein the partitioning step comprises immunoprecipitation of methylated DNA.

[0088] Embodiment 66. The method of any one of embodiments 5 to 58, wherein the partitioning step comprises partitioning based on binding to a protein, optionally wherein the protein is a methylated protein, an acetylated protein, a non-methylated protein, a non-acetylated protein; and / or optionally wherein the protein is a histone.

[0089] Embodiment 67. The method of the immediately preceding embodiment, wherein said distributing step comprises contacting said DNA of said sample with a binding reagent specific for said protein and immobilized on a solid support.

[0090] Embodiment 68. The method of any one of embodiments 5 to 67, comprising contacting at least one aliquot with a restriction enzyme prior to the capturing step or the sequencing step, and optionally, the contacting step being performed after partitioning the sample into the plurality of aliquots.

[0091] Embodiment 69. The method of the immediately preceding embodiment, wherein said restriction enzyme is MDRE.

[0092] Embodiment 70. The method of the immediately preceding embodiment, wherein said second aliquot is contacted with said MDRE.

[0093] Embodiment 71. The method of any one of embodiments 68 to 70, wherein the restriction enzyme is an MSRE.

[0094]

[0073] Embodiment 72. The method of the immediately preceding embodiment, wherein the first aliquot is contacted with the MSRE.

[0095] Embodiment 73. The method of any one of the preceding embodiments, comprising ligating an adaptor to said DNA, thereby producing an adaptor-ligated DNA.

[0096]

[0046] Embodiment 74. The method of the immediately preceding embodiment, wherein said adaptor-ligated DNA is amplified prior to said sequencing step.

[0097]

[0081] Embodiment 75. The method of any one of embodiments 5 to 74, wherein the aliquots are pooled prior to the sequencing step.

[0098]

[0046] Embodiment 76. The method of any one of embodiments 1-4 or 6-75, wherein the set of epigenetic target regions comprises hypomethylated variable target regions that comprise DNA sequences that are differentially hypomethylated in multiple immune cell types.

[0099] Embodiment 77. The method of any one of embodiments 3, 4, 7, or 10-76, wherein the hypomethylated variable target region comprises a DNA sequence that is differentially hypomethylated in multiple immune cell types.

[0100] Embodiment 78. The method of any one of embodiments 3, 4, 76, or 77, wherein the DNA sequence that is differentially hypomethylated in a plurality of immune cell types comprises a degree of methylation in at least one immune cell type that is detectably lower than the degree of methylation of the same sequence in any other immune cell type in the sample.

[0101] Embodiment 79. The method of any one of embodiments 3, 4, 76, or 77, wherein said DNA sequence that is differentially hypomethylated in a plurality of immune cell types comprises a degree of methylation in at least one immune cell type that is detectably lower than the degree of methylation of the same sequence in any other immune cell type.

[0102]

[0046] Embodiment 80. The method of any one of embodiments 3, 4, 76, or 77, wherein the DNA sequence that is differentially hypomethylated in a plurality of immune cell types comprises a degree of methylation in one immune cell type that is detectably lower than the degree of methylation of the same sequence in any other immune cell type in the sample.

[0103] Embodiment 81. The method of any one of embodiments 3, 4, 76, or 77, wherein the DNA sequence that is differentially hypomethylated in a plurality of immune cell types comprises a degree of methylation in one immune cell type that is detectably lower than the degree of methylation of the same sequence in any other immune cell type.

[0104] Embodiment 82. The method of any one of embodiments 3, 4, 76, or 77, wherein said DNA sequences that are differentially hypomethylated in a plurality of immune cell types comprise a detectably lower degree of methylation in at least one immune cell type than the degree of methylation of the same sequence in at least one other immune cell type and comprise a detectably lower degree of methylation than the degree of methylation of the same sequence in at least one non-immune cell type in said sample.

[0105] Embodiment 83. The method of any one of embodiments 3, 4, 76, or 77, wherein said DNA sequences that are differentially hypomethylated in a plurality of immune cell types comprise a detectably lower degree of methylation in at least one immune cell type than the degree of methylation of the same sequence in at least one other immune cell type, and comprise a detectably lower degree of methylation than the degree of methylation of the same sequence in any non-immune cell type in said sample.

[0106] Embodiment 83.1 The method of any one of embodiments 3, 4, 7 or 10-77, wherein the differentially hypomethylated DNA comprises a reduced level or degree of methylation in one cell type compared to DNA containing the same genetic information in one or more other cell types.

[0107] Embodiment 83.2 The method of any one of embodiments 3, 4, 7 or 10-77, wherein the differentially hypomethylated DNA comprises a reduced level or degree of methylation in one or more immune cell types compared to DNA containing the same genetic information in all other immune cell types.

[0108] Embodiment 83.3 The method of any one of embodiments 3, 4, 7 or 10-77, wherein the differentially hypomethylated DNA comprises a reduced level or degree of methylation in one or more immune cell types compared to DNA containing the same genetic information in all other blood cell types, and optionally the level or degree of methylation in the DNA of all other blood cell types is expressed as a weighted average according to the abundance of DNA from the cell type.

[0109] Embodiment 84. The method of any one of embodiments 78 to 83, wherein said detectably lower degree of methylation is one less methylated cytosine than the same sequence in said other cell types.

[0110] Embodiment 85. The method of any one of embodiments 78 to 83, wherein said detectably lower degree of methylation is two fewer methylated cytosines than the same sequence in said other cell type.

[0111] Embodiment 86. The method of any one of embodiments 78 to 83, wherein said detectably lower degree of methylation is 3 fewer methylated cytosines than the same sequence in said other cell types.

[0112] Embodiment 87. The method of any one of embodiments 78 to 83, wherein said detectably lower degree of methylation is 4 fewer methylated cytosines than the same sequence in said other cell types.

[0113] Embodiment 88. The method of any one of embodiments 78 to 83, wherein said detectably lower degree of methylation is 5 or fewer methylated cytosines than the same sequence in said other cell types.

[0114]

[0082] Embodiment 89. The method of any one of embodiments 1-4 or 6-88, wherein the set of epigenetic target regions comprises hypermethylated variable target regions comprising DNA sequences that are differentially hypermethylated in multiple immune cell types.

[0115]

[0046] Embodiment 90. The method of embodiment 89, wherein said DNA sequence that is differentially hypermethylated in a plurality of immune cell types comprises a degree of methylation in at least one immune cell type that is detectably higher than the degree of methylation of the same sequence in any other immune cell type in said sample.

[0116]

[0046] Embodiment 91. The method of embodiment 89, wherein said DNA sequence that is differentially hypermethylated in a plurality of immune cell types comprises a degree of methylation in at least one immune cell type that is detectably higher than the degree of methylation of the same sequence in any other immune cell type.

[0117]

[0046] Embodiment 92. The method of embodiment 89, wherein the DNA sequence that is differentially hypermethylated in a plurality of immune cell types comprises a degree of methylation in one immune cell type that is detectably higher than the degree of methylation of the same sequence in any other immune cell type in the sample.

[0118]

[0081] Embodiment 93. The method of embodiment 89, wherein said DNA sequence that is differentially hypermethylated in a plurality of immune cell types comprises a degree of methylation in one immune cell type that is detectably higher than the degree of methylation of the same sequence in any other immune cell type.

[0119]

[0081] Embodiment 94. The method of embodiment 89, wherein said DNA sequence that is differentially hypermethylated in a plurality of immune cell types comprises a degree of methylation in at least one immune cell type that is detectably higher than the degree of methylation of the same sequence in at least one other immune cell type and comprises a degree of methylation that is detectably lower than the degree of methylation of the same sequence in at least one non-immune cell type in said sample.

[0120] Embodiment 95. The method of embodiment 89, wherein the DNA sequence that is differentially hypermethylated in a plurality of immune cell types comprises a degree of methylation in at least one immune cell type that is detectably higher than the degree of methylation of the same sequence in at least one other immune cell type and comprises a degree of methylation that is detectably lower than the degree of methylation of the same sequence in any non-immune cell type in the sample.

[0121] Embodiment 95.1 The method of embodiment 89, wherein differentially hypermethylated DNA comprises an increased level or degree of methylation in one cell type compared to DNA containing the same genetic information in one or more other cell types.

[0122] Embodiment 95.2 The method of embodiment 89, wherein the differentially hypermethylated DNA comprises an increased level or degree of methylation in one or more immune cell types compared to DNA containing the same genetic information in all other immune cell types.

[0123] Embodiment 95.3 The method of embodiment 89, wherein the differentially hypermethylated DNA comprises an increased level or degree of methylation in one or more immune cell types compared to DNA containing the same genetic information in all other blood cell types, and optionally the level or degree of methylation in the DNA of all other blood cell types is expressed as a weighted average according to the abundance of DNA from the cell type.

[0124] Embodiment 96. The method of any one of embodiments 90 to 95, wherein said detectably higher degree of methylation is one more cytosine methylation than the same sequence in said other cell types.

[0125] Embodiment 97. The method of any one of embodiments 90 to 95, wherein said detectably higher degree of methylation is two more cytosine methylations than the same sequence in said other cell types.

[0126] Embodiment 98. The method of any one of embodiments 90 to 95, wherein said detectably higher degree of methylation is 3 more cytosine methylations than the same sequence in said other cell types.

[0127] Embodiment 99. The method of any one of embodiments 90 to 95, wherein said detectably higher degree of methylation is 4 more cytosine methylations than the same sequence in said other cell types.

[0128] Embodiment 100. The method of any one of embodiments 90 to 95, wherein said detectably higher degree of methylation is 5 or more than 5 cytosine methylations than the same sequence in said other cell type.

[0129] Embodiment 101. The method of any one of the preceding embodiments, comprising determining the amount or detecting the level of DNA in said sample originating from erythrocytes or erythrocyte precursors.

[0130] Embodiment 102. The method of any one of the preceding embodiments, comprising determining the amount or level of DNA in said sample originating from granulosa cells.

[0131] Embodiment 103. The method of any one of embodiments 3, 4, or 76-102, wherein the detectably lower or higher degree of methylation is present in samples from at least one group of donors compared to another group of donors, and optionally, the at least one group of donors has a cancer that responds to the treatment and the other group of donors has a cancer that does not respond to the treatment. [Brief description of the drawings]

[0132] [Figure 1-1] FIG. 1A illustrates an example workflow according to certain embodiments disclosed herein. [Figure 1-2] Same as above.

[0133] [Figure 1-3] Figure 1B is a heat map showing the methylation levels of loci identified as having cell type-specific or cell cluster-specific differential methylation as a function of cell type or cell cluster. DMS and DMR indicate differentially methylated sites (e.g., individual CpGs) and differentially methylated regions (including multiple DMSs).

[0134] [Figure 1-4] FIG. 1C shows the relative methylation of exemplary hypermethylated regions identified for the indicated cell types and cell clusters in samples from individuals with colorectal cancer (CRC) and from individuals without cancer as box plots. The box plots show the distribution of methylation scores in CRC samples and samples without cancer. The methylation scores are the total molecules in the methylation fraction (hypermethylated and intermediate distributions) normalized by input cfDNA. In each box in the box plot, the rightmost line, the middle line, and the leftmost line correspond to the 75% quantile (Q75), 50% quantile or median (Q50), and 25% quantile (Q25) of the methylation score across the samples. The rightmost and leftmost whiskers correspond to Q75+1.5*interquartile range (IQR) and Q25-1.5IQR, where IQR is Q75-Q25. The dots are outliers whose values ​​lie outside the range marked by the whiskers. [Figure 1-5] Same as above.

[0135] [Figure 1-6]FIG. 1D shows the relative methylation of the exemplary hypermethylated regions identified for the indicated cell types and cell clusters in samples from individuals with the indicated types of early cancer and samples from individuals without cancer as box plots. The box plots show the distribution of methylation scores in the samples. The methylation scores are the total molecules in the methylation fraction (hypermethylated and intermediate distributions) normalized by the input cfDNA. In each box in the box plot, the rightmost line, the middle line, and the leftmost line correspond to the 75% quantile (Q75), 50% quantile or median (Q50), and 25% quantile (Q25) of the methylation scores across the samples. The rightmost and leftmost whiskers correspond to Q75+1.5*interquartile range (IQR) and Q25-1.5IQR, where IQR is Q75-Q25. The dots are outliers whose values ​​are outside the range marked by the whiskers. [Figure 1-7] Same as above.

[0136] [Figure 1-8] FIG. 1E shows the relative methylation of the exemplary hypermethylated regions identified for the indicated cell types and cell clusters in samples from individuals with the indicated types of late-stage cancer and samples from individuals without cancer as box plots. The box plots show the distribution of methylation scores in the samples. The methylation scores are the total molecules in the methylation fraction (hypermethylated and intermediate distributions) normalized by the input cfDNA. In each box in the box plot, the rightmost line, the middle line, and the leftmost line correspond to the 75% quantile (Q75), 50% quantile or median (Q50), and 25% quantile (Q25) of the methylation scores across the samples. The rightmost and leftmost whiskers correspond to Q75+1.5*interquartile range (IQR) and Q25-1.5IQR, where IQR is Q75-Q25. The dots are outliers whose values ​​are outside the range marked by the whiskers. [Figure 1-9] Same as above.

[0137] [Diagram 2] FIG. 2 is a schematic diagram of an example of a system suitable for use with some embodiments of the present disclosure.

[0138] [Figure 3-1] FIG. 3 shows the estimated percentages of B cells, granulocytes, NK cells, T cells, and erythroid precursors as contributors to cfDNA in blood samples from cancer-free subjects and subjects with colorectal cancer (crc). [Figure 3-2] Same as above. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0139] DETAILED DESCRIPTION OF CERTAIN EMBODIMENTS Reference will now be made in detail to certain specific embodiments of the invention. While the invention will be described in conjunction with such embodiments, it will be understood that they are not intended to limit the invention to those embodiments. On the contrary, the invention is intended to cover all alternatives, modifications, and equivalents that may be included within the invention as defined by the appended claims.

[0140] Before describing the present teachings in detail, it should be understood that the present disclosure is not limited to specific compositions or process steps, and therefore may vary. It should be noted that, as used herein and in the appended claims, the singular forms "a", "an" and "the" include plural references unless the context clearly dictates otherwise. Thus, for example, reference to "a nucleic acid" includes multiple nucleic acids, reference to "a cell" includes multiple cells, and so on.

[0141] Numeric ranges are inclusive of the numbers defining the range. Measured and measurable values ​​are understood to be approximate, taking into account significant digits and errors associated with measurement. Similarly, the use of "comprise," "comprises," "comprising," "contain," "contains," "containing," "include," "includes," and "including" are not intended to be limiting. It is to be understood that both the foregoing general and detailed description are exemplary and explanatory only and are not restrictive of the teachings.

[0142] Unless specifically stated in the specification above, embodiments herein that recite "comprising" various components are also contemplated as "consisting of" or "consisting essentially of" the recited components, and embodiments herein that recite "consisting of" various components are also contemplated as "comprising" or "consisting essentially of" the recited components, and embodiments herein that recite "consisting essentially of" various components are also contemplated as "consisting of" or "comprising" the recited components (this interchangeability does not apply to the use of these terms in the claims).

[0143] The section headings used herein are for organizational purposes only and should not be construed as limiting the disclosed subject matter in any way. In the event that any document or other material incorporated by reference conflicts with any express content of this specification, the present specification, including definitions, will control. definition

[0144] "Cell-free DNA", "cfDNA molecule" or simply "cfDNA" includes DNA molecules that naturally exist in a subject in extracellular form (e.g., in blood, serum, plasma, or other bodily fluids, such as lymph, cerebrospinal fluid, urine, or sputum). cfDNA was previously present in a cell or cells in a large complex organism, such as a mammal, but has undergone release from the cell into the fluid found in the organism, and can be obtained from a sample of the fluid without the need to perform an in vitro cell lysis step. cfDNA molecules can exist as DNA fragments.

[0145] As used herein, "distribution" of nucleic acids, e.g., DNA molecules, refers to separating, fractionating, sorting, or enriching a sample or population of nucleic acids into multiple subsamples or subpopulations of nucleic acids based on one or more modifications or features present in different proportions in each of the multiple subsamples or subpopulations. Distributing can include physically distributing nucleic acid molecules based on the presence or absence of one or more methylated nucleic acid bases. A sample or population can be distributed into one or more distributed subsamples or subpopulations based on characteristics indicative of genetic or epigenetic changes or disease states.

[0146] As used herein, if the fraction of nucleotides having a modification or other feature is higher in a first sample or population than in a second population, then the modification or other feature is present in a "greater proportion" in a first sample or population than in a second sample or population of nucleic acids. For example, if in a first sample, 1 / 10 of the nucleotides are mC, and in a second sample, 1 / 20 of the nucleotides are mC, then the first sample contains a greater proportion of 5-methylated cytosine modifications than the second sample.

[0147] As used herein, the form of a sample "originally isolated" refers to the composition or chemical structure of the sample at the time it is isolated, before it is subjected to any procedure that changes the chemical structure of the isolated sample. Similarly, a feature "originally present" in a DNA molecule refers to a feature present in an "original DNA molecule" or a DNA molecule "originally containing" that feature, before the DNA molecule is subjected to a procedure that changes the chemical structure of the DNA molecule.

[0148] As used herein, "substantially does not change the base pairing specificity" of a given nucleobase means that the majority of molecules that contain a nucleobase that can be sequenced have no change in the base pairing specificity of the given nucleobase compared to its base pairing specificity in the sample that was originally isolated.In some embodiments, 75%, 90%, 95%, or 99% of molecules that contain a nucleobase that can be sequenced have no change in base pairing specificity compared to its base pairing specificity in the sample that was originally isolated.As used herein, "changed base pairing specificity" of a given nucleobase means that the majority of molecules that contain a nucleobase that can be sequenced have base pairing specificity at that nucleobase compared to its base pairing specificity in the sample that was originally isolated.

[0149] As used herein, "base pairing specificity" refers to the standard DNA base (A, C, G, or T) with which a given base pairs most preferentially. For example, unmodified cytosine and 5-methylcytosine have the same base pairing specificity (i.e., specificity for G), whereas uracil and cytosine have different base pairing specificities, since uracil has base pairing specificity for A, whereas cytosine has base pairing specificity for G. The ability of uracil to form an unstable pair with G is irrelevant, since uracil nevertheless pairs most preferentially with A of the four standard DNA bases.

[0150] As used herein, a "combination" containing multiple members refers to either a single composition containing those members, or a set of adjacent compositions, for example, in separate containers or compartments within a larger container, such as a multi-well plate, tube rack, refrigerator, freezer, incubator, water bath, ice bucket, machine, or other form of storage.

[0151] The "capture yield" of a collection of probes for a given target set refers to the amount of nucleic acid corresponding to the target set that the collection of probes captures under typical conditions (e.g., the amount relative to another target set, or the absolute amount). Exemplary typical capture conditions are incubation of the sample nucleic acid with the probes for 10-18 hours at 65°C in a small reaction volume (about 20 μL) containing a stringent hybridization buffer. Capture yields can be expressed in absolute terms, or in relative terms for multiple collections of probes. When capture yields for multiple sets of target regions are compared, they are normalized with respect to the footprint size of the target region set (e.g., on a per kilobase basis). Thus, for example, when the footprint sizes of the first and second target regions are 50 kb and 500 kb, respectively (giving a normalization factor of 0.1), the DNA corresponding to the first set of target regions is captured with a higher yield than the DNA corresponding to the second set of target regions if the mass per volume concentration of the captured DNA corresponding to the first set of target regions is higher than 0.1 times the mass per volume concentration of the captured DNA corresponding to the second set of target regions. As a further example, when using the same footprint size, the DNA corresponding to the first set of target regions is captured with a capture yield that is 2 times higher than the DNA corresponding to the second set of target regions if the captured DNA corresponding to the first set of target regions has a mass per volume concentration that is 0.2 times the mass per volume concentration of the captured DNA corresponding to the second set of target regions.

[0152] "Capturing" one or more target nucleic acids, or one or more nucleic acids that contain at least one target region, refers to preferentially isolating or separating one or more target nucleic acids, or one or more nucleic acids that contain at least one target region, from non-target nucleic acids or from nucleic acids that do not contain at least one target region.

[0153] A "captured set" of nucleic acids or a "captured" nucleic acid refers to the nucleic acids that have undergone capture.

[0154] As used herein, a "capture moiety" is a molecule that allows for affinity separation of a molecule, e.g., a nucleic acid, linked to the capture moiety from a molecule that lacks the capture moiety. Exemplary capture moieties include biotin, which allows for affinity separation by binding to streptavidin linked or linkable to a solid phase, or oligonucleotides, which allow for affinity separation through binding to complementary oligonucleotides linked or linkable to a solid phase.

[0155] As used herein, a "cell cluster" or "cluster" refers to a plurality of related cell types, e.g., immune cell types. In some embodiments, cell types within a cluster have similar DNA methylation profiles, e.g., at multiple hypermethylated and / or hypomethylated variable target regions.

[0156] A "target region" refers to a genomic locus that is targeted for identification and / or capture, e.g., by using a probe (e.g., via sequence complementarity). A "target region set" or "set of target regions" refers to a plurality of genomic loci that are targeted for identification and / or capture, e.g., by using a set of probes (e.g., via sequence complementarity).

[0157] "Specifically binds" in the context of primers, probes, or other oligonucleotides and target sequences means that under appropriate hybridization conditions, the primer, oligonucleotide, or probe hybridizes to its target sequence or a copy thereof to form a stable hybrid, while at the same time minimizing the formation of stable non-target hybrids. Thus, the primer or probe hybridizes to the target sequence or a copy thereof to a sufficiently greater extent than to non-target sequences to ultimately allow capture or detection of the target sequence. Suitable hybridization conditions are well known in the art and can be predicted based on sequence composition or determined using routine testing methods (see, e.g., Sambrook et al., Molecular Cloning, A Laboratory Manual, 2nd ed. (Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY, 1989) §§ 1.90-1.91, 7.37-7.57, 9.47-9.51 and 11.47-11.57, in particular §§ 9.50-9.51, 11.12-11.13, 11.45-11.47 and 11.55-11.57, which are incorporated herein by reference).

[0158] "Sequence variable target region" refers to a target region that may show sequence changes such as nucleotide substitutions (i.e., single nucleotide mutations), insertions, deletions, or gene fusions or rearrangements in neoplastic cells (e.g., tumor cells and cancer cells) compared to normal cells. A sequence variable target region set is a set of sequence variable target regions. In some embodiments, a sequence variable target region is a target region that may show changes affecting less than or equal to 50 consecutive nucleotides, such as less than or equal to 40, less than or equal to 30, less than or equal to 20, less than or equal to 10, less than or equal to 5, less than or equal to 4, less than or equal to 3, less than or equal to 2, or less than or equal to 1 nucleotide.

[0159] An "epigenetic target region" refers to a target region that may exhibit sequence-independent differences in different cell or tissue types (e.g., different types of immune cells) or in neoplastic cells (e.g., tumor cells and cancer cells) compared to normal cells; or in DNA from different cell types, or in DNA from a subject with cancer compared to DNA, e.g., cfDNA, from a healthy subject, or in cfDNA originating from a different cell or tissue type (e.g., immune, lung, colon, etc.) that does not normally contribute substantially to cfDNA compared to background cfDNA (e.g., cfDNA originating from hematopoietic cells). Examples of sequence-independent changes include, but are not limited to, methylation (increase or decrease), nucleosome distribution, cfDNA fragmentation pattern, CCCTC binding factor ("CTCF") binding, transcription start site (e.g., in terms of any one or more of RNA polymerase component binding, regulatory protein binding, fragmentation characteristics, and nucleosome distribution), and changes in regulatory protein binding regions.Thus, epigenetic target region sets include, but are not limited to, hypermethylated variable target region sets, hypomethylated variable target region sets, and fragmented variable target region sets, such as CTCF binding sites and transcription start sites. For present purposes, loci that are subject to neoplasia-, tumor-, or cancer-associated local amplifications and / or gene fusions may also be included in the set of epigenetic target regions because, for example, detection of copy number changes by sequencing or fusion sequences that map to more than one locus in a reference genome tends to be more similar to detection of the exemplary epigenetic changes discussed above than detection of nucleotide substitutions, insertions, or deletions, in that local amplifications and / or gene fusions can be detected at relatively shallow sequencing depths because their detection does not depend on the accuracy of base calls at one or a few individual positions.The set of epigenetic target regions is a set of epigenetic target regions.

[0160] As used herein, "differentially methylated region" refers to a region of DNA that has a detectably different degree of methylation in at least one cell or tissue type compared to the degree of methylation in the same region of DNA from at least one other cell or tissue type; or has a detectably different degree of methylation in at least one cell or tissue type obtained from a subject with a disease or disorder compared to the degree of methylation in the same region of DNA in the same cell or tissue type obtained from a healthy subject.In some embodiments, a differentially methylated region has a detectably higher degree of methylation in at least one cell or tissue type, for example, at least one immune cell type, compared to the degree of methylation in the same region of DNA from at least one other cell or tissue type, for example, other immune cell types and / or cell types that contribute to cfDNA in a healthy individual, or from the same cell or tissue type from a healthy subject (e.g., a hypermethylated region). In some embodiments, a differentially methylated region has a detectably lower degree of methylation in at least one cell or tissue type, e.g., at least one immune cell type, compared to the degree of methylation in the same region of DNA from at least one other cell or tissue type, e.g., other immune cell types and / or cell types that contribute to cfDNA in a healthy individual, or from the same cell or tissue type from a healthy subject (e.g., a hypomethylated region).

[0161] Nucleic acids are "produced by tumors" or "circulating tumor DNA" ("ctDNA") when they originate from tumor cells. Tumor cells are neoplastic cells that originate from tumors, whether they remain in the tumor or are separated from the tumor (e.g., as in the case of metastatic cancer cells and circulating tumor cells). As used herein, a "precancer" or "precancerous condition" is an abnormality that has the potential to become cancerous, and the potential to become cancerous is greater than the potential that would exist if the abnormality were not present, i.e., normal. Examples of precancer include, but are not limited to, adenoma, hyperplasia, dysplasia, dysplasia, benign neoplasm (benign tumor), premalignant intraepithelial carcinoma, and polyps. It should be noted that certain types of intraepithelial carcinomas are recognized in the art as cancerous, e.g., stage 0 cancer, as opposed to premalignant.

[0162] The term "methylation" or "DNA methylation" refers to the addition of a methyl group to a nucleic acid base in a nucleic acid molecule. In some embodiments, methylation refers to the addition of a methyl group to a cytosine at a CpG site (cytosine-phosphate-guanine site, i.e., a cytosine followed by a guanine in the 5'→3' direction of a nucleic acid sequence). In some embodiments, DNA methylation refers to the addition of a methyl group to an adenine, e.g., in N6-methyladenine. In some embodiments, DNA methylation is 5-methylation (modification of the fifth carbon of the 6-carbon ring of cytosine). In some embodiments, 5-methylation refers to the addition of a methyl group to the 5C position of cytosine to create 5-methylcytosine (5mC). In some embodiments, methylation includes derivatives of 5mC. Derivatives of 5mC include, but are not limited to, 5-hydroxymethylcytosine (5-hmC), 5-formylcytosine (5-fC), and 5-caryboxylcytosine (5-caC). In some embodiments, DNA methylation is 3C methylation (modification of the third carbon of the 6-carbon ring of cytosine). In some embodiments, 3C methylation includes the addition of a methyl group to the 3C position of cytosine to generate 3-methylcytosine (3mC). Methylation can also occur at non-CpG sites, for example, methylation can occur at CpA, CpT, or CpC sites. DNA methylation can change the activity of methylated DNA regions. For example, when DNA in a promoter region is methylated, gene transcription can be suppressed. DNA methylation is crucial for normal development, and abnormalities in methylation can disrupt epigenetic regulation. Disruption, for example, suppression, of epigenetic regulation can cause diseases such as cancer. Promoter methylation in DNA can be indicative of cancer.

[0163] The term "hypermethylation" refers to an increased level or degree of methylation of a nucleic acid molecule compared to other nucleic acid molecules containing the same genetic information within a population of nucleic acid molecules (e.g., a sample). In some embodiments, hypermethylated DNA can include DNA molecules that contain at least one methylated residue, at least two methylated residues, at least three methylated residues, at least five methylated residues, or at least ten methylated residues.

[0164] The term "hypomethylation" refers to a reduced level or degree of methylation of a nucleic acid molecule compared to other nucleic acid molecules containing the same genetic information within a population (e.g., a sample) of nucleic acid molecules. In some embodiments, hypomethylated DNA includes unmethylated DNA molecules. In some embodiments, hypomethylated DNA may include DNA molecules containing 0 methylated residues, at most 1 methylated residue, at most 2 methylated residues, at most 3 methylated residues, at most 4 methylated residues, or at most 5 methylated residues.

[0165] The term "agent that recognizes modified nucleobases in DNA", e.g., "agent that recognizes modified cytosine in DNA", refers to a molecule or reagent that binds to or detects one or more modified nucleobases in DNA, e.g., methylcytosine. A "modified nucleobase" is a nucleobase that includes a difference in chemical structure from an unmodified nucleobase. In the case of DNA, the unmodified nucleobase is adenine, cytosine, guanine, or thymine. In some embodiments, the modified nucleobase is a modified cytosine. In some embodiments, the modified nucleobase is a methylated nucleobase. In some embodiments, the modified cytosine is a methylcytosine, e.g., 5-methylcytosine. In such embodiments, the cytosine modification is methyl. Agents that recognize methylcytosine in DNA include, but are not limited to, "methyl-binding reagents", which herein refer to reagents that bind to methylcytosine. Methyl-binding reagents include, but are not limited to, methyl-binding domains (MBDs) and methyl-binding proteins (MBPs), as well as antibodies specific for methylcytosine. In some embodiments, such antibodies bind to 5-methylcytosine in DNA. In some such embodiments, the DNA can be single-stranded or double-stranded. Suitable agents include agents that recognize double-stranded DNA, single-stranded DNA, and modified nucleotides in both double-stranded and single-stranded DNA.

[0166] The term "or combinations thereof" as used herein refers to any and all permutations and combinations of the terms listed before the term. For example, "A, B, C, or combinations thereof" is intended to include at least one of A, B, C, AB, AC, BC, or ABC, and also BA, CA, CB, ACB, CBA, BCA, BAC, or CAB, if order is important in a particular context. Continuing with this example, combinations containing repeats of one or more items or terms are expressly included, such as BB, AAA, AAB, BBC, AAABCCCC, CBBAAA, CABABB, etc. Those skilled in the art will understand that there is typically no limit to the number of items or terms in any combination, unless otherwise clear from the context.

[0167] "Or" is used in its inclusive sense, ie, equivalent to "and / or," unless the context otherwise requires.

[0168] Exemplary Methods A. Identification and quantification of immune cell types

[0169] In some embodiments, the method disclosed herein comprises sequencing cfDNA from a sample and determining methylation levels for a plurality of target regions comprising DNA sequences that are differentially methylated in a plurality of immune cell types. In some embodiments, the method disclosed herein comprises capturing at least one set of epigenetic target regions from cfDNA or a subsample thereof, comprising contacting the cfDNA or a subsample thereof with a target-specific probe specific for at least one set of epigenetic target regions, the set of epigenetic target regions comprising target regions comprising DNA sequences that are differentially methylated in a plurality of immune cell types, and determining methylation levels for the target regions. In some embodiments, the method disclosed herein comprises sequencing cfDNA and determining methylation levels for a plurality of hypomethylated variable target regions comprising DNA sequences that are differentially hypomethylated in a plurality of immune cell types. The target regions that are differentially hypomethylated in a plurality of immune cell types exhibit lower levels of methylation in the plurality of immune cell types than other cell types. In some embodiments, the method disclosed herein comprises: capturing at least one epigenetic target region set from cfDNA or a subsample thereof, comprising contacting cfDNA or a subsample thereof with a target-specific probe specific for at least one epigenetic target region set, wherein the epigenetic target region set comprises a hypomethylated variable target region that comprises a DNA sequence that is differentially hypomethylated in a plurality of immune cell types; and determining a methylation level for the target region.In any of these embodiments, the methylation level can be determined using partitioning, methylation-sensitive conversion, e.g., bisulfite conversion, direct detection during sequencing, or any other suitable approach.Various approaches are described herein.

[0170] Methylation levels can be used to determine the amount of each of multiple immune cell types from which the cfDNA originates. This can be useful, for example, to detect the presence of cancer or precancer, or other conditions (e.g., infection, transplant rejection), in that the state of the immune system reflected in the distribution of cell types contributing to the cfDNA can change as a result of such conditions. In some embodiments, the cfDNA originated from tumor cells and the cancer is a hematological cancer. In some embodiments, the cfDNA did not originate from tumor cells. In some such embodiments, the cancer is not a hematological cancer. In some such embodiments, the cancer is a solid tumor cancer, e.g., carcinoma or sarcoma. Without wishing to be bound by theory, cancers including solid tumor cancers, e.g., carcinomas and sarcomas, can cause changes to immune cell type distribution, including with respect to differentiated immune cell types and immune cell activation status, compared to immune cell distribution in healthy subjects or subjects without cancer. Such changes can be detected by the methods herein and can be useful for detecting cancer, as well as for determining cancer prognosis and / or treatment options.

[0171] In some embodiments, the method disclosed herein comprises: distributing a sample containing DNA by contacting the DNA with an agent that recognizes modified cytosine in the DNA; sequencing the DNA; and determining the level of each of a plurality of immune cell types from which the DNA originates.The level of immune cell type can be expressed, for example, as a relative amount or percentage for each cell type being quantified. Such determination is illustrated, for example, in Example 3. In some embodiments, the method comprises capturing or enriching a set of epigenetic target regions of DNA from one or more distributed subsamples before sequencing.In some embodiments, the modified cytosine is methylcytosine.

[0172] Thus, the methods herein allow for the detection and / or identification of immune-specific differentially methylated genomic regions, which can be used to identify and quantify different immune cell types from which DNA in a sample originates. Immune cell types can include immune cells of different differentiation types, different activation types, or both different differentiation types and different activation types. In fact, differentiation status and activation status overlap considerably and often change together in a given immune cell. For example, activation of an immune cell can induce differentiation of the cell. Immune cells of different activation types include activated cells, e.g., cells activated by inflammatory cytokines or antigens, and suppressed cells, e.g., cells suppressed by Tregs. Immune cell types include activated B cells (including memory B cells and plasma cells), activated T cells (including regulatory T cells (Tregs), CD4 effector memory T cells, CD4 central memory T cells, CD8 effector memory T cells, and CD8 central memory T cells), and natural killer (NK) cells. DNA from such cell types may be rare in samples from healthy individuals, e.g., cfDNA samples, but more common in samples from individuals with disease or disorders, e.g., cancer or precancerous conditions, e.g., cfDNA samples. In some embodiments, both hypermethylated and hypomethylated regions can be detected to distinguish DNA from closely related cell types, e.g., naive B cells and activated B cells, naive T cells and activated T cells, or different stages of myeloid lineage. In some embodiments, at least some of the differentially methylated regions are exclusively hypermethylated or exclusively hypomethylated in only one cell type, or in only one cell type within a cluster.In some embodiments, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10 differentially methylated regions are exclusively hypermethylated or exclusively hypomethylated in only one cell type identified or quantified within the cluster.

[0173] In some embodiments, determining the levels of different immune cell types from which the DNA in a sample originates facilitates disease diagnosis or identification of appropriate treatment. In some embodiments, changes in the levels of one or more immune cell types indicate the presence of a disease or disorder in the subject, such as cancer, precancer, infection, graft rejection, or other disorder that causes changes in the relative amount of a particular immune cell type compared to the amount present in a healthy subject. In some embodiments, changes in both the levels of one or more immune cell types in combination with sequence-independent changes in epigenetic target regions indicate the presence of a disease or disorder in the subject, such as cancer, precancer, infection, graft rejection, or other disorder that causes changes in the relative amount of a particular immune cell type compared to the amount present in a healthy subject and epigenetic changes. In some embodiments, the method facilitates identification of appropriate treatment based on the likelihood that the subject will respond to the treatment. In some such embodiments, determining the levels of DNA from one or more immune cell types in a sample from a subject with a particular cancer type facilitates prediction of clinical outcome of immunotherapy in the subject. When determining the level of different immune cell types facilitates disease diagnosis, identification of appropriate treatment, and association with therapeutic response, the threshold for disease diagnosis and identification of appropriate treatment can be the same or different.The level can be determined based on the number of molecules corresponding to different immune cell types, or the relative frequency of such molecules, or any value or ratio based on the number of molecules corresponding to one or more different immune cell types. b. Dividing the sample into multiple aliquots

[0174] In some embodiments described herein, different forms of DNA (e.g., hypermethylated and hypomethylated DNA) are physically partitioned based on one or more characteristics of the DNA. This approach can be used, for example, to determine whether a particular site or region is hypermethylated or hypomethylated. Partitioning can be performed, for example, before attaching adapters to the DNA molecules in the sample to facilitate the inclusion of partitioning tags in the adapters. The partitioning tags can be used to identify in which partition the molecule is found. After partitioning (and, if applicable, attachment of adapters), further steps can be performed, such as amplification, target capture, and sequencing.

[0175] Methylation profiling can involve determining methylation patterns across different regions of a genome. For example, after further steps discussed above, including distributing the molecules based on the degree of methylation (e.g., the relative number of methylated nucleobases per molecule) and sequencing, the sequences of the molecules in the different distributions can be mapped to a reference genome. This can indicate regions of the genome that are more highly methylated or less highly methylated compared to other regions. In this way, genomic regions can differ in their degree of methylation as opposed to individual molecules.

[0176] Partitioning the nucleic acid molecules in a sample can increase rare signals, for example, by enriching rare nucleic acid molecules that are more abundant in one partition of the sample. For example, genetic variations that are present in hypermethylated DNA but less abundant (or absent) in hypomethylated DNA can be more easily detected by partitioning the sample into hypermethylated and hypomethylated nucleic acid molecules. By analyzing multiple partitions of a sample, multidimensional analysis of a single molecule can be performed, and thus higher sensitivity can be achieved. Partitioning can include physically partitioning the nucleic acid molecules into partitions or subsamples based on the presence or absence of one or more methylated nucleic acid bases. The sample can be partitioned into partitions or subsamples based on features that indicate differential gene expression or disease state. The sample can be partitioned based on features or combinations thereof that provide a signal difference between normal and disease state during the analysis of nucleic acids, for example, cell-free DNA (cfDNA), non-cfDNA, tumor DNA, circulating tumor DNA (ctDNA) and cell-free nucleic acid (cfNA).

[0177] In some embodiments, hypermethylated and / or hypomethylated variable epigenetic target regions are analyzed to determine whether they exhibit differential methylation signatures of specific immune cell types, e.g., rare immune cell types, tumor cells, or types of cells that do not normally contribute to the DNA sample (e.g., cfDNA) being analyzed.

[0178] In some examples, the heterogeneous DNA in a sample is divided into two or more partitions (e.g., at least 3, 4, 5, 6 or 7 partitions). In some embodiments, each partition is differentially tagged. The tagged partitions can then be pooled together for collective sample preparation and / or sequencing. The partition-tagging-pooling step can be performed more than once, and each round of partitioning is tagged using a differential tag that is based on a different feature (examples provided herein) and is distinct from other partitions and partitioning means. In other examples, the differentially tagged partitions are sequenced separately.

[0179] In some embodiments, sequence read data from the differentially tagged pooled DNA is obtained and analyzed in silico. The tags are used to sort the read data from different distributions. Analysis to detect genetic variants can be performed at the level of each distribution as well as the total nucleic acid population level. For example, the analysis can include in silico analysis to determine genetic variants, such as CNVs, SNVs, indels, fusions, in the nucleic acids in each distribution. In some examples, the in silico analysis can include determining chromatin structure. For example, the coverage of sequence read data can be used to determine the positioning of nucleosomes in chromatin. Higher coverage can be correlated with higher nucleosome occupancy in genomic regions, while lower coverage can be correlated with lower nucleosome occupancy or nucleosome depleted regions (NDRs).

[0180] In some embodiments, the partitioning is based on one or more characteristics, e.g., methylation. Molecules can be sorted according to other characteristics, e.g., sequence length, nucleosome binding, sequence mismatch, immunoprecipitation, and / or proteins binding to DNA, using appropriate techniques as part of data analysis or partitioning, if applicable. The resulting partitioning can include one or more of the following nucleic acid forms: single-stranded DNA (ssDNA), double-stranded DNA (dsDNA), shorter DNA fragments, and longer DNA fragments. In some embodiments, partitioning based on cytosine modification (e.g., cytosine methylation) or methylation is typically performed, optionally combined with at least one additional partitioning step that can be based on any of the aforementioned characteristics or forms of DNA. In some embodiments, the heterogeneous population of nucleic acids is partitioned into nucleic acids with one or more epigenetic modifications and nucleic acids without one or more epigenetic modifications. Examples of epigenetic modifications include the presence or absence of methylation; the level of methylation; the type of methylation (e.g., 5-methylcytosine versus other types of methylation, e.g., adenine methylation and / or cytosine hydroxymethylation); and the association and level of association with one or more proteins, e.g., histones. Alternatively or additionally, the heterogeneous population of nucleic acids can be distributed into nucleic acid molecules associated with nucleosomes and nucleic acid molecules lacking nucleosomes. Alternatively or additionally, the heterogeneous population of nucleic acids can be distributed into single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA). Alternatively or additionally, the heterogeneous population of nucleic acids can be distributed based on the length of the nucleic acid (e.g., molecules up to 160 bp and molecules having a length longer than 160 bp).

[0181] The agent used to partition the population of nucleic acids within the sample can be an affinity agent, e.g., an antibody with a desired specificity, a natural binding partner or variant thereof (Bock et al., Nat Biotech 28: 1106-1114 (2010); Song et al., Nat Biotech 29: 68-72 (2011)), or an artificial peptide selected, e.g., by phage display, to have specificity for a given target. In some embodiments, the agent used in partitioning is an agent that recognizes a modified nucleobase. In some embodiments, the modified nucleobase recognized by the agent is a modified cytosine, e.g., a methylcytosine (e.g., 5-methylcytosine). In some embodiments, the modified nucleobase recognized by the agent is the product of a procedure that affects a first nucleobase in the DNA of the sample to be different from a second nucleobase in the DNA. In some embodiments, the modified nucleobase can be a "converted nucleobase," meaning that its base-pairing specificity has been altered by the procedure. For example, certain procedures convert unmethylated or unmodified cytosine to dihydrouracil, or more generally, at least one modified or unmodified form of cytosine undergoes deamination, resulting in uracil (which in the context of DNA is considered a modified nucleobase) or a further modified form of uracil. Examples of partitioning agents include antibodies, such as antibodies that recognize modified nucleobases, which may be modified cytosines, such as methylcytosines (e.g., 5-methylcytosine). In some embodiments, the partitioning agent is an antibody that recognizes modified cytosines other than 5-methylcytosine, such as 5-carboxylcytosine (5caC). Alternative partitioning agents include the methyl-binding domains (MBDs) and methyl-binding proteins (MBPs) described herein, including proteins such as MeCP2.

[0182] Additional non-limiting examples of partitioning agents are histone-binding proteins that can separate histone-bound nucleic acids from free or unbound nucleic acids. Examples of histone-binding proteins that can be used in the methods disclosed herein include RBBP4, RbAp48 and SANT domain peptides.

[0183] The binding of the partitioning agent to a particular nucleic acid and the partitioning of the nucleic acid into the subsamples can be performed to a certain degree, or can be performed in an essentially binary manner. In some cases, the nucleic acid that contains a greater proportion of a particular modification binds to the agent to a greater degree than the nucleic acid that contains a smaller proportion of modification. Similarly, partitioning can produce a subsample that contains a greater proportion and a smaller proportion of the nucleic acid that contains a particular modification. Alternatively, partitioning can produce a subsample that contains essentially all of the nucleic acid that contains modification or a subsample that does not contain such nucleic acid. In all cases, various levels of modification can be eluted from the partitioning agent sequentially.

[0184] In some embodiments, partitioning may include both binary partitioning and partitioning based on the degree / level of modification. For example, methylated fragments may be partitioned by methylated DNA immunoprecipitation (MeDIP), or all methylated fragments may be partitioned from non-methylated fragments using a methyl-binding domain protein (e.g., MethylMinder Methylated DNA Enrichment Kit (ThermoFisher Scientific)). Then, additional partitioning may involve eluting fragments with different levels of methylation by adjusting the salt concentration in the solution containing the methyl-binding domain and the bound fragments. As the salt concentration increases, fragments with higher methylation levels are eluted.

[0185] In some cases, the final distribution is enriched for nucleic acids with different degrees of modification (over- or under-representation of the modification). Over- and under-representation can be defined by the number of modifications that a nucleic acid has compared to the median number of modifications per strand in the population. For example, if the median number of 5-methylcytosine residues in the nucleic acids in a sample is two, then nucleic acids containing more than two 5-methylcytosine residues will be over-represented in this modification, and nucleic acids containing one or zero 5-methylcytosine residues will be under-represented. The effect of affinity separation is to enrich for nucleic acids with over-represented modifications in the binding phase and for nucleic acids with under-represented modifications in the non-binding phase (i.e. in solution). The nucleic acids in the binding phase can be eluted before further processing.

[0186] When using MeDIP or MethylMiner® Methylated DNA Enrichment Kit (ThermoFisher Scientific), different levels of methylation can be partitioned using sequential elution. For example, the low methylation partition (no methylation) can be separated from the methylation partition by contacting the nucleic acid population with MBD from the kit attached to magnetic beads. The beads are used to separate the methylated nucleic acids from the unmethylated nucleic acids. One or more elution steps are then performed sequentially to elute the nucleic acids with different levels of methylation. For example, the first set of methylated nucleic acids can be eluted with a salt concentration of 160 mM or higher, for example, at least 150 mM, at least 200 mM, 300 mM, 400 mM, 500 mM, 600 mM, 700 mM, 800 mM, 900 mM, 1000 mM, or 2000 mM. After such methylated nucleic acids are eluted, magnetic separation is once again used to separate the higher levels of methylated nucleic acids from those with lower levels of methylation. The elution and magnetic separation steps can be repeated to create various partitions, for example, a low methylation partition (enriched for nucleic acids with no methylation), a methylation partition (enriched for nucleic acids with low levels of methylation), and a high methylation partition (enriched for nucleic acids with high levels of methylation).

[0187] In some methods, the nucleic acids bound to the agent used for affinity separation-based partitioning are subjected to a washing step. The washing step washes away the nucleic acids that are weakly bound to the affinity agent. Such nucleic acids can be enriched to a degree that is close to the mean or median (i.e., halfway between the nucleic acids that remain bound to the solid phase and the nucleic acids that are not bound to the solid phase upon initial contact of the sample with the agent).

[0188] Affinity separation results in at least two, sometimes three or more distributions of nucleic acids with different degrees of modification. Although the distributions are still separate, the nucleic acids of at least one distribution, and usually two or three (or more) distributions, are linked to nucleic acid tags, usually provided as components of adapters, and the nucleic acids in different distributions are given different tags that distinguish the members of one distribution from the members of another distribution. The tags linked to the nucleic acid molecules of the same distribution can be the same or different from each other. However, when different from each other, the tags can have part of their code in common to identify the molecules to which they are attached as molecules of a particular distribution.

[0189] For further details regarding separating nucleic acid samples based on characteristics such as methylation, see WO2018 / 119452, which is incorporated herein by reference.

[0190] In some embodiments, the nucleic acid molecules may be fractionated into different partitions based on the nucleic acid molecules that are bound to a particular protein or fragment thereof and the nucleic acid molecules that are not bound to that particular protein or fragment thereof.

[0191] Nucleic acid molecules can be fractionated based on DNA-protein binding. Protein-DNA complexes can be fractionated based on the specific properties of proteins. Examples of such properties include various epitopes, modifications (e.g., histone methylation or acetylation) or enzymatic activity. Examples of proteins that can bind to DNA and serve as the basis for fractionation can include, but are not limited to, protein A and protein G. Any suitable method can be used to fractionate nucleic acid molecules based on protein binding regions. Examples of methods used to fractionate nucleic acid molecules based on protein binding regions include, but are not limited to, SDS-PAGE, chromatin immunoprecipitation (ChIP), heparin chromatography, and asymmetric flow field separation (AF4).

[0192] In some embodiments, the distribution of the sample into multiple subsamples is carried out by contacting the nucleic acid with an antibody that recognizes a modified nucleobase in DNA, which may be a modified cytosine or a product of a procedure that affects a first nucleobase in DNA differently from a second nucleobase in the DNA of the sample. In some embodiments, the modified nucleobase is 5mC. In some embodiments, the modified nucleobase is 5caC. In some embodiments, the modified nucleobase is dihydrouracil (DHU). In some embodiments, an antibody that recognizes a modified nucleobase in DNA is used to distribute single-stranded DNA.

[0193] In some embodiments, partitioning is performed by contacting the nucleic acid with the methyl-binding domain ("MBD") of a methyl-binding protein ("MBP"). In some such embodiments, the nucleic acid is contacted with the entire MBP. In some embodiments, the MBD binds 5-methylcytosine (5mC), and the MBP comprises an MBD, and is interchangeably referred to herein as a methyl-binding protein or a methyl-binding domain protein. In some embodiments, the MBD binds 5mC and 5hmC. In some embodiments, the MBD is coupled to paramagnetic beads, e.g., Dynabeads® M-280 streptavidin, via a biotin linker. Partitioning into fractions with different degrees of methylation can be performed by eluting the fractions by increasing the NaCl concentration.

[0194] In some embodiments, the bound DNA is eluted by contacting the antibody or MBD with a protease, such as proteinase K. This can be performed instead of, or in addition to, the elution step using NaCl, as discussed above.

[0195] Examples of agents that recognize modified nucleobases contemplated herein include, but are not limited to, the following:

[0196] (a) MeCP2 is a protein that preferentially binds 5-methyl-cytosine over unmodified cytosine.

[0197] (b) RPL26, PRP8 and the DNA mismatch repair protein MHS6 bind preferentially to 5-hydroxymethyl-cytosine over unmodified cytosine.

[0198] (c) FOXK1, FOXK2, FOXP1, FOXP4 and FOXI3 preferably bind 5-formyl-cytosine over unmodified cytosine (Iurlaro et al., Genome Biol. 14: R119 (2013)).

[0199] (d) An antibody specific for one or more methylated or modified nucleobases or their conversion products, e.g., 5mC, 5caC, or DHU.

[0200] Generally, elution is a function of the number of modifications, e.g., the number of methylation sites per molecule, with molecules with more methylation eluting under increasing salt concentrations. A series of elution buffers with increasing NaCl concentrations can be used to elute DNA into separate populations based on the degree of methylation. The salt concentrations can range from about 100 nM to about 2500 mM NaCl. In one embodiment, the process results in three partitions. The molecules are contacted with a solution of a first salt concentration that contains molecules that contain an agent that recognizes modified nucleobases, and the molecules can be attached to a capture moiety such as streptavidin. At the first salt concentration, one population of molecules binds to the agent and one population remains unbound. The unbound population can be separated as a "hypomethylated" population. For example, the first partition enriched for hypomethylated forms of DNA is the partition that remains unbound at a lower salt concentration, e.g., 100 mM or 160 mM. A second partition, enriched for intermediately methylated DNA, is eluted using an intermediate salt concentration, for example between 100 mM and 2000 mM, which is also separated from the sample. A third partition, enriched for highly methylated forms of DNA, is eluted using a high salt concentration, for example at least about 2000 mM.

[0201] In some embodiments, a monoclonal antibody against 5-methylcytidine (5mC) is used to purify methylated DNA. The DNA is denatured, for example, at 95°C to obtain single-stranded DNA fragments. Standard or magnetic bead-coupled protein G after incubation with anti-5mC antibody and washing are used to immunoprecipitate the DNA bound to the antibody. Such DNA can then be eluted. Partitions can include non-precipitated DNA and one or more partitions eluted from the beads.

[0202] In some embodiments, sample DNA (e.g., between 5-200 ng) is mixed with methyl-binding domain (MBD) buffer and magnetic beads conjugated with MBD protein and incubated overnight. Methylated DNA (highly methylated DNA) binds to the MBD protein on the magnetic beads during this incubation. Unmethylated (low methylated DNA) or less methylated DNA (intermediate methylation) is washed off the beads with buffers containing increasing concentrations of salt. For example, one, two, or more fractions containing unmethylated, low methylated, and / or intermediate methylated DNA may be obtained from such washes. Finally, highly methylated DNA (highly methylated DNA) is eluted from the MBD protein using a high salt buffer. In some embodiments, these washes result in three partitions of DNA with increasing methylation levels (low methylated partition, intermediate methylated fraction, and high methylated partition).

[0203] In some embodiments, the partitioning procedure may result in incomplete sorting of DNA molecules between subsamples.For example, a small number of molecules in unmethylated or hypomethylated subsamples may be highly modified (e.g., hypermethylated), and / or a small number of molecules in hypermethylated subsamples may be unmodified or mostly unmodified (e.g., unmethylated or mostly unmethylated).Such molecules are considered to be non-specifically partitioned.

[0204] In some embodiments, non-specifically distributed molecules are removed using a methylation-dependent nuclease, such as a methylation-dependent restriction enzyme (MDRE) that digests / cuts DNA when the restriction enzyme (RE) recognition site contains a methylated nucleotide, but does not cut DNA when the restriction enzyme (RE) recognition site contains an unmethylated nucleotide. In some embodiments, non-specifically distributed molecules are removed using a methylation-sensitive nuclease, such as a methylation-sensitive restriction enzyme (MSRE) that digests / cuts DNA when the restriction enzyme (RE) recognition site contains an unmethylated nucleotide, but does not cut DNA when the restriction enzyme (RE) recognition site contains a methylated nucleotide. For example, in some embodiments, the low methylation partial sample is contacted with a methylation-dependent nuclease, such as a methylation-dependent restriction enzyme, thereby degrading the non-specifically distributed DNA, such as methylated DNA, in the partial sample. Alternatively or additionally, the high methylation partial sample is contacted with a methylation-sensitive endonuclease, such as a methylation-sensitive restriction enzyme, thereby degrading the non-specifically distributed DNA in the partial sample.

[0205] The decomposition of non-specifically distributed DNA in one or more divided aliquot samples can improve the performance of methods that rely on accurate distribution of DNA based on cytosine modification.For example, such decomposition can provide improved sensitivity and / or simplify downstream analysis.In some embodiments, distributing DNA based on modification, such as methylation, and then removing non-specifically distributed DNA using MDRE and / or MSRE as described herein provides improved efficiency and / or cost compared to DNA analysis methods that include procedures that affect a first nucleobase differently from a second nucleobase, such as bisulfite sequencing or bisulfite conversion.

[0206] In some embodiments, one or more nucleases are used to degrade non-specifically distributed DNA molecules. In some embodiments, the partial sample is contacted with multiple nucleases. The partial sample can be contacted with the nucleases sequentially or simultaneously. The simultaneous use of nucleases can be advantageous when the nucleases are active under similar conditions (e.g., buffer composition) to avoid unnecessary manipulation of the sample. By contacting the partial sample with more than one methylation-dependent restriction enzyme, non-specifically distributed hypermethylated DNA can be degraded more completely. By contacting the partial sample with more than one methylation-sensitive restriction enzyme, non-specifically distributed hypomethylated and / or unmethylated DNA can be degraded more completely.

[0207] In some embodiments, the methylation-dependent nuclease comprises one or more of MspJI, LpnPI, FspEI, or McrBC. In some embodiments, at least two methylation-dependent nucleases are used. In some embodiments, at least three methylation-dependent nucleases are used.

[0208] In some embodiments, the methylation-sensitive nuclease comprises one or more of AatII, AccII, AciI, Aor13HI, Aor15HI, BspT104I, BssHII, BstUI, Cfr10I, ClaI, CpoI, Eco52I, HaeII, HapII, HhaI, Hin6I, HpaII, HpyCH4IV, MluI, MspI, NaeI, NotI, NruI, NsbI, PmaCI, Psp1406I, PvuI, SacII, SalI, SmaI, and SnaBI. In some embodiments, at least two methylation-sensitive nucleases are used. In some embodiments, at least three methylation-sensitive nucleases are used. In some embodiments, the methylation-sensitive nuclease comprises BstUI and HpaII. In some embodiments, the two methylation-sensitive nucleases comprise HhaI and AccII. In some embodiments, the methylation sensitive nucleases include BstUI, HpaII and Hin6I.

[0209] In some embodiments, the DNA fraction is desalted and concentrated in preparation for the enzymatic steps of library preparation. c. Ligation or addition of adapters

[0210] In some embodiments, adapters are added to the DNA. This can be done simultaneously with the amplification procedure, for example, by providing an adapter at the 5' portion of the primer (if PCR is used, this can be called library prep-PCR or LP-PCR). In some embodiments, adapters are added by other approaches, for example, ligation. In some such methods, before partitioning or capture, a first adapter is added to the nucleic acid by ligation to its 3' end, which can include ligation to single-stranded DNA. The adapter can be used, for example, as a priming site for second strand synthesis using a universal primer and DNA polymerase. A second adapter can then be ligated to at least the 3' end of the second strand of the double-stranded molecule in turn. In some embodiments, the first adapter includes an affinity tag, for example, biotin, and the nucleic acid ligated to the first adapter is bound to a solid support (e.g., beads), which can include a binding partner for the affinity tag, for example, streptavidin. For further discussion of related procedures, see Gansauge et al., Nature Protocols 8:737-748 (2013). Commercially available kits for sequencing library preparation compatible with single-stranded nucleic acids are available, such as the Accel-NGS® Methyl-Seq DNA Library Kit from Swift Biosciences. In some embodiments, after adaptor ligation, the nucleic acid is amplified.

[0211] Preferably, the adaptors contain a sufficient number of different tags such that the number of tag combinations results in a low probability, e.g., 95, 99 or 99.9%, of two nucleic acids having the same start and end points being endowed with the same combination of tags. Adaptors, whether with the same or different tags, can contain the same or different primer binding sites, although preferably the adaptors contain the same primer binding sites.

[0212] In some embodiments, after attachment of the adaptors, the nucleic acid is subjected to amplification, which may, for example, use a universal primer that recognizes a primer binding site in the adaptor.

[0213] In some embodiments, after the attachment of the adaptor, the DNA is partitioned, which includes contacting the DNA with an agent that preferentially binds to nucleic acids with epigenetic modifications. The nucleic acid is partitioned from binding to the agent into at least two subsamples that differ in the degree to which the nucleic acid has the modification. For example, if the agent has an affinity for nucleic acids with modifications, nucleic acids with over-represented modifications (compared to the median occurrence in the population) will preferentially bind to the agent, while nucleic acids with under-represented modifications will not bind to the agent or will be more easily eluted from the agent. The nucleic acid can then be amplified from a primer that is bound to the primer binding site in the adaptor. Alternatively, partitioning can be performed before the attachment of the adaptor, in which case the adaptor can include a differential tag that includes a component that identifies which partition the molecule is present in.

[0214] In some embodiments, the nucleic acid is linked at both ends to a Y-shaped adaptor that contains a primer binding site and a tag, and the molecule is amplified. d. Tagging

[0215] "Tagging" a DNA molecule is the procedure in which a tag is attached to or associated with a DNA molecule. A tag can be a molecule, e.g., a nucleic acid, that contains information that indicates the characteristics of the molecule with which it is associated. For example, a molecule can have a sample tag (that identifies a molecule in one sample from a molecule in a different sample), or a molecular tag / molecular barcode / barcode (that identifies different molecules from each other (in both unique and non-unique tagging scenarios)). For methods that involve a partitioning step, a partitioning tag (that identifies a molecule in one partition from a molecule in a different partition) can be included. In some embodiments, the adapter that is added to the DNA molecule comprises a tag. In certain embodiments, the tag can include one barcode or a combination of barcodes. As used herein, the term "barcode" refers to a nucleic acid molecule having a specific nucleotide sequence, or the nucleotide sequence itself, depending on the context. A barcode can have, for example, between 10 and 100 nucleotides. A collection of barcodes can have degenerate sequences or sequences with a certain Hamming distance that is desirable for a particular purpose. So, for example, a molecular barcode can be composed of one barcode or a combination of two barcodes, each attached to a different end of the molecule. Additionally or alternatively, different sets of molecular barcodes, or molecular tags, can be used for different partitions and / or samples, such that the barcodes serve as molecular tags through their individual sequences and serve to identify the partitions and / or samples to which they correspond based on the sets of which they are members.

[0216] In some embodiments, two or more distributions, for example each distribution, are differentially tagged. Tags can be used to label individual polynucleotide population distributions to correlate the tag (or multiple tags) with a specific distribution. Alternatively, tags can be used in embodiments that do not use a distribution step. In some embodiments, a single tag can be used to label a specific distribution. In some embodiments, multiple different tags can be used to label a specific distribution. In embodiments that use multiple different tags to label a specific distribution, the set of tags used to label one distribution can be easily distinguished from the set of tags used to label another distribution. In some embodiments, the tags may have additional functions, e.g., the tags may be used to index the origin of a sample or may be used as a unique molecular identifier (e.g., may be used to improve the quality of sequencing data by distinguishing sequencing errors from mutations, e.g., as in Kinde et al., Proc Nat'l Acad Sci USA 108: 9530-9535 (2011); Kou et al., PLoS ONE,11: e0146638 (2016)), or may be used as a non-unique molecular identifier, e.g., as described in U.S. Pat. No. 9,598,731. Similarly, in some embodiments, the tags may have additional functions, e.g., the tags may be used to index the origin of a sample or may be used as a non-unique molecular identifier (e.g., may be used to improve the quality of sequencing data by distinguishing sequencing errors from mutations).

[0217] In some embodiments, distribution tagging includes tagging the molecules in each distribution with a distribution tag. After recombining the distributions (e.g., to reduce the number of required sequencing runs and avoid unnecessary costs) and sequencing the molecules, the distribution tag identifies the distribution of origin. In some embodiments, the distribution tag can serve as an identifier of the distribution of origin and the molecule, i.e., different distributions are tagged with different sets of molecular tags, e.g., composed of pairs of barcodes. In this way, one or more molecular barcodes attached to the molecules indicate the distribution of origin, as well as the usefulness for identifying the molecules within the distribution. For example, a first set of 35 barcodes can be used to tag the molecules in the first distribution, and a second set of 35 barcodes can be used to tag the molecules in the second distribution.

[0218] In some embodiments, after partitioning and tagging with partition tags, the molecules can be pooled for sequencing in a single run. In some embodiments, sample tags are added to the molecules, for example, in a step after partition tag addition and pooling. Sample tags can facilitate pooling of material generated from multiple samples for sequencing in a single sequencing run.

[0219] Alternatively, in some embodiments, the distribution tag can be correlated with the sample as well as the distribution. As a simple example, a first tag can indicate a first distribution of a first sample, a second tag can indicate a second distribution of the first sample, a third tag can indicate a first distribution of a second sample, and a fourth tag can indicate a second distribution of the second sample.

[0220] Tags may be attached to molecules that have already been distributed based on one or more characteristics, but the final tagged molecules in the library may no longer possess that characteristic. For example, single-stranded DNA molecules may be distributed and tagged, but the final tagged molecules in the library are likely to be double-stranded. Similarly, DNA may be subjected to distribution based on different levels of methylation, but the tagged molecules derived from these molecules in the final library are likely to be unmethylated. Thus, the tags attached to molecules in the library typically represent the characteristics of the "parent molecule" from which the final tagged molecules are derived, and not necessarily the characteristics of the tagged molecules themselves.

[0221] As an example, barcodes 1, 2, 3, 4, etc. are used to tag and label molecules in a first distribution; barcodes A, B, C, D, etc. are used to tag and label molecules in a second distribution; and barcodes a, b, c, d, etc. are used to tag and label molecules in a third distribution. Differentially tagged distributions can be pooled before sequencing. Differentially tagged distributions can be sequenced individually or sequenced together simultaneously, for example, in the same flow cell of an Illumina sequencer.

[0222] After sequencing, analysis of read data can be performed at the level of each distribution as well as the level of the total DNA population. Tags are used to sort read data from different distributions. Analysis can include in silico analysis to determine genetic and epigenetic variations (one or more of methylation, chromatin structure, etc.) using sequence information, genomic coordinate length, coverage, and / or copy number. In some embodiments, higher coverage can be correlated with higher nucleosome occupancy in a genomic region, while lower coverage can be correlated with lower nucleosome occupancy or nucleosome depleted regions (NDRs). e. Enrichment / capture step; Amplification

[0223] The method disclosed herein may comprise capturing DNA, for example, cfDNA target region.In some embodiments, capturing comprises contacting DNA with a probe (e.g., oligonucleotide) specific to the target region.Enrichment or capture can be carried out on any sample or subsample described herein using any suitable approach known in the art.

[0224] In some embodiments, enrichment or capture is performed after attachment of adapters to sample molecules. In some embodiments, enrichment or capture is performed after a partitioning step. In some embodiments, enrichment or capture is performed after an amplification step. In some embodiments, sample molecules are partitioned, then adapters are attached, then the sample molecules are amplified, and then the amplified molecules are subjected to enrichment or capture. The enriched or captured molecules can then be subjected to another amplification and then sequenced.

[0225] In some embodiments, the probe specific for the target region includes a capture moiety that facilitates enrichment or capture of DNA hybridized to the probe. In some embodiments, the capture moiety is biotin. In some such embodiments, streptavidin attached to a solid support, e.g., magnetic beads, is used to bind to the biotin. Non-specifically bound DNA that does not include the target region is washed away from the captured DNA. In some embodiments, the DNA is then dissociated from the probe and eluted from the solid support using a salt wash, or a buffer containing another DNA denaturing agent. In some embodiments, the probe is also eluted from the solid support, e.g., by disrupting the biotin-streptavidin interaction. In some embodiments, the captured DNA is amplified after elution from the solid support. In some such embodiments, the DNA that includes the adapter is amplified using a PCR primer that anneals to the adapter. In some embodiments, the captured DNA is amplified while still attached to the solid support. In some such embodiments, the amplification includes the use of a PCR primer that anneals to a sequence within the adapter and a PCR primer that anneals to a sequence within the probe that anneals to the target region of the DNA.

[0226] In some embodiments, the methods herein include enriching for or capturing DNA that includes epigenetic and / or sequence variable target regions. Such regions may be captured from an aliquot of a sample (e.g., a sample that has undergone adapter attachment and amplification), but distributing the DNA with an agent that recognizes modified cytosine, e.g., methylcytosine, is performed on a separate aliquot of the sample. Enriching for or capturing DNA that includes epigenetic and / or sequence variable target regions may include contacting the DNA with a first or second set of target-specific probes. Such target-specific probes may have any of the features described herein for a set of target-specific probes, including, but not limited to, in the above embodiments and in the following section related to probes. The capturing step may be performed on one or more aliquots prepared during the methods disclosed herein. In some embodiments, DNA is captured from a first aliquot or a second aliquot, e.g., a first aliquot and a second aliquot. In some embodiments, the aliquots are differentially tagged (e.g., as described herein) and then pooled before undergoing capture. Exemplary methods for capturing DNA containing epigenetic and / or sequence variable target regions can be found, for example, in WO2020 / 160414, which is hereby incorporated by reference herein.

[0227] The capturing step can be carried out using the conditions suitable for specific nucleic acid hybridization, which generally depend to some extent on the characteristics of the probe, such as length, base composition, etc. Those skilled in the art are familiar with the appropriate conditions, taking into account the general knowledge in the art of nucleic acid hybridization. In some embodiments, a complex of target-specific probe and DNA is formed.

[0228] In some embodiments, the methods described herein include capturing a plurality of sets of target regions of cfDNA obtained from a subject. The target regions may include differences depending on whether they originate from a tumor, from a healthy cell, or from a particular cell type. The capturing produces a captured set of cfDNA molecules. In some embodiments, the cfDNA molecules corresponding to the sequence variable target region set are captured with a higher capture yield in the captured set of cfDNA molecules than the cfDNA molecules corresponding to the epigenetic target region set. In some embodiments, the methods described herein include contacting the cfDNA obtained from the subject with a set of target-specific probes, the set of target-specific probes being configured to capture the cfDNA corresponding to the sequence variable target region set with a higher capture yield than the cfDNA corresponding to the epigenetic target region set. For additional discussion of the capturing steps, capture yields, and related aspects, see WO2020 / 160414, which is incorporated herein by reference for all purposes.

[0229] Because sequence-variable target regions may require a greater sequencing depth than epigenetic target regions may require to analyze them with sufficient confidence or accuracy, it may be beneficial to capture cfDNA corresponding to sequence-variable target regions set with a higher capture yield than cfDNA corresponding to epigenetic target regions set.The amount of data required to determine fragmentation patterns (e.g., to test for disruption of transcription start sites or CTCF binding sites) or fragment abundances (e.g., in hypermethylation and hypomethylation distribution) is generally less than the amount of data required to determine the presence or absence of cancer-associated sequence mutations.Capturing target regions set with different yields may facilitate sequencing target regions to different sequencing depths in the same sequencing run (e.g., using pooled mixtures and / or in the same sequencing cell).

[0230] In some embodiments, DNA is amplified. In some embodiments, amplification is carried out before the capture step. In some embodiments, amplification is carried out after the capture step. In some embodiments, amplification is carried out before and after the capture step. In various embodiments, the method further comprises sequencing the captured DNA, for example, to various degrees of sequencing depth for epigenetic and sequence variable target region set, in accordance with the discussion herein.

[0231] In some embodiments, the capture step is carried out with the probe of sequence variable target region set and the probe of epigenetic target region set at the same time in the same container, for example, the probe of sequence variable target region set and the probe of epigenetic target region set are in the same composition.This approach provides a relatively streamlined workflow.In some embodiments, the concentration of the probe of sequence variable target region set is higher than the concentration of the probe of epigenetic target region set.

[0232] Alternatively, the capturing step is performed with a sequence variable target region probe set in a first container and with an epigenetic target region probe set in a second container, or the contacting step is performed with a sequence variable target region probe set at a first time point and the first container, and with an epigenetic target region probe set at a second time point before or after the first time point. This approach allows for the preparation of separate first and second compositions that contain captured DNA corresponding to the sequence variable target region set and captured DNA corresponding to the epigenetic target region set. The compositions can be processed separately as desired (e.g., to be divided based on methylation as described herein) and pooled in appropriate proportions to provide material for further processing and analysis, such as sequencing.

[0233] In some embodiments, as described herein, the adapter is included in the DNA. In some embodiments, a tag, which may be or may include a barcode, is included in the DNA. In some embodiments, such a tag is included in the adapter. The tag may facilitate the identification of the origin of the nucleic acid. For example, the barcode may be used to allow the origin (e.g., subject) from which the DNA originates to be identified after pooling of multiple samples for parallel sequencing. This may be done simultaneously with the amplification procedure, for example, by providing a barcode in the 5' portion of the primer, for example, as described herein. In some embodiments, the adapter and the tag / barcode are provided by the same primer or primer set. For example, the barcode may be located 3' of the adapter and 5' of the portion of the primer that hybridizes to the target. Alternatively, the barcode may be added with the adapter by other approaches, for example, ligation, optionally in the same ligation substrate.

[0234] Additional details regarding amplification, tags, and barcodes are discussed herein, which can be combined to the extent practicable with any of these embodiments. f. A procedure that affects a first nucleobase in DNA differently than a second nucleobase in the DNA.

[0235] In some embodiments, the method disclosed herein comprises subjecting DNA to a procedure that affects a first nucleobase in DNA differently from a second nucleobase in DNA, wherein the first nucleobase is a modified or unmodified nucleobase, the second nucleobase is a modified or unmodified nucleobase different from the first nucleobase, and the first nucleobase and the second nucleobase have the same base pairing specificity.In some embodiments, the procedure chemically converts the first or second nucleobase, so that the base pairing specificity of the converted nucleobase is changed. In some embodiments, when the first nucleobase is modified or unmodified adenine, the second nucleobase is modified or unmodified adenine; when the first nucleobase is modified or unmodified cytosine, the second nucleobase is modified or unmodified cytosine; when the first nucleobase is modified or unmodified guanine, the second nucleobase is modified or unmodified guanine; and when the first nucleobase is modified or unmodified thymine, the second nucleobase is modified or unmodified thymine (wherein modified and unmodified uracil are encompassed within modified thymine for purposes of this step).

[0236] In some embodiments, when the first nucleobase is modified or unmodified cytosine, the second nucleobase is modified or unmodified cytosine.For example, the first nucleobase can include unmodified cytosine (C), and the second nucleobase can include one or more of 5-methylcytosine (mC) and 5-hydroxymethylcytosine (hmC).Alternatively, the second nucleobase can include C, and the first nucleobase can include one or more of mC and hmC.For example, as shown in the summary above and the discussion below, other combinations are also possible, such as when one of the first and second nucleobases includes mC and the other includes hmC.

[0237] In some embodiments, the procedure that affects the first nucleobase in DNA differently from the second nucleobase in DNA comprises bisulfite conversion. Treatment with bisulfite converts unmodified cytosine and certain modified cytosines (e.g., 5-formylcytosine (fC) or 5-carboxylcytosine (caC)) to uracil, while other modified cytosines (e.g., 5-methylcytosine, 5-hydroxylmethylcystosine) are not converted. Carrying out bisulfite conversion can facilitate using sequence read data to identify positions that contain mC or hmC. For an exemplary description of bisulfite conversion, see, for example, Moss et al., Nat Commun. 2018; 9: 5068.

[0238] In some embodiments, the procedure of affecting the first nucleobase in DNA differently from the second nucleobase in DNA comprises oxidative bisulfite (Ox-BS) conversion.Performing Ox-BS conversion can facilitate identifying the position containing mC using sequence reading data.For an exemplary description of oxidative bisulfite conversion, see, for example, Booth et al., Science 2012; 336: 934-937.

[0239] In some embodiments, the procedure of affecting a first nucleobase in DNA differently from a second nucleobase in DNA comprises Tet-assisted bisulfite (TAB) conversion. For example, as described in Yu et al., Cell 2012; 149: 1368-80, β-glucosyltransferase can be used to protect hmC (forming 5-glucosylhydroxymethylcytosine (ghmC)), then TET protein, e.g., mTet1, can be used to convert mC to caC, and then bisulfite treatment can be used to convert C and caC to U, while ghmC remains unaffected. Thus, when TAB conversion is used, the first nucleobase comprises one or more of unmodified cytosine, fC, caC, mC, or other cytosine forms affected by bisulfite, and the second nucleobase comprises hmC. Performing TAB conversion can facilitate identifying positions containing hmC using sequence read data.

[0240] In some embodiments, the procedure of affecting a first nucleobase in DNA differently from a second nucleobase in DNA includes Tet-assisted conversion with a substituted borane reducing agent, optionally the substituted borane reducing agent is 2-picoline borane, borane pyridine, tert-butylamine borane, or ammonia borane. See, for example, Liu et al., Nature Biotechnology 2019; 37:424-429 (e.g., Supplementary Figure 1 and Supplementary Note 7). Performing TAP conversion can facilitate identifying positions containing unmodified C using sequence read data. This procedure encompasses Tet-assisted pyridine borane sequencing (TAPS), which is described in more detail in Liu et al. 2019 supra.

[0241] Alternatively, protection of hmC (e.g., using βGT) can be combined with Tet-assisted conversion using a substituted borane reducing agent. Performing such a TAPSβ conversion can facilitate using sequence read data to distinguish positions containing one unmodified C or hmC from positions containing mC. For an exemplary description of this type of conversion, see, for example, Liu et al., Nature Biotechnology 2019; 37:424-429.

[0242] In some embodiments, the procedure of affecting the first nucleobase in DNA differently from the second nucleobase in DNA comprises APOBEC coupling epigenetic (ACE) conversion.Performing ACE conversion can facilitate using sequence read data to distinguish the position containing hmC from the position containing mC or unmodified C.For an exemplary description of ACE conversion, see, for example, Schutsky et al., Nature Biotechnology 2018; 36: 1083-1090.

[0243] In some embodiments, the procedure that affects a first nucleobase in DNA differently from a second nucleobase in DNA comprises enzymatic conversion of the first nucleobase, such as in EM-Seq.See, for example, Vaisvila R, et al. (2019) EM-seq: Detection of DNA methylation at single base resolution from picograms of DNA. bioRxiv; DOI: 10.1101 / 2019.12.20.884692v1, available at www.biorxiv.org / content / 10.1101 / 2019.12.20.884692v1.

[0244] In some embodiments, the first nucleobase is a modified or unmodified adenine and the second nucleobase is a modified or unmodified adenine. In some embodiments, the modified adenine is N6-methyladenine (mA). In some embodiments, the modified adenine is N 6 -Methyladenine (mA), N 6 -Hydroxymethyladenine (hmA), or N 6 -formyl adenine (fA). g. Captured set; target area

[0245] In some embodiments, the nucleic acid captured or enriched using the methods described herein comprises captured DNA, for example, one or more captured sets of DNA.In some embodiments, the captured DNA comprises a target region that is differentially methylated in different immune cell types.In some embodiments, the immune cell types comprise rare or closely related immune cell types, for example, activated lymphocytes and naive lymphocytes, or myeloid cells at different stages of differentiation.

[0246] In some embodiments, the captured epigenetic target region set captured from the sample or the first subsample comprises a hypermethylated variable target region. In some embodiments, the hypermethylated variable target region is differentially or exclusively hypermethylated in one cell type or one immune cell type, or in one immune cell type in a cluster. In some embodiments, the hypermethylated variable target region is hypermethylated to the extent that it is identifiably higher or exclusively present in one cell type or one immune cell type, or in one immune cell type in a cluster. Such a hypermethylated variable target region may be hypermethylated in other cell types, but not to the extent observed in one cell type. In some embodiments, the hypermethylated variable target region shows lower methylation in healthy cfDNA than at least one other tissue type.

[0247] In some embodiments, the captured epigenetic target region set captured from the sample or second subsample comprises a hypomethylated variable target region. In some embodiments, the hypomethylated variable target region is exclusively hypomethylated in one cell type or in one immune cell type, or in one immune cell type in a cluster. In some embodiments, the hypomethylated variable target region is hypomethylated to the extent that it is exclusively present in one cell type or in one immune cell type, or in one immune cell type in a cluster. Such a hypomethylated variable target region may be hypomethylated in other cell types, but not to the extent observed in one cell type. In some embodiments, the hypomethylated variable target region shows higher methylation in healthy cfDNA than at least one other tissue type.

[0248] Without wishing to be bound by any particular theory, in individuals with cancer, proliferating or activated immune cells (and potentially also cancer cells) may shed more DNA into the bloodstream than immune cells in healthy individuals (and, respectively, healthy cells of the same tissue type). Thus, the distribution of cell types and / or tissues of origin of cfDNA may change during carcinogenesis. For example, the distribution of immune cell types of origin may change in subjects with cancer, precancer, infection, graft rejection, or other diseases or disorders that directly or indirectly affect the immune system. Similarly, the status of epigenetic target regions of certain immune cell types may change in subjects with such diseases compared to healthy subjects or compared to the same subjects before they had the disease or disorder. Thus, alterations in hypermethylation and / or hypomethylation may be indicative of disease. For example, increased levels of hypermethylated and / or hypomethylated variable target regions in the partial samples after the partitioning step may be indicative of the presence (or recurrence depending on the subject's history) of cancer.

[0249] Exemplary hypermethylated and hypomethylated variable target regions useful for discriminating between various cell types, including but not limited to immune cell types, have been identified by analyzing DNA obtained from various cell types via whole genome bisulfite sequencing, as described, for example, in Stunnenberg, HG et al., "The International Human Epigenome Consortium: A Blueprint for Scientific Collaboration and Discovery," Cell 167, 1145 (2016) (doi.org / 10.1186 / s13059-020-02065-5). Whole genome bisulfite sequencing data is available from the Blueprint Consortium, available on the internet at dcc.blueprint-epigenome.eu.

[0250] In some embodiments, the first and second captured target region sets comprise DNA corresponding to a set of sequence variable target regions and DNA corresponding to a set of epigenetic target regions, respectively, as described, for example, in WO2020 / 160414. The first and second captured sets can be combined to provide a combined captured set.

[0251] If DNA (e.g., a sample or aliquot) has been subjected to a procedure, such as bisulfite conversion, treatment with deaminase, or any of the other such procedures mentioned herein that alter the base-pairing specificity of certain bases, enrichment or capture can optionally use oligonucleotides (e.g., primers or probes) specific for the altered or unaltered sequences.

[0252] In some embodiments, where the captured set includes DNA corresponding to the set of sequence variable target regions and the set of epigenetic target regions, including combinations of captured sets as discussed above, the DNA corresponding to the set of sequence variable target regions is at a higher concentration than the DNA corresponding to the set of epigenetic target regions, e.g., 1.1-1.2-fold higher, 1.2-fold higher, 1.4-fold higher, 1.4-fold higher, 1.6-fold higher, 1.8-fold higher, 1.8-fold higher, 2.0-fold higher, 2.2-fold higher, 2.4-fold higher, 2.6-fold higher, 2.8-fold higher, 3.0-fold higher, 3.0-fold higher, 3.5-fold higher, 4.0-fold higher, 4.0-fold higher, 4.5-fold higher, 5.0-fold higher, 5.5-fold higher, 5. 5x to 6.0x higher concentration, 6.0x to 6.5x higher concentration, 6.5x to 7.0x higher, 7.0x to 7.5x higher concentration, 7.5x to 8.0x higher concentration, 8.0x to 8.5x higher concentration, 8.5x to 9.0x higher concentration, 9.0x to 9.5x higher concentration, 9.5x to 10.0x higher concentration, 10x to 11x higher concentration, 11x to 12x higher concentration, 12x to 13x higher concentration, 13x to 14x higher concentration, 14x The concentration may be present at ~15x higher, 15x-16x higher, 16x-17x higher, 17x-18x higher, 18x-19x higher, 19x-20x higher, 20x-30x higher, 30x-40x higher, 40x-50x higher, 50x-60x higher, 60x-70x higher, 70x-80x higher, 80x-90x higher, or 90x-100x higher. The degree of concentration difference accounts for normalization with respect to the footprint size of the target region, as discussed in the definition section. (a) Epigenetic target region set

[0253] In some embodiments, the epigenetic target region set may include one or more types of target regions that are likely to distinguish DNA from different immune cell types and other non-immune cell types and / or to distinguish neoplastic (e.g., tumor or cancer) cells from healthy cells, e.g., non-neoplastic circulating cells. Exemplary types of such regions are discussed in detail herein. The epigenetic target region set may also include one or more control regions, e.g., as described herein.

[0254] In some embodiments, the set of epigenetic target regions has a footprint of at least 100 kb, e.g., at least 200 kb, at least 300 kb, or at least 400 kb. In some embodiments, the set of epigenetic target regions has a footprint in the range of 100-1000 kb, e.g., 100-200 kb, 200-300 kb, 300-400 kb, 400-500 kb, 500-600 kb, 600-700 kb, 700-800 kb, 800-900 kb, and 900-1,000 kb. 1. Hypermethylated variable target regions

[0255] In some embodiments, the epigenetic target region set comprises one or more hypermethylated variable target regions. In some embodiments, the hypermethylated variable target regions are exclusively hypermethylated in one immune cell type, or are hypermethylated to a greater extent in one immune cell type than in any other immune cell type, or in any other immune cell type within the same immune cell cluster. In some such embodiments, the hypermethylated variable target regions indicate the level of a particular immune cell type from which the DNA originates, including rare immune cell types, for example, activated B cells (including memory B cells and plasma cells), activated T cells (including regulatory T cells (Tregs), CD4 effector memory T cells, CD4 central memory T cells, CD8 effector memory T cells, and CD8 central memory T cells), and natural killer (NK) cells. The methylation pattern of the hypermethylated variable target regions useful for deconvoluting immune cell types may further be altered in certain disease states, for example, cancer. Thus, in some embodiments, hypermethylated variable target regions useful for deconvoluting immune cell types are also useful for determining the likelihood that a subject from which a sample was obtained has cancer or precancer. In some such embodiments, hypermethylated variable target regions are useful for determining whether levels of particular immune cell types are abnormal, and whether such abnormal levels are likely to be associated with the presence of cancer or precancer, or whether they are associated with a different disease or condition other than cancer or precancer.

[0256] In some embodiments, certain hypermethylated variable target regions indicate an increased level of observed methylation, e.g., hypermethylated, in DNA produced by neoplastic cells, e.g., tumor or cancer cells. Detection of such hypermethylated variable target regions, e.g., in conjunction with detection of hypermethylated variable target regions indicative of immune cell types, may further increase the specificity and / or sensitivity of the methods described herein. In some embodiments, such an increase in observed methylation in hypermethylated variable target regions indicates an increased likelihood that the sample (e.g., of cfDNA) was obtained from a subject with cancer. For example, hypermethylation of promoters of tumor suppressor genes has been repeatedly observed. See, e.g., Kang et al., Genome Biol. 18:53 (2017) and references cited therein. In another example, as discussed above, hypermethylated variable target regions may include regions that are not necessarily methylated differently in cancerous tissue compared to DNA from healthy tissue of the same type, but are differentially methylated (e.g., have more methylation) compared to cfDNA that is typical in healthy subjects. For example, if the presence of cancer results in increased cell death, such as apoptosis, of cells of a tissue type corresponding to the cancer, such cancer can be at least partially detected using such hypermethylated variable target regions. In some embodiments, the hypermethylated variable target regions useful for determining the likelihood that a subject has cancer are different from the hypermethylated variable target regions useful for determining the level of a particular immune cell type. In some embodiments, at least a portion of the hypermethylated variable target regions useful for determining the likelihood that a subject has cancer are the same as the hypermethylated variable target regions useful for determining the level of a particular immune cell type.

[0257] A comprehensive review of methylation variable target regions in colorectal cancer is provided in Lam et al., Biochim Biophys Acta. 1866:106-20 (2016). These include VIM, SEPT9, ITGA4, OSM4, GATA4 and NDRG4. An exemplary set of hypermethylation variable target regions based on colorectal cancer (CRC) studies is provided in Table 1. Many of these genes are likely to have relevance to cancers other than colorectal cancer, for example, TP53 is widely recognized as a crucial tumor suppressor, and hypermethylation-based inactivation of this gene may be a common oncogenic mechanism. Table 1. Exemplary hypermethylated target regions based on CRC studies [Table 1]

[0258] In some embodiments, the hypermethylated variable target region comprises a plurality of loci listed in Table 1, e.g., at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% of the loci listed in Table 1. For example, for each locus included as a target region, there may be one or more probes having hybridization sites that bind between the transcription start site of the gene and the stop codon (the last stop codon of an alternatively spliced ​​gene) or in the promoter region of the gene. In some embodiments, the one or more probes bind within 300 bp, e.g., within 200 or 100 bp, of the transcription start site of a gene in Table 1.

[0259] Methylation variable target regions in various types of lung cancer are described, for example, in Ooki et al., Clin. Cancer Res. 23:7141-52 (2017);Belinksy, Annu. Rev. Physiol. 77:453-74 (2015);Hulbert et al., Clin. Cancer Res. 23:1998-2005 (2017);Shi et al., BMC Genomics 18:901 (2017);Schneider et al., BMC Cancer. 11:102 (2011);Lissa et al., Transl Lung Cancer Res 5(5):492-504 (2016);Skvortsova et al., Br. J. Cancer. 94(10):1492-1495 (2006);Kim et al., Cancer Res. 61:3419-3424 (2001);Furonaka et al., Pathology International 55:303-309 (2005);Gomes et al., Rev. Port. Pneumol. 20:20-30 (2014);Kim et al., Oncogene. 20:1765-70 (2001);Hopkins-Donaldson et al., Cell Death Differ. 10:356-64 (2003);Kikuchi et al., Clin. Cancer Res. 11:2954-61 (2005);Heller et al., Oncogene 25:959-968 (2006);Licchesi et al., Carcinogenesis. 29:895-904 (2008);Guo et al., Clin. Cancer Res. 10:7917-24 (2004);Palmisano et al., Cancer Res. 63:4620-4625 (2003); and Toyooka et al., Cancer Res. 61:4556-4560, (2001).

[0260] An exemplary set of hypermethylated variable target regions based on lung cancer studies is provided in Table 2. Many of these genes are likely to have relevance to cancers other than lung cancer, e.g., Casp8 is a key enzyme in programmed cell death, and hypermethylation-based inactivation of this gene may be a general oncogenic mechanism not limited to lung cancer. Additionally, some genes appear in both Tables 1 and 2, indicating generality. Table 2. Exemplary hypermethylated target regions based on lung cancer studies [Table 2-1] [Table 2-2]

[0261] Any of the foregoing embodiments relating to target regions identified in Table 2 may be combined with any of the above embodiments relating to target regions identified in Table 1. In some embodiments, the hypermethylated variable target regions include multiple loci listed in Table 1 or Table 2, e.g., at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% of the loci listed in Table 1 or Table 2.

[0262] In some embodiments, the hypermethylated variable target region comprises a region of one or more genes listed in Table 2b, for example, at least 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1000, 1050, 1000, 1100, 1150, or 1200 genes listed in Table 2b. Hypermethylation of these genes may be useful for detecting contributions from immune cells to a DNA sample. In some embodiments, the hypermethylated variable target region comprises regions of multiple genes listed in Table 2b, e.g., at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% of the genes listed in Table 2b. In some embodiments, the hypermethylated variable target region comprises regions of all of the genes listed in Table 2b. Table 2b. Exemplary genes containing exemplary hypermethylated variable target regions [Table 2B-1] [Table 2B-2] [Table 2B-3] [Table 2B-4] [Table 2B-5] [Table 2B-6]

[0263] Additional hypermethylated target regions may be obtained, for example, from the Cancer Genome Atlas. Kang et al., Genome Biology 18:53 (2017) describes the construction of a probabilistic method called CancerLocator that uses hypermethylated target regions from breast, colon, kidney, liver, and lung. In some embodiments, the hypermethylated target regions may be specific to one or more types of cancer. Thus, in some embodiments, the hypermethylated target regions include a subset of 1, 2, 3, 4, or 5 hypermethylated target regions that collectively exhibit hypermethylation in 1, 2, 3, 4, or 5 of breast cancer, colon cancer, kidney cancer, liver cancer, and lung cancer.

[0264] In some embodiments, when different epigenetic target regions are captured from the first and second sub-samples, the epigenetic target region captured from the first sub-sample comprises a hypermethylated variable target region. a. Hypomethylated variable target regions

[0265] In some embodiments, the epigenetic target region set comprises one or more hypomethylated variable target regions. In some embodiments, the hypomethylated variable target regions are exclusively hypomethylated in one immune cell type, or are hypomethylated to a greater extent in one immune cell type than in any other immune cell type or in any other immune cell type within the same immune cell cluster. In some such embodiments, the hypomethylated variable target regions indicate the level of the specific immune cell type from which the DNA originates, including rare immune cell types, for example, activated B cells (including memory B cells and plasma cells), activated T cells (including regulatory T cells (Tregs), CD4 effector memory T cells, CD4 central memory T cells, CD8 effector memory T cells, and CD8 central memory T cells), and natural killer (NK) cells. The methylation pattern of the hypomethylated variable target regions useful for deconvoluting immune cell types may further be altered in certain disease states, for example, cancer. Thus, in some embodiments, hypomethylated variable target regions useful for deconvoluting immune cell types are also useful for determining the likelihood that the subject from which the sample was obtained has cancer or precancer. In some such embodiments, hypomethylated variable target regions are useful for determining whether levels of particular immune cell types are abnormal, and whether such abnormal levels are likely to be associated with the presence of cancer or precancer, or whether they are associated with a different disease or condition other than cancer or precancer.

[0266] Moreover, global hypomethylation is a phenomenon commonly observed in various cancers. See, for example, Hon et al., Genome Res. 22:246-258 (2012) (breast cancer); Ehrlich, Epigenomics 1:239-259 (2009) (review article that mentions the observation of hypomethylation in colon cancer, ovarian cancer, prostate cancer, leukemia, hepatocellular carcinoma, and cervical cancer). For example, regions such as repetitive elements, e.g., LINE1 elements, Alu elements, centromeric tandem repeats, pericentromeric tandem repeats, and satellite DNA, as well as intergenic regions that are normally methylated in healthy cells, may show reduced methylation in tumor cells. Thus, in some embodiments, the epigenetic target region set includes hypomethylated variable target regions, and a decrease in the level of observed methylation indicates an increased likelihood of the presence of cancer. For example, detection of such hypomethylated variable target regions in conjunction with detection of hypomethylated variable target regions indicative of immune cell types may further increase the specificity and / or sensitivity of the methods described herein. In another example, as discussed above, hypomethylated variable target regions may include regions that are not necessarily differently methylated in cancerous tissue compared to DNA from healthy tissue of the same type, but are differentially methylated (e.g., less methylated) compared to cfDNA that is typical in healthy subjects. For example, if the presence of cancer results in increased cell death, such as apoptosis, of cells of a tissue type corresponding to the cancer, such cancer can be at least partially detected using such hypomethylated variable target regions. In some embodiments, hypomethylated variable target regions useful for determining the likelihood that a subject has cancer are different from hypomethylated variable target regions useful for determining the level of a particular immune cell type. In some embodiments, at least a portion of hypomethylated variable target regions useful for determining the likelihood that a subject has cancer are the same as hypomethylated variable target regions useful for determining the level of a particular immune cell type.

[0267] In some embodiments, the hypomethylated variable target region comprises a repetitive element and / or an intergenic region. In some embodiments, the repetitive element comprises one, two, three, four, or five of a LINE1 element, an Alu element, a centromeric tandem repeat, a pericentromeric tandem repeat, and / or satellite DNA.

[0268] Exemplary specific genomic regions that exhibit cancer-associated hypomethylation include nucleotides 8403565-8953708 and 151104701-151106035 of human chromosome 1. In some embodiments, the hypomethylated variable target region overlaps with or includes one or both of these regions.

[0269] Additionally, hypomethylated target regions can be obtained, for example, from Fox-Fisher et al., Elife Nov 29;10 (2021), EpiDISH R package, Moss et al., Nat Commun 9:1 (2018), and Loyfer et al. bioRxiv https: / / doi.org / 10.1101 / 2022.01.24.477547 (2022). In some embodiments, the hypomethylated target regions can be specific to one or more types of immune cells.

[0270] In some embodiments, when different epigenetic target regions are captured from the first and second sub-samples, the epigenetic target region captured from the second sub-sample comprises a hypomethylated variable target region. In some embodiments, the epigenetic target region captured from the second sub-sample comprises a hypomethylated variable target region and the epigenetic target region captured from the first sub-sample comprises a hypermethylated variable target region. b.CTCF binding region

[0271] CTCF is a DNA-binding protein that contributes to chromatin organization and often colocalizes with cohesin. Disruption of CTCF binding sites has been reported in a variety of different cancers. See, for example, Katainen et al., Nature Genetics, doi:10.1038 / ng.3335, published online June 8, 2015; Guo et al., Nat. Commun. 9:1520 (2018). CTCF binding results in a recognizable pattern of cfDNA that can be detected by sequencing, for example, through fragment length analysis. Details regarding sequencing-based fragment length analysis are provided in Snyder et al., Cell 164:57-68 (2016); WO2018 / 009723; and US20170211143A1, each of which is incorporated herein by reference.

[0272] Thus, disruption of CTCF binding leads to altered fragmentation patterns of cfDNA, and thus CTCF binding sites are a type of fragmentation variable target region.

[0273] There are many known CTCF binding sites.See, for example, CTCFBSDB (CTCF Binding Site Database) available on the Internet at insulatordb.uthsc.edu / ; Cuddapah et al., Genome Res. 19:24-32 (2009); Martin et al., Nat. Struct. Mol. Biol. 18:708-14 (2011); Rhee et al., Cell. 147:1408-19 (2011), each of which is incorporated by reference.Exemplary CTCF binding sites are located at nucleotides 56014955-56016161 on chromosome 8 and 95359169-95360473 on chromosome 13.

[0274] Thus, in some embodiments, the set of epigenetic target regions comprises CTCF binding regions, in some embodiments, the CTCF binding regions include at least 10, 20, 50, 100, 200, or 500 CTCF binding regions, or 10-20, 20-50, 50-100, 100-200, 200-500, or 500-1000 CTCF binding regions, such as those described above or in the CTCFBSDB cited above, or in one or more of the articles by Cuddapah et al., Martin et al., or Rhee et al.

[0275] In some embodiments, at least a portion of the CTCF sites can be methylated or unmethylated, and the methylation status correlates with whether the cell is a cancer cell. In some embodiments, the set of epigenetic target regions includes at least 100 bp, at least 200 bp, at least 300 bp, at least 400 bp, at least 500 bp, at least 750 bp, at least 1000 bp upstream and downstream of the CTCF binding site. C transcription start site

[0276] Transcription start sites may also show perturbations in neoplastic cells. For example, the nucleosome organization at various transcription start sites in healthy cells of hematopoietic lineage that contribute substantially to cfDNA in healthy individuals may differ from the nucleosome organization at those transcription start sites in neoplastic cells. This results in different cfDNA patterns that can be detected by sequencing, as generally discussed in Snyder et al., Cell 164:57-68 (2016); WO2018 / 009723: and US20170211143A1. In another example, transcription start sites may not necessarily be epigenetically different in cancerous tissue compared to DNA from healthy tissue of the same type, but may be epigenetically different (e.g., in terms of nucleosome organization) compared to cfDNA that is typical in healthy subjects. For example, if the presence of cancer results in increased cell death, such as apoptosis, of cells of the tissue type corresponding to the cancer, such cancer can be detected at least in part using such differences in transcription start sites.

[0277] Thus, perturbations in transcription start sites also result in variations in the fragmentation patterns of cfDNA, and thus transcription start sites are also a type of fragmentation variable target region.

[0278] Human transcription start sites are available from the Database of Human Transcription Start Sites (DBTSS), available on the Internet at dbtss.hgc.jp, and are described in Yamashita et al., Nucleic Acids Res. 34(Database issue): D86-D89 (2006), which is incorporated herein by reference.

[0279] Thus, in some embodiments, the set of epigenetic target regions includes a transcription start site. In some embodiments, the transcription start site includes at least 10, 20, 50, 100, 200, or 500 transcription start sites, or 10-20, 20-50, 50-100, 100-200, 200-500, or 500-1000 transcription start sites, such as those listed in the DBTSS. In some embodiments, at least a portion of the transcription start sites can be methylated or unmethylated, and the methylation status correlates with whether the cell is a cancer cell. In some embodiments, the set of epigenetic target regions includes at least 100 bp, at least 200 bp, at least 300 bp, at least 400 bp, at least 500 bp, at least 750 bp, at least 1000 bp upstream and downstream of the transcription start site. d. Local amplification

[0280] Although local amplifications are somatic mutations, they can be detected by sequencing based on the frequency of read data in a manner similar to the approach of detecting certain epigenetic changes such as methylation changes.Therefore, the region that may show local amplification in cancer can be included in epigenetic target region set, and can include one or more of AR, BRAF, CCND1, CCND2, CCNE1, CDK4, CDK6, EGFR, ERBB2, FGFR1, FGFR2, KIT, KRAS, MET, MYC, PDGFRA, PIK3CA and RAF1.For example, in some embodiments, epigenetic target region set includes at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 or 18 of the above targets. e. Methylation control region

[0281] It may be useful to include control regions to facilitate data validation. In some embodiments, the set of epigenetic target regions includes a control region that is expected to be methylated or unmethylated in essentially all samples, regardless of whether the DNA is from cancer cells or normal cells. In some embodiments, the set of epigenetic target regions includes a control hypomethylated region that is expected to be hypomethylated in essentially all samples. In some embodiments, the set of epigenetic target regions includes a control hypermethylated region that is expected to be hypermethylated in essentially all samples. 2. Set of sequence-variable target regions

[0282] In some embodiments, the set of sequence variable target regions includes a plurality of regions known to undergo somatic mutations (e.g., single nucleotide mutations and / or indels) in cancer. The single nucleotide mutations and / or indels can be compared to a reference sequence, e.g., a published human genome sequence, e.g., the GRCh38 human genome assembly.

[0283] In some embodiments, the sequence variable target region set targets a plurality of different genes or genomic regions ("panels") that are selected such that a predetermined percentage of subjects with cancer exhibits genetic variants or tumor markers in one or more different genes or genomic regions in the panel. The panels can be selected to limit the region of sequencing to a fixed number of base pairs. The panels can be selected to sequence a desired amount of DNA, for example, by adjusting the affinity and / or amount of probes as described elsewhere herein. The panels can also be selected to achieve a desired sequence read data depth. The panels can be selected to achieve a desired sequence read data depth or sequence read data coverage in terms of the amount of sequenced base pairs. The panels can be selected to achieve a theoretical sensitivity, theoretical specificity, and / or theoretical accuracy for detecting one or more genetic variants in a sample.

[0284] The probe for detecting the panel of regions can include the probe for detecting the genomic region of interest (hotspot region).When designing the probe, information about chromatin structure can be taken into account, and / or the probe can be designed to maximize the possibility that a specific site (e.g., KRAS codons 12 and 13) can be captured, and can be designed to optimize capture based on the analysis of cfDNA coverage and fragment size variation that is influenced by nucleosome binding pattern and GC sequence composition.Region as used herein can also include non-hotspot regions that are optimized based on nucleosome position and GC model.

[0285] Examples of lists of genomic locations of interest can be found in Tables 3 and 4. In some embodiments, the sequence variable target region set used in the methods of the present disclosure includes at least a portion of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, at least 40, at least 45, at least 50, at least 55, at least 60, at least 65, or 70 of the genes in Table 3. In some embodiments, the sequence variable target region set used in the methods of the present disclosure includes at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, at least 40, at least 45, at least 50, at least 55, at least 60, at least 65, or 70 of the SNVs in Table 3. In some embodiments, the sequence variable target region set used in the methods of the present disclosure includes at least 1, at least 2, at least 3, at least 4, at least 5, or 6 of the fusions in Table 3. In some embodiments, the sequence variable target region set used in the disclosed method comprises at least a portion of at least one, at least two, or three indels of Table 3. In some embodiments, the sequence variable target region set used in the disclosed method comprises at least a portion of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, at least 40, at least 45, at least 50, at least 55, at least 60, at least 65, at least 70, or 73 genes of Table 4. In some embodiments, the sequence variable target region set used in the disclosed method comprises at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, at least 40, at least 45, at least 50, at least 55, at least 60, at least 65, at least 70, or 73 SNVs of Table 4. In some embodiments, the sequence variable target region set used in the disclosed method comprises at least 1, at least 2, at least 3, at least 4, at least 5, or 6 fusions of Table 4.In some embodiments, the sequence variable target region set used in the method of the present disclosure includes at least a portion of 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 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, or at least 18 of the indels in Table 4. Each of these genomic locations of interest can be identified as a scaffold region or a hotspot region for a given panel. An example list of hotspot genomic locations of interest can be found in Table 5. In some embodiments, the sequence variable target region set used in the method of the present disclosure includes at least a portion of 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 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, at least 19, or at least 20 of the genes in Table 5. Each hotspot genomic region is listed with several characteristics, including the associated gene, the chromosome on which it resides, the genomic start and end positions representing the gene's locus, the length of the gene's locus in base pairs, the exons covered by the gene, and the key features that a given genomic region of interest may seek to capture (e.g., type of mutation). Table 3 [Table 3-1] [Table 3-2] Table 4 [Table 4] Table 5 [Table 5-1] [Table 5-2] [Table 5-3]

[0286] Additionally or alternatively, suitable target region set can be obtained from literature.For example, Gale et al., PLoS One 13: e0194630 (2018), incorporated herein by reference, describes a panel of 35 cancer-related gene targets that can be used as part or all of sequence variable target region set.These 35 targets are AKT1, ALK, BRAF, CCND1, CDK2A, CTNNB1, EGFR, ERBB2, ESR1, FGFR1, FGFR2, FGFR3, FOXL2, GATA3, GNA11, GNAQ, GNAS, HRAS, IDH1, IDH2, KIT, KRAS, MED12, MET, MYC, NFE2L2, NRAS, PDGFRA, PIK3CA, PPP2R1A, PTEN, RET, STK11, TP53 and U2AF1.

[0287] In some embodiments, the set of sequence variable target regions includes target regions from at least 10, 20, 30, or 35 cancer-associated genes, such as those listed above. B. Target

[0288] In some embodiments, the DNA (e.g., cfDNA) is obtained from a subject having cancer or precancer, an infectious disease, transplant rejection, or other disease that directly or indirectly affects the immune system. In some embodiments, the DNA (e.g., cfDNA) is obtained from a subject suspected of having cancer or precancer, an infectious disease, transplant rejection, or other disease that directly or indirectly affects the immune system. In some embodiments, the DNA (e.g., cfDNA) is obtained from a subject having a tumor. In some embodiments, the DNA (e.g., cfDNA) is obtained from a subject suspected of having a tumor. In some embodiments, the DNA (e.g., cfDNA) is obtained from a subject having a neoplasm. In some embodiments, the DNA (e.g., cfDNA) is obtained from a subject suspected of having a neoplasm. In some embodiments, the DNA (e.g., cfDNA) is obtained from a subject in remission from a tumor, cancer, or neoplasm (e.g., following chemotherapy, surgical resection, radiation, or a combination thereof). In any of the foregoing embodiments, the cancer, tumor, or neoplasm or suspected cancer, tumor, or neoplasm may be of the lung, colon, rectum, kidney, breast, prostate, or liver. In some embodiments, the cancer, tumor, or neoplasm or suspected cancer, tumor, or neoplasm is of the lung. In some embodiments, the cancer, tumor, or neoplasm or suspected cancer, tumor, or neoplasm is of the colon or rectum. In some embodiments, the cancer, tumor, or neoplasm or suspected cancer, tumor, or neoplasm is of the breast. In some embodiments, the cancer, tumor, or neoplasm or suspected cancer, tumor, or neoplasm is of the prostate. In any of the foregoing embodiments, the subject may be a human subject. C. Pooling DNA from Samples or Subsamples or Portions thereof

[0289] In some embodiments, the method herein comprises preparing one or more pools comprising tagged DNA from a plurality of distributed subsamples. In some embodiments, the pool comprises at least a portion of DNA with low methylation distribution and at least a portion of DNA with high methylation distribution. For example, target regions comprising epigenetic target regions and / or sequence variable target regions can be captured from the pool. The step of capturing a set of target regions from at least one aliquot or portion of a sample or subsample described elsewhere herein includes a capture step performed on a pool comprising DNA from a first and second subsample. The step of amplifying DNA in the pool can be performed prior to the step of capturing target regions from the pool. The capture step can have any of the features described elsewhere herein with respect to the capture step.

[0290] In some embodiments, the method includes preparing a first pool comprising at least a portion of the DNA with a low methylation distribution. In some embodiments, the method includes preparing a second pool comprising at least a portion of the DNA with a high methylation distribution. In some embodiments, the method includes capturing at least a first set of target regions from the first pool, the first set comprising sequence variable target regions. Amplifying the DNA in the first pool may be performed prior to the capturing step. In some embodiments, capturing the first set of target regions from the first pool comprises contacting the DNA of the first pool with a first set of target specific probes, the first set of target specific probes comprising target binding probes specific for sequence variable target regions. In some embodiments, the method includes capturing a second plurality of sets of target regions from the second pool, the second plurality comprising sequence variable target regions and epigenetic target regions. Amplifying the DNA in the second pool may be performed prior to the capturing step. In some embodiments, capturing a second plurality of sets of target regions from the second pool comprises contacting the DNA of the first pool with a second set of target-specific probes, the second set of target-specific probes comprising target-binding probes specific for sequence-variable target regions and target-binding probes specific for epigenetic target regions.

[0291] In some embodiments, the sequence variable target region is captured from the second portion of the divided aliquot sample.The second portion can contain some, most, substantially all, or all of the DNA of the aliquot sample that was not included in the pool.The regions captured from the pool and from the aliquot sample can be combined and analyzed in parallel.

[0292] Epigenetic target regions may exhibit differences in methylation levels and / or fragmentation patterns depending on whether they originate from a particular cell or tissue type, or from a tumor, or from a healthy cell, as discussed elsewhere herein. Sequence-variable target regions may exhibit sequence differences depending on whether they originate from a tumor or from a healthy cell.

[0293] Analysis of epigenetic target regions from low methylation distribution may be less informative in some applications than analysis of sequence variable target regions from high methylation and low methylation distributions and epigenetic target regions from high methylation distributions.Therefore, in methods where sequence variable target regions and epigenetic target regions are captured, the latter may be captured to a lesser extent than when one or more of the sequence variable target regions are captured from high methylation and low methylation distributions, and / or when epigenetic target regions are captured from high methylation distributions.For example, sequence variable target regions can be captured from a portion of low methylation distributions that are not pooled with high methylation distributions, and pools can be prepared with a portion (e.g., most, substantially all, or all) of DNA from high methylation distributions and no or a portion (e.g., a minority) of DNA from low methylation distributions.Such an approach can reduce or eliminate sequencing of epigenetic target regions from low methylation distributions, thereby reducing the amount of sequencing data that is sufficient for further analysis.

[0294] In some embodiments, including a minority portion of DNA with a low methylation distribution in the pool facilitates, for example, relative quantification of one or more epigenetic features (e.g., methylation or other epigenetic features discussed in detail elsewhere herein).

[0295] In some embodiments, the pool comprises a minority of DNA with hypomethylated distribution, e.g., less than about 50% of the DNA with hypomethylated distribution, e.g., less than or equal to about 45%, less than or equal to 40%, less than or equal to 35%, less than or equal to 30%, less than or equal to 25%, less than or equal to 20%, less than or equal to 15%, less than or equal to 10%, or less than or equal to 5% of the DNA with hypomethylated distribution. In some embodiments, the pool comprises about 5%-25% of the DNA with hypomethylated distribution. In some embodiments, the pool comprises about 10%-20% of the DNA with hypomethylated distribution. In some embodiments, the pool comprises about 10% of the DNA with hypomethylated distribution. In some embodiments, the pool comprises about 15% of the DNA with hypomethylated distribution. In some embodiments, the pool comprises about 20% of the DNA with hypomethylated distribution.

[0296] In some embodiments, the pool comprises a portion of the hypermethylated distribution, which may be at least 50% of the DNA of the hypermethylated distribution. For example, the pool may comprise at least about 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, or 95% of the DNA of the hypermethylated distribution. In some embodiments, the pool comprises 50-55%, 55-60%, 60-65%, 65-70%, 70-75%, 75-80%, 80-85%, 85-90%, 90-95%, or 95-100% of the DNA of the hypermethylated distribution. In some embodiments, the second pool comprises all or substantially all of the DNA of the hypermethylated distribution.

[0297] In some embodiments, the first pool contains substantially all or all of the DNA with a low methylation distribution (e.g., the second pool does not contain DNA with a low methylation distribution). In some embodiments, the second pool does not contain DNA with a low methylation distribution (e.g., the first pool contains substantially all or all of the DNA with a low methylation distribution).

[0298] In some embodiments, the second pool comprises a portion of the high methylation distribution, which may be any of the values ​​and ranges described above for the low methylation distribution. In some embodiments, the second pool comprises all or substantially all of the DNA of the high methylation distribution.

[0299] In an exemplary embodiment, after partitioning, the partitions are individually subjected to end repair and ligation to adapters that contain molecular barcodes, and then are individually amplified.After amplification, the amplified molecules are enriched (still keeping the partitions separate).After enrichment, the enriched DNA is pooled according to any of the embodiments described herein, and then amplified again.After amplification, the molecules are sequenced.

[0300] In various embodiments, the method further comprises sequencing the captured DNA, for example to different degrees of sequencing depth for the set of epigenetic and sequence variable target regions, consistent with the above discussion. D. Sequencing

[0301] Generally, the sample nucleic acid comprising the nucleic acid flanked by adaptors can be subjected to sequencing with or without prior amplification.Sequencing methods include, for example, Sanger sequencing, high throughput sequencing, pyrosequencing, sequencing by synthesis, single molecule sequencing, nanopore sequencing, semiconductor sequencing, sequencing by ligation, sequencing by hybridization, digital gene expression (Helicos), next generation sequencing (NGS), single molecule sequencing by synthesis (SMSS) (Helicos), massively parallel sequencing, clonal single molecule array (Solexa), shotgun sequencing, Ion Torrent, Oxford Nanopore, Roche Genia, Maxam-Gilbert sequencing, primer walking, and sequencing using PacBio, SOLiD, Ion Torrent or Nanopore platform.

[0302] In some embodiments, sequencing includes detecting and / or identifying unmodified and modified nucleobases. For example, PacBio sequencing (e.g., single molecule real-time (SMRT) sequencing) provides the ability to directly detect, for example, 5-methylcytosine and 5-hydroxymethylcytosine as well as unmodified cytosine. See, for example, Schatz., Nature Methods. 14(4): 347-348 (2017); and US9,150,918. Also, the Oxford nanopore sequencing system (e.g., MinION sequencer) that can directly detect DNA methylation (e.g., 5-methylcytosine and 5-hydroxymethylcytosine) can be used herein. Sequencing reactions can be performed in a variety of sample processing units that may include multiple lanes, multiple channels, multiple wells, or other means of processing multiple sample sets substantially simultaneously. The sample processing unit may also include multiple sample chambers to allow for the processing of multiple runs simultaneously. Similarly, Ion Torrent sequencing can also be used to directly detect methylation. Thus, in some embodiments, the methylation state can be determined during sequencing, for example, without or independent of a partitioning step or conversion procedure, for example, bisulfite treatment.

[0303] Sequencing reactions can be performed on one or more forms of nucleic acid, such as those known to contain markers for cancer or other diseases. Sequencing reactions can also be performed on any nucleic acid fragments present in the sample. In some embodiments, the sequence coverage of the genome can be less than 5%, less than 10%, less than 15%, less than 20%, less than 25%, less than 30%, less than 40%, less than 50%, less than 60%, less than 70%, less than 80%, less than 90%, less than 95%, less than 99%, less than 99.9%, or less than 100%. In some embodiments, sequence reactions can provide at least 5%, 10%, 15%, 20%, 25%, 30%, 40%, 50%, 60%, 70%, or 80% sequence coverage of the genome. Sequence coverage can be performed for at least 5, 10, 20, 70, 100, 200 or 500 different genes, or for at most 5000, 2500, 1000, 500 or 100 different genes.

[0304] Simultaneous sequencing reaction can be carried out using multiplex sequencing.In some examples, cell-free nucleic acid can be sequenced by at least 1000 times, 2000 times, 3000 times, 4000 times, 5000 times, 6000 times, 7000 times, 8000 times, 9000 times, 10000 times, 50000 times, 100,000 times sequencing reaction.In other examples, cell-free nucleic acid can be sequenced by less than 1000 times, less than 2000 times, less than 3000 times, less than 4000 times, less than 5000 times, less than 6000 times, less than 7000 times, less than 8000 times, less than 9000 times, less than 10000 times, less than 50000 times, less than 100,000 times sequencing reaction.Sequencing reaction can be carried out sequentially or simultaneously. Subsequent data analysis may be performed on all or part of the sequencing reactions. In some examples, data analysis may be performed on at least 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 50000, 100,000 sequencing reactions. In other examples, data analysis may be performed on less than 1000, less than 2000, less than 3000, less than 4000, less than 5000, less than 6000, less than 7000, less than 8000, less than 9000, less than 10000, less than 50000, less than 100,000 sequencing reactions. An exemplary read data depth is 1000 to 50000 read data per locus (base). 1. Differential Depth of Sequencing

[0305] In some embodiments, the nucleic acid corresponding to the sequence variant target region set is sequenced to a greater sequencing depth than the nucleic acid corresponding to the epigenetic target region set.For example, the sequencing depth for the nucleic acid corresponding to the sequence variant target region set is at least 1.25 times, 1.5 times, 1.75 times, 2 times, 2.25 times, 2.5 times, 2.75 times, 3 times, 3.5 times, 4 times, 4.5 times, 5 times, 6 times, 7 times, 8 times, 9 times, 10 times, 11 times, 12 times, 13 times, 14 times, or 15 times greater than the sequencing depth for the nucleic acid corresponding to the epigenetic target region set, or is 1.25 times to 1.5 times greater than the sequencing depth for the nucleic acid corresponding to the epigenetic target region set. The sequencing depth may be 1.5x, 1.5x-1.75x, 1.75x-2x, 2x-2.25x, 2.25x-2.5x, 2.5x-2.75x, 2.75x-3x, 3x-3.5x, 3.5x-4x, 4x-4.5x, 4.5x-5x, 5x-5.5x, 5.5x-6x, 6x-7x, 7x-8x, 8x-9x, 9x-10x, 10x-11x, 11x-12x, 13x-14x, 14x-15x, or 15x-100x greater. In some embodiments, the sequencing depth is at least 2x greater. In some embodiments, the sequencing depth is at least 5x greater. In some embodiments, the sequencing depth is at least 10x greater. In some embodiments, the sequencing depth is between 4-fold and 10-fold greater. In some embodiments, the sequencing depth is between 4-fold and 100-fold greater.

[0306] In some embodiments, DNA corresponding to a set of sequence variable target regions and / or DNA corresponding to a set of epigenetic target regions are sequenced simultaneously, e.g., in the same sequencing cell (e.g., a flow cell of an Illumina sequencer) and / or in the same composition, which can be a combined or pooled composition obtained from recombining the captured sets individually, or a composition obtained by capturing cfDNA corresponding to a set of sequence variable target regions and / or captured cfDNA corresponding to a set of epigenetic target regions in the same container. E. Analysis

[0307] In some embodiments, the methods described herein comprise determining the level of the specific immune cell type from which the DNA originates. The immune cell type may include naive and activated lymphocytes, myeloid cells at different times of differentiation, and / or other types described elsewhere herein. In some methods, determining the level of the immune cell type facilitates determining the likelihood that the subject from which the DNA is obtained has a disease or disorder related to the immune system, such as an infectious disease, transplant rejection, or cancer or precancer.

[0308] In some embodiments, the methods described herein include identifying the presence of DNA produced by tumor (or neoplastic, or cancer cells) or by precancerous cells. In some embodiments, the methods described herein include identifying the presence of DNA produced by immune cells that are not tumor, cancer, or precancerous cells. In some such embodiments, determining immune cell distribution facilitates detection or diagnosis of cancer or precancerous, or determining cancer prognosis or cancer treatment options. For example, determining the ratio of different immune cell types may facilitate such detection or determination. In some embodiments, the numerator of the ratio is the number or relative number of neutrophils, monocytes, or both, and the denominator of the ratio is the number or relative number of T cells, B cells, NK cells, or total lymphocytes. In some embodiments, the numerator of the ratio is the number or relative number of neutrophils, and the denominator of the ratio is the number or relative number of T cells, B cells, NK cells, or total lymphocytes. In some embodiments, the numerator of the ratio is the number or relative number of monocytes and the denominator of the ratio is the number or relative number of T cells, B cells, NK cells, or total lymphocytes. In some embodiments, the numerator of the ratio is the number or relative number of neutrophils and monocytes and the denominator of the ratio is the number or relative number of T cells, B cells, NK cells, or total lymphocytes. In some embodiments, the ratio is the ratio of neutrophils to lymphocytes. In some embodiments, the ratio is the ratio of monocytes to T cells. In some embodiments, an increase in such a ratio is associated with cancer. In other embodiments, a decrease in such a ratio is associated with cancer.

[0309] The method may be used to diagnose the presence of a condition, particularly cancer or precancer, in a subject, characterize the condition (e.g., stage the cancer or determine the heterogeneity of the cancer), monitor the response to treatment of the condition, and prognose the risk of developing the condition or the subsequent course of the condition. The present disclosure may also be useful for determining the effectiveness of a particular treatment option. A successful treatment option may increase the amount of copy number alterations or rare mutations detected in the subject's blood, since more cancers may die and shed DNA if the treatment is successful. In other examples, this may not occur. In another example, perhaps a particular treatment option may correlate with the genetic profile of the cancer over time. This correlation may be useful for selecting a treatment.

[0310] Additionally, if the cancer is observed to be in remission following treatment, the method can be used to monitor for residual disease or recurrence of the disease.

[0311] The type and number of cancers that can be detected can include blood cancer, brain cancer, lung cancer, skin cancer, nose cancer, throat cancer, liver cancer, bone cancer, lymphoma, pancreatic cancer, skin cancer, intestinal cancer, rectal cancer, thyroid cancer, bladder cancer, kidney cancer, oral cancer, stomach cancer, solid tumors, heterogeneous tumors, homogeneous tumors, etc. The type and / or stage of cancer can be detected from genetic variations including mutations, rare mutations, indels, copy number variations, transversions, translocations, recombinations, inversions, deletions, aneuploidy, partial aneuploidy, polyploidy, chromosomal instability, alterations in chromosomal structure, gene fusions, chromosomal fusions, gene truncations, gene amplifications, gene duplications, chromosomal lesions, DNA lesions, abnormal changes in nucleic acid chemical modifications, abnormal changes in epigenetic patterns, and abnormal changes in nucleic acid 5-methylcytosine.

[0312] Genetic data can also be used to characterize specific forms of cancer. Cancers are often heterogeneous in both composition and stage classification. Genetic profile data can allow characterization of a particular subtype of cancer, which may be important in the diagnosis or treatment of that particular subtype. This information can also provide clues to the subject or practitioner regarding the prognosis of a particular type of cancer, allowing either the subject or practitioner to adapt treatment options as the disease progresses. Some cancers can progress to become more aggressive and genetically unstable. Other cancers can remain benign, inactive, or dormant. The systems and methods of the present disclosure can be useful for determining disease progression.

[0313] Furthermore, the method of the present disclosure can be used to characterize the heterogeneity of abnormal conditions in a subject. Such a method can include, for example, creating a genetic profile of extracellular polynucleotides from a subject, where the genetic profile includes a plurality of data obtained from the analysis of copy number variation and rare mutations. In some embodiments, the abnormal condition is cancer or precancer. In some embodiments, the abnormal condition can be a condition that results in a heterogeneous genomic population. In the example of cancer, it is known that some tumors contain tumor cells at different stages of cancer. In other examples, the heterogeneity can constitute multiple foci of disease. Again, in the example of cancer, there may be multiple tumor foci, perhaps one or more foci are the result of metastasis that has spread from the primary site.

[0314] The methods can be used to generate or profile fingerprints or sets of data that are summaries of genetic information from different cells in a heterogeneous disease, which sets of data can include analysis of copy number variations, epigenetic variations, or other mutations, either alone or in combination.

[0315] This method can be used to diagnose, prognose, monitor or observe cancer or other diseases.In some embodiments, the method herein does not involve diagnosing, prognosing or monitoring fetus, and therefore is not intended for non-invasive prenatal testing.In other embodiments, these methodologies can be used on pregnant subjects to diagnose, prognose, monitor or observe cancer or other diseases in unborn subjects whose DNA and other polynucleotides may co-circulate with maternal molecules.

[0316] An exemplary method for identification of immune cell types via NGS includes the following steps: 1. Preparing an extracted DNA sample (e.g., plasma DNA extracted from a human sample) by ligating adapters containing molecular tags to the DNA. 2. Partitioning the adaptor-ligated DNA into a plurality of differentially methylated subsamples by contacting the DNA with an agent that recognizes modified cytosines, e.g., methylcytosines, in the DNA. 4. Capturing hypermethylated and hypomethylated variable target regions from the distributed aliquots by contacting the aliquots with target-specific probes. 5. Enriching and / or eluting DNA containing the target region. 6. Amplifying the DNA and assaying it in multiplex on an NGS instrument. 7. Analyzing the NGS data, where molecular tags are used to identify unique molecules.

[0317] An exemplary workflow is shown in Figure 1A, in which cfDNA obtained from a sample is divided based on the level of methylation of cfDNA molecules. Molecular barcodes are then added to the cfDNA molecules of each division, and then epigenetic and optionally sequence variable target regions are then captured from the divided partial samples to provide a targeted library. The epigenetic target regions include hypermethylated and / or hypomethylated variable target regions that are differentially methylated in certain types of immune cells. The targeted library can be amplified before sequencing, and then sequencing provides sequence information that is used to determine the level of immune cell type and / or the possibility of the presence of a disease or disorder.

[0318] In some embodiments of the methods described herein, the molecular tag consists of nucleotides that are not altered by a procedure that affects a first nucleobase in DNA differently than a second nucleobase in DNA, e.g., any of those described herein (e.g., mC with A, T, and G if the procedure is a bisulfite conversion or any other conversion that does not affect mC; hmC with A, T, and G if the procedure is a conversion that does not affect hmC, etc.). In some embodiments of the methods described herein, the molecular tag does not include nucleotides that are altered by a procedure that affects a first nucleobase in DNA differently than a second nucleobase in DNA, e.g., any of those described herein (e.g., if the procedure is a bisulfite conversion or any other conversion that affects C, the tag does not include unmodified C; if the procedure is a conversion that affects mC, the tag does not include mC; if the procedure is a conversion that affects hmC, the tag does not include hmC, etc.). II. ADDITIONAL FEATURES OF CERTAIN DISCLOSED METHODS A. Sample

[0319] The sample can be any biological sample isolated from a subject. The sample can be a body sample. The sample can include body tissue, such as known or suspected solid tumor, whole blood, platelets, serum, plasma, feces, red blood cells, white blood cells or leucocytes, endothelial cells, tissue biopsy, cerebrospinal fluid, synovial fluid, lymphatic fluid, ascites, interstitial or extracellular fluid, fluid in the space between cells including gingival crevicular fluid, bone marrow, pleural fluid, cerebrospinal fluid, saliva, mucus, sputum, semen, sweat, urine. The sample is preferably a body fluid, in particular blood and its fractions, as well as urine. The sample may be in the form originally isolated from the subject, or may have been subjected to further processing, removing or adding components, such as cells, or enriching for one component compared to another. Thus, the preferred body fluid for analysis is plasma or serum, which contains cell-free nucleic acid.

[0320] In some embodiments, the nucleic acid population is obtained from serum, plasma or blood samples from subjects suspected of having neoplasm, tumor, precancer or cancer, or previously diagnosed with neoplasm, tumor, precancer or cancer.The population comprises nucleic acids with different levels of sequence mutation, epigenetic mutation, and / or post-replicative or post-transcriptional modification.Post-replicative modification includes, in particular, modification of cytosine at the 5th position of nucleic acid base, such as 5-methylcytosine, 5-hydroxymethylcytosine, 5-formylcytosine and 5-carboxylcytosine.

[0321] The sample may be isolated or obtained from the subject and transported to the site of sample analysis. The sample may be stored and shipped at a desired temperature, for example, room temperature, 4°C, -20°C, and / or -80°C. The sample may be isolated or obtained from the subject at the site of sample analysis. The subject may be a human, a mammal, an animal, a companion animal, a service animal, or a pet. The subject may have cancer, precancer, an infectious disease, a transplant rejection, or other disease or disorder associated with alterations in the immune system. The subject may not have cancer or detectable symptoms of cancer. The subject may have been treated with one or more cancer therapies, such as any one or more of chemotherapy, antibodies, vaccines, or biologics. The subject may be in remission. The subject may or may not be diagnosed as susceptible to cancer or any cancer-related genetic mutation / disorder.

[0322] In some embodiments, the sample comprises plasma. The volume of the plasma obtained may depend on the desired read depth of the region to be sequenced. Exemplary volumes are 0.4-40 ml, 5-20 ml, 10-20 ml. For example, the volume may be 0.5 mL, 1 mL, 5 mL, 10 mL, 20 mL, 30 mL, or 40 mL. The volume of the sampled plasma may be 5-20 mL.

[0323] A sample can contain various amounts of nucleic acid containing genome equivalents. For example, a sample of about 30 ng of DNA contains about 10,000 (10 4 ) haploid human genome equivalents, and for cfDNA, approximately 200 billion (2×10 11 Similarly, a sample of about 100 ng of DNA may contain about 30,000 haploid human genome equivalents, and in the case of cfDNA, about 600 billion individual molecules.

[0324] The sample may include nucleic acids from different sources, e.g., from cells and acellular of the same subject, from cells and acellular of different subjects. The sample may include nucleic acids with mutations. For example, the sample may include DNA with germline mutations and / or somatic mutations. Germline mutations refer to mutations present in the germline DNA of the subject. Somatic mutations refer to mutations originating from the somatic cells of the subject, e.g., pre-cancerous or cancerous cells. The sample may include DNA with cancer-associated mutations (e.g., cancer-associated somatic mutations). The sample may include epigenetic variants (i.e., chemical or protein modifications), where the epigenetic variants are associated with the presence of genetic variants, e.g., cancer-associated mutations. In some embodiments, the sample includes epigenetic variants associated with the presence of genetic variants, and the sample does not include genetic variants.

[0325] Exemplary amounts of cell-free nucleic acid in a sample prior to amplification range from about 1 fg to about 1 μg, e.g., 1 pg to 200 ng, 1 ng to 100 ng, 10 ng to 1000 ng. For example, the amount can be up to about 600 ng, up to about 500 ng, up to about 400 ng, up to about 300 ng, up to about 200 ng, up to about 100 ng, up to about 50 ng, or up to about 20 ng of cell-free nucleic acid molecules. The amount can be at least 1 fg, at least 10 fg, at least 100 fg, at least 1 pg, at least 10 pg, at least 100 pg, at least 1 ng, at least 10 ng, at least 100 ng, at least 150 ng, or at least 200 ng of cell-free nucleic acid molecules. The amount can be up to 1 femtogram (fg), 10 fg, 100 fg, 1 picogram (pg), 10 pg, 100 pg, 1 ng, 10 ng, 100 ng, 150 ng, or 200 ng of cell-free nucleic acid molecules. The method can include obtaining between 1 femtogram (fg) and 200 ng.

[0326] Cell-free nucleic acids are nucleic acids that are not contained within or otherwise bound to cells, or in other words, nucleic acids that remain in a sample after removal of intact cells. Cell-free nucleic acids include DNA, RNA, and hybrids thereof, including genomic DNA, mitochondrial DNA, siRNA, miRNA, circular RNA (cRNA), tRNA, rRNA, small nucleolar RNA (snoRNA), Piwi-interacting RNA (piRNA), long non-coding RNA (long ncRNA), or fragments of any of these. Cell-free nucleic acids can be double-stranded, single-stranded, or hybrids thereof. Cell-free nucleic acids can be released into bodily fluids through secretion or cell death processes, such as necrosis and apoptosis of cells. Some cell-free nucleic acids are released into bodily fluids from cancer cells, such as circulating tumor DNA (ctDNA). Others are released from healthy cells. In some embodiments, the cfDNA is cell-free fetal DNA (cffDNA). In some embodiments, the cell-free nucleic acids are produced by tumor cells. In some embodiments, the cell-free nucleic acid is produced by a mixture of tumor cells and non-tumor cells.

[0327] Cell-free nucleic acids have an exemplary size distribution of about 100 to 500 nucleotides, with molecules of 110 to about 230 nucleotides accounting for about 90% of the molecules, the mode being about 168 nucleotides, and a second minor peak in the range between 240 nucleotides and 440 nucleotides.

[0328] Cell-free nucleic acids can be isolated from bodily fluids through a fractionation step, where the cell-free nucleic acids found in solution are separated from intact cells and other insoluble components of the bodily fluid. Partitioning can include techniques such as centrifugation or filtration. Alternatively, cells in the bodily fluid can be lysed, and the cell-free and cellular nucleic acids can be processed together. Generally, after addition of buffer and washing steps, the nucleic acids can be precipitated with alcohol. Further clean-up steps, such as silica-based columns, can be used to remove contaminants or salts. Non-specific bulk carrier nucleic acids, such as C1 DNA, DNA or proteins for bisulfite sequencing, hybridization, and / or ligation, can be added throughout the reaction to optimize certain aspects of the procedure, such as yield.

[0329] After such processing, the sample may contain various forms of nucleic acid, including double-stranded DNA, single-stranded DNA, and single-stranded RNA. In some embodiments, single-stranded DNA and RNA may be converted to double-stranded form so that they can be included in subsequent processing and analysis steps.

[0330] The DNA molecule can be ligated to an adaptor at either or both ends. Typically, the double-stranded molecule is blunt-ended by treatment with a polymerase having a 5'-3' polymerase and a 3'-5' exonuclease (or proofreading function) in the presence of all four standard nucleotides. Klenow large fragment and T4 polymerase are examples of suitable polymerases. The blunt-ended DNA molecule can be ligated with an at least partially double-stranded adaptor (e.g., a Y-shaped or bell-shaped adaptor). Alternatively, complementary nucleotides can be added to the blunt ends of the sample nucleic acid and the adaptor to facilitate ligation. Both blunt-end ligation and sticky-end ligation are contemplated herein. In blunt-end ligation, both the nucleic acid molecule and the adaptor tag have blunt ends. In sticky-end ligation, typically, the nucleic acid molecule has an "A" overhang and the adaptor has a "T" overhang. B. Amplification

[0331] The sample nucleic acid flanked by adaptors can be amplified by PCR and other amplification methods. Amplification is typically primed by a primer that anneals or binds to a primer binding site in the adaptor flanking the DNA molecule to be amplified. The amplification method can involve cycles of denaturation, annealing and extension resulting from thermocycling, or can be isothermal as in transcription-mediated amplification. Other amplification methods include ligase chain reaction, strand displacement amplification, nucleic acid sequence-based amplification, and self-sustained sequence-based replication. In some embodiments, the method performs dsDNA ligation with T-tail and C-tail adaptors, which results in at least 50, 60, 70, or 80% amplification of double-stranded nucleic acid before ligation to the adaptor. Preferably, the method increases the amount or number of amplified molecules by at least 10, 15, or 20% compared to a control method performed with T-tail adaptors alone. C. Tag

[0332] Tags, including barcodes, can be incorporated or otherwise attached to adapters. Tags can be incorporated by ligation, overlap extension PCR, among other methods. 1. Molecular tagging strategy

[0333] Molecular tagging refers to tagging practices that allow sequence read data to distinguish between DNA molecules from which they originate. Tagging strategies can be divided into unique tagging and non-unique tagging strategies. In unique tagging, all or substantially all molecules in a sample have different tags, so that read data can be assigned to the original molecule based on tag information alone. Tags used in such methods are sometimes called "unique tags". In non-unique tagging, different molecules in the same sample can have the same tag, so that sequence read data is assigned to the original molecule using other information in addition to tag information. Such information can include start and end coordinates, coordinates to which the molecule is mapped, start or end coordinates only, etc. Tags used in such methods are sometimes called "non-unique tags". Thus, it is not necessary to uniquely tag every molecule in a sample. It is sufficient to uniquely tag molecules that fall within an identifiable class in a sample. In this way, molecules in different identifiable families can have the same tag without losing information about the identity of the tagged molecule.

[0334] In certain embodiments of non-unique tagging, the number of different tags used may be sufficient if there is a very high probability (e.g., at least 99%, at least 99.9%, at least 99.99%, or at least 99.999%) that all DNA molecules in a particular group have different tags. Note that when barcodes are used as tags, and when barcodes are attached, for example, randomly, to both ends of a molecule, a combination of barcodes may together constitute a tag. This number is a function of the number of molecules that fall into a distinct call. For example, a class may be all molecules that map to the same start-end position on a reference genome. A class may be all molecules that map to a particular locus, such as a particular base or over a particular region (e.g., up to 100 bases or a gene or exon of a gene). In certain embodiments, the number of different tags used to uniquely identify a number z of molecules in a class can be between any of 2*z, 3*z, 4*z, 5*z, 6*z, 7*z, 8*z, ​​9*z, 10*z, 11*z, 12*z, 13*z, 14*z, 15*z, 16*z, 17*z, 18*z, 19*z, 20*z, or 100*z (e.g., a lower limit) and any of 100,000*z, 10,000*z, 1000*z, or 100*z (e.g., an upper limit).

[0335] For example, in a sample of about 5 ng to 30 ng of cell-free DNA, approximately 3000 molecules are expected to map to a particular nucleotide coordinate, with between about 3 to 10 molecules with any given start coordinate sharing the same end coordinate. Thus, about 50 to about 50,000 different tags (e.g., between about 6 to 220 barcode combinations) may be sufficient to uniquely tag all such molecules. To uniquely tag all 3000 molecules mapped across nucleotide coordinates, about 1 million to about 20 million different tags would be required.

[0336] Generally, assignment of unique or non-unique tag barcodes in reactions follows the methods and systems described in U.S. Patent Application Nos. 20010053519, 20030152490, 20110160078, and U.S. Patent Nos. 6,582,908 and 7,537,898 and 9,598,731. Tags can be randomly or non-randomly linked to sample nucleic acids.

[0337] Unique tags can be loaded such that about more than 1, more than 2, more than 3, more than 4, more than 5, more than 6, more than 7, more than 8, more than 9, more than 10, more than 20, more than 50, more than 100, more than 500, more than 1000, more than 5000, more than 10000, more than 50,000, more than 100,000, more than 500,000, more than 1,000,000, more than 10,000,000, more than 50,000,000, or more than 1,000,000,000 unique tags are loaded per genomic sample. In some examples, unique tags may be loaded such that less than about 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 50, 100, 500, 1000, 5000, 10000, 50,000, 100,000, 500,000, 1,000,000, 10,000,000, 50,000,000, or 1,000,000,000 unique tags are loaded per genomic sample.In some examples, the average number of unique tags loaded per sample genome is about less than 1 or more, less than 2 or more, less than 3 or more, less than 4 or more, less than 5 or more, less than 6 or more, less than 7 or more, less than 8 or more, less than 9 or more, less than 10 or more, less than 20 or more, less than 50 or more, less than 100 or more per genome sample. , less than 500 or more, less than 1000 or more, less than 5000 or more, less than 10000 or more, less than 50,000 or more, less than 100,000 or more, less than 500,000 or more, less than 1,000,000 or more, less than 10,000,000 or more, less than 50,000,000 or more, or less than 1,000,000,000 unique tags.

[0338] A preferred format uses 20-50 different tags (e.g., barcodes) ligated to both ends of a target nucleic acid. For example, 35 different tags (e.g., barcodes) ligated to both ends of a target molecule creates 35x35 permutations, which is equal to 1225 for 35 tags. Such a number of tags is sufficient so that different molecules with the same start and end points will receive different combinations of tags with a high probability (e.g., at least 94%, 99.5%, 99.99%, 99.999%). Other barcode combinations include any number between 10 and 500, such as about 15x15, about 35x35, about 75x75, about 100x100, about 250x250, about 500x500.

[0339] In some examples, the unique tag may be a predefined or random or semi-random sequence oligonucleotide. In other examples, multiple barcodes may be used such that the barcodes are not necessarily unique to each other among the multiple. In this example, the barcode may be ligated to an individual molecule such that the combination of the barcode and the sequence to which it may be ligated creates a unique sequence that may be tracked individually. As described herein, detection of a non-unique barcode in combination with sequence data at the beginning (start) and end (stop) portions of the sequence read data may allow for the assignment of a unique identity to a particular molecule. The length or number of base pairs of an individual sequence read data may also be used to assign a unique identity to such a molecule. As described herein, a fragment from a single strand of nucleic acid that has been assigned a unique identity may thereby allow subsequent identification of the fragment from the parent strand. D. Capturing part

[0340] As discussed above, the nucleic acid in the sample may be subjected to a capture step, in which molecules having target regions are captured for subsequent analysis. Target capture may involve the use of a capture moiety, such as a probe (e.g., an oligonucleotide) labeled with biotin, and a second moiety or binding partner, such as streptavidin, that binds to the capture moiety. In some embodiments, the capture moiety and binding partner may have higher and lower capture yields for different sets of target regions, such as the capture yields of a set of sequence-variable target regions and a set of epigenetic target regions, respectively, as discussed elsewhere herein. Methods involving capture moieties are further described, for example, in U.S. Patent No. 9,850,523, issued December 26, 2017, which is incorporated herein by reference.

[0341] Capture moieties include, but are not limited to, biotin, avidin, streptavidin, nucleic acids containing specific nucleotide sequences, haptens recognized by antibodies, and magnetically adsorbable particles. Extraction moieties can be members of binding pairs, such as biotin / streptavidin or hapten / antibody. In some embodiments, the capture moiety attached to the analyte is captured by its binding partner attached to an isolable moiety, such as a magnetically adsorbable particle or a larger particle that can be sedimented through centrifugation. The capture moiety can be any type of molecule that allows affinity separation of nucleic acids with the capture moiety from nucleic acids that lack the capture moiety. Exemplary capture moieties are biotin, which allows affinity separation by binding to streptavidin linked or linkable to a solid phase, or oligonucleotides, which allow affinity separation through binding to complementary oligonucleotides linked or linkable to a solid phase. E. Collection of target-specific probes

[0342] In some embodiments, the collection of target-specific probes is used in the method comprising a set of epigenetic target regions and / or a set of sequence variable target regions as described herein. In some embodiments, the collection of target-specific probes comprises a target binding probe specific to a set of sequence variable target regions and a target binding probe specific to a set of epigenetic target regions. In some embodiments, the capture yield of the target binding probe specific to a set of sequence variable target regions is higher (e.g., at least 2-fold higher) than the capture yield of the target binding probe specific to a set of epigenetic target regions. In some embodiments, the collection of target-specific probes is configured to have a capture yield specific to a set of sequence variable target regions that is higher (e.g., at least 2-fold higher) than its capture yield specific to a set of epigenetic target regions.

[0343] In some embodiments, the capture yield of target binding probes specific for the set of sequence variable target regions is at least 1.25x, 1.5x, 1.75x, 2x, 2.25x, 2.5x, 2.75x, 3x, 3.5x, 4x, 4.5x, 5x, 6x, 7x, 8x, 9x, 10x, 11x, 12x, 13x, 14x, or 15x higher than the capture yield of target binding probes specific for the set of epigenetic target regions. In some embodiments, the capture yield of target binding probes specific for the set of sequence variable target regions is 1.25x to 1.5x, 1.5x to 1.75x, 1.75x to 2x, 2x to 2.25x, 2.25x to 2.5x, 2.5x to 2.75x, 2.75x to 3x, 3x to 3.5x, 3.5x to 4x, 4x to 4.5x, 4.5x to 5x, 5x to 5.5x, 5.5x to 6x, 6x to 7x, 7x to 8x, 8x to 9x, 9x to 10x, 10x to 11x, 11x to 12x, 13x to 14x, or 14x to 15x higher than the capture yield of target binding probes specific for the set of epigenetic target regions.

[0344] In some embodiments, the collection of target-specific probes is configured to have a capture yield specific for a set of sequence variable target regions that is at least 1.25x, 1.5x, 1.75x, 2x, 2.25x, 2.5x, 2.75x, 3x, 3.5x, 4x, 4.5x, 5x, 6x, 7x, 8x, 9x, 10x, 11x, 12x, 13x, 14x, or 15x higher than its capture yield for a set of epigenetic target regions. In some embodiments, the collection of target-specific probes is configured to have a capture yield specific for a set of sequence variable target regions that is 1.25x-1.5x, 1.5x-1.75x, 1.75x-2x, 2x-2.25x, 2.25x-2.5x, 2.5x-2.75x, 2.75x-3x, 3x-3.5x, 3.5x-4x, 4x-4.5x, 4.5x-5x, 5x-5.5x, 5.5x-6x, 6x-7x, 7x-8x, 8x-9x, 9x-10x, 10x-11x, 11x-12x, 13x-14x, or 14x-15x higher than its capture yield specific for the set of epigenetic target regions.

[0345] A collection of probes can be configured to provide higher capture yields for a set of sequence-variable target regions in a variety of ways, including concentration, varying length, and / or chemistry (e.g., to affect affinity), as well as combinations thereof. Affinity can be modulated by adjusting the length of the probe and / or including nucleotide modifications, as discussed below.

[0346] In some embodiments, the target-specific probes specific for the set of sequence variable target regions are present at a higher concentration than the target-specific probes specific for the set of epigenetic target regions. In some embodiments, the concentration of the target-binding probes specific for the set of sequence variable target regions is at least 1.25-fold, 1.5-fold, 1.75-fold, 2-fold, 2.25-fold, 2.5-fold, 2.75-fold, 3-fold, 3.5-fold, 4-fold, 4.5-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 11-fold, 12-fold, 13-fold, 14-fold, or 15-fold higher than the concentration of the target-binding probes specific for the set of epigenetic target regions. In some embodiments, the concentration of target binding probes specific for the set of sequence variable target regions is 1.25x to 1.5x, 1.5x to 1.75x, 1.75x to 2x, 2x to 2.25x, 2.25x to 2.5x, 2.5x to 2.75x, 2.75x to 3x, 3x to 3.5x, 3.5x to 4x, 4x to 4.5x, 4.5x to 5x, 5x to 5.5x, 5.5x to 6x, 6x to 7x, 7x to 8x, 8x to 9x, 9x to 10x, 10x to 11x, 11x to 12x, 13x to 14x, or 14x to 15x higher than the concentration of target binding probes specific for the set of epigenetic target regions. In such embodiments, concentration may refer to the average mass per volume concentration of the individual probes in each set.

[0347] In some embodiments, target-specific probes specific to sequence-variable target regions set have higher affinity to their targets than target-specific probes specific to epigenetic target regions set. Affinity can be modulated in any manner known to those skilled in the art, including by using different probe chemistries. Certain nucleotide modifications, such as cytosine 5-methylation (in the context of certain sequences), modifications that provide heteroatoms at the 2' position of the sugar, and LNA nucleotides, can increase the stability of double-stranded nucleic acids, and oligonucleotides with such modifications have shown to have relatively high affinity for their complementary sequences. See, for example, Severin et al., Nucleic Acids Res. 39: 8740-8751 (2011); Freier et al., Nucleic Acids Res. 25: 4429-4443 (1997); U.S. Patent No. 9,738,894. Similarly, longer sequence lengths generally provide increased affinity. Other nucleotide modifications, such as substituting the nucleobase hypoxanthine for guanine, reduce affinity by reducing the amount of hydrogen bonding between the oligonucleotide and its complementary sequence. In some embodiments, a target-specific probe specific to a set of sequence-variable target regions has a modification that increases its affinity for its target. In some embodiments, alternatively or additionally, a target-specific probe specific to a set of epigenetic target regions has a modification that decreases its affinity for its target. In some embodiments, a target-specific probe specific to a set of sequence-variable target regions has a longer average length and / or a higher average melting temperature than a target-specific probe specific to a set of epigenetic target regions. These embodiments may be combined with each other and / or with the concentration differences discussed above to achieve a desired fold difference in capture yield, such as any of the fold differences or ranges described above.

[0348] In some embodiments, the target-specific probe comprises a capture moiety. The capture moiety may be any of the capture molecules described herein, such as biotin. In some embodiments, the target-specific probe is covalently or non-covalently linked to a solid support, such as through the interaction of the binding pair of the capture moiety. In some embodiments, the solid support is a bead, such as a magnetic bead.

[0349] In some embodiments, the target specific probes specific for the set of sequence variable target regions and / or the target specific probes specific for the set of epigenetic target regions comprise capture moieties as discussed above, e.g., capture moieties and probes that comprise sequences selected for tiling across a panel of regions, such as genes.

[0350] In some embodiments, the target-specific probes are provided in a single composition. The single composition can be a solution (liquid or frozen). Alternatively, it can be a lyophilizate.

[0351] Alternatively, the target-specific probes can be provided as multiple compositions, including, for example, a first composition comprising probes specific to a set of epigenetic target regions, and a second composition comprising probes specific to a set of sequence-variable target regions. These probes can be mixed in appropriate proportions to provide a combined probe composition with any of the aforementioned fold differences in concentration and / or capture yield. Alternatively, they can be used in separate capture procedures (e.g., with an aliquot of a sample, or sequentially with the same sample) to provide first and second compositions comprising captured epigenetic and sequence-variable target regions, respectively. 1. Probes specific to epigenetic target regions

[0352] The probes of the epigenetic target region set may include probes specific for one or more types of target regions that are likely to distinguish DNA originating from different types of immune cells, including rare immune cell types, and / or distinguish DNA from precancerous or neoplastic (e.g., tumor or cancer) cells from healthy cells, e.g., non-neoplastic circulating cells.Exemplary types of such regions are discussed in detail herein.The probes of the epigenetic target region set may also include probes of one or more control regions, for example, as described herein.

[0353] In some embodiments, the probes of the epigenetic target region probe set have a footprint of at least 100 kb, for example, at least 200 kb, at least 300 kb, or at least 400 kb. In some embodiments, the probes of the epigenetic target region probe set have a footprint in the range of 100 to 1000 kb, for example, 100 to 200 kb, 200 to 300 kb, 300 to 400 kb, 400 to 500 kb, 500 to 600 kb, 600 to 700 kb, 700 to 800 kb, 800 to 900 kb, and 900 to 1,000 kb. In some embodiments, the probes of the epigenetic target region probe set have a footprint of at least 5 kb, for example, at least 10, 20, or 50 kb. A. Hypermethylated variable target region

[0354] In some embodiments, the probe of the epigenetic target region set comprises a probe specific for one or more hypermethylated variable target regions. The hypermethylated variable target region can be any of those described above. For example, in some embodiments, the probe specific for the hypermethylated variable target region comprises a probe specific for a plurality of loci that are differentially methylated in different immune cell types. In some embodiments, each immune cell type-specific hypermethylated variable target region comprises at least one CpG site that is methylated at a frequency of greater than or equal to 0.3, greater than or equal to 0.4, greater than or equal to 0.5, or greater than or equal to 0.6 in one immune cell type, and less than or equal to 0.1, less than or equal to 0.2, or less than or equal to 0.3 in all other immune cell types. In some embodiments, each immune cell type-specific hypermethylated variable target region comprises at least two CpG sites within 100 base pairs of each other that are each methylated at a frequency greater than or equal to 0.3, greater than or equal to 0.4, greater than or equal to 0.5, or greater than or equal to 0.6 in one immune cell type and less than or equal to 0.1, less than or equal to 0.2, or less than or equal to 0.3 in all other immune cell types. In some such embodiments, each immune cell type-specific hypermethylated variable target region comprises a total of at least 2, 3, 4, 5, 6, 7, 8, 9, or 10 CpG sites within 150 or 200 base pairs, and less than three of the at least 2, 3, 4, 5, 6, 7, 8, 9, or 10 CpG sites are methylated at a frequency greater than 0.1, greater than 0.2, or greater than 0.3 in any normal tissue type. In some embodiments, each immune cell type-specific set of epigenetic target regions comprises at least 3, at least 5, at least 10, at least 20, or at least 30 hypermethylated variable target regions that are uniquely hypermethylated in each one of the immune cell types identified in the method.

[0355] In some embodiments, probes specific for hypermethylated variable target regions include probes specific for a plurality of loci listed in Table 1, e.g., at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% of the loci listed in Table 1. In some embodiments, probes specific for hypermethylated variable target regions include probes specific for a plurality of loci listed in Table 2, e.g., at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% of the loci listed in Table 2. In some embodiments, probes specific for hypermethylated variable target regions include probes specific for multiple loci listed in Table 1 or Table 2, e.g., at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% of the loci listed in Table 1 or Table 2.

[0356] In some embodiments, for each locus included as a target region, there may be one or more probes with hybridization sites that bind between the transcription start site of the gene and the stop codon (or the last stop codon in the case of an alternatively spliced ​​gene). In some embodiments, one or more probes bind within 300 bp, for example within 200 or 100 bp, of the recited position. In some embodiments, the probes have hybridization sites that overlap with the recited positions above. In some embodiments, the probes specific for the hypermethylated target regions include probes specific for a subset of 1, 2, 3, 4, or 5 hypermethylated target regions that collectively show hypermethylation in 1, 2, 3, 4, or 5 of breast cancer, colon cancer, kidney cancer, liver cancer, and lung cancer. b. Hypomethylated variable target regions

[0357] In some embodiments, the probe of epigenetic target region set comprises a probe specific for one or more hypomethylated variable target regions. The hypomethylated variable target region can be any of those described above. For example, in some embodiments, the probe specific for the hypomethylated variable target region comprises a probe specific for a plurality of loci that are differentially methylated in different immune cell types. In some embodiments, each immune cell type-specific hypomethylated variable target region comprises at least one CpG site that is methylated at a frequency of less than or equal to 0.1, less than or equal to 0.2, or less than or equal to 0.3 in one immune cell type, and at a frequency of greater than or equal to 0.3, greater than or equal to 0.4, greater than or equal to 0.5, or greater than or equal to 0.6 in all other immune cell types. In some embodiments, each immune cell type-specific hypomethylated variable target region comprises at least two CpG sites within 100 base pairs of each other that are each methylated at a frequency of less than or equal to 0.1, less than or equal to 0.2, or less than or equal to 0.3 in one immune cell type and at a frequency of greater than or equal to 0.3, greater than or equal to 0.4, greater than or equal to 0.5, or greater than or equal to 0.6 in all other immune cell types. In some such embodiments, each immune cell type-specific hypomethylated variable target region comprises a total of at least 2, 3, 4, 5, 6, 7, 8, 9, or 10 CpG sites within 150 or 200 base pairs, and less than three of the at least 2, 3, 4, 5, 6, 7, 8, 9, or 10 CpG sites are methylated at a frequency of less than 0.1, less than 0.2, or less than 0.3 in any normal tissue type. In some embodiments, each immune cell type-specific set of epigenetic target regions comprises at least 3, at least 5, at least 10, at least 20, or at least 30 hypomethylated variable target regions that are uniquely hypomethylated in each one of the immune cell types identified in the method.

[0358] In some embodiments, probes specific for one or more hypomethylated variable target regions may include probes for regions such as repetitive elements, e.g., LINE1 elements, Alu elements, centromeric tandem repeats, pericentromeric tandem repeats, and satellite DNA, and intergenic regions that are normally methylated in healthy cells may show reduced methylation in tumor cells.

[0359] In some embodiments, the probes specific for the hypomethylated variable target region comprise probes specific for repetitive elements and / or intergenic regions, hi some embodiments, the probes specific for repetitive elements comprise probes specific for one, two, three, four, or five of the following: a LINE1 element, an Alu element, a centromeric tandem repeat, a pericentromeric tandem repeat, and / or satellite DNA.

[0360] Exemplary probes specific for genomic regions exhibiting cancer-associated hypomethylation include probes specific for nucleotides 8403565-8953708 and / or 151104701-151106035 of human chromosome 1. In some embodiments, probes specific for hypomethylated variable target regions include probes specific for regions overlapping with or including nucleotides 8403565-8953708 and / or 151104701-151106035 of human chromosome 1. c.CTCF binding region

[0361] In some embodiments, the probes of the set of epigenetic target regions include probes specific for CTCF binding regions. In some embodiments, the probes specific for CTCF binding regions include at least 10, 20, 50, 100, 200, or 500 CTCF binding regions, or 10-20, 20-50, 50-100, 100-200, 200-500, or 500-1000 CTCF binding regions, such as those described above, or in one or more of the CTCFBSDB, or in the Cuddapah et al., Martin et al., or Rhee et al. papers cited above. In some embodiments, the probes of the set of epigenetic target regions include at least 100 bp, at least 200 bp, at least 300 bp, at least 400 bp, at least 500 bp, at least 750 bp, or at least 1000 bp upstream and downstream of the CTCF binding site. D transcription start site

[0362] In some embodiments, the probes for the set of epigenetic target regions include a transcription start site, In some embodiments, the probes specific for the transcription start site include probes specific for at least 10, 20, 50, 100, 200, or 500 transcription start sites, or 10-20, 20-50, 50-100, 100-200, 200-500, or 500-1000 transcription start sites, such as those listed in the DBTSS. In some embodiments, the probes of the epigenetic target region set include probes for sequences at least 100 bp, at least 200 bp, at least 300 bp, at least 400 bp, at least 500 bp, at least 750 bp, or at least 1000 bp upstream and downstream of the transcription start site. e. Local Amplification

[0363] As mentioned above, local amplifications are somatic mutations, but they can be detected by sequencing based on the frequency of read data in a similar manner to the approach for detecting certain epigenetic changes, such as methylation changes.Therefore, the region that may show local amplification in cancer can be included in the epigenetic target region set as discussed above.In some embodiments, the probe specific to the epigenetic target region set comprises a probe specific to local amplification.In some embodiments, the probe specific to local amplification comprises a probe specific to one or more of AR, BRAF, CCND1, CCND2, CCNE1, CDK4, CDK6, EGFR, ERBB2, FGFR1, FGFR2, KIT, KRAS, MET, MYC, PDGFRA, PIK3CA, and RAF1. For example, in some embodiments, probes specific for local amplification include probes specific for one or more of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, or 18 of the aforementioned targets. f. Control area

[0364] It may be useful to include control regions to facilitate data validation. In some embodiments, the probes specific for the set of epigenetic target regions include probes specific for control methylation regions that are expected to be methylated in essentially all samples. In some embodiments, the probes specific for the set of epigenetic target regions include probes specific for control hypomethylation regions that are expected to be hypomethylated in essentially all samples. ii. Probes specific for sequence-variable target regions

[0365] The sequence variable target region set probes may include probes specific for multiple regions known to undergo somatic mutation in cancer. The probes may be specific for any sequence variable target region set described herein. Exemplary sequence variable target region sets are discussed in detail herein, for example, in the section above regarding captured sets.

[0366] In some embodiments, the sequence variable target region probe set has a footprint of at least 0.5 kb, e.g., at least 1 kb, at least 2 kb, at least 5 kb, at least 10 kb, at least 20 kb, at least 30 kb, or at least 40 kb. In some embodiments, the epigenetic target region probe set has a footprint in the range of 0.5-100 kb, e.g., 0.5-2 kb, 2-10 kb, 10-20 kb, 20-30 kb, 30-40 kb, 40-50 kb, 50-60 kb, 60-70 kb, 70-80 kb, 80-90 kb, and 90-100 kb.

[0367] In some embodiments, the probes specific for the set of sequence variable target regions include probes specific for at least a portion of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, at least 40, at least 45, at least 50, at least 55, at least 60, at least 65, or 70 of the genes of Table 3. In some embodiments, the probes specific for the set of sequence variable target regions include probes specific for at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, at least 40, at least 45, at least 50, at least 55, at least 60, at least 65, or 70 of the SNVs of Table 3. In some embodiments, the probes specific for the set of sequence variable target regions include probes specific for at least 1, at least 2, at least 3, at least 4, at least 5, or 6 of the fusions of Table 3. In some embodiments, the probes specific for the set of sequence variable target regions include probes specific for at least a portion of at least 1, at least 2, or 3 of the indels of Table 3. In some embodiments, the probes specific for the set of sequence variable target regions include probes specific for at least a portion of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, at least 40, at least 45, at least 50, at least 55, at least 60, at least 65, at least 70, or 73 of the genes in Table 4. In some embodiments, the probes specific for the set of sequence variable target regions include probes specific for at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, at least 40, at least 45, at least 50, at least 55, at least 60, at least 65, at least 70, or 73 of the SNVs in Table 4. In some embodiments, the probes specific for the set of sequence variable target regions include probes specific for at least 1, at least 2, at least 3, at least 4, at least 5, or 6 of the fusions in Table 4.In some embodiments, the probes specific for the set of sequence variable target regions include probes specific for at least a portion of 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 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, or 18 of the indels of Table 4. In some embodiments, the probes specific for the set of sequence variable target regions include probes specific for at least a portion of 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 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, at least 19, or at least 20 of the genes of Table 5.

[0368] In some embodiments, the probes specific for the set of sequence variable target regions include probes specific for target regions from at least 10, 20, 30, or 35 cancer-associated genes, such as AKT1, ALK, BRAF, CCND1, CDK2A, CTNNB1, EGFR, ERBB2, ESR1, FGFR1, FGFR2, FGFR3, FOXL2, GATA3, GNA11, GNAQ, GNAS, HRAS, IDH1, IDH2, KIT, KRAS, MED12, MET, MYC, NFE2L2, NRAS, PDGFRA, PIK3CA, PPP2R1A, PTEN, RET, STK11, TP53, and U2AF1. F. Computer Systems

[0369] The methods of the present disclosure can be implemented using or with the aid of a computer system. Figure 2 shows a computer system 201 programmed or otherwise configured to implement the methods of the present disclosure. The computer system 201 can regulate various aspects of sample preparation, sequencing, and / or analysis. In some examples, the computer system 201 is configured to perform sample preparation and sample analysis, including nucleic acid sequencing, for example, according to any of the methods disclosed herein.

[0370] The computer system 201 includes a central processing unit (CPU, also referred to herein as "processor" and "computer processor") 205, which may be a single-core or multi-core processor, or multiple processors for parallel processing. The computer system 201 also includes memory or memory locations 210 (e.g., random access memory, read-only memory, flash memory), an electronic storage unit 215 (e.g., hard disk), a communication interface 220 (e.g., network adapter) for communicating with one or more other systems, and peripheral devices 225, such as cache, other memory, data storage, and / or an electronic display adapter. The memory 210, the storage unit 215, the interface 220, and the peripheral devices 225 communicate with the CPU 205 through a communication network or bus (solid lines), such as a motherboard. The storage unit 215 may be a data storage unit (or data repository) for storing data. The computer system 201 may be operatively coupled to a computer network 230 with the aid of the communication interface 220. The computer network 230 may be the Internet, an Internet and / or an extranet, or an intranet and / or extranet in communication with the Internet. The computer network 230 may be a telecommunications and / or data network in some examples. The computer network 230 may include one or more computer servers, which may enable distributed computing, such as cloud computing. The computer network 230 may implement a peer-to-peer network in some examples, which may enable devices coupled to the computer system 201 to behave as clients or servers with the help of the computer system 0.

[0371] CPU 205 may execute sequences of machine-readable instructions, which may be embodied in a program or software. The instructions may be stored in a memory location, such as memory 210. Examples of operations performed by CPU 205 may include fetch, decode, execute, and write-back.

[0372] The storage unit 215 can store files such as drivers, libraries, and saved programs. The storage unit 215 can store user created programs and recorded sessions, as well as output associated with the programs. The storage unit 215 can store user data, such as user preferences and user programs. The computer system 201 may include one or more additional data storage units external to the computer system 201, in some examples, located, for example, on a remote server that communicates with the computer system 201 through an intranet or the Internet. Data may be transferred from one location to another, for example, using a communications network or physical data transfer (e.g., using a hard drive, thumb drive, or other data storage mechanism).

[0373] Computer system 201 can communicate with one or more remote computer systems through network 230. For an embodiment, computer system 201 can communicate with a remote computer system of a user (e.g., an operator). Examples of remote computer systems include a personal computer (e.g., a portable PC), a slate or tablet PC (e.g., Apple® iPad®, Samsung® Galaxy Tab), a phone, a smartphone (e.g., Apple® iPhone®, Android® enabled device, Blackberry®), or a personal digital assistant. A user can access computer system 201 through network 230.

[0374] The methods described herein may be implemented by machine (e.g., a computer processor) executable code stored in an electronic storage location of the computer system 201, such as memory 210 or electronic storage unit 215. The machine executable or machine readable code may be provided in the form of software. During use, the code may be executed by the processor 205. In some examples, the code may be read from the storage unit 215 and stored in memory 210 for easy access by the processor 205. In some situations, the electronic storage unit 215 may be omitted and the machine executable instructions are stored in memory 210.

[0375] In one aspect, the disclosure provides a non-transitory computer readable medium comprising computer executable instructions that, when executed by at least one electronic processor, perform at least a portion of a method comprising: collecting cfDNA from a sample or a subject; capturing a plurality of sets of target regions from the cfDNA, wherein the plurality of sets of target regions comprises a set of sequence variable target regions, and / or a set of epigenetic target regions; sequencing the captured cfDNA molecules, wherein the captured cfDNA molecules of the set of sequence variable target regions are sequenced to a greater sequencing depth than the captured cfDNA molecules of the set of epigenetic target regions; obtaining a plurality of sequence read data generated by a nucleic acid sequencer from the sequencing of the captured cfDNA molecules; mapping the plurality of sequence read data to one or more reference sequences to generate mapped sequence read data; and processing the mapped sequence read data corresponding to the set of sequence variable target regions and the mapped sequence read data corresponding to the set of epigenetic target regions to determine a level of a plurality of immune cell types and / or a likelihood that the subject has cancer.

[0376] The code may be pre-compiled and configured for use with a machine having a processor adapted to execute the code, or it may be compiled during run-time. The code may be provided in a programming language that may be selected to enable the code to be executed as pre-compiled or as compiled.

[0377] Aspects of the systems and methods provided herein, such as the computer system 201, can be embodied in programming. Various aspects of the technology can be considered to be a "product" or "article of manufacture" in the form of machine (or processor) executable code and / or associated data typically executed or embodied in one type of machine-readable medium. The machine executable code can be stored in an electronic storage unit, such memory (e.g., read-only memory, random access memory, flash memory) or hard disk. A "storage" type medium can include any or all of the tangible memory of a computer, processor, etc., or its associated modules, such as various semiconductor memories, tape drives, disk drives, etc., that can provide non-transitory storage at any time for software programming.

[0378] All or a portion of the software may at times be communicated through the Internet or various other telecommunications networks. Such communication may, for example, allow the software from one computer or processor to be loaded into another computer or processor, for example, from a management server or host computer to a computer platform of an application server. Thus, other types of media that may bear software elements include media used across physical interfaces between local devices, such as light waves, radio waves, and electromagnetic waves, such as wired and optical landline telephone networks, and various air links. Physical elements that convey such waves, such as wired or wireless links, optical links, and the like, may also be considered to be media bearing software. As used herein, unless limited to non-transitory tangible "storage" media, terms such as computer or machine "readable medium" refer to any medium that participates in providing instructions to a processor for execution.

[0379] Thus, the machine-readable medium, e.g., computer executable code, may take many forms, including but not limited to tangible storage media, carrier wave media, or physical transmission media. Non-volatile storage media include, e.g., optical or magnetic disks, any of the storage devices in, e.g., any computer, e.g., that may be used to implement a database, as shown in the drawings. Volatile storage media include dynamic memory, e.g., the main memory of such a computer platform. Tangible transmission media include coaxial cables; copper wire and fiber optics, including the wires that comprise a bus within a computer system. Carrier wave transmission media may take the form of electric or electromagnetic signals, or acoustic or light waves, such as those generated during radio frequency (RF) and infrared (IR) data communications. Thus, common forms of computer readable media include, for example, a floppy disk, a flexible disk, a hard disk, a magnetic tape, any other magnetic medium, a CD-ROM, a DVD or DVD-ROM, any other optical medium, punch cards, paper tape, any other physical storage medium with a pattern of holes, RAM, ROM, PROM and EPROM, FLASH-EPROM, any other memory chip or cartridge, a carrier wave carrying data or instructions, a cable or link which transports such a carrier wave, or any other medium from which a computer may read programming code and / or data. Many of these forms of computer readable media may be involved in carrying one or more sequences of one or more instructions to a processor for execution.

[0380] The computer system 201 can include or communicate with, for example, an electronic display that includes a user interface (UI) for providing one or more results of a sample analysis. Examples of UIs include, but are not limited to, graphical user interfaces (GUIs) and web-based user interfaces.

[0381] Additional details regarding computer systems and networks, databases, and computer program products can also be found in, for example, Peterson, Computer Networks: A Systems Approach, Morgan Kaufmann, 5th Ed. (2011), Kurose, Computer Networking: A Top-Down Approach, Pearson, 7 th Ed. (2016), Elmasri, Fundamentals of Database Systems, Addison Wesley, 6th Ed. (2010), Coronel, Database Systems: Design, Implementation, & Management, Cengage Learning, 11 th Ed. (2014), It is also provided in Tucker, Programming Languages, McGraw-Hill Science / Engineering / Math, 2nd Ed. (2006), and Rhoton, Cloud Computing Architected: Solution Design Handbook, Recursive Press(2011). G. Application 1. Quantification of immune cell types, cancer, and other diseases

[0382] The method may be used to quantify levels of different immune cell types, including rare immune cell types, e.g., activated lymphocytes, and myeloid cells at a particular stage of differentiation. Such quantification may be based on the number of molecules corresponding to a given cell type in the sample. For example, Examples 2 and 3 illustrate quantification based on hypermethylated and hypomethylated variable target regions, respectively. The sequence information obtained by the method may include sequence read data of the nucleic acid generated by a nucleic acid sequencer. In some embodiments, the nucleic acid sequencer performs pyrosequencing, single molecule sequencing, nanopore sequencing, semiconductor sequencing, sequencing by synthesis, sequencing by ligation, or sequencing by hybridization on the nucleic acid to generate sequencing read data. In some embodiments, the method further includes grouping the sequence read data into families of sequence read data, each family including sequence read data generated from a nucleic acid in the sample. In some embodiments, the method includes determining the likelihood that the subject from whom the sample was obtained has cancer, precancer, infection, transplant rejection, or other disease or disorder associated with changes in the proportion of immune cell types.

[0383] The method may be used to diagnose the presence of a condition, particularly cancer or precancer, in a subject, characterize the condition (e.g., stage the cancer or determine the heterogeneity of the cancer), monitor the response to treatment of the condition, and prognose the risk of developing the condition or the subsequent course of the condition. The present disclosure may also be useful for determining the effectiveness of a particular treatment option. A successful treatment option may increase the amount of copy number alterations or rare mutations detected in the subject's blood, since more cancers may die and shed DNA if the treatment is successful. In other examples, this may not occur. In another example, perhaps a particular treatment option may correlate with the genetic profile of the cancer over time. This correlation may be useful for selecting a treatment.

[0384] Additionally, if the cancer is observed to be in remission following treatment, the method can be used to monitor for residual disease or recurrence of the disease.

[0385] In some embodiments, the methods and systems disclosed herein may be used to identify customized or targeted therapies for treating a given disease or condition in a patient based on the classification of the nucleic acid variant as being of somatic or germline origin. Typically, the disease under consideration is a type of cancer. Non-limiting examples of such cancers include cholangiocarcinoma, bladder cancer, transitional cell carcinoma, urothelial carcinoma, brain cancer, glioma, astrocytoma, breast cancer, metaplastic carcinoma, cervical cancer, cervical squamous cell carcinoma, rectal cancer, colorectal cancer, colon cancer, hereditary nonpolyposis colorectal cancer, colorectal adenocarcinoma, gastrointestinal stromal tumor (GIST), endometrial cancer, endometrial stromal sarcoma, esophageal cancer, esophageal squamous cell carcinoma, esophageal adenocarcinoma, intraocular melanoma, uveal melanoma, gallbladder cancer, gallbladder adenocarcinoma, renal cell carcinoma, clear cell renal cell carcinoma, transitional cell carcinoma, urothelial carcinoma, Wilms' tumor, leukemia, acute lymphocytic leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), chronic myelogenous leukemia (CML), chronic myelomonocytic ... and / or pulmonary fibrosis (PFFS), hepatoma, hepatoma, hepatocellular carcinoma, cholangiocarcinoma, hepatoblastoma, lung cancer, non-small cell lung cancer (NSCLC), mesothelioma, B cell lymphoma, non-Hodgkin's lymphoma, diffuse large B cell lymphoma, mantle cell lymphoma, T cell lymphoma, non-Hodgkin's lymphoma, precursor T lymphoblastic lymphoma / leukemia, peripheral T cell lymphoma, multiple myeloma, nasopharyngeal carcinoma (NPC), neuroblastoma, oropharyngeal carcinoma, oral squamous cell carcinoma, osteosarcoma, ovarian cancer, pancreatic cancer, pancreatic ductal adenocarcinoma, pseudopapillary tumor, pancreatic acinar cell carcinoma, prostate cancer, prostate adenocarcinoma, skin cancer, melanoma, malignant melanoma, cutaneous melanoma, small intestine cancer, gastric cancer, gastrointestinal stromal tumor (GIST), uterine cancer, or uterine sarcoma. In some embodiments, the cancer is a type of cancer that is not a hematological cancer, e.g., a solid tumor cancer, e.g., a carcinoma or a sarcoma.The type and / or stage of cancer can be detected from genetic variations including mutations, rare mutations, indels, rearrangements, copy number variations, transversions, translocations, recombinations, inversions, deletions, aneuploidy, partial aneuploidy, polyploidy, chromosomal instability, alterations in chromosomal structure, gene fusions, chromosomal fusions, gene truncations, gene amplifications, gene duplications, chromosomal lesions, DNA lesions, abnormal changes in nucleic acid chemical modifications, abnormal changes in epigenetic patterns, and abnormal changes in nucleic acid 5-methylcytosine.

[0386] Genetic data can also be used to characterize specific forms of cancer. Cancers are often heterogeneous in both composition and stage classification. Genetic profile data can allow characterization of a particular subtype of cancer, which may be important in the diagnosis or treatment of that particular subtype. This information can also provide clues to the subject or practitioner regarding the prognosis of a particular type of cancer, allowing the subject or practitioner to adapt treatment options according to the progression of the disease. Some cancers can progress to become more aggressive and genetically unstable. Other cancers can remain benign, inactive, or dormant. The systems and methods of the present disclosure can be useful for determining disease progression.

[0387] Furthermore, the method of the present disclosure may be used to characterize the heterogeneity of abnormal conditions in a subject. Such a method may include, for example, creating a genetic profile of extracellular polynucleotides from a subject, where the genetic profile includes a plurality of data resulting from the analysis of copy number variation and rare mutations. In some embodiments, the abnormal condition is cancer. In some embodiments, the abnormal condition may be a condition that results in a heterogeneous genomic population. In the example of cancer, it is known that some tumors contain tumor cells at different stages of cancer. In other examples, the heterogeneity may constitute multiple foci of disease. Again, in the example of cancer, there may be multiple tumor foci, perhaps one or more foci are the result of metastasis spreading from the primary site.

[0388] The method can be used to generate or profile a fingerprint or set of data that is a summary of the genetic information from different cells in a heterogeneous disease, which may include copy number variation, epigenetic variation, and mutation analysis, either alone or in combination.

[0389] The method can be used to diagnose, prognose, monitor or observe cancer, precancer or other diseases.In some embodiments, the method herein does not involve diagnosing, prognosing or monitoring fetus, and therefore is not intended for non-invasive prenatal testing.In other embodiments, these methodologies can be used on pregnant subjects to diagnose, prognose, monitor or observe cancer or other diseases in unborn subjects whose DNA and other polynucleotides may co-circulate with maternal molecules.

[0390] Non-limiting examples of other genetically-based diseases, disorders, or conditions that may be optionally evaluated using the methods and systems disclosed herein include achondroplasia, alpha-1 antitrypsin deficiency, antiphospholipid syndrome, autism, autosomal dominant polycystic kidney disease, Charcot-Marie-Tooth disease (CMT), Cri-du-Chat disease, Crohn's disease, cystic fibrosis, Dercum's disease, Down's syndrome, Duane's syndrome, Duchenne muscular dystrophy, factor V Leiden thrombophilia, familial hypercholesterolemia, familial Mediterranean fever, fragile kidney disease, and idiopathic pulmonary fibrosis. These include Weak X syndrome, Gaucher disease, hemochromatosis, hemophilia, holoprosencephaly, Huntington's disease, Klinefelter syndrome, Marfan syndrome, myotonic dystrophy, neurofibromatosis, Noonan syndrome, osteogenesis imperfecta, Parkinson's disease, phenylketonuria, Poland syndrome, porphyria, progeria, retinitis pigmentosa, severe combined immunodeficiency (SCID), sickle cell disease, spinal muscular atrophy, Tay-Sachs disease, thalassemia, trimethylaminuria, Turner syndrome, palatocardiofacial syndrome, WAGR syndrome, and Wilson's disease.

[0391] In some embodiments, the methods described herein include detecting the presence or absence of DNA originating from or derived from tumor cells at a preselected time point after a previous cancer treatment in a subject previously diagnosed with cancer using a set of sequence information obtained as described herein. The methods may further include determining a cancer recurrence score for the subject indicative of the presence or absence of DNA originating from or derived from tumor cells.

[0392] When the cancer recurrence score is determined, it can be further used to determine the cancer recurrence status.For example, when the cancer recurrence score is above a predefined threshold, the cancer recurrence status can be at risk of cancer recurrence.For example, when the cancer recurrence score is above a predefined threshold, the cancer recurrence status can be at low or lower risk of cancer recurrence.In certain embodiments, a cancer recurrence score equal to a predefined threshold can result in a cancer recurrence status of either at risk of cancer recurrence or at low or lower risk of cancer recurrence.

[0393] In some embodiments, the cancer recurrence score is compared to a predefined cancer recurrence threshold, and if the cancer recurrence score is above the cancer recurrence threshold, the subject is classified as a candidate for subsequent cancer treatment, and if the cancer recurrence score is below the cancer recurrence threshold, the test subject is classified as not being a candidate for treatment. In certain embodiments, a cancer recurrence score equal to the cancer recurrence threshold may result in classification as either a candidate for subsequent cancer treatment or not being a candidate for treatment.

[0394] The methods discussed above may further include any suitability feature(s) described elsewhere herein, including the sections regarding methods for determining the risk of cancer recurrence in a subject and / or classifying a subject as a candidate for subsequent cancer treatment. 2. Methods for determining the risk of cancer recurrence in a subject and / or classifying a subject as a candidate for subsequent cancer treatment

[0395] In some embodiments, the methods provided herein are methods of determining the risk of cancer recurrence in a subject. In some embodiments, the methods provided herein are methods of classifying a subject as a candidate for a subsequent cancer treatment.

[0396] Any of such methods may include collecting DNA (e.g., originating from or derived from tumor cells) from a subject diagnosed with cancer at one or more preselected time points after one or more previous cancer treatments for the subject. The subject may be any of the subjects described herein. The DNA may be cfDNA. The DNA may be obtained from a tissue sample.

[0397] Any such method may include capturing a set of multiple target regions from the DNA of the subject, the set of multiple target regions including a set of sequence variable target regions and / or a set of epigenetic target regions, thereby producing a set of captured DNA molecules. The capturing step may be performed according to any of the embodiments described elsewhere herein.

[0398] In any of such methods, the previous cancer treatment may include surgery, administration of a therapeutic composition, and / or chemotherapy.

[0399] Any of such methods may include sequencing the captured DNA molecules, thereby producing a set of sequence information. The captured DNA molecules of the set of sequence-variable target regions may be sequenced to a greater depth of sequencing than the captured DNA molecules of the set of epigenetic target regions.

[0400] Any of such methods may include detecting the presence or absence of DNA originating from or derived from a tumor cell at a preselected time point using the set of sequence information. Detecting the presence or absence of DNA originating from or derived from a tumor cell may be performed according to any of the embodiments thereof described elsewhere herein.

[0401] The method for determining the risk of cancer recurrence in a subject may include determining a cancer recurrence score, which indicates the presence or absence or amount of DNA originating from or derived from the subject's tumor cells. The cancer recurrence score may further be used to determine a cancer recurrence status. For example, if the cancer recurrence score is above a predefined threshold, the cancer recurrence status may be at risk of cancer recurrence. For example, if the cancer recurrence score is above a predefined threshold, the cancer recurrence status may be at low or lower risk of cancer recurrence. In certain embodiments, a cancer recurrence score equal to a predefined threshold may result in a cancer recurrence status of either at risk of cancer recurrence or at low or lower risk of cancer recurrence.

[0402] The method of classifying a subject as a candidate for subsequent cancer treatment may include comparing the subject's cancer recurrence score with a predefined cancer recurrence threshold, thereby classifying the subject as a candidate for subsequent cancer treatment if the cancer recurrence score is above the cancer recurrence threshold, or as not a candidate for treatment if the cancer recurrence score is below the cancer recurrence threshold. In certain embodiments, a cancer recurrence score equal to the cancer recurrence threshold may result in classification as either a candidate for subsequent cancer treatment or as not a candidate for treatment. In some embodiments, the subsequent cancer treatment comprises administration of chemotherapy or a therapeutic composition.

[0403] Any of such methods may include determining a disease-free survival (DFS) period of the subject based on the cancer recurrence score, for example, the DFS period may be 1 year, 2 years, 3 years, 4 years, 5 years, or 10 years.

[0404] In some embodiments, the set of sequence information comprises a sequence variable target region sequence, and determining the cancer recurrence score may comprise determining at least a first subscore indicative of the level of a particular immune cell type, SNV, insertion / deletion, CNV and / or fusion present in the sequence variable target region sequence.

[0405] In some embodiments, the number of mutations in the sequence variable target region selected from 1, 2, 3, 4, or 5 is sufficient to result in a cancer recurrence score in which the first subscore is classified as positive for cancer recurrence. In some embodiments, the number of mutations is selected from 1, 2, or 3.

[0406] In some embodiments, the set of sequence information includes epigenetic target region sequences, and determining the cancer recurrence score includes determining a second subscore indicative of the amount of molecules (obtained from the epigenetic target region sequences) that exhibit an epigenetic state different from the DNA found in a corresponding sample from a healthy subject (e.g., cfDNA found in a blood sample from a healthy subject, or DNA found in a tissue sample from a healthy subject if the tissue sample is of the same type of tissue as that obtained from the subject). These abnormal molecules (i.e., molecules having an epigenetic state different from the DNA found in the corresponding sample from the healthy subject) may be consistent with epigenetic changes associated with cancer, such as methylation of a hypermethylated variable target region and / or perturbed fragmentation of a fragmented variable target region, where "perturbed" means different from the DNA found in the corresponding sample from the healthy subject.

[0407] In some embodiments, a percentage of molecules corresponding to the hypermethylated variable target region set and / or the fragmented variable target region set that exhibit hypermethylation in the hypermethylated variable target region set and / or aberrant fragmentation in the fragmented variable target region set greater than or equal to a value in the range of 0.001% to 10% is sufficient for the second subscore to be classified as positive for cancer recurrence. The range may be 0.001% to 1%, 0.005% to 1%, 0.01% to 5%, 0.01% to 2%, or 0.01% to 1%.

[0408] In some embodiments, any of such methods may include determining the fraction of tumor DNA from the fraction of molecules in the set of sequence information that exhibit one or more features indicative of origin from tumor cells. This may be done for molecules corresponding to some or all of the target regions, including, for example, one or both of hypermethylated variable target regions, hypomethylated variable target regions, and fragmented variable target regions (hypermethylation of hypermethylated variable target regions and / or aberrant fragmentation of fragmented variable target regions may be considered indicative of origin from tumor cells). This may be done for molecules corresponding to sequence variable target regions, for example, molecules that include alterations consistent with cancer, such as SNVs, indels, CNVs, and / or fusions. The fraction of tumor DNA may be determined based on a combination of molecules corresponding to epigenetic target regions and molecules corresponding to sequence variable target regions.

[0409] The determination of the Cancer Recurrence Score may be based at least in part on a fraction of tumor DNA, where a fraction of tumor DNA greater than a threshold in the range of 10-11 to 1 or 10-10 to 1 is sufficient for the Cancer Recurrence Score to be classified as positive for cancer recurrence. In some embodiments, a fraction of tumor DNA greater than or equal to a threshold in the range of 10-10 to 10-9, 10-9 to 10-8, 10-8 to 10-7, 10-7 to 10-6, 10-6 to 10-5, 10-5 to 10-4, 10-4 to 10-3, 10-3 to 10-2, or 10-2 to 10-1 is sufficient for the Cancer Recurrence Score to be classified as positive for cancer recurrence. In some embodiments, a fraction of tumor DNA greater than a threshold of at least 10-7 is sufficient for the Cancer Recurrence Score to be classified as positive for cancer recurrence. The determination that tumor DNA fraction is greater than a threshold, for example, the threshold corresponding to any of the above-mentioned embodiments, can be based on cumulative probability.For example, a sample is considered positive when the cumulative probability that tumor DNA fraction is greater than a threshold in any of the above-mentioned ranges exceeds a probability threshold of at least 0.5, 0.75, 0.9, 0.95, 0.98, 0.99, 0.995 or 0.999.In some embodiments, the probability threshold is at least 0.95, for example 0.99.

[0410] In some embodiments, the set of sequence information includes sequence variable target region sequences and epigenetic target region sequences, and determining the cancer recurrence score includes determining a first subscore indicating the level of a particular immune cell type, a second subscore indicating the amount of SNVs, insertions / deletions, CNVs and / or fusions present in the sequence variable target region sequence, and a third subscore indicating the amount of abnormal molecules in the epigenetic target region sequence, and combining the first, second and third subscores to provide a cancer recurrence score. When the subscores are combined, they can be combined by applying a threshold value to each subscore independently, or by training a machine learning classifier to determine the status based on multiple positive and negative training samples, each of which is greater than a predefined fraction of abnormal molecules (i.e., molecules having an epigenetic state different from that found in the corresponding sample from a healthy subject; e.g., tumor) in the epigenetic target region, respectively in the sequence variable target region.

[0411] In some embodiments, a combined score value in the range of -4 to 2 or -3 to 1 is sufficient for the Cancer Recurrence Score to be classified as positive for cancer recurrence.

[0412] In any embodiment in which the Cancer Recurrence Score is classified as positive for cancer recurrence, the subject's Cancer Recurrence Status may be at risk of cancer recurrence and / or the subject may be classified as a candidate for subsequent cancer treatment.

[0413] In some embodiments, the cancer is any one of the types of cancer described elsewhere herein, for example, colorectal cancer. 3. Treatment and Related Administration

[0414] In certain embodiments, the methods disclosed herein relate to identifying a treatment, such as a customized treatment, and administering it to a patient or subject. In some embodiments, determining the level of a particular immune cell type, including a rare immune cell type, facilitates the selection of an appropriate treatment. In some embodiments, the patient or subject has a given disease, disorder, or condition. Essentially any cancer treatment (e.g., surgery, radiation, chemotherapy, and / or the like) may be included as part of these methods. In certain embodiments, the treatment administered to the subject includes at least one chemotherapeutic agent. In some embodiments, the chemotherapy agent may include alkylating agents (e.g., but not limited to, chlorambucil, cyclophosphamide, cisplatin and carboplatin), nitrosoureas (e.g., but not limited to, carmustine and lomustine), antimetabolites (e.g., but not limited to, Fluorauracil, methotrexate and fludarabine), plant alkaloids and natural products (e.g., but not limited to, vincristine, paclitaxel and topotecan), antitumor antibiotics (e.g., but not limited to, bleomycin, doxorubicin and mitoxantrone), hormonal agents (e.g., but not limited to, prednisone, dexamethasone, tamoxifen and leuprolide) and biological response modifiers (e.g., but not limited to, Herceptin and Avastin, Erbitux and Rituxan). In some embodiments, the chemotherapy administered to the subject may include FOLFOX or FOLFIRI. In certain embodiments, a treatment comprising at least one PARP inhibitor may be administered to the subject.In certain embodiments, PARP inhibitors may include, among others, olaparib, talazoparib, rucaparib, niraparib (brand name ZEJULA).Typically, the treatment comprises at least one immunotherapy (or immunotherapeutic agent).Immunotherapy generally refers to a method of enhancing immune response to a certain cancer type.In certain embodiments, immunotherapy refers to a method of enhancing T cell response to tumor or cancer.

[0415] In some embodiments, the treatment is customized based on the status of the nucleic acid variant being of somatic or germline origin. In some embodiments, essentially any cancer treatment (e.g., surgery, radiation, chemotherapy, and / or the like) can be included as part of these methods. Typically, the customized treatment includes at least one immunotherapy (or immunotherapeutic agent). Immunotherapy generally refers to a method of enhancing immune response to a given cancer type. In certain embodiments, immunotherapy refers to a method of enhancing T cell response to tumor or cancer.

[0416] In some embodiments, the immunotherapy or immunotherapeutic agent targets immune checkpoint molecules. Certain tumors can evade the immune system by utilizing immune checkpoint pathways. Thus, targeting immune checkpoints has emerged as an effective approach to combat the ability of tumors to evade the immune system and activate antitumor immunity against certain cancers. Pardoll, Nature Reviews Cancer, 2012, 12:252-264.

[0417] In certain embodiments, the immune checkpoint molecule is an inhibitory molecule that reduces signals involved in T cell response to antigen. For example, CTLA4 is expressed on T cells and plays a role in downregulating T cell activation by binding to CD80 (also known as B7.1) or CD86 (also known as B7.2) on antigen presenting cells. PD-1 is another inhibitory checkpoint molecule expressed on T cells. PD-1 limits the activity of T cells in peripheral tissues during inflammatory responses. In addition, the ligands of PD-1 (PD-L1 or PD-L2) are commonly upregulated on the surface of many different tumors, resulting in downregulation of anti-tumor immune responses in the tumor microenvironment. In certain embodiments, the inhibitory immune checkpoint molecule is CTLA4 or PD-1. In other embodiments, the inhibitory immune checkpoint molecule is a ligand of PD-1, such as PD-L1 or PD-L2. In other embodiments, the inhibitory immune checkpoint molecule is a ligand of CTLA4, such as CD80 or CD86. In other embodiments, the inhibitory immune checkpoint molecule is lymphocyte activation gene 3 (LAG3), killer cell immunoglobulin-like receptor (KIR), T cell membrane protein 3 (TIM3), galectin 9 (GAL9), or adenosine A2a receptor (A2aR).

[0418] Antagonists targeting these immune checkpoint molecules can be used to enhance antigen-specific T cell responses to certain cancers. Thus, in certain embodiments, the immunotherapy or immunotherapeutic agent is an inhibitory immune checkpoint molecule antagonist. In certain embodiments, the inhibitory immune checkpoint molecule is PD-1. In certain embodiments, the inhibitory immune checkpoint molecule is PD-L1. In certain embodiments, the inhibitory immune checkpoint molecule antagonist is an antibody (e.g., a monoclonal antibody). In certain embodiments, the antibody or monoclonal antibody is an anti-CTLA4, anti-PD-1, anti-PD-L1, or anti-PD-L2 antibody. In certain embodiments, the antibody is a monoclonal anti-PD-1 antibody. In some embodiments, the antibody is a monoclonal anti-PD-L1 antibody. In certain embodiments, the monoclonal antibody is a combination of an anti-CTLA4 antibody and an anti-PD-1 antibody, an anti-CTLA4 antibody and an anti-PD-L1 antibody, or an anti-PD-L1 antibody and an anti-PD-1 antibody. In certain embodiments, the anti-PD-1 antibody is one or more of pembrolizumab (Keytruda®) or nivolumab (Opdivo®). In certain embodiments, the anti-CTLA4 antibody is ipilimumab (Yervoy®). In certain embodiments, the anti-PD-L1 antibody is one or more of atezolizumab (Tecentriq®), avelumab (Bavencio®), or durvalumab (Imfinzi®).

[0419] In certain embodiments, the immunotherapy or immunotherapeutic agent is an antagonist (e.g., an antibody) against CD80, CD86, LAG3, KIR, TIM3, GAL9, or A2aR. In other embodiments, the antagonist is a soluble version of an inhibitory immune checkpoint molecule, such as a soluble fusion protein comprising the extracellular domain of an inhibitory immune checkpoint molecule and the Fc domain of an antibody. In certain embodiments, the soluble fusion protein comprises the extracellular domain of CTLA4, PD-1, PD-L1, or PD-L2. In some embodiments, the soluble fusion protein comprises the extracellular domain of CD80, CD86, LAG3, KIR, TIM3, GAL9, or A2aR. In one embodiment, the soluble fusion protein comprises the extracellular domain of PD-L2 or LAG3.

[0420] In certain embodiments, the immune checkpoint molecule is a costimulatory molecule that amplifies the signal involved in T cell response to antigen. For example, CD28 is a costimulatory receptor expressed on T cells. When T cells bind to antigen through their T cell receptor, CD28 binds to CD80 (also known as B7.1) or CD86 (also known as B7.2) on antigen-presenting cells to amplify T cell receptor signaling and promote T cell activation. Because CD28 binds to the same ligands (CD80 and CD86) as CTLA4, CTLA4 can counter or regulate the costimulatory signaling mediated by CD28. In certain embodiments, the immune checkpoint molecule is a costimulatory molecule selected from CD28, inducible T cell costimulatory agent (ICOS), CD137, OX40, or CD27. In other embodiments, the immune checkpoint molecule is a ligand for a costimulatory molecule, including, for example, CD80, CD86, B7RP1, B7-H3, B7-H4, CD137L, OX40L, or CD70.

[0421] Agonists that target these costimulatory checkpoint molecules can be used to enhance antigen-specific T cell responses to certain cancers. Thus, in certain embodiments, the immunotherapy or immunotherapeutic agent is an agonist of costimulatory checkpoint molecules. In certain embodiments, the agonist of costimulatory checkpoint molecules is an agonist antibody, preferably a monoclonal antibody. In certain embodiments, the agonist antibody or monoclonal antibody is an anti-CD28 antibody. In other embodiments, the agonist antibody or monoclonal antibody is an anti-ICOS, anti-CD137, anti-OX40, or anti-CD27 antibody. In other embodiments, the agonist antibody or monoclonal antibody is an anti-CD80, anti-CD86, anti-B7RP1, anti-B7-H3, anti-B7-H4, anti-CD137L, anti-OX40L, or anti-CD70 antibody.

[0422] In certain embodiments, the state of nucleic acid variants from a sample from a subject of somatic or germline origin can be compared with a database of comparator results from a reference population to identify customized or targeted treatment for the subject.Typically, the reference population includes patients with the same cancer or disease type as the subject, and / or patients who are undergoing or have undergone the same treatment as the test subject.Customized or targeted treatment (or multiple treatments) can be identified when the nucleic acid variants and the comparator results meet certain classification criteria (e.g., substantially or approximately match).

[0423] In certain embodiments, the customized treatment described herein is typically administered parenterally (e.g., intravenously or subcutaneously). Pharmaceutical compositions containing immunotherapeutic agents are typically administered intravenously. Certain therapeutic agents are administered orally. However, customized treatments (e.g., immunotherapeutic agents, etc.) may also be administered by any method known in the art, such as buccal, sublingual, rectal, vaginal, urethral, ​​topical, intraocular, intranasal, and / or auricular, and administration may include tablets, capsules, granules, aqueous suspensions, gels, sprays, suppositories, smears, ointments, etc.

[0424] Therapeutic options for treating particular genetically-based diseases, disorders, or conditions other than cancer are generally well known to those of skill in the art and will become apparent in light of the particular disease, disorder, or condition being considered. III. Kit

[0425] Kits comprising the compositions described herein are also provided. The kits may be useful for carrying out the methods described herein. In some embodiments, the kits comprise an agent that recognizes methylcytosine in DNA. In some such embodiments, the agent is an antibody or a methyl-binding protein or a methyl-binding domain. In some embodiments, the kits comprise target-specific probes that specifically bind to a set of epigenetic and / or sequence variable target regions, and the target-specific probes of at least one of the set of epigenetic target regions bind to a target region that is differentially methylated in different immune cell types. In some such embodiments, the target-specific probe comprises a capture moiety. In some embodiments, the kits comprise a solid support linked to a binding partner of the capture moiety. In some embodiments, the kits comprise an adaptor. In some embodiments, the kits comprise PCR primers, and the PCR primers anneal to the target region or the adaptor. In some embodiments, the kits comprise additional elements elsewhere herein. In some embodiments, the kits comprise instructions for carrying out the methods described herein.

[0426] The kit also includes: ALK, APC, BRAF, CDKN2A, EGFR, ERBB2, FBXW7, KRAS, MYC, NOTCH1, NRAS, PIK3CA, PTEN, RBI, TP53, MET, AR, ABLl, AKTl, ATM, CDHl, CSFIR, CTNNBl, ERBB4, EZH2, FGFRl, FGFR2, FGFR3, FLT3, GNA11, GNAQ , GNAS, HNF1A, HRAS, IDH1, IDH2, JAK2, JAK3, KDR, KIT, MLH1, MPL, NPM1, PDGFRA, PROC, PTPN11, RET, SMAD4, SMARCB1, SMO, SRC, STK11, VHL, TERT, CCND1, CDK4, CDKN2B, RAF1, BRCA1, CCND2, CDK6, NF1, TP53, ARID 1 A, BRCA2, CCNE1, ESR1, RIT1, GATA3, MAP2K1, RHEB, ROS1, ARAF, MAP2K2, NFE2L2, RHOA, and NTRKl. The number of genes that the oligonucleotide probe can selectively hybridize to can be different. For example, the number of genes can include 1, 2, 3, 4, 5, 6, 7, 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, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, or 54. The kits may include a container containing a plurality of oligonucleotide probes and instructions for use in practicing any of the methods described herein.

[0427] The oligonucleotide probe can selectively hybridize to the exon region of a gene, for example, at least 5 genes. In some examples, the oligonucleotide probe can selectively hybridize to at least 30 exons of a gene, for example, at least 5 genes. In some examples, the multiple probes can selectively hybridize to each of the at least 30 exons. The probe hybridizing to each exon can have a sequence that overlaps with at least one other probe. In some embodiments, the oligo probe can selectively hybridize to the non-coding region of a gene disclosed herein, for example, the intron region of a gene. The oligo probe can also selectively hybridize to the region of a gene, including both the exon and intron regions of a gene disclosed herein.

[0428] Any number of exons can be targeted by an oligonucleotide probe, for example, at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 260, 270, 280, 290, 300, 310, 320, 330, 340, 350, 360, 370, 380, 390, 400, 410, 420, 430, 440, 450, 460, 470, 480, 490, 500, 510, 520, 530, 540, 550, 560, 570, 580, 590, 600, 600, 610, 620, 630, 640, 650, 660, 670, 680, 700, 710, 720, 730, 55, 160, 165, 170, 175, 180, 185, 190, 195, 200, 205, 210, 215, 220, 225, 230, 235, 240, 245, 250, 255, 260, 265, 270, 275, 280, 285, 290, 295, 300, 400, 500, 600, 700, 800, 900, 1,000 or more exons can be targeted.

[0429] The kit may include at least 4, 5, 6, 7, or 8 different library adapters with distinct molecular barcodes and identical sample barcodes. The library adapters may not be sequencing adapters. For example, the library adapters do not include flow cell sequences or sequences that allow for the formation of hairpin loops for sequencing. Different mutations and combinations of molecular barcodes and sample barcodes are described throughout this specification and are applicable to the kit. Furthermore, in some examples, the adapters are not sequencing adapters. Furthermore, the adapters provided in the kit may also include sequencing adapters. The sequencing adapters may include sequences that hybridize to one or more sequencing primers. The sequencing adapters may further include sequences that hybridize to a solid support, such as flow cell sequences. For example, the sequencing adapters may be flow cell adapters. The sequencing adapters may be attached to one or both ends of the polynucleotide fragments. In some examples, the kit may include at least 8 different library adapters with distinct molecular barcodes and identical sample barcodes. The library adaptor may not be a sequencing adaptor. The kit may further include a sequencing adaptor having a first sequence that selectively hybridizes to the library adaptor and a second sequence that selectively hybridizes to the flow cell sequence. In another example, the sequencing adaptor may be hairpin-shaped. For example, the hairpin-shaped adaptor may include a complementary double-stranded portion and a loop portion, and the double-stranded portion may be attached (e.g., ligated) to a double-stranded polynucleotide. The hairpin-shaped sequencing adaptor may be attached to both ends of a polynucleotide fragment to generate a circular molecule, which may be sequenced multiple times.Sequencing adapters, end-to-end, up to 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54 , 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 or more bases. The sequencing adapter may comprise 20-30, 20-40, 30-50, 30-60, 40-60, 40-70, 50-60, 50-70 bases from end to end. In a particular example, the sequencing adapter may comprise 20-30 bases from end to end. In another example, the sequencing adapter may comprise 50-60 bases from end to end. The sequencing adapter may comprise one or more barcodes. For example, the sequencing adapter may comprise a sample barcode. The sample barcode may comprise a predetermined sequence. The sample barcode may be used to identify the origin of the polynucleotide. A sample barcode can be at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, or more (or any length described throughout) nucleic acid bases, e.g., at least 8 bases. Barcodes can be continuous or discontinuous sequences as described above.

[0430] The library adaptors can be blunt ended, Y-shaped, and less than or equal to 40 nucleobases in length. Other variations can be found throughout and are applicable to the kits.

[0431] Although preferred embodiments of the present invention have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. It is not intended that the present invention be limited to the specific examples provided herein. Although the present invention has been described with reference to the above specification, the description and illustration of the embodiments herein are not meant to be construed in a limiting sense. Numerous variations, changes, and substitutions will occur to those skilled in the art without departing from the present invention. Furthermore, it should be understood that all aspects of the present invention are not limited to the specific descriptions, configurations, or relative proportions described herein, which depend upon a variety of conditions and variables. It should be understood that various alternatives to the embodiments of the present disclosure described herein may be used in the practice of the present invention. Therefore, it is intended that the present disclosure also covers any such alternatives, modifications, variations, or equivalents. It is intended that the following claims define the scope of the present invention, and that methods and structures that fall within the scope of these claims, and their equivalents, are covered thereby.

[0432] Although the foregoing disclosure has been described in some detail by way of illustration and example for purposes of clarity and understanding, it will be apparent to those skilled in the art upon reading the disclosure that various changes in form and detail may be made without departing from the true scope of the disclosure and may be practiced within the scope of the appended claims. For example, all of the features, steps, elements, or other aspects of the methods, systems, computer readable media, and / or components thereof may be used in various combinations.

[0433] All patents, patent applications, websites, other publications or documents, accession numbers, etc. cited herein are incorporated by reference in their entirety for all purposes to the same extent as if each individual item was specifically and individually indicated to be incorporated by reference. Where different versions of a sequence are associated with accession numbers at different times, the version associated with the accession number at the effective filing date of this application is meant. By effective filing date is meant the earlier of the actual filing date or, where applicable, the filing date of the priority application that refers to the accession number. Similarly, where different versions of publications, websites, etc. are published at different times, the version most recently published at the effective filing date of this application is meant, unless otherwise indicated. EXAMPLES

[0434] Example 1 Analysis of methylation data to identify differentially methylated regions restricted to specific immune cell types Whole genome bisulfite sequencing data from the Blueprint consortium, available on the internet at dcc.blueprint-epigenome.eu, was used in the panel design. The data set contains methylation profiles of hundreds of cell types from hematopoietic lineages, including naive and activated T and B cells. Rare immune cell types are likely to have elevated turnover in disease states and are therefore targeted in the panel, including memory B cells, plasma cells, Tregs, CD4 effector memory T cells, CD4 central memory T cells, CD8 effector memory T cells, CD8 central memory T cells, NK cells, and various myeloid cell types.

[0435] The Blueprint dataset contains single-CpG-level methylation levels. A CpG site was considered detected if it was present in at least one sample, and samples with no data for more than 10^7 detected CpG sites were excluded from further analysis. CpG sites missing from at least five samples were filtered out. Cell types with similar results were first grouped into clusters including myeloid cells, naive B cells, activated B cells, naive T cells, activated T cells, and NK cells.

[0436] The genome was divided into 200 base pair bins of 50 base pair width. Any bin in which fewer than seven CpG sites were detected was excluded from downstream analysis. The methylation level of each bin in each sample was calculated as the average of the CpG methylation levels.

[0437] The average methylation level per bin per cell cluster was calculated. Bins were identified as differentially methylated regions (DMRs) for a cluster based on the extent to which the methylation level in the cluster for the DMR exceeded the maximum methylation of the region in any other cluster (hypermethylated regions) or the extent to which the methylation level was below the minimum methylation level of the other cluster (hypomethylated regions). The aim was to identify 25 hypermethylated and 25 hypomethylated regions for each cluster. In some clusters, the aim was not achieved for hypermethylated regions, but more than 25 hypomethylated regions were easily identified; therefore, when the aim was not achieved for hypermethylated regions, additional hypomethylated regions were identified. The results are shown in the table below. The total footprint of the panel of regions identified for a cluster was 33.9 kb. Table 6 [Table 6]

[0438] The average methylation level per bin per cell type was then calculated. In all cell types within the cluster, DMRs were identified that could distinguish one cell type from other cell types within the same cluster. Bins were identified as cell type DMRs based on the extent to which the methylation level in the cell type for the DMR exceeded the average methylation of the region in any other cell type within the cluster (hypermethylated regions) or the extent to which the methylation level was below the average methylation level of other cell types within the cluster (hypomethylated regions). The aim was to identify 25 hypermethylated and 25 hypomethylated regions for each cell type. The results are shown in the table below. The total footprint of the panel of regions identified for the cell type was 63.75 kb. Table 7 [Table 7]

[0439] Overlapping DMRs identified from the bins were merged into regions and hg38 coordinates from the Blueprint dataset were converted to hg19 coordinates using liftover (see genome.ucsc.edu / cgi-bin / hgLiftOver). The total footprint of the resulting panel of DMRs was 95.9 kb with respect to hg19. The results are shown in the table below. Table 8 [Table 8]

[0440] Loci showing differential methylation in cell types or clusters were plotted in a heatmap showing methylation levels as a function of cell type or cluster in FIG. 1B. Example 2 Analysis of cfDNA to detect hypermethylation signals associated with certain immune cell types to detect cancer

[0441] A set of samples from healthy subjects and subjects with early stage colorectal cancer (Figure 1C), early stage cancer types shown in Figure 1D, or late stage cancer types shown in Figure 1E were analyzed by a blood-based assay to detect hypermethylation signals associated with certain immune cell types and test whether such signals predict colorectal cancer. cfDNA was extracted from the plasma of these patients and then combined with MBD-coated beads to partition hypermethylated DNA from hypomethylated DNA. Any unmethylated or less methylated DNA was first eluted from the beads with buffers containing increasing concentrations of salt. Finally, hypermethylated DNA was washed away from the antibody specific for methylcytosine using a high salt buffer. The unbound DNA and these washes resulted in three partitions of cfDNA with increasing methylation (hypomethylated partition, residual methylated partition, and hypermethylated partition). In preparation for the enzymatic step of library preparation, the partitioned cfDNA molecules were cleaned to remove salt and concentrated.

[0442] After the cfDNA in the partition was concentrated, the first adapter was added to the cfDNA by ligation to its 3' end. The adapter was used as a priming site for second strand synthesis using a universal primer and DNA polymerase. The first adapter contained biotin, and the nucleic acid ligated to the first adapter was bound to beads containing streptavidin. The second adapter was then ligated to the 3' end of the second strand of the double-stranded molecule. These adapters contained non-unique molecular barcodes, and each partition was ligated to an adapter with a non-unique molecular barcode that was distinguishable from the barcodes in the adapters used in the other partitions. After ligation, the hypermethylated and residually methylated partitions were treated with methylation-sensitive restriction enzymes to degrade mis-partitioned non-methylated DNA. The partitions were pooled together and amplified by PCR.

[0443] After PCR, the amplified DNA was washed and concentrated prior to enrichment. Once concentrated, the amplified DNA was combined with a salt buffer and a biotinylated RNA target-specific probe for the hypermethylated DMR in certain immune cell types used in the analysis in Example 1, and the mixture was incubated overnight.

[0444] Biotinylated RNA target-specific probes (hybridized to DNA) were captured by streptavidin magnetic beads and separated from non-captured amplified DNA by a series of salt-based washes, thereby enriching the sample. After enrichment, an aliquot of the enriched sample was sequenced using an Illumina NovaSeq sequencer. The sequence read data generated by the sequencer was then analyzed using bioinformatics tools / algorithms. Molecular barcodes were used to identify unique molecules and to deconvolute samples into differentially distributed molecules. The hypermethylated target region sequences were analyzed to detect cfDNA molecules that were methylated in the regions used in Example 1. Relative methylation frequency was determined as the total number of molecules in methylated fractions (hypermethylated and intermediate distribution) normalized by the amount of input cfDNA. The results shown in Figures 1C-1E show that a subset of randomly selected examples of immune cell type-specific hypermethylated DMRs showed mutations and segregation between CRC and healthy samples, supporting the conclusion that immune cell type-specific DMRs can be informative of cancer status. Example 3 Analysis of cfDNA to detect hypomethylation signals associated with specific immune cell types to detect early stage colorectal cancer

[0445] A set of samples from healthy subjects and subjects with early stage colorectal cancer was analyzed by a blood-based assay to detect hypomethylation signals associated with certain immune cell types and to test whether such signals predict colorectal cancer. cfDNA was extracted from the plasma of these patients, then contacted with MBD and partitioned into hypomethylated, intermediate, and hypermethylated partitions. The hypomethylated partition was subjected to methylation-dependent restriction enzyme (MDRE) digestion to degrade mispartitioned molecules. In preparation for the enzymatic step of library preparation, the cfDNA molecules in the partitions were cleaned to remove salts and concentrated. Adapters containing molecular barcodes were ligated to the cfDNA molecules. The cfDNA molecules were enriched for regions of interest using biotin-labeled oligonucleotides, amplified, and sequenced.

[0446] The resulting molecular sequences were filtered to require cell type-specific hypomethylation (i.e., <10% methylation in one cell type of interest and >90% methylation in the other cell type) (according to published data, e.g., Loyfer et al., 2022, doi.org / 10.1101 / 2022.01.24.477547; Fox-Fisher et al., eLife 2021, 10:e70520; Moss et al., Nature Communications 2021, 9:5068; and the EpiDISH R package available at www.bioconductor.org / packages / release / bioc / html / EpiDISH.html), the presence of at least one MDRE restriction site. The cell types of interest were B cells, granulocytes, NK cells, T cells, and erythroid precursors. Sites with low molecular coverage were also filtered out.

[0447] The fraction of cfDNA contributed by each cell type of interest was determined as follows: for each site showing hypomethylation specific to that cell type, the percentage of hypomethylated DNA was determined, and these values ​​were averaged to obtain the fraction of cfDNA contributed by the cell type. The results are shown in Figure 3 and are consistent with a higher contribution from B cells, NK cells, and T cells, and a lower contribution from granulosa cells, to cfDNA from subjects with CRC than from healthy subjects. Example 4 Analysis of cfDNA to quantify immune cell types and to detect the presence or absence of cancer in a subject

[0448] A set of samples from healthy subjects, subjects with early stage colorectal cancer, and cancer patients are analyzed by blood-based assays to detect the levels of immune cell types and the presence / absence of mutations. cfDNA is extracted from the plasma of these patients and then combined with an antibody specific for methylcytosine. Magnetic beads conjugated with protein G are used to immunoprecipitate the antibody and its bound DNA, thus partitioning the hypermethylated DNA from the hypomethylated DNA. Any unmethylated or less methylated DNA is first eluted from the beads with buffers containing increasing concentrations of salt. Finally, a high salt buffer is used to wash away the hypermethylated DNA from the antibody specific for methylcytosine. The unbound DNA and these washes result in at least three partitions of cfDNA with increasing methylation: a hypomethylated partition, a residually methylated partition, and a hypermethylated partition. In preparation for the enzymatic step of library preparation, the partitioned cfDNA molecules are cleaned to remove salt and concentrated.

[0449] After the cfDNA in the distribution is concentrated, the first adaptor is added to the cfDNA by ligation to its 3' end. The adaptor is used as a priming site for second strand synthesis using a universal primer and DNA polymerase. The first adaptor contains biotin, and the nucleic acid ligated to the first adaptor is bound to a bead containing streptavidin. The second adaptor is then ligated to the 3' end of the second strand of the double-stranded molecule. These adaptors contain non-unique molecular barcodes, and each distribution is ligated to an adaptor that has a non-unique molecular barcode that is distinguishable from the barcodes in the adaptors used in other distributions. After ligation, the distributions are pooled together and amplified by PCR.

[0450] After PCR, the amplified DNA is washed and concentrated prior to enrichment. Once concentrated, the amplified DNA is combined with a salt buffer and biotinylated RNA target specific probes including a sequence variable target region set probe and an epigenetic target region set probe, and the mixture is incubated overnight. The sequence variable region set probe has a footprint of approximately 50 kb, and the epigenetic target region set probe has a footprint of approximately 500 kb. The sequence variable target region set probe includes oligonucleotides targeting at least a subset of the genes identified in Tables 3-5, and the epigenetic target region set probe includes oligonucleotides targeting a selection including at least a hypermethylated variable target region and a hypomethylated variable target region, and optionally including a CTCF binding target region, a transcription start site target region, a local amplification target region, and a methylation control region. The hypermethylated variable target region and the hypomethylated variable target region include regions specific to a plurality of clusters and / or immune cell types selected from those listed in Table 8.

[0451] Biotinylated RNA target-specific probes (hybridized to DNA) are captured by streptavidin magnetic beads and separated from non-captured amplified DNA by a series of salt-based washes, thereby enriching the sample. After enrichment, an aliquot of the enriched sample is sequenced using an Illumina NovaSeq sequencer. The sequence read data generated by the sequencer is then analyzed using bioinformatics tools / algorithms. Molecular barcodes are used to identify unique molecules and to deconvolute the sample into differentially distributed molecules. Sequence-variable target region sequences are analyzed by detecting genomic alterations, such as SNVs, insertions, deletions and fusions, that can be called with sufficient justification to distinguish true tumor variants from technical errors (e.g., PCR errors, sequencing errors). Epigenetic target region sequences are analyzed independently to detect methylated cfDNA molecules in regions shown to be differentially methylated in different immune cells and in cancer compared to normal cells. Finally, the results of both analyses are combined to generate a final determination of the likelihood of cancer or precancer in the subject from which the sample was obtained.

Claims

1. 1. A method for analyzing DNA in a sample, comprising: a) partitioning the sample into a plurality of aliquots by contacting the DNA with an agent that recognizes modified cytosines in the DNA, the plurality comprising a first aliquot and a second aliquot, the first aliquot comprising a greater proportion of DNA having modified cytosines than the second aliquot; b) sequencing DNA from one or more of the plurality of aliquots; and c) detecting the level of the DNA sequence to determine the amount of each of a plurality of immune cell types from which the DNA originates, the plurality of immune cell types comprising: i. Naive and activated lymphocytes; ii. monocytes and macrophages; or iii. Myelocytes, neutrophils, and eosinophils Including steps A method comprising:

2. 1. A method for analyzing DNA in a sample, comprising: a) partitioning the sample into a plurality of aliquots by contacting the DNA with an agent that recognizes modified cytosines in the DNA, the plurality comprising a first aliquot and a second aliquot, the first aliquot comprising a greater proportion of DNA having modified cytosines than the second aliquot; b) capturing at least one set of epigenetic target regions of DNA from at least one of said first and second subsamples, comprising contacting said DNA with target-specific probes specific for said at least one set of epigenetic target regions, said target regions of said set of epigenetic target regions comprising DNA sequences that are differentially methylated in a plurality of immune cell types, said plurality of immune cell types comprising: i. Naive and activated lymphocytes; ii. monocytes and macrophages; or iii. Myelocytes, neutrophils, and eosinophils thereby providing captured DNA; and c) sequencing the captured DNA to determine the level of each of the multiple immune cell types from which the DNA originates. A method comprising:

3. 2. The method of claim 1, comprising capturing at least one set of epigenetic target regions of DNA from at least one of the first and second subsamples, wherein the target regions of the set of epigenetic target regions comprise DNA sequences that are differentially methylated in multiple immune cell types, and wherein the capturing step is performed prior to the sequencing step. (a) the set of epigenetic target regions comprises a set of hypermethylated variable target regions and a set of hypomethylated variable target regions; and / or (b) the capturing step includes capturing sequence-variable target regions, e.g., the capturing step includes contacting the DNA with a target-specific probe specific for the at least one set of epigenetic target regions and a target-specific probe specific for the sequence-variable target regions; The method according to claim 2 or claim 3.

5. (a) the plurality of immune cell types comprises naive lymphocytes and activated lymphocytes, e.g., the plurality of immune cell types comprises naive T cells, naive B cells, effector CD4 T cells, effector CD8 T cells, Treg cells, plasma cells, and memory cells, e.g., the effector CD4 T cells comprise effector memory CD4 T cells and central memory CD4 T cells, and the effector CD8 T cells comprise effector memory CD8 T cells and central memory CD8 T cells; (b) the multiple immune cell types include monocytes and macrophages; (c) the plurality of immune cell types comprises myelocytes, neutrophils, and eosinophils, e.g., the plurality of immune cell types comprises metamyelocytes; and / or (d) the multiple immune cell types include natural killer (NK) cells; 10. A method according to any one of the preceding claims. (a) determining a level of each of the plurality of immune cell types relative to a level of total blood cells; (b) the sample is a blood sample, a plasma sample or is obtained from a tissue sample, e.g., the tissue sample is a biopsy, a fine needle aspirate, or a formalin-fixed, paraffin-embedded tissue sample; and / or (c) the DNA comprises cell-free DNA (cfDNA) or the DNA comprises DNA isolated from intact cells naturally present in the sample; 10. A method according to any one of the preceding claims. (a) determining a ratio of levels or amounts of immune cell types based on the determined levels or amounts of the plurality of immune cell types, e.g., (i) the numerator of the ratio comprises the level or amount of neutrophils, monocytes, or both neutrophils and monocytes; (ii) the denominator of the ratio comprises the level or amount of T cells, B cells, NK cells, or total lymphocytes; (iii) the numerator of the ratio comprises a neutrophil level or amount and the denominator of the ratio comprises a total lymphocyte level or amount; and / or (iv) the numerator of the ratio comprises the level or amount of monocytes and the denominator of the ratio comprises the level or amount of T cells; ratio, (b) the turnover frequency of at least one of the plurality of immune cell types, e.g., (i) the turnover comprises proliferation; or (ii) the turnover includes apoptosis; Frequency, and / or (c) the level of at least one cell type other than the immune cell type from which the DNA originates, e.g., (i) the method comprises capturing at least one set of epigenetic target regions that comprise sequence-independent differences in target regions in DNA originating from a cell type other than an immune cell type compared to the same target regions in DNA originating from all other cell types in the sample or sub-sample; and / or (ii) the cell type other than an immune cell type is not a blood cell type, e.g., the cell type other than an immune cell type is colorectal, lung, breast, prostate, skin, stomach, bladder, liver, ovary, pancreas, squamous epithelium, salivary gland, larynx, hypopharynx, nose, paranasal sinuses, nasopharynx, or kidney; level determining 13. A method according to any one of the immediately preceding claims.

8. Optionally, the sample is a sample obtained from a subject, and the amount of each of a plurality of immune cell types from which the DNA originates, or the level of each of a plurality of immune cell types from which the DNA originates, is determined by determining whether the subject is: (a) cancer or precancer, e.g. (i) the cancer is an immune cell type cancer, e.g., the cancer is a lymphocytic cancer, and / or the cancer is a leukemia, lymphoma, or myeloma; (ii) the cancer is a myeloid cancer; (iii) the cancer is a cancer of a cell or tissue type other than an immune cell type; (iv) the cancer or precancer is a cancer or precancer other than a hematological cancer or precancer, or the cancer or precancer is a solid tumor cancer, and optionally the solid tumor cancer is a carcinoma or sarcoma. (v) the cancer is colorectal cancer, lung cancer, breast cancer, prostate cancer, skin cancer, gastric cancer, bladder cancer, liver cancer, ovarian cancer, pancreatic cancer, head and neck cancer, or kidney cancer; (vi) the precancer is an adenoma, e.g., the adenoma is an advanced adenoma; or (vii) the precancer is colorectal precancer, lung precancer, breast precancer, prostate precancer, skin precancer, gastric precancer, bladder precancer, liver precancer, ovarian precancer, pancreatic precancer, head and neck precancer, or renal precancer; Cancer or precancerous (b) infectious disease, and / or (c) Graft rejection and optionally wherein the step of determining the amount of each of the plurality of immune cell types or the step of sequencing comprises generating a plurality of sequencing reads, the method further comprising the steps of mapping the plurality of sequence reads to one or more reference sequences to generate mapped sequence reads, and processing the mapped sequence reads to determine an indication of the likelihood that the subject has cancer, precancer, an infection, or transplant rejection.

13. A method according to any one of the immediately preceding claims.

9. wherein the sample is obtained from a subject who has previously been diagnosed with cancer and has undergone one or more previous cancer treatments, and optionally the sample is obtained at one or more preselected time points after the one or more previous cancer treatments, and the method optionally comprises: (a) determining a cancer recurrence score as an indication of a cancer recurrence status of the subject, optionally wherein the cancer recurrence status of the subject is indicated as being at risk of cancer recurrence if the Cancer Recurrence Score is determined to be at or above a pre-defined threshold, or the cancer recurrence status of the subject is indicated as being at lower risk of cancer recurrence if the Cancer Recurrence Score is below the pre-defined threshold, and optionally (b) comparing the subject's cancer recurrence score to a pre-defined cancer recurrence threshold as an indication that the subject is a candidate for a subsequent cancer treatment, wherein the subject is indicated as a candidate for a subsequent cancer treatment if the cancer recurrence score is above the cancer recurrence threshold, or is indicated as not a candidate for a subsequent cancer treatment if the cancer recurrence score is below the cancer recurrence threshold.

13. A method according to any one of the immediately preceding claims. (a) the modified cytosine is a methylcytosine; (b) the agent that recognizes the modified cytosine is a methyl-binding reagent, e.g., the methyl-binding reagent is an antibody, or the agent that recognizes the modified cytosine is a methyl-binding protein or comprises a methyl-binding domain, e.g., (i) the methyl-binding reagent specifically recognizes 5-methylcytosine, and / or (ii) the methyl-binding reagent is immobilized on a solid support; (c) the partitioning step comprises immunoprecipitation of methylated DNA; and / or (d) the partitioning step comprises partitioning based on binding to a protein; (i) optionally, the protein is a methylated protein, an acetylated protein, a non-methylated protein, a non-acetylated protein; and / or optionally, the protein is a histone; and / or (ii) optionally, the distributing step comprises contacting the DNA of the sample with a binding reagent specific for the protein, the binding reagent being immobilized on a solid support; 13. A method according to any one of the immediately preceding claims.

11. contacting at least one aliquot with a restriction enzyme prior to said capturing or sequencing, optionally with said contacting occurring after splitting said sample into said plurality of aliquots, e.g. (a) the restriction enzyme is an MDRE, e.g., the second aliquot is contacted with the MDRE; and / or (b) the restriction enzyme is a MSRE, e.g., the first aliquot is contacted with the MSRE; 13. A method according to any one of the immediately preceding claims.

12. (a) the method comprises the step of ligating an adapter to the DNA, thereby producing an adapter-ligated DNA, and optionally the adapter-ligated DNA is amplified prior to the sequencing step; and / or (b) the aliquots are pooled prior to the sequencing step; 13. A method according to any one of the immediately preceding claims.

13. The set of epigenetic target regions includes hypomethylated variable target regions that include DNA sequences that are differentially hypomethylated in a plurality of immune cell types, e.g., the DNA sequences that are differentially hypomethylated in a plurality of immune cell types include: (a) comprises a degree of methylation in at least one immune cell type that is detectably lower than the degree of methylation of the same sequence in any other immune cell type in the sample; (b) contains a degree of methylation in at least one immune cell type that is detectably lower than the degree of methylation of the same sequence in any other immune cell type; (c) contains a degree of methylation in one immune cell type that is detectably lower than the degree of methylation of the same sequence in any other immune cell type in the sample; (d) contains a degree of methylation in one immune cell type that is detectably lower than the degree of methylation of the same sequence in any other immune cell type; (e) comprises a detectably lower degree of methylation in at least one immune cell type than the degree of methylation of the same sequence in at least one other immune cell type and comprises a detectably lower degree of methylation than the degree of methylation of the same sequence in at least one non-immune cell type in said sample; or (f) comprising a detectably lower degree of methylation in at least one immune cell type than the degree of methylation of the same sequence in at least one other immune cell type and comprising a detectably lower degree of methylation than the degree of methylation of the same sequence in any non-immune cell type in said sample; For example, the detectably low degree of methylation is (i) one less methylated cytosine than the same sequence in the other cell type; (ii) two fewer methylated cytosines than the same sequence in the other cell type; (iii) three fewer methylated cytosines than the same sequence in the other cell type; (iv) 4 fewer methylated cytosines than the same sequence in the other cell type, or (v) 5 or fewer methylated cytosines than the same sequence in the other cell type. The method according to any one of claims 2 to 12, wherein

14. The set of epigenetic target regions includes hypermethylated variable target regions that include DNA sequences that are differentially hypermethylated in a plurality of immune cell types, e.g., the DNA sequences that are differentially hypermethylated in a plurality of immune cell types include: (a) contains a degree of methylation in at least one immune cell type that is detectably higher than the degree of methylation of the same sequence in any other immune cell type in the sample; (b) contains a degree of methylation in at least one immune cell type that is detectably higher than the degree of methylation of the same sequence in any other immune cell type; (c) contains a degree of methylation in one immune cell type that is detectably higher than the degree of methylation of the same sequence in any other immune cell type in the sample; (d) contains a degree of methylation in one immune cell type that is detectably higher than the degree of methylation of the same sequence in any other immune cell type; (e) comprises a degree of methylation in at least one immune cell type that is detectably higher than the degree of methylation of the same sequence in at least one other immune cell type and a degree of methylation that is detectably lower than the degree of methylation of the same sequence in at least one non-immune cell type in said sample; or (f) comprising a degree of methylation in at least one immune cell type that is detectably higher than the degree of methylation of the same sequence in at least one other immune cell type and a degree of methylation that is detectably lower than the degree of methylation of the same sequence in any non-immune cell type in the sample; For example, the detectably high degree of methylation is (i) one more cytosine methylation than the same sequence in the other cell type; (ii) two more cytosine methylations than the same sequence in the other cell type. (iii) three more cytosine methylations than the same sequence in the other cell type. (iv) four more cytosine methylations than the same sequence in the other cell type; or (v) 5 or more cytosine methylations than the same sequence in the other cell type. That is, The method according to any one of claims 2 to 13. (a) red blood cells or red blood cell precursors, and / or (b) Granule cells 2. The method of any one of the preceding claims, comprising determining the amount or detecting the level of DNA in the sample originating from.

16. 16. The method of any one of claims 13 to 15, wherein the detectably lower or higher degree of methylation is present in samples from at least one group of donors compared to another group of donors, optionally wherein the at least one group of donors has a cancer that responds to the treatment and the other group of donors has a cancer that does not respond to the treatment.

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