Methods, kits and systems for determining the transcriptional subtype of pancreatic cancer and methods for treating based on the same

Abstract

Methods and systems are provided for determining the transcriptional subtype of pancreatic cancer. In various embodiments, the present disclosure relates to the use of one or more histone modifications and / or chromatin accessibility that are characteristic of basal or classical transcriptional subtypes of pancreatic cancer. In some embodiments, differential modifications are detected and quantified at one or more genomic loci. In various embodiments, a determination of transcriptional subtype is useful, e.g., for identifying, selecting treatment for, and / or treating a subject having pancreatic cancer.

Description

Attorney Docket No.: DFS-34525 (DFCI 3605)METHODS, KITS AND SYSTEMS FOR DETERMINING THE TRANSCRIPTIONAL SUBTYPE OF PANCREATIC CANCER AND METHODS FOR TREATING BASED ON THE SAMECROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of priority to U. S. Application No. 63 / 777,458, filed March 25, 2025, the entire contents of which is incorporated herein by reference.BACKGROUND

[0002] Pancreatic cancer accounts for about 3% of all cancers in the United States and about 8% of all cancer deaths. Pancreatic cancer is predicted to become the second most common cause of cancer death by 2030. Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, accounting for more than 90 percent of pancreatic cancer diagnoses. Prognosis of PDAC relies mainly on clinical staging and histopathological assessment. Recently, two transcriptional subtypes of pancreatic cancer have been identified: a classical subtype and a basal subtype. The basal subtype is associated with higher rates of metastases, chemoresistance and poor outcomes.

[0003] Current subtyping methods rely on tissue biopsies, which may not capture subtype heterogeneity, and are difficult to implement clinically. Currently there is no approach to identify transcriptional subtypes of pancreatic cancer using plasma. There remains a need in the art for improved methods for determining the transcriptional subtype of pancreatic cancer.SUMMARY

[0004] The present disclosure is based, at least in part, on the demonstration that the basal / classical subtype status of a pancreatic cancer in a subject can be determined by detecting and quantifying the presence of histone modifications at one or more genomic loci in cell-free DNA (cfDNA) from a liquid biopsy sample, e.g., a plasma sample obtained or derived from the subject. The present disclosure also encompasses methods where chromatin accessibility is detected at the one or more genomic loci instead of (or in addition to) histone modifications.

[0005] The present disclosure includes, among other things, technologies for transcriptional subtyping of pancreatic cancer by epigenomic profiling. The present disclosure is based, at least in part, on the demonstration that the classical / basal subtype of a pancreatic cancer in a subject can be determined by detecting and quantifying the presence of histone modifications and / or chromatin accessibility at one or more genomic loci in cell-free DNA (cfDNA) from a liquid biopsy sample, e.g., a plasma sample obtained or derived from the subject.Attorney Docket No.: DFS-34525 (DFCI 3605)

[0006] The present disclosure includes, among other things, technologies for the determination of basal / classical subtype status and for the detection, monitoring, and / or treatment of pancreatic cancer based on basal / classical subtype status. In various embodiments, the present disclosure relates to the measurement of histone modifications in a sample obtained or derived from a subject to detect and / or treat pancreatic cancer based on basal / classical subtype status. The present disclosure includes, among other things, histone modification measurements in cell-free DNA (cfDNA) that are characteristic of pancreatic cancer, and which in various embodiments are useful, e.g., for detecting, monitoring, selecting treatment for, and / or treating pancreatic cancer based on basal / classical subtype status. The present disclosure includes, among other things, histone modification measurements in cfDNA that are characteristic of basal subtype pancreatic cancers, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and / or treating a basal subtype pancreatic cancer. The present disclosure includes, among other things, histone modification measurements in cfDNA that are characteristic of classical subtype pancreatic cancers, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and / or treating classical subtype pancreatic cancer. In various embodiments, the present disclosure includes exemplary genomic loci that are differentially modified in basal and classical subtypes of pancreatic cancer. In various embodiments, a genomic locus is differentially modified if it is characterized by increased or decreased histone modification as compared to a reference (e.g., a sample from a healthy subject, a sample from a subject with classical subtype pancreatic cancer, or a sample from a subject with basal subtype pancreatic cancer).

[0007] In some aspects, provided are methods of determining a classical / basal subtype of a pancreatic cancer in a subject, the method comprising quantifying, at one or more genomic loci in a biological sample obtained or derived from the subject: (i) one or more histone modifications, (ii) DNA methylation, and / or (iii) chromatin accessibility. In some embodiments, the sample comprises cell-free DNA (cfDNA) from a liquid biopsy sample.

[0008] In some aspects, provided are methods of determining if a subject has basal subtype pancreatic cancer, the method comprising quantifying, at one or more genomic loci in a biological sample obtained or derived from the subject: (i) one or more histone modifications, (ii) DNA methylation, and / or (iii) chromatin accessibility. In some embodiments, the sample comprises cell-free DNA (cfDNA) from a liquid biopsy sample.

[0009] In some embodiments, the one or more histone modifications are quantified using a histone modification assay that measures one or more of H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, H3K4me3, and pan-acetylation. In some embodiments, the histone modification assay detects H3K4me3 modifications. In some embodiments, the histone modification assay detects H3K27ac modifications.Attorney Docket No.: DFS-34525 (DFCI 3605)

[0010] In some embodiments, the histone modification assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT& RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT& Tag (Cleavage Under Targets and Tagmentation) sequencing.

[0011] In some embodiments, chromatin accessibility is quantified using a chromatin accessibility assay selected from ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde-Assisted Isolation of Regulatory Elements sequencing), MNase-seq (Micrococcal Nuclease digestion with sequencing), and a DNase hypersensitivity assay.

[0012] In some embodiments, the sample is blood, plasma, serum, or urine.

[0013] In some embodiments, the pancreatic cancer is pancreatic ductal adenocarcinoma (PDAC).

[0014] In some embodiments, the subject has previously been determined to have pancreatic cancer. In some embodiments, the subject has previously been determined to have PDAC.

[0015] In some embodiments, the subject is a mammal. In some embodiments, the subject is a human.

[0016] In some embodiments, quantification of one or more histone modifications and / or chromatin accessibility at the one or more genomic loci as compared to a reference indicates that the subject has a classical subtype pancreatic cancer. In some embodiments, the reference is a predetermined threshold, a measurement from a liquid biopsy sample, and / or a normalized value, optionally wherein the reference is a measurement from a liquid biopsy sample obtained from a cohort of subjects who have previously been determined to have a basal subtype pancreatic cancer (e.g., a basal subtype PDAC).

[0017] In some embodiments, quantification of one or more histone modifications and / or chromatin accessibility at the one or more genomic loci as compared to a reference indicates that the subject has a basal subtype pancreatic cancer. In some embodiments, the reference is a predetermined threshold, a measurement from a liquid biopsy sample, and / or a normalized value, optionally wherein the reference is a measurement from a liquid biopsy sample obtained from a cohort of subjects who have previously been determined to have classical subtype pancreatic cancer (e.g., a classical subtype PDAC).

[0018] In some embodiments, the method comprises quantifying one or more histone modifications and / or chromatin accessibility at one or more genomic loci in Tables 1-2. In some embodiments, the method comprises quantifying H3K4me3 modifications for at least 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200, 250, 300, 350, 400, 450, 500, 600, 700, 800, 900, 1000, 1500, 2000, or 2500 genomic loci identified in Table 1. In some embodiments, the method comprises quantifying H3K4me3 modifications for at least 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200,Attorney Docket No.: DFS-34525 (DFCI 3605)250, 300, 350, 400, 450, or 465 genomic loci identified in Table 1. In some embodiments, the method comprises quantifying H3K4me3 modifications for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1. In some embodiments, the method comprises quantifying H3K27ac modifications for at least 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200, 250, 300, 350, 400, 450, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 5500, 6000, 6500, 7000, 7500, 8000, 8500, 9000, 9500, 10000, 10500, 11000, 11500, 12000, 12500, 13000, 13500, 14000, 14500, 15000, 15500, 16000, 16500, 17000, 17500, 18000, 18500, 19000, 19500, 20000, 20500, 21000, 21500, or 21982 genomic loci in Table 2. In some embodiments, the method comprises quantifying H3K27ac modifications for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2.

[0019] In some embodiments, the method comprises quantifying DNA methylation for at least 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 260, 270, or 274 genomic loci in Table 3. In some embodiments, the method comprises quantifying DNA methylation for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 3.

[0020] In some embodiments, provided are methods of treating a subject having pancreatic cancer, the method comprising: administering a pancreatic cancer therapy to the subject based on the classical / basal status of the pancreatic cancer, wherein the classical / basal status of the pancreatic cancer has been determined using a method described herein. In some embodiments, the pancreatic cancer of the subject is PDAC.

[0021] In some aspects, provided are kits comprising reagents for determining histone modification at one or more genomic loci, wherein the one or more genomic loci are selected from Tables 1-2 and / or DNA methylation at one or more genomic loci from Table 3. In some embodiments, provided kits comprise reagents for quantifying H3K4me3 for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1. In some embodiments, provided kits comprise reagents for quantifying H3K27ac for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2. In some embodiments, provided kits comprise reagents for quantifying MeDIP for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 3

[0022] In some aspects, provided are kits comprising reagents for determining histone modification at one or more genomic loci, wherein the one or more genomic loci are selected from Tables 1-2. In some embodiments, provided kits comprise (i) reagents for quantifying H3K4me3 for at least 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200, 250, 300, 350, 400, 450, or 465 genomic loci in Table 1 and / or (ii) reagents for quantifying H3K27ac for at least 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200, 250, 300, 350, 400, 450, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 5500, 6000, 6500, 7000, 7500, 8000, 8500, 9000, 9500, 10000, 10500, 11000, 11500, 12000, 12500, 13000, 13500, 14000, 14500, 15000, 15500, 16000, 16500, 17000, 17500, 18000, 18500, 19000, 19500, 20000, 20500, 21000, 21500, or 21982 genomic loci in Table 2. In some embodiments, provided kits comprise (i) reagents for quantifying H3K4me3 for at least 5, 10,Attorney Docket No.: DFS-34525 (DFCI 3605)20, 30, 40, or 50 genomic loci in Table 1 and / or (ii) reagents for quantifying H3K27ac for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2. In some embodiments, provided kits comprise one or more antibodies for use in ChIP-seq. In some embodiments, the one or more antibodies specifically bind H3K4me3-modified histones or H3K27ac-modified histones. In some embodiments, provided kits comprise reagents for isolation of cell-free DNA (cfDNA) from a liquid biopsy sample. In some embodiments, provided kits comprise instructions for determining if a subject has basal or classical subtype of pancreatic cancer.

[0023] In further aspects, there are provided non-transitory computer readable storage media encoded with a computer program, wherein the program comprises instructions that when executed by one or more processors cause the one or more processors to perform operations to perform a method as described herein. In further aspects, there are provided computer systems comprising a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform operations to perform the method as described herein. In further aspects, there are provided systems for determining if a pancreatic cancer is classical or basal subtype in a subject, the system comprising a sequencer configured to generate a sequencing data set from a sample; and a non-transitory computer readable storage medium and / or a computer system as described herein.BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings included herein are for illustration purposes only and not for limitation.

[0025] FIG. 1 shows a schematic of an experimental framework for the epigenomic profiling ofPDAC PDX.

[0026] FIG. 2 shows representative epigenomic data from 3 classical and 3 basal-like PDAC PDX at classical associated (CLDN18, GATA6, HNFla) and basal-like associated (KRT6A, PTGES, SNAI2) loci.

[0027] FIGS. 3A-3E show unsupervised hierarchical clustering of classical subtype PDAC and basal subtype PDAC patient-derived xenografts (PDXs) for H3K27ac ChIP-seq (FIG. 3A), H3K4me3 ChIP-seq (FIG. 3B), ATAC-seq (FIG. 3C), MeDIP-seq (FIG. 3D), and H3K27me3 ChIP-seq (FIG. 3E) data.

[0028] FIGs. 4A-4D show that integrating multiple epigenomic analytes improves signal. FIG. 4A provides a Venn diagram showing the overlap of differential H3K27ac and open chromatin sites for classical and basal subtype PDAC PDX models. FIG. 4B and FIG. 4C show mean signal differences between basal and classical PDAC at classical-up sites (classical minus basal) and basal-up sites (basal minus classical), respectively. Columns from left to right depict mean signal difference for “intersection” sites (e.g., sites situated in the middle of the Venn diagram of FIG. 4A, which are both differentially H3K27ac and ATAC), ATAC-only sites, and H3K27ac-only sites. In some embodiments of any aspect described herein using genomic loci, intersection sites can be chosen (e.g.,Attorney Docket No.: DFS-34525 (DFCI 3605)exclusively chosen) to increase or maximize the separation as compared to sites that are not only differentially H3K27ac (but not differentially ATAC-seq) or differentially ATAC-seq (but not differentially H3K27ac). In some embodiments, genomic loci are used that have an |LFC| > 3 and FDR-q < 0.05 for a genomic modification of interest. In some embodiments, genomic loci are used that have an |LFC| > 3 and FDR-q < 0.01 for a genomic modification of interest. FIG. 4D provides boxplots showing signal at classical: basal-like (C: B) sites in an independent cohort of PDX (Wilcoxon rank-sum test).

[0029] FIG. 5 shows a schematic overview of the experimental approach to perform multianalyte epigenetic profiling of cell-free DNA from 1 mb of patient plasma.

[0030] FIG. 6A shows an integrated epigenomic signal at upregulated loci and comparison between classical subtype PDAC and basal subtype PDAC of human plasma samples. Panels from left to right show: H3K27ac (p=3.4x10-4), H3K4me3 (p=5x10-7), integration of the two were used to create an example PIES.

[0031] FIG. 6B shows from left to right: boxplot of H3K27ac cfChIP C: B ratio of aggregate signal at tissue-informed classical and basal-like specific enhancer-centric sites in plasma samples by PDAC subtype (Wilcoxon rank-sum test); boxplot showing H3K4me3 cfChIP aggregate signal at tissue-informed classical and basal-like specific promoter centric sites in plasma samples by PDAC subtype (Wilcoxon rank-sum test); and boxplot showing cfMeDIP C: B ratio aggregate signal at tissue-informed classical and basal-like DMRs in plasma samples by PDAC subtype (Wilcoxon ranksum test).

[0032] FIG. 7 shows a graph of True Positive Rate (TPR) vs False Positive Rate (FPR) of the model based on H3K27ac epigenomic loci, H3K4me3 epigenomic loci, and an integrated epigenomic score.

[0033] FIG 8 shows a framework to integrate epigenomic information and evaluate its performance.

[0034] FIG. 9A shows a boxplot comparing pancreatic integrated epigenomic scores for plasma samples of patients with classical and basal -like pancreatic cancer (Wilcoxon rank-sum test).

[0035] FIG. 9B shows a comparison of PIES (Plasma Integrated Epigenomic Scores) calculated using full and partial sets of informative loci. PIES were calculated for all plasma samples using the full set of differential loci (x-axis) and a partial high stringency set of loci (y-axis). Scores from the full set of loci (H3K27ac, H3K4me3 and MeDIP) correspond to the PIES scores shown in FIG. 9A. Scores from the high stringency subset of loci utilized only H3K27ac peaks that were significantly differential at high stringency (p < 1x10-8) recited in Table 2 in addition to the full set of differential H3K4me3 and MeDIP sites of Tables 1 and 3, respectively. Pearson correlation coefficient (R) and corresponding p-value are shown.Attorney Docket No.: DFS-34525 (DFCI 3605)

[0036] FIG. 10A shows area under the receiver operating characteristic (AUROC) curve for distinguishing classical and basal-like pancreatic cancer via cfDNA epigenomic profiles.

[0037] FIG. 10B shows area under the precision-recall curve (AUPRC) for distinguishing classical and basal-like pancreatic cancer via cfDNA epigenomic profiles.

[0038] FIG. 11 shows a forest plot for multivariable Cox proportional hazards regression model for progression-free survival of patients with metastatic PDAC. Bars represent the 95% CI.

[0039] FIGs. 12A-12F shows Kaplan-Meier curves of clinical outcomes stratified by circulating epigenomic and tissue transcriptomic PDAC subtypes across treatment regimens. FIG. 12A shows Kaplan-Meier curves of progression-free survival of patients with metastatic PDAC stratified by high and low PIES. FIG. 12B shows Kaplan-Meier curves of progression-free survival of patients with metastatic PDAC stratified by tissue transcriptomics subtypes. FIG. 12C shows Kaplan-Meier curves of progression-free survival of patients with metastatic PDAC receiving FOLFIRINOX (FFX) stratified by high and low PIES. FIG. 12D shows Kaplan-Meier curves of progression-free survival of patients with metastatic PDAC receiving FFX stratified by tissue transcriptomics subtypes. FIG. 12E shows Kaplan-Meier curves of progression-free survival of patients with metastatic PDAC with low PIES stratified by treatment regimen. FIG. 12F shows Kaplan-Meier curves of progression-free survival of patients with metastatic PDAC with basal -like subtype per tissue transcriptomics stratified by treatment regimen.DEFINITIONS

[0040] Unless otherwise defined, all terms of art, notations, and other scientific terms or terminology used herein are intended to have the meanings commonly understood by those of skill in the art to which this application pertains.

[0041] Further, nomenclature used herein is as commonly used in the art as can be seen by reference to, e.g., informatics.jax.org / mgihome / nomen / gene.shtml and genenames.org / .

[0042] As used herein, the following terms have the meanings as ascribed to them below, unless specified otherwise or obvious from context.

[0043] The term "or" is understood to be inclusive. Unless specifically stated or obvious from context, as used herein, the terms "a", "an", and "the" are understood to be singular or plural.

[0044] About: The term “about” is understood as within a range of normal tolerance in the art, for example within 2 standard deviations of the mean. “About” may be understood as within 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, 0.5%, 0.1%, 0.05%, or 0.01% of the stated value. All numerical values provided herein are modified by the term about. Ranges provided herein are understood to be shorthand for all values within the range, including fractions / decimals. For example,Attorney Docket No.: DFS-34525 (DFCI 3605)a range of 1 to 50 is understood to include any number, combination of numbers, or sub-range from the group consisting of 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, or 50. In addition, the term applies to each numerical value within a listed range of values (e.g., “at least 1, 2, or 3” means “at least 1, at least 2, or at least 3”).

[0045] “Accessibility Status” or “Chromatin Accessibility Status”: As used herein, “accessibility status” or “chromatin accessibility status” of a genomic locus refers to the frequency with which DNA sequences corresponding to the genomic locus are identified in an assay for detection of accessible chromatin. Accessibility status can be determined by various assays known in the art, including without limitation ChIP-seq as one example. Where two samples are separately analyzed by the same assay or comparable assays for detection of accessible DNA sequences, differences in chromatin accessibility status of genomic loci can be detected. Accessibility status can be compared to a standard or reference. A sample that has an accessibility status that differs in accessibility status from a standard or reference can be referred to as differentially modified. Suitable assays for determining chromatin accessibility are known in the art. Exemplary assays include ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde-Assisted Isolation of Regulatory Elements sequencing), MNase-seq (Micrococcal Nuclease digestion with sequencing), and / or a DNase hypersensitivity assay.

[0046] Administration: As used herein, the term “administration” refers to the act of the attending physician or caregiver, prescribing the agent for administration and thereby causing the application of an agent to a subject, through ingestion, infusion, injection, or any other means, whether self-administered or administered by a clinician or other qualified care giver

[0047] Agent: As used herein, the term “agent” may refer to any chemical entity, including without limitation any of one or more of an atom, molecule, compound, amino acid, polypeptide, nucleotide, nucleic acid, protein, protein complex, liquid, solution, saccharide, polysaccharide, lipid, or combination or complex thereof.

[0048] Antibody: As used herein, the term “antibody” refers to a polypeptide that includes one or more canonical immunoglobulin sequence elements sufficient to confer specific binding to a particular antigen (e.g., a heavy chain variable domain, a light chain variable domain, and / or one or more CDRs). Thus, the term antibody includes, without limitation, human antibodies, non-human antibodies, synthetic and / or engineered antibodies, fragments thereof, and agents including the same. Antibodies can be naturally occurring immunoglobulins (e.g., generated by an organism reacting to an antigen). Synthetic, non-naturally occurring, or engineered antibodies can be produced by recombinant engineering, chemical synthesis, or other artificial systems or methodologies known to those of skill in the art.Attorney Docket No.: DFS-34525 (DFCI 3605)

[0049] As is well known in the art, typical human immunoglobulins are approximately 150 kD tetrameric agents that include two identical heavy (H) chain polypeptides (about 50 kD each) and two identical light (L) chain polypeptides (about 25 kD each) that associate with each other to form a structure commonly referred to as a “Y-shaped” structure. Typically, each heavy chain includes a heavy chain variable domain (VH) and a heavy chain constant domain (CH). The heavy chain constant domain includes three CH domains: CHI, CH2 and CH3. A short region, known as the “switch”, connects the heavy chain variable and constant regions. The “hinge” connects CH2 and CH3 domains to the rest of the immunoglobulin. Each light chain includes a light chain variable domain (VL) and a light chain constant domain (CL), separated from one another by another “switch.” Each variable domain contains three hypervariable loops known as “complement determining regions” (CDR1, CDR2, and CDR3) and four somewhat invariant “framework” regions (FR1, FR2, FR3, and FR4). In each VH and VL, the three CDRs and four FRs are arranged from amino-terminus to carboxy-terminus in the following order: FR1, CDR1, FR2, CDR2, FR3, CDR3, and FR4. The variable regions of a heavy and / or a light chain are typically understood to provide a binding moiety that can interact with an antigen. Constant domains can mediate binding of an antibody to various immune system cells (e.g., effector cells and / or cells that mediate cytotoxicity), receptors, and elements of the complement system. Heavy and light chains are linked to one another by a single disulfide bond, and two other disulfide bonds connect the heavy chain hinge regions to one another, so that the dimers are connected to one another and the tetramer is formed. When natural immunoglobulins fold, the FR regions form the beta sheets that provide the structural framework for the domains, and the CDR loop regions from both the heavy and light chains are brought together in three-dimensional space so that they create a single hypervariable antigen binding site located at the tip of the Y structure.

[0050] In some embodiments, an antibody is a polyclonal, monoclonal, monospecific, or multispecific antibody (e.g., a bispecific antibody). In some embodiments, an antibody includes at least one light chain monomer or dimer, at least one heavy chain monomer or dimer, at least one heavy chain-light chain dimer, or a tetramer that includes two heavy chain monomers and two light chain monomers. Moreover, the term “antibody” can include (unless otherwise stated or clear from context) any art-known constructs or formats utilizing antibody structural and / or functional features including without limitation intrabodies, domain antibodies, antibody mimetics, Zybodies®, Fab fragments, Fab’ fragments, F(ab’)2 fragments, Fd’ fragments, Fd fragments, isolated CDRs or sets thereof, single chain antibodies, single-chain Fvs (scFvs), disulfide-linked Fvs (sdFv), polypeptide-Fc fusions, single domain antibodies (e.g., shark single domain antibodies such as IgNAR or fragments thereof), cameloid antibodies, camelized antibodies, masked antibodies (e.g., Probodies®), affybodies, anti -idiotypic (anti -Id) antibodies (including, e.g., anti-anti -Id antibodies), Small Modular ImmunoPharmaceuticals (SMIPs), single chain or Tandem diabodies (TandAb®), VHHs, Anticalins®,Attorney Docket No.: DFS-34525 (DFCI 3605)Nanobodies®, minibodies, BiTE®s, ankyrin repeat proteins or DARPINs®, Avimers®, DARTs, TCR-like antibodies, Adnectins®, Affilins®, Trans-bodies®, Affibodies®, TrimerX®, MicroProteins, Fynomers®, Centyrins®, KALBITOR®s, CARs, engineered TCRs, and antigen-binding fragments of any of the above.

[0051] In various embodiments, an antibody includes one or more structural elements recognized by those skilled in the art as a complementarity determining region (CDR) or variable domain. In some embodiments, an antibody can be a covalently modified (“conjugated”) antibody (e.g., an antibody that includes a polypeptide including one or more canonical immunoglobulin sequence elements sufficient to confer specific binding to a particular antigen, where the polypeptide is covalently linked with one or more of a therapeutic agent, a detectable moiety, another polypeptide, a glycan, or a polyethylene glycol molecule). In some embodiments, antibody sequence elements are humanized, primatized, chimeric, etc., as is known in the art.

[0052] An antibody including a heavy chain constant domain can be, without limitation, an antibody of any known class, including but not limited to, IgA, secretory IgA, IgG, IgE and IgM, based on heavy chain constant domain amino acid sequence (e.g., alpha (a), delta (5), epsilon (a), gamma (y) and mu (p)). IgG subclasses are also well known to those in the art and include but are not limited to human IgGl, IgG2, IgG3 and IgG4. “Isotype” refers to the Ab class or subclass (e.g., IgM or IgGl) that is encoded by the heavy chain constant region genes. As used herein, a “light chain” can be of a distinct type, e.g., kappa (K) or lambda (X), based on the amino acid sequence of the light chain constant domain. In some embodiments, an antibody has constant region sequences that are characteristic of mouse, rabbit, primate, or human immunoglobulins. Naturally-produced immunoglobulins are glycosylated, typically on the CH2 domain. As is known in the art, affinity and / or other binding attributes of Fc regions for Fc receptors can be modulated through glycosylation or other modification. In some embodiments, an antibody may lack a covalent modification (e.g., attachment of a glycan) that it would have if produced naturally. In some embodiments, antibodies produced and / or utilized in accordance with the present disclosure include glycosylated Fc domains, including Fc domains with modified or engineered such glycosylation.

[0053] Antibody fragment: As used herein, an “antibody fragment” refers to a portion of an antibody or antibody agent as described herein, and typically refers to a portion that includes an antigen-binding portion or variable region thereof. An antibody fragment can be produced by any means. For example, in some embodiments, an antibody fragment can be enzymatically or chemically produced by fragmentation of an intact antibody or antibody agent. Alternatively, in some embodiments, an antibody fragment can be recombinantly produced (i.e., by expression of an engineered nucleic acid sequence. In some embodiments, an antibody fragment can be wholly or partially synthetically produced. In some embodiments, an antibody fragment (particularly an antigenbinding antibody fragment) can have a length of at least about 50, 60, 70, 80, 90, 100, 110, 120, 130,Attorney Docket No.: DFS-34525 (DFCI 3605)140, 150, 160, 170, 180, 190 amino acids or more, in some embodiments at least about 200 amino acids.

[0054] Associated with: Two events or entities are “associated” with one another, as that term is used herein, if the presence, level and / or form of one is correlated with that of the other. For example, a particular entity (e.g., an epigenetic profde comprising one or more histone modifications at a set of genomic loci, etc.) is considered to be associated with a particular disease, disorder, or condition, if its presence, level and / or form correlates with incidence of and / or susceptibility to the disease, disorder, or condition (e.g., across a relevant population). In some embodiments, two or more entities are physically “associated” with one another if they interact, directly or indirectly, so that they are and / or remain in physical proximity with one another. In some embodiments, two or more entities that are physically associated with one another are covalently linked to one another; in some embodiments, two or more entities that are physically associated with one another are not covalently linked to one another but are non-covalently associated, for example by means of hydrogen bonds, van der Waals interaction, hydrophobic interactions, magnetism, or a combination thereof.

[0055] “Between” or “From”: As used herein, the term “between” refers to content that falls between indicated upper and lower, or first and second, boundaries, inclusive of the boundaries. Similarly, the term “from”, when used in the context of a range of values, indicates that the range includes content that falls between indicated upper and lower, or first and second, boundaries, inclusive of the boundaries.

[0056] Biological Sample: As used herein, the term “biological sample” typically refers to a sample obtained or derived from a biological source (e.g., a tissue or organism or cell) of interest, as described herein. In some embodiments, a biological source is or includes an organism, such as a human subject. In some embodiments, a biological sample is or includes a biological tissue or fluid. In some embodiments, a biological sample can be or include cells, tissue, or bodily fluid. “Bodily fluids” refer to fluids that are excreted or secreted from the body as well as fluids that are normally not (e.g., blood, serum, plasma, Cowper’s fluid or pre-ejaculate fluid, chyle, chyme, stool, interstitial fluid, intracellular fluid, lymph, menses, saliva, sebum, semen, serum, sweat, synovial fluid, tears, urine, vitreous humor, vomit). In some embodiments, a biological sample can be or include blood, blood components, cell-free DNA (cfDNA), circulating-tumor DNA (ctDNA), ascites, biopsy samples, surgical specimens, cell-containing body fluids, sputum, saliva, feces, urine, cerebrospinal fluid, peritoneal fluid, pleural fluid, lymph, gynecological fluids, secretions, excretions, skin swabs, vaginal swabs, oral swabs, nasal swabs, washings or lavages such as a ductal lavages or bronchoalveolar lavages, aspirates, scrapings, or bone marrow. In some embodiments, a biological sample is a liquid biopsy sample obtained from a bodily fluid. In some embodiments, a biological sample is or includes DNA obtained from a single subject or from a plurality of subjects. A biological sample can be a “primary sample” obtained directly from a biological source or can be a “processed sample”, i.e., aAttorney Docket No.: DFS-34525 (DFCI 3605)sample that was derived from a primary sample, e.g., via dilution, purification, mixing with one or more reagents, or any other processing step(s) as described herein. A biological sample can also be referred to as a “sample.”

[0057] Blood component: As used herein, the term “blood component” refers to any component of whole blood, including red blood cells, white blood cells, plasma, platelets, endothelial cells, mesothelial cells, epithelial cells, and cell-free DNA. Blood components also include the components of plasma, including proteins, metabolites, lipids, nucleic acids, and carbohydrates, and any other cells that can be present in blood, e.g. due to pregnancy, organ transplant, infection, injury, or disease.

[0058] Cancer: As used herein, the terms “cancer,” “malignancy,” “tumor,” and “carcinoma,” are used interchangeably to refer to a disease, disorder, or condition in which cells exhibit or exhibited relatively abnormal, uncontrolled, and / or autonomous growth, so that they display or displayed an abnormally elevated proliferation rate and / or aberrant growth phenotype. In some embodiments, a cancer can include one or more tumors. In some embodiments, a cancer can be or include cells that are precancerous (e.g., benign), malignant, pre-metastatic, metastatic, and / or non-metastatic. In some embodiments, a cancer can be or include a solid tumor. In some embodiments, a cancer is or includes a pancreatic cancer. In some embodiments, a cancer can be associated with classical or basal status (e.g., a pancreatic cancer with a classical or basal transcriptional subtype).

[0059] Combination therapy: As used herein, the term “combination therapy” refers to administration to a subject of to two or more agents or regimens such that the two or more agents or regimens together treat a disease, condition, or disorder of the subject. In some embodiments, the two or more therapeutic agents or regimens can be administered simultaneously, sequentially, or in overlapping dosing regimens. Those of skill in the art will appreciate that combination therapy includes but does not require that the two agents or regimens be administered together in a single composition, nor at the same time.

[0060] Corresponding to: As used herein, the term “corresponding to” may be used to designate the position / identity of a structural element in a compound or composition through comparison with an appropriate reference compound or composition. For example, in some embodiments, a monomeric residue in a polymer (e.g., an amino acid residue in a polypeptide or a nucleic acid residue in a polynucleotide) may be identified as “corresponding to” a residue in an appropriate reference polymer. For example, those of skill in the art appreciate that residues in a provided polypeptide or polynucleotide sequence are often designated (e.g., numbered or labeled) according to the scheme of a related reference sequence (even if, e.g., such designation does not reflect literal numbering of the provided sequence). By way of illustration, if a reference sequence includes a particular amino acid motif at positions 100-110, and a second related sequence includes the same motif at positions 110-120, the motif positions of the second related sequence can be said toAttorney Docket No.: DFS-34525 (DFCI 3605)“correspond to” positions 100-110 of the reference sequence. Those of skill in the art appreciate that corresponding positions can be readily identified, e.g., by alignment of sequences, and that such alignment is commonly accomplished by any of a variety of known tools, strategies, and / or algorithms, including without limitation software programs such as, for example, BLAST, CS-BLAST, CUDASW++, DIAMOND, FASTA, GGSEARCH / GLSEARCH, Genoogle, HMMER, HHpred / HHsearch, IDF, Infernal, KLAST, USEARCH, parasail, PSI-BLAST, PSI-Search, ScalaBLAST, Sequilab, SAM, SSEARCH, SWAPHI, SWAPHI-LS, SWIMM, or SWIPE. Two sequences can be identified as corresponding if they are identical or if they share substantial identity, e.g., at least 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% identity, e.g., over a length of at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500 or more residues. In various embodiments, a nucleic acid sequence can correspond to a sequence that is identical or substantially identical (e.g., at least 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% identical) to the complement of the nucleic acid sequence, e.g., over a length of at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500 or more nucleic acid residues.

[0061] “Diagnosing”, “Detecting”, “Determining” or “Screening for”: As used herein, “diagnosing”, “detecting”, “determining”, “screening for” the presence of a condition or disease (e.g., pancreatic cancer of classical or basal transcriptional subtype), or a related state (e.g., responsiveness of pancreatic cancer to one or more therapies) includes the act, process, and / or outcome of determining whether, and / or the qualitative of quantitative probability that, a subject has or will develop the condition, disease, or related state. In some instances, diagnosing can include a determination relating to prognosis and / or likely response to one or more general or particular therapeutic agents or regimens.

[0062] Differentially accessible: As used herein, the term “differentially accessible” describes a genomic locus for which chromatin accessibility status differs between a first condition or sample and a second condition or sample (e.g., a standard or reference). A differentially accessible genomic locus can include a greater or smaller measured accessibility under a selected condition of interest as compared to a reference state.

[0063] Differentially modified: As used herein, the term “differentially modified” describes a genomic locus for which histone modification status and / or chromatin accessibility status differs between a first condition or sample and a second condition or sample (e.g., a standard or reference). A differentially modified genomic locus can include a greater or smaller number or frequency of histone modification(s) and / or chromatin accessibility under a selected condition of interest, such as basal subtype of pancreatic cancer, as compared a reference state, such as classical subtype of pancreatic cancer.

[0064] Identity: As used herein, the term “identity” refers to the overall relatedness between polymeric molecules, e.g., between nucleic acid molecules (e.g., DNA molecules) and / or betweenAttorney Docket No.: DFS-34525 (DFCI 3605)polypeptide molecules. Methods for the calculation of a percent identity as between two provided sequences are known in the art. The term “% sequence identity” refers to a relationship between two or more sequences, as determined by comparing the sequences. In the art, “identity” also means the degree of sequence relatedness between protein and nucleic acid sequences as determined by the match between strings of such sequences. “Identity” (often referred to as “similarity”) can be readily calculated by known methods, including those described in: Computational Molecular Biology (Lesk, A. M. ed.) Oxford University Press, NY (1988); Biocomputing: Informatics and Genome Projects (Smith, D. W. ed.) Academic Press, NY (1994); Computer Analysis of Sequence Data, Part I (Griffin, A. M. and Griffin, H. G. eds.) Humana Press, NJ (1994); Sequence Analysis in Molecular Biology (Von Heijne, G. ed.) Academic Press (1987); and Sequence Analysis Primer (Gribskov, M. and Devereux, J. eds.) Oxford University Press, NY (1992), each of which are separately incorporated by reference in their entirety. Preferred methods to determine identity are designed to give the best match between the sequences tested. Methods to determine identity and similarity are codified in publicly available computer programs. For example, calculation of the percent identity of two nucleic acid or polypeptide sequences can be performed by aligning the two sequences (or the complement of one or both sequences) for optimal comparison purposes (e.g., gaps can be introduced in one or both of a first and a second sequences for optimal alignment and non-identical sequences can be disregarded for comparison purposes). The nucleotides or amino acids at corresponding positions are then compared. When a position in the first sequence is occupied by the same residue (e.g., nucleotide or amino acid) as the corresponding position in the second sequence, then the molecules are identical at that position. The percent identity between the two sequences is a function of the number of identical positions shared by the sequences, optionally accounting for the number of gaps, and the length of each gap, which may need to be introduced for optimal alignment of the two sequences. The comparison of sequences and determination of percent identity between two sequences can be accomplished using a computational algorithm, such as BLAST (basic local alignment search tool). Sequence alignments and percent identity calculations may be performed using the Megalign program of the LASERGENE bioinformatics computing suite (DNASTAR, Inc., Madison, Wisconsin). Multiple alignment of the sequences can also be performed using the Clustal method of alignment (Higgins and Sharp, Comp Appl Biosci (1989) 5(2): 151-153), incorporated by reference herein in its entirety, with default parameters (GAP PENALTY=10, GAP LENGTH PENALTY=10). Relevant programs also include the GCG suite of programs (Wisconsin Package Version 9.0, Genetics Computer Group (GCG), Madison, Wisconsin); BLASTP, BLASTN, BLASTX (Altschul et al., J Mol Biol (1990) 215:403-410); DNASTAR (DNASTAR, Inc., Madison, Wisconsin); and the FASTA program incorporating the Smith-Waterman algorithm (Pearson, Comput Methods Genome Res [Proc Int Symp] (1994), Meeting Date 1992, 111-120. Eds. Suhai, Sandor. Plenum, New York, NY (the contents of each of which is separately incorporated herein by reference in its entirety). Within the context of thisAttorney Docket No.: DFS-34525 (DFCI 3605)disclosure, it will be understood that where sequence analysis software is used for analysis, the results of the analysis are based on the “default values” of the program referenced. “Default values” will mean any set of values or parameters, which originally load with the software when first initialized.

[0065] “ Improve" “increase" “inhibit" or “reduce": As used herein, the terms “improve”, “increase”, “inhibit”, and “reduce”, and grammatical equivalents thereof, indicate qualitative or quantitative difference from a reference.

[0066] Methylation Status: As used herein, “methylation status” of a genomic locus refers to the frequency with which DNA sequences corresponding to the genomic locus are identified in an assay for detection of DNA methylated sequences and / or the density (e.g., the measured density) of DNA methylation corresponding to the genomic locus. Methylation status can be determined by various assays known in the art, including without limitation Bisulfite sequencing (BS-Seq), Whole Genome Bisulfite Sequencing (WGBS), Methylated DNA ImmunoPrecipitation sequencing (MeDIP-seq), or Methyl-CpG-Binding Domain sequencing (MBD-seq). Where two samples are separately analyzed by the same assay or comparable assays for detection of DNA methylated sequences, differences in methylation status of genomic loci can be detected. Methylation status can be compared to a standard or reference. A sample that has a methylation status that differs from a standard or reference can be referred to as differentially modified.

[0067] Modification Status or Histone Modification Status: As used herein, “modification status” or “histone modification status” of a genomic locus refers to the frequency with which DNA sequences corresponding to the genomic locus are identified in an assay for detection of DNA sequences associated with histones bearing one or more histone modifications (e.g., one or more particular histone modifications) and / or the density (e.g., the measured density) of histone modifications (e.g., one or more particular histone modifications) corresponding to the genomic locus. Modification status can be determined by various assays known in the art, including without limitation CHiP-seq as one example. Other well-known assays include CUT& RUN (Cleavage Under Targets and Release Using Nuclease) sequencing and CUT& Tag (Cleavage Under Targets and Tagmentation). Where two samples are separately analyzed by the same assay or comparable assays for detection of DNA sequences associated with histones bearing one or more histone modifications (e.g., one or more particular histone modifications), differences in modification status of genomic loci can be detected. Modification status can be compared to a standard or reference. A sample that has a modification status that differs in modification status or histone modification status from a standard or reference can be referred to as differentially modified.

[0068] Regulatory sequence: As used herein in the context of expression of a nucleic acid coding sequence, a regulatory sequence is a nucleic acid sequence that controls expression of a coding sequence. In some embodiments, a regulatory sequence can control or impact one or more aspects of gene expression (e.g. cell-type-specific expression, inducible expression, etc.).Attorney Docket No.: DFS-34525 (DFCI 3605)

[0069] Subject: As used herein, the term “subject” refers to an organism, typically a mammal (e.g. a human). In some embodiments, a subject is suffering from a disease, disorder or condition (e.g., pancreatic cancer). In some embodiments, a subject is susceptible to a disease, disorder, or condition. In some embodiments, a subject displays one or more symptoms or characteristics of a disease, disorder or condition. In some embodiments, a subject is not suffering from a disease, disorder or condition. In some embodiments, a subject does not display any symptom or characteristic of a disease, disorder, or condition. In some embodiments, a subject has one or more features characteristic of susceptibility to or risk of a disease, disorder, or condition. In some embodiments, a subject is a subject that has been tested for a disease, disorder, or condition, and / or to whom therapy has been administered. The terms "subject" and “patient” are used interchangeably herein and indicate a human.

[0070] Therapeutic agent: As used herein, the term “therapeutic agent” refers to any agent that elicits a desired pharmacological effect when administered to a subject. In some embodiments, an agent is considered to be a therapeutic agent if it demonstrates a statistically significant effect across an appropriate population. In some embodiments, the appropriate population can be a population of model organisms or a human population. In some embodiments, an appropriate population can be defined by various criteria, such as a certain age group, gender, genetic background, preexisting clinical conditions, etc. In some embodiments, a therapeutic agent is a substance that can be used for treatment of a disease, disorder, or condition (e.g., pancreatic cancer). In some embodiments, a therapeutic agent is an agent that has been or is required to be approved by a government agency before it can be marketed for administration to humans. In some embodiments, a therapeutic agent is an agent for which a medical prescription is required for administration to humans.

[0071] Therapeutically effective amount: As used herein, “therapeutically effective amount” refers to an amount that produces the desired effect for which it is administered. In some embodiments, the term refers to an amount that is sufficient, when administered to a population suffering from or susceptible to a disease, disorder, and / or condition (e.g., pancreatic cancer) in accordance with a therapeutic dosing regimen, to treat the disease, disorder, and / or condition. In some embodiments, a therapeutically effective amount is one that reduces the incidence and / or severity of, and / or delays onset of, one or more symptoms of the disease, disorder, and / or condition. Those of ordinary skill in the art will appreciate that the term “therapeutically effective amount” does not in fact require successful treatment be achieved in a particular individual. Rather, a therapeutically effective amount may be that amount that provides a particular desired pharmacological response in a significant number of subjects when administered to patients in need of such treatment. In some embodiments, reference to a therapeutically effective amount may be a reference to an amount as measured in one or more specific tissues (e.g., a tissue affected by the disease, disorder or condition) or fluids (e.g., blood, saliva, serum, sweat, tears, urine, etc.). Those of ordinary skill in the art willAttorney Docket No.: DFS-34525 (DFCI 3605)appreciate that, in some embodiments, a therapeutically effective amount of a particular agent or therapy may be formulated and / or administered in a single dose. In some embodiments, a therapeutically effective amount of a particular agent or therapy may be formulated and / or administered in a plurality of doses, for example, as part of a dosing regimen.Treatment: As used herein, the term “treatment” (also “treat” or “treating”) refers to administration of a therapy that partially or completely alleviates, ameliorates, relieves, inhibits, delays onset of, reduces severity of, and / or reduces incidence of one or more symptoms, features, and / or causes of a particular disease, disorder, or condition, or is administered for the purpose of achieving any such result. In some embodiments, such treatment can be of a subject who does not exhibit signs of the relevant disease, disorder, or condition and / or of a subject who exhibits only early signs of the disease, disorder, or condition (e.g., pancreatic cancer). Alternatively, or additionally, such treatment can be of a subject who exhibits one or more established signs of the relevant disease, disorder and / or condition. In some embodiments, treatment can be of a subject who has been diagnosed as suffering from the relevant disease, disorder, and / or condition. In some embodiments, treatment can be of a subject known to have one or more susceptibility factors that are statistically correlated with increased risk of development of the relevant disease, disorder, or condition. A “prophylactic treatment” includes a treatment administered to a subject who does not display signs or symptoms of a condition to be treated or displays only early signs or symptoms of the condition to be treated such that treatment is administered for the purpose of diminishing, preventing, or decreasing the risk of developing the condition. Thus, a prophylactic treatment functions as a preventive treatment against a condition. A “therapeutic treatment” includes a treatment administered to a subject who displays symptoms or signs of a condition and is administered to the subject for the purpose of reducing the severity or progression of the condition.DETAILED DESCRIPTION

[0072] Pancreatic cancer has two major transcriptional subtypes: classical and basal. The classical and basal subtypes are clinically highly prognostic; the basal subtype has poor prognosis and worse overall survival. In addition, these transcriptional subtypes may be predictive of response to therapies (e.g., chemotherapy, targeted therapy, etc.). Methods for basal / classical subtyping of pancreatic cancer typically involve performing tissue-based testing with bulk RNA sequencing or candidate marker protein expression. The present disclosure encompasses a recognition that current subtyping approaches that rely on tissue biopsy, are challenging to implement in clinical practice, and are limited by tumor heterogeneity and sampling error. Currently, there is no approach to identify transcriptional subtypes of pancreatic cancer using plasma.

[0073] The present disclosure demonstrates, inter alia, that classical subtype or basal subtype of pancreatic cancer (e.g., PDAC) in a subject can be determined by detecting and quantifying theAttorney Docket No.: DFS-34525 (DFCI 3605)presence of histone modifications at one or more genomic loci in cell-free DNA (cfDNA) from a liquid biopsy sample, e.g., a plasma sample obtained or derived from the subject.

[0074] As described at least in the Examples below, by performing CHIP-seq on PDX models, the present disclosure identified key regions in the genome which can identify these two transcriptional subtypes. The ability to discriminate the two subtypes using plasma samples was also validated by performing circulating tumor DNA chip seq of one or more histone modifications (e.g., H3K27Ac, H3K4me3, MeDIP) and comparing signal on these unique subtype specific sites in the genome. This represents the first epigenomic characterization of transcriptional subtype of pancreatic cancer (e.g., PDAC) from patient plasma.

[0075] The Examples below demonstrate that epigenomic signatures of pancreatic cancer (e.g., PDAC) can identify classical / basal subtype from plasma epigenomic profiling in a multi-institutional cohort of patients with metastatic PDAC and integrate information from circulating histone modifications and DNA methylation to develop a Pancreatic Integrated Epigenomic Score (PIES). PIES is concordant with tissue-based labels and captures transcriptional subtype heterogeneity observed within biopsies. Furthermore, it improves prognostication over tissue-based subtyping suggestive of the recovery of ground truth tumor biology from plasma ctDNA.

[0076] The present disclosure describes a new non-invasive approach for PDAC subtyping using circulating tumor DNA (ctDNA) epigenomic profiling. The present disclosure recognizes that provided non-invasive approaches for determining classical / basal subtypes of pancreatic cancer (e.g., PDAC) using ctDNA chromatin epigenomic profiling may facilitate rapid and broad adoption of transcriptional subtyping for clinical use. In addition, provided non-invasive approaches may better capture the heterogeneity in the system.Pancreatic Cancer

[0077] Pancreatic cancer is one of the leading causes for cancer-related deaths in the United States. Pancreatic ductal adenocarcinoma (PDAC) is the third overall leading cause for cancer-related mortality in the US. The vast majority of pancreatic cancers (>90%) are PDAC. The prognosis of patients with PDAC remains poor, with a median survival of less than one year. This poor prognosis is believed to be largely due to the majority of diagnoses occurring at an advanced stage, development of early therapeutic resistance, and the lack of reliable biomarkers to inform treatment decisions.

[0078] There are also other, less common pancreatic cancers include, but are not limited to, pancreatic adenosquamous carcinomas, pancreatic squamous cell carcinomas, pancreatic signet ring cell carcinomas, pancreatic acinar cell carcinomas, undifferentiated pancreatic carcinomas, undifferentiated pancreatic carcinomas with giant cells, pancreatic islet cell tumors, and pancreatic neuroendocrine tumors.Attorney Docket No.: DFS-34525 (DFCI 3605)

[0079] In some embodiments, a pancreatic cancer is a pancreatic exocrine tumor (e.g., PDAC, pancreatic adenosquamous carcinoma, pancreatic squamous cell carcinoma, pancreatic acinar cell carcinoma, etc.). In some embodiments, a pancreatic cancer is PDAC.

[0080] The poor prognosis associated with pancreatic cancer is attributable to its early systemic spread and aggressive local growth. Nearly 50-60% of PDAC patients present with distant metastatic disease, 25-30% with regional disease and only 10-15% of patients present with local disease. Patients with locally advanced or metastatic PDAC are generally considered non-curative and managed with palliative intent.

[0081] Various means of detecting and / diagnosing pancreatic cancer are known in the art. These include imaging tests (e.g., ultrasound, computed tomography (CT) scan, magnetic resonance imaging (MRI) scan, positron emission tomography (PET) scan, etc.), endoscopic ultrasound (EUS), pancreatic biopsy, blood tests (e.g., CA19-9 marker), and others.

[0082] Physical symptoms of pancreatic cancer may include jaundice, light-colored stools, dark urine, pain in the upper or middle abdomen and back, weight loss for no known reason, loss of appetite, fatigue.

[0083] Despite extensive genomic characterization of pancreatic ductal adenocarcinoma (PDAC), most pancreatic cancers do not harbor therapeutically tractable alterations. However, transcriptional subtypes from bulk measurements have emerged as an important clinical biomarker.Subtypes of Pancreatic Cancer

[0084] Classical and basal transcriptional subtypes of pancreatic cancer were first described in Moffitt RA, et al. Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma. Nat Genet. 2015 Oct;47(10): 1168-78, the entire contents of which are incorporated herein by reference.

[0085] Classical and basal transcriptional subtypes are key prognostic biomarkers of pancreatic cancers such as, e.g., pancreatic ductal adenocarcinoma (PDAC). The basal subtype is associated with higher rates of metastases, chemoresistance and poor outcomes. See Raghavan S, et al. Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer. Cell. 2021 Dec 9;184(25):6119-6137.e26.

[0086] Current methods for performing tissue-based testing with bulk RNA sequencing or candidate marker protein expression. Multiplex immunofluorescence (mIF) methods that quantify protein expression of six PDAC subtype markers (CLDN18.2, TFF1, GATA6, KRT17, KRT5, and S100A2) have been used to assess classical / basal subtypes. See Williams HL, et al. Spatially Resolved Single-Cell Assessment of Pancreatic Cancer Expression Subtypes Reveals Co-expressor Phenotypes and Extensive Intratumoral Heterogeneity. Cancer Res. 2023 Feb 3;83(3):441-455. TheseAttorney Docket No.: DFS-34525 (DFCI 3605)current subtyping methods rely on tissue biopsies, which may not capture subtype heterogeneity, and are difficult to implement clinically.

[0087] Basal subtype of pancreatic cancer is a strong independent predictor of worse outcomes, regardless of the up-front chemotherapy regimen used. See Singh H, et al. Clinical and Genomic Features of Classical and Basal Transcriptional Subtypes in Pancreatic Cancer. Clin Cancer Res. 2024 Nov l;30(21):4932-4942. Early data also suggest that the basal subtype may predict responses to KRAS inhibition. Dilly J, et al. Mechanisms of Resistance to Oncogenic KRAS Inhibition in Pancreatic Cancer. Cancer Discov. 2024 Nov 1; 14(11):2135-2161. Basal subtype pancreatic cancer could be identified by GATA6 expression and keratin 5, were more hypoxic, and were enriched for a T-cell-inflamed gene expression signature. See O'Kane GM, et al. GATA6 Expression Distinguishes Classical and Basal-like Subtypes in Advanced Pancreatic Cancer. Clin Cancer Res. 2020 Sep 15;26( 18):4901 -4910. doi: 10.1158 / 1078-0432. CCR-19-3724. Epub 2020 Mar 10. Erratum in: Clin Cancer Res. 2022 Jun 13;28(12):2715.Treatments for Pancreatic Cancer

[0088] The present disclosure encompasses a recognition that classical and basal transcriptional subtypes of pancreatic cancer (e.g., PDAC) are prognostic and may predict response to different treatments, such as chemotherapy programs and RAS inhibitors.

[0089] Current treatments for pancreatic cancer include surgery, radiation therapy, chemotherapy, targeted therapy, and immunotherapy. Surgical interventions are only available for early stage pancreatic cancer, and include Whipple procedure, total pancreatectdomy, and distal pancreatectomy. Pancreatic cancer is sometimes treated with radiation therapy, such as external beam radiation therapy.

[0090] Chemotherapy is typically part of the treatment for mid- to later stage pancreatic cancers. This is because pancreatic cancer has usually already spread by the time it is found, so other treatments such as surgery or radiation therapy would not reach all areas of cancer.

[0091] Chemotherapy drugs to treat pancreatic cancer may include, e.g., capecitabine, fluorouracil (5-FU), gemcitabine, irinotecan, irinotecan sucrosofate (also known as nanoliposomal irinotecan), FOLFIRINOX (which is a combination of 5-FU and leucovorin (a vitamin that improves the effectiveness of 5-FU)), and oxaliplatin.

[0092] Chemotherapeutic agents for pancreatic cancer are typically administered intravenously, either as an injection over a few minutes or as an infusion over a longer period of time. Chemotherapy may also be administered in combination with radiation therapy (e.g., chemoradiation therapy) to treat pancreatic cancer.

[0093] Medical practitioners administer chemotherapy in cycles, with each period of treatment followed by a rest period to give the subject time to recover from the effects of theAttorney Docket No.: DFS-34525 (DFCI 3605)chemotherapeutic agents. Cycles are most often 3 or 4 weeks long, and initial treatment is typically 4 to 6 cycles. The schedule varies depending on the chemotherapeutic agents used. For example, some chemotherapeutic agents are given only on the first day of the chemotherapy cycle. Others are given for a few days in a row, or once a week. Then, at the end of the cycle, the chemotherapy schedule repeats to start the next cycle.

[0094] Various targeted therapies are also available for the treatment of pancreatic cancer. The term “targeted therapy” refers to administration of agents that selectively interact with a chosen biomolecule to thereby treat cancer.

[0095] Immunotherapies using cancer-targeted antibodies are one example of a targeted therapy. Broadly, the field of cancer-targeted antibodies includes, for example, immune checkpoint inhibitors (e.g., anti-PD-1, anti-PD-Ll, anti-PD-L2, and / or anti-CTLA-4 antibody therapeutics), which are well known in the art. For example, “PD-1 pathway inhibitors” can block or otherwise reduce the interaction between PD-1 and one or both of its ligands (PD-L1 and PD-L2) such that the immunoinhibitory signaling otherwise generated by the interaction is blocked or otherwise reduced.

[0096] Immunotherapies may also be used for the treatment of pancreatic cancer. An important part of the immune system is its ability to keep itself from attacking normal cells in the body. To do this, it uses “checkpoints” or proteins on immune cells that need to be turned on (or off) to start an immune response. Cancer cells sometimes use checkpoints to avoid being attacked by the immune system. Therapeutic agents that target these checkpoints (e.g., PD-1) can be used to treat some subjects with pancreatic cancer. Pembrolizumab (Keytruda) and Dostarlimab-gxly (Jemperli) are immunotherapies that target PD-1, a checkpoint protein on T cells to boost the immune response against pancreatic cancer cells.

[0097] Targeted therapy for pancreatic cancer can include KRAS inhibitors. KRAS inhibitors are drugs that target the cancer-causing gene mutation KRAS. Recent advances have led to the development of KRAS inhibitors like KRAZATI® (adagrasib) and LUMAKRAS® (sotorasib). MRTX1133 is a potent, selective, and non-covalent KRASG12Dinhibitor that has been shown to preferentially target the inactive, GDP-bound form of the mutant protein with > 1,000-fold selectivity over wild-ty pe (WT) KRAS. Combination treatment with KRASG12D inhibition and chemotherapy significantly improved tumor control in PDAC mouse models. See Dilly J, et al. Mechanisms of Resistance to Oncogenic KRAS Inhibition in Pancreatic Cancer. Cancer Discov. 2024 Nov 1;14(11):2135-2161. However, classical subtype pancreatic cancers have been found to be acutely resistant to KRAS inhibition. See Singhal A, et al. A Classical Epithelial State Drives Acute Resistance to KRAS Inhibition in Pancreatic Cancer. Cancer Discov. 2024 Nov 1; 14(11):2122-2134; Knox JJ, et al. Early results of the PASS-01 trial: Pancreatic adenocarcinoma signature stratification for treatment-01. Journal of Clinical Oncology 202442(17 supp.): Meeting Abstract: 2024 ASCO Annual Meeting II.Attorney Docket No.: DFS-34525 (DFCI 3605)

[0098] In some embodiments, a pancreatic cancer is a classical transcriptional subtype. In some embodiments, a classical transcriptional subtype PDAC can be treated by chemotherapy, radiation therapy, targeted therapy (e.g., immunotherapy), or a combination thereof. In some embodiments, a classical subtype pancreatic cancer can be treated with the well-known pancreatic cancer therapy FOLFIRINOX (i.e., fluorouracil; FOL, leucovorin calcium (folinic acid); IRIN, irinotecan hydrochloride; and OX, Oxaliplatin; see, for example cancer.gov / about-cancer / treatment / dmgs / folfirinox). In some embodiments, a classical subtype pancreatic cancer is treated with FOLFIRINOX rather than gemcitabine or nab-paclitaxel (i.e., is not treated with gemcitabine and / or nab-paclitaxel).

[0099] In some embodiments, a pancreatic cancer is a basal transcriptional subtype. In some embodiments, a basal transcriptional subtype PDAC can be treated by chemotherapy, radiation therapy, targeted therapy (e.g., KRAS inhibition), or a combination thereof. In some embodiments, a basal subtype pancreatic cancer can be treated with a chemotherapy (e.g., gemcitabine and / or nab-paclitaxel). In some embodiments, a basal subtype pancreatic cancer is treated with gemcitabine and / or nab-paclitaxel rather than FOLFIRINOX (i.e., is not treated with FOLFIRINOX). In some embodiments, a basal subtype pancreatic cancer is treated with a targeted therapy (e.g., KRAS inhibitor). In some embodiments, a basal transcriptional subtype PDAC can be treated by a combination of therapies selected from chemotherapy, radiation therapy, and targeted therapy. In some embodiments, a basal subtype pancreatic cancer can be treated by a combination of chemotherapy (e.g., gemcitabine and / or nab-paclitaxel) and a targeted therapy (e.g., KRAS inhibitor). In some embodiments, a basal subtype pancreatic cancer can be treated with a combination of gemcitabine, nab-paclitaxel and / or a KRAS inhibitor since, for example, data indicate that basal subtype pancreatic cancer respond better to both gemcitabine-based chemotherapy and preclinically also to KRAS inhibitors.Subjects and Samples

[0100] A sample analyzed using methods and compositions provided herein can be any biological sample and / or any sample including nucleic acid. In some embodiments, a sample includes circulating tumor DNA (ctDNA) derived from a biological sample. In various embodiments, a sample analyzed using methods and compositions provided herein can be a sample from a mammalian subject. In various embodiments, a sample analyzed using methods and compositions provided herein can be a sample from a human subject.

[0101] In various instances, a human subject is a subject diagnosed or seeking diagnosis as having, diagnosed as or seeking diagnosis as at risk of having, and / or diagnosed as or seeking diagnosis as at immediate risk of having a pancreatic cancer, e.g., basal subtype pancreatic cancer or a classical subtype pancreatic cancer. In various instances, a human subject is identified as a subject inAttorney Docket No.: DFS-34525 (DFCI 3605)needing pancreatic cancer basal / classical subtype screening. In certain instances, a human subject is a subject identified as in need of pancreatic cancer basal / classical subtype screening by a medical practitioner.

[0102] The subject may not have undergone previous treatments for cancer, e.g., pancreatic cancer, e.g., PDAC, such as the treatments recited in this disclosure. In other embodiments, the subject has undergone previous treatments for cancer, e.g., pancreatic cancer, e.g., PDAC, such as the treatments recited in this disclosure.

[0103] In various embodiments a subject has one or more biomarkers and / or risk factors for cancer, e.g., pancreatic cancer, e.g., PDAC, etc. In certain embodiments, a human subject is identified as in need of basal / classical status screening based on an initial pancreatic cancer diagnosis, e.g., a PDAC diagnosis. In various instances, a human subject is a subject not yet diagnosed as having, not at risk of having, not at immediate risk of having, not diagnosed as having, and / or not seeking diagnosis for a pancreatic cancer, e.g., a PDAC.

[0104] In various embodiments, a sample from a subject, e.g., a human can be obtained from a liquid biopsy. In certain embodiments, a sample and / or reference is obtained from serum, plasma, or urine. In certain embodiments, the sample is serum. In certain embodiments, a sample comprises circulating tumor DNA (ctDNA). In certain embodiments, a sample is derived from about 1 mL of blood obtained from the subject. In certain embodiments, a sample is derived from about 0.5-2 mL of blood obtained from the subject, e.g., about 0.5 to 1.75 mL, about 0.5 to 1.5 mL, about 0.75 to 1.25 mL or about 0.9 to 1.1 mL of blood.

[0105] In various embodiments, a sample is a sample of cell-free DNA (cfDNA). cfDNA is typically found in human biofluids (e.g., plasma, serum, or urine) in short, double-stranded fragments. The concentration of cfDNA is typically low, but can significantly increase under particular conditions, including without limitation pregnancy, autoimmune disorders, myocardial infarction, and cancer. Circulating tumor DNA (ctDNA) is the component of cell-free DNA specifically derived from cancer cells. ctDNA can be present in human biofluids bound to leukocytes and erythrocytes or not bound to leukocytes and erythrocytes. Various tests for detection of tumor-derived ctDNA are based on detection of genetic or epigenetic modifications that are characteristic of cancer (e.g., of a relevant cancer). Genetic or epigenetic factors characteristic of cancer (e.g., pancreatic cancer) can include, without limitation, oncogenic or cancer-associated mutations in tumor-suppressor genes, activated oncogenes, chromosomal disorders, histone modifications (e.g., histone methylation and / or histone acetylation), chromatin accessibility, binding of one or more transcription factors and / or DNA methylation.

[0106] In various embodiments, a sample is a sample of cfDNA comprising ctDNA. In various embodiments, ctDNA comprises less than 30%, less than 20%, or less than 10% of the cfDNA in the liquid biopsy sample obtained from the subject, e.g., less than 9%, 8%, 7%, 6%, 5%, 4%, 3%,Attorney Docket No.: DFS-34525 (DFCI 3605)2% or less than 1% of the cfDNA in the sample. In some embodiments, the percentage of ctDNA in the liquid biopsy sample is assessed using ichorCNA which estimates the percentage of ctDNA in a sample probabilistically (see Adalsteinsson et al., Nat Commun (2017) 8(1): 1324).

[0107] cfDNA and ctDNA can provide a real-time or nearly real time metric of status of a source tissue. cfDNA and ctDNA demonstrate a half-life in blood of about 2 hours, such that a sample taken at a given time provides a relatively timely reflection of the status of a source tissue.

[0108] Various methods of isolating nucleic acids from a sample (e.g., of isolating cfDNA from blood or plasma) are known in the art. Nucleic acids can be isolated using, without limitation, standard DNA purification techniques, by direct gene capture (e.g., by clarification of a sample to remove assay-inhibiting agents and capturing a target nucleic acid, if present, from the clarified sample with a capture agent to produce a capture complex and isolating the capture complex to recover the target nucleic acid).

[0109] Reagents and protocols for obtaining and analyzing cfDNA and ctDNA, such as circulating in blood or other tissue, are commercially available as described in the Examples and well-known in the art (see, for example, Anker et al., Cancer and Metastasis Rev (1999) 18:65-73; Wua et al., Clin ChimActa (2002) 321:77-87; Fiegl etal., Cancer Res (2005) 15:1141-1145; Pathak et al., Clin Chem (2006) 52:1833-1842; Schwarzenbach et al., Clin Cancer Res (2009) 15:1032-1038;Schwarzenbach et al., Nat Rev Cancer (2011) 11:426-437); the contents of each of which is separately incorporated herein by reference in their entirety).

[0110] In various embodiments, samples can be collected from individuals repeatedly over a period of time (e.g., once daily, weekly, monthly, annually, biannually, etc.). In various embodiments, such samples can be used to verify results from earlier detections and / or to identify an alteration in biological pattern because of, for example, disease progression, resistance to therapy, treatment, remission, and the like. For example, subject samples can be taken and monitored every month, every two months, or combinations of one, two, or three-month intervals according to the present disclosure. In various embodiments, samples can be collected for monitoring over time beginning at or at certain clinically determined stages, such as at resistance to a therapy, before radiographic progression, after radiographic progression, and / or at tissue biopsy. In addition, the classical / basal features obtained at different points in time can be conveniently compared with each other, as well as with those of normal controls during the monitoring period, thereby providing the subject’s own values, as an internal, or personal, control for long-term monitoring.

[0111] Samples include materials prepared by processes including, without limitation, steps such as concentration, dilution, adjustment of pH, removal of high abundance polypeptides (e.g., albumin, gamma globulin, and transferrin, etc.), addition of preservatives, addition of calibrants, addition of protease inhibitors, addition of denaturants, desalting, concentration and / or extraction of sample nucleic acids, and / or amplification of sample nucleic acids (e.g., by PCR or other nucleic acidAttorney Docket No.: DFS-34525 (DFCI 3605)amplification techniques). Samples also include materials prepared by techniques that isolate, e.g., nucleosomes or transcription factors and / or nucleic acids associated with nucleosomes or transcription factors.

[0112] Removal from a sample of proteins that are not desirable for a relevant purpose or context (e.g., high abundance, uninformative, or undetectable proteins) can be achieved using high affinity reagents, high molecular weight filters, ultracentrifugation and / or electrodialysis. High affinity reagents include antibodies or other reagents (e.g., aptamers) that selectively bind to high abundance proteins. Sample preparation can also include ion exchange chromatography, metal ion affinity chromatography, gel filtration, hydrophobic chromatography, chromatofocusing, adsorption chromatography, isoelectric focusing and related techniques. Molecular weight filters include membranes that separate molecules on the basis of size and molecular weight. Such filters may further employ reverse osmosis, nanofiltration, ultrafiltration and microfiltration. Ultracentrifugation is the centrifugation of a sample at about 15,000-60,000 rpm while monitoring with an optical system the sedimentation (or lack thereof) of particles. Electrodialysis is a procedure which uses an electromembrane or semipermeable membrane in a process in which ions are transported through semi-permeable membranes from one solution to another under the influence of a potential gradient. Since the membranes used in electrodialysis may have the ability to selectively transport ions having positive or negative charge, reject ions of the opposite charge, or to allow species to migrate through a semipermeable membrane based on size and charge, it renders electrodialysis useful for concentration, removal, or separation of electrolytes.

[0113] Separation and purification in the present disclosure may include any procedure known in the art, such as capillary electrophoresis (e.g., in capillary or on-chip) or chromatography (e.g., in capillary, column or on a chip). Electrophoresis is a method that can be used to separate ionic molecules under the influence of an electric field. Electrophoresis can be conducted in a gel, capillary, or in a microchannel on a chip. Examples of gels used for electrophoresis include starch, acrylamide, polyethylene oxides, agarose, or combinations thereof. A gel can be modified by its cross-linking, addition of detergents, or denaturants, immobilization of enzymes or antibodies (affinity electrophoresis) or substrates (zymography) and incorporation of a pH gradient. Examples of capillaries used for electrophoresis include capillaries that interface with an electrospray.

[0114] Capillary electrophoresis (CE) is preferred for separating complex hydrophilic molecules and highly charged solutes. CE technology can also be implemented on microfluidic chips. Depending on the types of capillary and buffers used, CE can be further segmented into separation techniques such as capillary zone electrophoresis (CZE), capillary isoelectric focusing (CIEF), capillary isotachophoresis (cITP) and capillary electrochromatography (CEC). An embodiment to couple CE techniques to electrospray ionization involves the use of volatile solutions, for example,Attorney Docket No.: DFS-34525 (DFCI 3605)aqueous mixtures containing a volatile acid and / or base and an organic such as an alcohol or acetonitrile.

[0115] Capillary isotachophoresis (cITP) is a technique in which the analytes move through the capillary at a constant speed but are nevertheless separated by their respective mobilities.Capillary zone electrophoresis (CZE), also known as free-solution CE (FSCE), is based on differences in the electrophoretic mobility of the species, determined by the charge on the molecule, and the frictional resistance the molecule encounters during migration, which is often directly proportional to the size of the molecule. Capillary isoelectric focusing (CIEF) allows weakly-ionizable amphoteric molecules, to be separated by electrophoresis in a pH gradient. CEC is a hybrid technique between traditional high performance liquid chromatography (HPLC) and CE.

[0116] Separation and purification techniques used in the present disclosure can include any chromatography procedures known in the art. Chromatography can be based on the differential adsorption and elution of certain analytes or partitioning of analytes between mobile and stationary phases. Different examples of chromatography include, but not limited to, liquid chromatography (LC), gas chromatography (GC), high performance liquid chromatography (HPLC), etc.

[0117] In some embodiments, whole blood is collected from a subject, and a plasma layer is separated by centrifugation. Cell free DNA may be then extracted from the plasma using methods known in the art. In some embodiments, isolated cell free DNA can be used to detect methylation of genomic loci or other genomic and / or epigenomic alterations of biomarkers.Histone modifications, Chromatin Accessibility and Transcription Factor Binding

[0118] Histone methylation is understood to increase or decrease expression of associated coding sequences, depending on which histone residue is methylated. Histone methylation is an essential modification that can cause monomethylation (me1), dimethylation (me2), and trimethylation (me3) of several amino acids, thus directly affecting heterochromatin formation, gene imprinting, X chromosome inactivation, and gene transcriptional regulation. Histone methyltransferases promote monomethylation, dimethylation, or trimethylation of histones while histone demethylases promote demethylation of histones. In general, lysine (Lys or K), arginine (Arg or R), and rarely histidine (His or H) are the most common histone methyl acceptors. Histone methylation only occurs at specific lysine and arginine sites of histone H3 and H4. In histone H3, lysine 4, 9, 26, 27, 36, 56, and 79 and arginine 2, 8, and 17 can be methylated. By comparison, histone H4 has fewer methylation sites, in which only lysine 5, 12, and 20 and arginine 3 can be methylated. Histone methylation is often associated with transcriptional activation or inhibition of downstream genes. The methylation of histone H3K4, R8, R17, K26, K36, K79, H4R3, and K12 can activate gene transcription. However, the methylation of histone H3K9, K27, K56, H4K5, and K20 can inhibit geneAttorney Docket No.: DFS-34525 (DFCI 3605)transcription. Thus, for example, H3K4 methylation generally activates gene expression, while H3K27 methylation generally represses gene expression.

[0119] Histone acetylation occurs predominantly at lysine residues and is generally understood to increase expression of associated coding sequences. Without wishing to be bound by any theory, acetylation of lysine residues is thought to neutralize lysine’s positive charge and thereby cause histones to drift away from DNA, which has a negative charge. The released structure facilitates access to transcriptional machinery such as transcription factors and RNA polymerase II. Histone acetylation and deacetylation are generally catalyzed by histone acetyltransferases (HATs) and HDACs, respectively. Acetyl-CoA can be a source and co-factor of acetylation. In regulatory regions, HATs can acetylate histones and recruit HAT-containing complexes to activate the transcriptional process. For instance, H3K9ac and H3K27ac levels can be associated with promoter and enhancer activities. Furthermore, H3K27ac enhances not only the kinetics of transcriptional activation, but also accelerates the transition of RNA polymerase II from the initiation state to the elongation state.

[0120] Differential modification of a genomic locus (e.g., differential histone methylation and / or differential histone acetylation) can refer to, or be determined by or detected as, a comparative difference or change in modification status of one or more genomic loci between a first sample, condition, disease, or state and a second or reference sample, condition, disease, or state. Those of skill in the art will appreciate that a reference is typically produced by measurement using a methodology identical, similar, or comparable to that by which a compared non-reference measurement was taken.

[0121] Chromatin accessibility can refer to the degree to which nuclear macromolecules are able to physically contact DNA and is determined in part by the occupancy and modification status of nucleosomes. Modified histones can regulate chromatin accessibility through a variety of mechanisms, such as altering transcription factor (TF) binding through steric hindrance and modulating nucleosome affinity for active chromatin remodelers. The topological organization of nucleosomes across the genome is non-uniform: while histones can be densely arranged within facultative and constitutive heterochromatin, histones can be depleted at regulatory loci, including within enhancers, insulators and transcribed gene bodies. Active regulatory elements of the genome are generally accessible.

[0122] Differential accessibility of a genomic locus can refer to, or be determined by or detected as, a comparative difference or change in modification status of one or more genomic loci between a first sample, condition, disease, or state and a second or reference sample, condition, disease, or state. Those of skill in the art will appreciate that a reference is typically produced by measurement using a methodology identical, similar, or comparable to that by which a compared nonreference measurement was taken.Attorney Docket No.: DFS-34525 (DFCI 3605)

[0123] A reference can be a value or set of values that are predetermined or derived from a sample or set of samples. A reference can be a sample or set of samples. A reference value can be a predetermined threshold value, a value that varies in accordance with circumstances (e.g., according to patient subpopulation, age, weight, or other variables), or a ratio. Reference ratios can be ratios relating to the modification of multiple loci within individual samples and / or references, or across or between samples and / or references. In various embodiments, a reference can have or represent a normal, non-diseased state. In some embodiments, such as for staging of disease or for evaluating the efficacy of treatment, a reference can have or represent a diseased state, e.g., a pancreatic cancer, stage of pancreatic cancer, or subtype of pancreatic cancer, e.g., classical or basal pancreatic cancer. In some embodiments, a reference can represent prostate cancer by being obtained from a subject diagnosed as having pancreatic cancer (e.g., based on imaging, symptoms, and / or biomarker analysis). In some embodiments, a reference can correspond to a subject having pancreatic cancer and / or a pancreatic cancer subtype, e.g., basal or classical pancreatic cancer.

[0124] In some instances, a reference is a non-contemporaneous sample from the same source, e.g., a prior sample from the same source, e.g., from the same subject. In some instances, a reference for the modification status of one or more genomic loci (e.g., one or more differentially modified genomic loci) can be the modification status of the one or more genomic loci (e.g., one or more differentially modified genomic loci) in a sample (e.g., a sample from a subject), or a plurality of samples, known to represent a particular state (e.g., basal subtype pancreatic cancer or classical subtype pancreatic cancer). In certain instances, a reference for the accessibility status of one or more genomic loci (e.g., one or more differentially accessible genomic loci) can be the accessibility status of the one or more genomic loci (e.g., one or more differentially accessible genomic loci) in a sample (e.g., a sample from a subject), or a plurality of samples, known to represent a particular state (e.g., basal subtype pancreatic cancer or classical subtype pancreatic cancer).

[0125] The present disclosure includes the discovery of genomic loci that are differentially modified and / or differentially accessible in basal and classical subtypes of pancreatic cancer. Tables 1-2 include genomic loci that are differentially modified in classical and basal subtypes of pancreatic cancer.

[0126] In some illustrative but non-limiting embodiments encompassed by the present disclosure differential modification can refer to a differential (e.g., between a sample and a reference) with an absolute log2(fold-change) that is greater than or equal to 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, or more, or any range in between, inclusive, e.g., as measured according to an assay provided herein.

[0127] Enhancers are genomic loci that can be differentially modified in and / or between conditions, diseases, and other states. Enhancers are cis-acting DNA regulatory regions that are thought to bind trans-acting proteins that contribute to expression patterns of associated genes.Attorney Docket No.: DFS-34525 (DFCI 3605)Chromatin ImmunoPrecipitation sequencing (ChlP-seq) of histone modifications (e.g., acetylation) have identified millions of enhancers in mammalian genomes. The number of active enhancers in any given cell type is estimated to be in the tens of thousands. Certain transcription factors (TFs), sometimes referred to as “master” transcription factors, associate with active enhancers with important impacts on gene expression and cell function. Certain such transcription factors preferentially associate with enhancers that regulate genes required for establishing cell identity and function, including enhancer domains known as “super-enhancers”. Moreover, master TFs can participate in inter-connected auto-regulatory circuitries or “cliques” that are self-reinforcing, show marked cell selectivity, and function to maintain cell state and / or cell survival.Techniques for Detecting and Quantifying Histone Modifications and Transcription Factor Binding

[0128] Various techniques of molecular biology are well-known in the art and / or disclosed in the present application for detecting and quantifying histone modifications and / or transcription factor binding. In some embodiments, the methods, kits and systems of present disclosure involve the detection and quantification of histone modifications and / or transcription factor binding in samples, e.g., in liquid biopsy samples including cfDNA such as plasma samples including cfDNA. Chromatin ImmunoPrecipitation (ChIP) is one technique of molecular biology useful in detecting and quantifying histone modifications and transcription factor binding in samples. CUT& RUN or CUT& Tag are other more recent techniques that can also be used to detect and quantify histone modifications and transcription factor binding sites. ChIP -chip, ChIP -exo, ChIP Re-ChIP, and ChlPmentation are other alternative techniques that could be used.

[0129] ChIP can involve various steps including one or more of fixation, sonication, immunoprecipitation, and analysis of the immunoprecipitated DNA. ChIP has become a very widely used tissue-based technique for determining the in vivo location of binding sites of various transcription factors and histones. Because the proteins are captured at the sites of their binding with DNA, ChIP helps to detect DNA-protein interactions that take place in living cells. More importantly, ChIP can be coupled to many commonly used molecular biology techniques such as PCR and realtime PCR, PCR with single-stranded conformational polymorphism, Southern blot analysis, Western blot analysis, cloning, and microarray. The resulting versatility has increased the potential of this technique.

[0130] ChIP of tissue samples usually involves cross-linking of the chromatin-bound proteins by formaldehyde, followed by sonication or nuclease treatment to obtain small DNA fragments. Immunoprecipitation can be then carried out using specific antibodies to the DNA-binding protein of interest. The DNA can be then released from the proteins and analyzed using various methods. ChIP has also been used to study RNA-protein interactions. X-ChIP methods utilize fixedAttorney Docket No.: DFS-34525 (DFCI 3605)chromatin fragmented by sonication, while the N-ChIP methods utilize native chromatin, which can be unfixed and nuclease digested.

[0131] The first step of the technique can be the cross-linking of DNA and proteins.Formaldehyde is one of the most used cross-linking agents. One advantage of using formaldehyde can be the ease of reversibility of the cross-links and its ability to form bonds that span approximately 2 angstroms. This means that formaldehyde can bind molecules in close association with each other. Generally, formaldehyde can be added to the medium in the cell culture flask or plate. It enters the cells through the cell membrane and cross-links the proteins to the chromatin. Formaldehyde fixation of tumor tissues has also been done. Other cross-linking agents that have been used include chemicals such as methylene blue and acridine orange, cisplatin, dimethylarsinic acid, potassium chromate, and ultraviolet (UV) light and lasers.

[0132] Harvested chromatin can be sonicated in one or more sonication cycles. DNA can be typically broken into to 100-500 bp fragments to pinpoint the location of the DNA sequence of interest. An alternative to sonication can be nuclease digestion of the chromatin, e.g., in N-ChIP methods. Purification of chromatin can be achieved using a cesium chloride (CsCl) gradient centrifugation.

[0133] Chromatin can be immunoprecipitated using one or more antibodies that bind a target epitope. For example, an antibody used in ChIP can selectively bind a particular transcription factor or one or more particular histone modifications, such as one or more particular histone acetylation modifications or histone methylation modifications. In some embodiments, an antibody used to bind a target epitope can be a “pan” antibody (e.g., a pan-acetylation antibody, a pan-methylation antibody, an antibody that binds a group of histone modifications associated with increased transcription activation, and / or an antibody that binds a group of histone modifications associated with increased transcription repression). The antibody against the protein of interest is allowed to bind to the protein-DNA complex, and the complex can be then precipitated. Immunosorbants commonly used to separate the antigen-antibody complex from the lysate include salmon sperm DNA-protein A-Sepharose®, protein G, magnetic beads, and other engineered immunoprecipitation systems known to those of skill in the art.

[0134] Immunoprecipitated DNA can be eluted. Once the DNA of interest is isolated, many detection and quantification methods can be used to study the isolated gene fragments. Commonly utilized methods include PCR, real-time PCR, slot blot hybridization, microarray techniques, and deep or next-generation sequencing. ChlP-seq combines chromatin immunoprecipitation (ChIP) with massively parallel DNA sequencing to identify the binding sites of DNA-associated proteins. ChlP-seq can be used to map DNA-binding proteins, e.g., transcription factor binding sites and histone modifications in a genome-wide manner.Attorney Docket No.: DFS-34525 (DFCI 3605)

[0135] Cell-free Chromatin ImmunoPrecipitation sequencing (cfChlP-seq) involves applying ChlP-seq to samples that include cell-free DNA, e.g., liquid biopsy samples including cfDNA such as plasma samples including cfDNA (e.g., see Sadeh et al., Nat Biotechnol (2021) 39:586-598, Jang et al., Life Sci Alliance (2023) 6(12):e202302003, and Baca et al., Nat Med (2023) 29:2737-2741; the entire contents of each of which are incorporated herein by reference). In some embodiments, cfChlP-seq uses antibodies or antibody fragments that bind specific histone modifications (e.g., H3K4me3 and / or H3K27ac) and / or transcription factors that are coupled (covalently or non-covalently) to beads, e.g., magnetic beads such as Dynabeads® magnetic beads and incubated with a volume, e.g., about 1 mL of thawed plasma obtained from a subject. Without limitation, exemplary antibodies that bind H3K4me3 include PA5-27029 (available from Thermo Fisher Scientific in Waltham, MA) and C15410003 (available from Diagenode in Denville, NJ) and exemplary antibodies that bind H3K27ac include ab21623 or ab4729 (both available from Abcam in Cambridge, UK) and C15210016 (available from Diagenode in Denville, NJ).

[0136] In some embodiments, the antibodies or antibody fragments can be covalently coupled to beads, e.g., epoxy beads. In some embodiments, the antibodies or antibody fragments can be non-covalently coupled to beads, e.g., Protein A or Protein G beads such as Dynabeads® Protein A or Dynabeads® Protein G beads. After washing, a cfDNA library is then typically prepared from the captured cfDNA. Library preparation can be done on-bead or after releasing the captured cfDNA by digestion of bound histones, e.g., using proteinase K. The cfDNA library is then sequenced to generate reads of captured cfDNA sequences, e.g., by next-generation sequencing (NGS) as is known in the art. The reads are then analyzed, e.g., aligned and counted using standard bioinformatic techniques as is known in the art. A cfChlP-seq bioinformatic pipeline can include, e.g., alignment of sequence reads to a reference genome (e.g., human genome build GRCh37 / hgl9 NCBI RefSeq assembly GCF_000001405.13) with BWA or Bowtie2. Aligned reads can be used to call and quantify peaks as compared to a reference.

[0137] CUT& Tag involves antibody-based binding of a target protein, e.g., transcription factor or histone modification of interest, where antibody incubation is directly followed by the shearing of the chromatin and library preparation (see Kaya-Okur et al., Nat Comm (2019) 10: 1930). CUT& Tag assays take advantage of a Tn5 transposase that is fused with Protein A to direct the enzyme to the antibody bound to its target on chromatin. Tn5 transposase is pre-loaded with sequencing adapters (generating the assembled pA-Tn5 adapter transposome) to carry out antibody-targeted tagmentation. In a typical CUT& Tag assay samples are incubated with an antibody immobilized on Concanavalin A-coated magnetic beads to facilitate subsequent washing steps. Cells can be incubated with a primary antibody specific for the target protein of interest followed by incubation with a secondary antibody. Samples can then be incubated with assembled transposomes, which consist of Protein A fused to the Tn5 transposase enzyme that is conjugated to NGS adapters.Attorney Docket No.: DFS-34525 (DFCI 3605)After incubation, unbound transposome can be washed away using stringent conditions. Tn5 is a Mg2+-dependent enzyme so Mg2+can be added to activate the reaction, which results in the chromatin being cut close to the protein binding site and simultaneous addition of the NGS adapter DNA sequences. Chromatin cleavage and library preparation can be achieved in one single step.

[0138] CUT& RUN is an epigenomic profiling strategy in which antibody-targeted controlled cleavage by micrococcal nuclease releases specific protein-DNA complexes into the supernatant for paired-end DNA sequencing (see Skene and Henikoff, Elife (2017) 6:1-35, Skene et al., Nat Protoc (2018) 13: 1006-1019). As only targeted fragments enter into solution, and the vast majority of DNA is left behind, CUT& RUN has low background levels. In an example CUT& RUN assay, a sample is incubated with an antibody or antibody fragment that binds the target protein, e.g., transcription factor or histone modification of interest. The sample is then incubated with Protein-A-MNase after which CaCl₂ can be added to initiate the calcium dependent nuclease activity of MNase to cleave the DNA around the target protein. The protein-A-MNase reaction can be quenched by adding chelating agents (EDTA and EGTA). Cleaved DNA fragments are then liberated, extracted, and used to construct a sequencing library.Techniques for Detecting and Quantifying Chromatin Accessibility

[0139] Various techniques of molecular biology are well known in the art and / or disclosed in the present application for detecting and quantifying chromatin accessibility. In some embodiments, the methods, kits and systems encompassed by the present disclosure involve the detection and quantification of chromatin accessibility in samples, e.g., in liquid biopsy samples including cfDNA such as plasma samples including cfDNA. ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde-Assisted Isolation of Regulatory Elements sequencing), MNase-seq (Micrococcal Nuclease digestion with sequencing), and DNase hypersensitivity assays are exemplary techniques of molecular biology useful in detecting and quantifying chromatin accessibility in samples.

[0140] DNase hypersensitivity assays can use the non-specific DNA endonuclease Deoxyribonuclease I (DNase I), which selectively digests accessible DNA regions. DNase I hypersensitivity sites (DHS) identified by DNase-seq include open chromatin regulatory regions. A typical DNase hypersensitivity assay can include a first step in which nuclei are isolated from cells using lysis buffer, and nuclei are digested using DNase I. DNA fragment sizes are measured to identify optimal digestion using gel electrophoresis. Biotinylated linkers can be ligated to the ends of digested DNA after polishing to make blunt ends, and the DNA can then be isolated. DNA with biotinylated linker can be digested by restriction endonuclease Mmel and captured by streptavidin coated Dynabeads® to generate short tags to which a second sequencing adaptor can be ligated. A second linker can be ligated and amplified to generate a library for sequencing. A DNase-seqAttorney Docket No.: DFS-34525 (DFCI 3605)bioinformatic pipeline can include, e.g., alignment of sequence reads to a reference genome with BWA or Bowtie2. Aligned reads can be used to call and quantify peaks as compared to a reference.

[0141] MNase-seq determines chromatin accessibility with micrococcal nuclease (MNase) that preferentially digests nucleosome-free, protein-unbound DNA. A typical MNase-seq assay can include a first step in which nuclei are isolated from either native or crosslinked chromatin and digested using MNase with titration. In vivo formaldehyde crosslinking step that is designed to capture the interaction between proteins and DNA. This crosslinking allows bound proteins to shield their associated DNA from digestion by MNase. Following crosslinking, samples are digested with MNase, which can be specifically activated by addition of Ca2+ to the buffer. Digestion can be halted by chelating the reaction, at which point the samples are RNase treated, crosslinks are reversed, and proteins are digested away from the chromatin. DNA can then be isolated via a phenol-chloroform extraction. Uncut DNA is purified and mononucleosome bands are isolated and excised through gel electrophoresis. Isolated DNA can be amplified by adding adapters to generate a library, and sequenced. MNase-seq primarily sequences regions of DNA bound by histones or other proteins. Therefore, it indirectly determines which regions of DNA are accessible by directly determining which regions are bound to nucleosomes or proteins.

[0142] FAIRE-seq is a method in which nucleosome-depleted regions of DNA (NDRs) are isolated from chromatin. A typical FAIRE-seq assay can include a first step in which cells are fixed using formaldehyde so that histones are crosslinked to interacting DNA. Crosslinked chromatin can then be sheared by sonication that generates protein-free DNA and protein-crosslinked DNA fragments. Protein-free DNA can be isolated using a phenol-chloroform extraction: DNA crosslinked with protein stays in organic phase, while protein-free DNA stays in aqueous phase. Highly crosslinked DNA remains in the organic phase and the non-crosslinked DNA is pulled to the aqueous phase. Non-crosslinked DNA from the aqueous phase can then be amplified and sequenced. Reads enriched in the sequencing pool tend to have lower nucleosome and transcription factor binding and are therefore inferred to come from accessible regions.

[0143] NOMe-seq is a method to identify nucleosome-depleted regions of DNA (NDRs) with M. CviPI methyltransferase that methylates cytosine in GpC dinucleotides not protected by nucleosomes or other proteins. Unlike CmpG, GpCmin the human genome does not occur naturally in most cell types. GpCmlevels at open chromatin regions can be compared to background signals and used to detect and quantify NDRs. A typical NOMe-seq protocol can include a step in which samples are treated with M. CviPI and S-adenosylhomocysteine (SAM) to methylate accessible GpC sites. M. CviPI treated DNA can be sheared using a sonicator, so that DNA fragments can be sequenced. DNA is treated with bisulfite, which converts unmethylated cytosine to uracil using sodium bisulfite, while methylated cytosine is unaffected. A library is generated using adapters and sequenced.Accessible chromatin is expected to have high levels of GpCmbut low levels of CmpG. Therefore,Attorney Docket No.: DFS-34525 (DFCI 3605)NOMe-seq identifies NDRs using the two separate methylation analyses that serve as independent (but opposite) measures, providing matched chromatin designations for each regulatory element.

[0144] ATAC-seq uses hyperactive Tn5 transposase that preferentially cuts accessible chromatin regions and simultaneously inserts adapters to the fragmented region (Buenrostro et al., Nat Methods (2013) 10(12): 1213-1218 the entirety of which is incorporated herein by reference). A typical ATAC-seq assay can include a first step in which samples are incubated with Tn5 transposase. DNA can then be isolated and purified. DNA fragmented and tagged by Tn5 transposase can be purified and then amplified to generate a library and sequenced for analysis.Techniques for Detecting and Quantifying DNA Methylation

[0145] Various techniques of molecular biology are well known in the art and / or disclosed in the present application for detecting and quantifying DNA methylation. In some embodiments, the methods, kits and systems of the present disclosure involve the detection and quantification of chromatin accessibility in samples, e.g., in liquid biopsy samples including cfDNA such as plasma samples including cfDNA. Bisulfite sequencing (BS-Seq), Whole Genome Bisulfite Sequencing (WGBS), Methylated DNA ImmunoPrecipitation sequencing (MeDIP-seq), or Methyl-CpG-Binding Domain sequencing (MBD-seq) are exemplary techniques of molecular biology useful in detecting and quantifying chromatin accessibility in samples.

[0146] Bisulfite sequencing (BS-Seq) or Whole-Genome Bisulfite Sequencing (WGBS) is a well-established protocol to detect methylated cytosines in genomic DNA. In this method, genomic DNA is treated with sodium bisulfite and then sequenced, providing single-base resolution of methylated cytosines in the genome. Upon bisulfite treatment, unmethylated cytosines are deaminated to uracils which, upon sequencing, are converted to thymidines. Simultaneously, methylated cytosines resist deamination and are read as cytosines. The location of the methylated cytosines can then be determined by comparing treated and untreated sequences.

[0147] MeDIP-seq was first reported by Weber et al., Nat Genet (2005) 37:853-862. In a typical MeDIP-seq protocol, antibody or antibody-fragment that binds 5 -methylcytidine (5mC) is used to enrich methylated DNA fragments, then these fragments are sequenced and analyzed. If using 5mC-specific antibodies or antibody fragments, methylated DNA is isolated from genomic DNA via immunoprecipitation. Anti-5mC antibodies are incubated with fragmented genomic DNA and precipitated, followed by DNA purification and sequencing.

[0148] Methyl-CpG-Binding Domain sequencing (MBD-seq) is similar to MeDIP-seq except that it uses methyl binding domain (MBD) proteins instead of antibodies or antibody fragments to bind methylated DNA. In a typical MBD-seq protocol, genomic DNA is first sonicated and incubated with tagged MBD proteins that can bind methylated cytosines. The protein-DNA complex is then precipitatedAttorney Docket No.: DFS-34525 (DFCI 3605)with antibody-conjugated beads that are specific to the MBD protein tag, followed by DNA purification and sequencing.Classifiers

[0149] In some embodiments, the present disclosure provides methods for obtaining a classifier, e.g., a validated classifier that can be used to determine classical / basal subtype of pancreatic cancer, e.g., PDAC. In some embodiments, a subject is determined to have a validated epigenetic profile indicative of classical subtype pancreatic cancer or basal subtype pancreatic cancer based on analysis of a biological sample, optionally of cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject. In some embodiments, the presence of the validated epigenetic profile has been determined using a validated classifier.

[0150] For illustration purposes and without limitation, in an exemplary embodiment of the present disclosure, the validated classifier may be obtained by:

[0151] (a) determining a genomic profile of one or more histone modifications, chromatin accessibility, and / or binding of one or more transcription factors in biological samples obtained from a first cohort of subjects who have previously been determined to have a basal subtype of pancreatic cancer;

[0152] (b) determining a genomic profile of one or more histone modifications, chromatin accessibility, and / or binding of one or more transcription factors in biological samples obtained from a second cohort of healthy subjects or subjects who have previously been determined to have classical subtype of pancreatic cancer;

[0153] (c) comparing the genomic profile determined in step (a) and the genomic profile determined in step (b), to identify genomic loci that have statistically different histone modification, chromatin accessibility, and / or binding of transcription factors (“differential loci”);

[0154] (d) training a classifier on histone modification, chromatin accessibility, and / or binding of transcription factors in the differential loci to distinguish between (i) samples from one or more biological samples obtained from the first cohort, and (ii) samples from one or more biological samples obtained from the second cohort, to identify samples having a profile of histone modification, chromatin accessibility, and / or binding of transcription factors (“epigenetic profile”) that indicates that the samples are likely obtained from the first cohort; and

[0155] (e) obtaining the validated classifier by validating the classifier from step (d) on a third cohort comprising an independent and blinded group of subjects with basal and classical subtypes of pancreatic cancer and selecting a threshold such that the validated classifier predicts basal or classical subtype pancreatic cancers, with an area under the receiver operating characteristic (AUROC) greater than 0.5 (e.g., greater than 0.55, greater than 0.6, greater than 0.65, greater than 0.7, greater than 0.75, greater than 0.8, greater than 0.85, greater than 0.9, or greater than 0.95), whereinAttorney Docket No.: DFS-34525 (DFCI 3605)subjects falling within the group of predicted basal or classical subtype pancreatic cancers display the validated epigenetic profde and subjects that do not fall within the group of basal or classical subtype pancreatic cancers lack the validated epigenetic profde.

[0156] A person of ordinary skill will appreciate that other methods can be used to obtain a classifier, e.g., a validated classifier that can be used to determine the classical / basal subtype and that the present disclosure is not limited to classifiers obtained in accordance with this method.Exemplary Genomic Loci

[0157] The present disclosure includes the identification of exemplary genomic loci that are differentially modified and / or differentially accessible in basal vs. classical subtype pancreatic cancer. See Tables 1-3 which show the chromosomal coordinates of each genomic locus and whether they are correlated with basal or classical subtype pancreatic cancer (genomic loci in columns with “Basal Locus Up” in the header are those whose enrichment or increase correlates with basal subtype pancreatic cancer; while genomic loci with “Classical Locus Up” in the header are those whose presence or increase correlate with classical subtype pancreatic cancer). The genomic loci are described by their chromosomal coordinates which are based on human genome build GRCh37 / hgl9 (NCBI RefSeq assembly GCF_000001405.13). As described further below, the skilled artisan can readily determine that the “classical locus up” loci are loci correlated with classical subtype pancreatic cancer such that their enrichment or increase is indicative of classical subtype pancreatic cancer as compared to samples obtained or derived from i) a healthy subject or ii) a subject with basal subtype pancreatic cancer. Similarly, the skilled artisan can readily determine that the “basal locus up” loci are loci correlated with basal subtype pancreatic cancer such that their enrichment or increase is indicative of basal subtype pancreatic cancer as compared to samples obtained or derived from i) a healthy subject or ii) a subject with classical subtype pancreatic cancer.

[0158] The present disclosure is not limited to methods that use the exact same chromosomal coordinates that are recited in Tables 1-3. The present disclosure encompasses methods that use any of the genomic loci in Table 1-3 and also subregions thereof, i.e., references herein to methods that involve detecting and / or quantifying one or more histone modifications and / or chromatin accessibility at one or more genomic loci of Table 1-3 encompasses methods that detect these marks anywhere within these genomic loci including within any subregions. For example, where Table 2 references chr4:109915141-109916081 as agenomic locus for detecting and / or quantifying H3K27ac modification, this encompasses methods that detect and / or quantify H3K27ac modification at any position or sub-region of chr4: 109915141-109916081, e.g., methods that detect and / or quantify H3K27ac modification within chr4:109915141-109916081, etc. In some embodiments, a subregion may span at least 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500 or at least 3000 contiguous base pairs that are located between the lower and upper coordinates of a genomic locus recited in Tables 1-3. In some embodiments, a subregion may span less than 100, 200, 300, 400, 500,Attorney Docket No.: DFS-34525 (DFCI 3605)600, 700, 800, 900, 1000, 1500, 2000, 2500 or at least 3000 contiguous base pairs that are located between the lower and upper coordinates of a genomic locus recited in Tables 1-3. In some embodiments, a subregion may have the same central coordinate as a genomic locus recited in Tables 1-3. In some embodiments, a subregion may have a different central coordinate as a genomic locus recited in Tables 1-3. It is also to be understood that the lower / upper coordinates of the genomic loci in Tables 1-3 are approximate and that the present disclosure encompasses methods where any one or more of the genomic loci are expanded by increasing the size of the genomic locus by 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or up to 50% in one or both directions.

[0159] In some embodiments, a classifier is generated using a set of differentially modified genomic loci that are correlated with basal subtype pancreatic cancer and a set of differentially modified and / or differentially accessible loci that are correlated with classical subtype pancreatic cancer. Sequence reads that fall into each selected genomic locus are analyzed and counted, e.g., as described herein including the Examples. In some embodiments, counts from genomic loci that are correlated with basal subtype are aggregated and counts from genomic loci that are correlated with classical subtype are aggregated. In some embodiments, a ratio of the aggregated basal subtype and classical subtype cancer counts is used to determine basal / classical status. Other ways of using the genomic loci and related sequencing data to generate and apply a classifier to determine basal / classical subtype status are described herein and known in the art, e.g., without limitation, methods that use a learning statistical classifier system or a combination of learning statistical classifier systems.

[0160] In some embodiments, exemplary genomic loci from Table 1 or 2 are used in a monomodal classifier, e.g., a classifier that uses a single histone modification (e.g., H3K4me3 or H3K27ac) at one or more genomic loci for purposes of determining basal / classical subtype status. In some embodiments, exemplary genomic loci from Table 1 and / or 2 are used in combination in a multimodal classifier, e.g., a classifier that uses more than one histone modification (e.g., H3K4me3 and H3K27ac) at one or more genomic loci for purposes of determining basal / classical subtype status.

[0161] In some embodiments, exemplary genomic loci from Tables 1-3 are used in a monomodal classifier, e.g., a classifier that uses a single histone modification (e.g., H3K4me3, H3K27ac and / or MeDIP) at one or more genomic loci for purposes of determining basal / classical subtype status. In some embodiments, exemplary genomic loci from Tables 1-3 are used in combination in a multimodal classifier, e.g., a classifier that uses more than one histone modification (e.g., H3K4me3, H3K27ac and / or MeDIP) at one or more genomic loci for purposes of determining basal / classical subtype status.Differential H3K4me3 modification

[0162] Genomic loci demonstrating differential H3K4 methylation (in particular H3K4 trimethylation, H3K4me3) in basal subtype vs. classical subtype pancreatic cancer are provided inAttorney Docket No.: DFS-34525 (DFCI 3605)Table 1 which shows the chromosomal coordinates of each genomic locus and whether they are correlated with basal subtype or classical subtype pancreatic cancer (genomic loci in columns with “H3K4me3 - Basal Locus Up” in the header correlate with basal subtype pancreatic cancer while genomic loci with “H3K4me3 - Classical Locus Up” in the header correlate with classical subtype pancreatic cancer). The genomic loci are sorted based on their chromosomal coordinates which are based on human genome build GRCh37 / hgl9 (NCBI RefSeq assembly GCF_000001405.13).

[0163] A person of skill in the art will recognize that the methods disclosed herein do not require that every genomic locus listed in Table 1 be assessed for H3K4me3 modification. Instead, a subset of loci may be assessed for H3K4me3 modification. Subsets of the genomic loci of Table 1 can be selected (e.g., for use in determining basal / classical subtype status) based on various performance criteria, e.g., to select genomic loci that demonstrate differential modification with a particular level of statistical significance and / or a particular threshold of differential between relevant states (e.g., a measured log2(fold-change)). Subsets of the genomic loci may also be selected based on an algorithm, e.g., during the process of obtaining a classifier. Those of skill in the art will appreciate that such subsets of loci of Table 1, and loci included in such subsets, are together, individually, and / or in randomly selected subsets, at least as informative (e.g., as statistically significant and / or reliable) for uses disclosed herein, e.g., for determining basal / classical subtype status. The present disclosure particularly includes, among other things, subsets of the genomic loci of Table 1, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 or higher, 5.0 or higher, 4.5 or higher, 4.0 or higher, 3.5 or higher, 3.0 or higher, 2.5 or higher, 2.0 or higher, 1.9 or higher, 1.8 or higher, 1.7 or higher, 1.6 or higher, 1.5 or higher, 1.4 or higher, 1.3 or higher, 1.2 or higher, 1.1 or higher, 1.0 or higher, 0.9 or higher, 0.8 or higher, 0.7 or higher, 0.6 or higher, or 0.5 or higher. The present disclosure also includes subsets of the genomic loci of Table 1, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 to less than 6.0, 5.0 to less than 5.5, 4.5 to less than 5.0, 4.0 to less than 4.5, 3.8 to less than 4.0, 3.6 to less than 3.8, 3.4 to less than 3.6, 3.2 to less than 3.4, 3.0 to less than 3.2, 2.8 to less than 3.0, 2.6 to less than 2.8, 2.4 to less than 2.6, 2.2 to less than 2.4, 2.0 to less than 2.2, 1.8 to less than 2.0, 1.6 to less than 1.8, 1.4 to less than 1.6, 1.2 to less than 1.4, 1.0 to less than 1.2, 0.8 to less than 1.0, or 0.6 to less than 0.8.

[0164] In various embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, or 465 loci identified in Table 1 (or any subset thereof) are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer). In certain embodiments, a subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status (e.g., basal subtype status) if at least a number of loci identified in a Table 1 (or any subset thereof)Attorney Docket No.: DFS-34525 (DFCI 3605)having a lower bound selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, or 400 and an upper bound selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, or 465 is found to be differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer).

[0165] In various embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1000, 1100, 1200, 1300, 1400, 1500, 1600, 1700, 1800, 1900, 2000, 2100, 2200, 2300, 2400, 2500, 2600, 2700, or 2737 loci identified in Table 1 (or any subset thereof) are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer).

[0166] In some embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, or 170 loci identified in Table 1 as classical locus up are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer). In some embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, or 295 loci identified in Table 1 as basal locus up are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer).

[0167] In some embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, or 977 loci identified in Table 1 as classical locus up are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer). In some embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1000, 1100, 1200, 1300, 1400, 1500, 1600, 1700, or 1760 loci identified in Table 1 as basal locus up are differentially H3K4me3 modified as compared toAttorney Docket No.: DFS-34525 (DFCI 3605)a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer).

[0168] In certain particular embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 loci identified in Table 1 (e.g., about 1 to about 450, about 5 to about 400, about 10 to about 300, about 25 to about 200, about 5, about 10, about 20, or about 50 loci) are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with classical subtype cancer). In various embodiments a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of loci identified in Table 1 are differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer). In certain embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least a percent of loci identified in Table 1 having a lower bound selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10%, and an upper bound selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% is found to be differentially H3K4me3 modified as compared to a reference (e.g., a sample from a healthy subject or a subject with classical subtype cancer).

[0169] In various embodiments, differentially H3K4me3 modified refers to a methylation status characterized by an increase or decrease in a value measuring methylation (e.g., of read counts and / or normalized read counts for a given genomic locus), and / or a mean, median and / or mode thereof, and / or a log thereof (e.g., log base 2 (log2)), of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40-fold, 45-fold, 50-fold, or greater, or any range in between, inclusive, such as 1% to 50%, 50% to 2-fold, 25% to 50-fold, 25% to 30-fold, 25% to 20-fold, 25% to 16-fold, 30% to 16-fold, 50% to 16-fold, 70% to 16-fold, 2-fold to 16-fold, 2.2-fold to 16-fold, 2.6-fold to 16-fold, 3-fold to 16-fold, 3.4-fold to 16-fold, 4-fold to 16-fold, 4.5-fold to 16-fold, 5.2-fold to 16-fold, 6-fold to 16-fold, 7-fold to 16-fold, or 8-fold to 16-fold, as compared to a reference, optionally where the statistical significance of the increase or decrease is at least 5e-2, le-2, 5e-3, le-3, 5e-4, le-4, 5e-5, le-5, 5e-6, or le-6. In various embodiments, an increase or decrease in a value measuring methylation can be, or is expressed as, a log2(fold-change), e.g., a log2(fold-change) of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, or greater, or any range in between, inclusive, such as an increase or decrease ofO.1-fold to 10-fold, 0.2-fold to 5-fold, 0.2-fold to 4.0-fold, 0.4-4.0-fold, 0.4-fold to 4.0-fold, 0.6-fold to 4.0-fold, 0.8-fold to 4.0-fold, 1.0-fold to 4.0-fold. 1.2-fold to 4.0-fold. 1.4-Attorney Docket No.: DFS-34525 (DFCI 3605)fold to 4.0-fold, 1.6-fold to 4.0-fold, 1.8-fold to 4.0-fold, 2.0-fold to 4.0-fold, 2.2-fold to 4.0-fold, 2.4-fold to 4.0-fold, 2.6-fold to 4.0-fold, 2.8-fold to 4.0-fold, or 3.0-fold to 4.0-fold, optionally where the statistical significance of the increase or decrease is at least 5e-2, le-2, 5e-3, le-3, 5e-4, le-4, 5e-5, le-5, 5e-6, or le-6.Differential H3K27ac modification

[0170] Genomic loci demonstrating differential H3K27ac modification in basal subtype vs. classical subtype pancreatic cancer are provided in Table 2 which shows the chromosomal coordinates of each genomic locus and whether they are correlated with basal subtype or classical subtype pancreatic cancer (genomic loci in columns with “H3K27ac - Basal Locus Up” in the header correlate with basal subtype pancreatic cancer while genomic loci with “H3K27ac - Classical Locus Up” in the header correlate with classical subtype pancreatic cancer). The genomic loci are sorted based on their chromosomal coordinates which are based on human genome build GRCh37 / hgl9 (NCBI RefSeq assembly GCF_000001405.13).

[0171] A person of skill in the art will recognize that the methods disclosed herein do not require that every genomic locus listed in Table 2 be assessed for H3K27ac modification. Instead, a subset of loci may be assessed for H3K27ac modification. Subsets of the genomic loci of Table 2 can be selected (e.g., for use in determining basal / classical subtype status) based on various performance criteria, e.g., to select genomic loci that demonstrate differential modification with a particular level of statistical significance and / or a particular threshold of differential between relevant states (e.g., a measured log2(fold-change)). Subsets of the genomic loci may also be selected based on an algorithm, e.g., during the process of obtaining a classifier. Those of skill in the art will appreciate that such subsets of loci of Table 2, and loci included in such subsets, are together, individually, and / or in randomly selected subsets, at least as informative (e.g., as statistically significant and / or reliable) for uses disclosed herein, e.g., for determining basal / classical subtype status. See also the Examples encompassed by the present disclosure for experiments showing that informative classifiers can be generated using many different combinations of the loci. The present disclosure particularly includes, among other things, subsets of the genomic loci of Table 2, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 or higher, 5.0 or higher, 4.5 or higher, 4.0 or higher, 3.5 or higher, 3.0 or higher, 2.5 or higher, 2.0 or higher, 1.9 or higher, 1.8 or higher, 1.7 or higher, 1.6 or higher, 1.5 or higher, 1.4 or higher, 1.3 or higher, 1.2 or higher, 1.1 or higher, 1.0 or higher, 0.9 or higher, 0.8 or higher, 0.7 or higher, 0.6 or higher, or 0.5 or higher. The present disclosure also includes subsets of the genomic loci of Table 2, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 to less than 6.0, 5.0 to less than 5.5, 4.5 to less than 5.0, 4.0 to less than 4.5, 3.8 to less than 4.0, 3.6 to less than 3.8, 3.4 to less than 3.6, 3.2 to less than 3.4, 3.0 to less than 3.2, 2.8 to less than 3.0, 2.6 to less than 2.8, 2.4 to less than 2.6, 2.2 to less than 2.4, 2.0 to less than 2.2, 1.8 to lessAttorney Docket No.: DFS-34525 (DFCI 3605)than 2.0, 1.6 to less than 1.8, 1.4 to less than 1.6, 1.2 to less than 1.4, 1.0 to less than 1.2, 0.8 to less than 1.0, or 0.6 to less than 0.8.

[0172] In various embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 5500, 6000, 6500, 7000, 7500, 8000, 8500, 9000, 9500, 10000, 10500, 11000, 11500, 12000, 12500, 13000, 13500, 14000, 14500, 15000, 15500, 16000, 16500, 17000, 17500, 18000, 18500, 19000, 19500, 20000, 20500, 21000, 21500, or 21982 loci identified in Table 2 (or any subset thereof) are H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer).

[0173] In some embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 5500, 6000, 6500, 7000, 7500, 8000, 8500, 9000, 9500, 10000, or 10498 loci identified in Table 2 as classical locus up are differentially H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer). In some embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 5500, 6000, 6500, 7000, 7500, 8000, 8500, 9000, 9500, 10000, 10500, 11000, or 11484 loci identified in Table 2 as basal locus up are differentially H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer).

[0174] In certain embodiments, a subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least a number of loci identified in a Table 2 (or any subset thereof) having a lower bound selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 5500, 6000, 6500, 7000, 7500, 8000, 8500, 9000, 9500, or 10000 and an upper bound selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 5500, 6000, 6500, 7000, 7500, 8000, 8500, 9000, 9500, 10000, 10500, 11000, 11500, 12000, 12500, 13000, 13500, 14000, 14500, 15000, 15500, 16000, 16500, 17000, 17500, 18000, 18500, 19000, 19500, 20000, 20500, or 21000 is found to be H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtypeAttorney Docket No.: DFS-34525 (DFCI 3605)cancer). In certain particular embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 loci identified in Table 2 (e.g., about 1 to about 21,000, about 10 to about 10,000, about 5 to about 5,000, about 1 to about 1,000, about 5 to about 3,000, about 10 to about 1000, about 25 to about 200, about 5, about 10, about 20, or about 50 loci) are H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer). In various embodiments a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of loci identified in Table 2 are H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject or a subject with classical subtype cancer). In certain embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least a percent of loci identified in Table 2 having a lower bound selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10%, and an upper bound selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% is found to be H3K27ac modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer).

[0175] In various embodiments, differentially H3K27ac modified refers to an acetylation status characterized by an increase or decrease in a value measuring acetylation (e.g., of read counts and / or normalized read counts for a given genomic locus), and / or a mean, median and / or mode thereof, and / or a log thereof (e.g., log base 2 (log2)), of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40-fold, 45-fold, 50-fold, or greater, or any range in between, inclusive, such as 1% to 50%, 50% to 2-fold, 25% to 50-fold, 25% to 30-fold, 25% to 20-fold, 25% to 16-fold, 30% to 16-fold, 50% to 16-fold, 70% to 16-fold, 2-fold to 16-fold, 2.2-fold to 16-fold, 2.6-fold to 16-fold, 3-fold to 16-fold, 3.4-fold to 16-fold, 4-fold to 16-fold, 4.5-fold to 16-fold, 5.2-fold to 16-fold, 6-fold to 16-fold, 7-fold to 16-fold, or 8-fold to 16-fold, as compared to a reference, optionally where the statistical significance of the increase or decrease is at least 5e-2, le-2, 5e-3, le-3, 5e-4, le-4, 5e-5, le-5, 5e-6, or le-6. In various embodiments, an increase or decrease in a value measuring acetylation can be, or is expressed as, a log2(fold-change), e.g., a log2(fold-change) of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, or greater, or any range in between, inclusive, such as an increase or decrease of 0.1-fold to 10-fold, 0.2-fold to 5-fold, 0.2-fold to 4.0-fold, 0.4-4.0-fold, 0.4-fold to 4.0-fold, 0.6-fold to 4.0-fold, 0.8-fold to 4.0-fold, 1.0-fold to 4.0-fold. 1.2-fold to 4.0-fold. 1.4-fold to 4.0-fold, 1.6-fold to 4.0-fold, 1.8-fold to 4.0-fold, 2.0-fold to 4.0-fold, 2.2-fold to 4.0-fold, 2.4-Attorney Docket No.: DFS-34525 (DFCI 3605)fold to 4.0-fold, 2.6-fold to 4.0-fold, 2.8-fold to 4.0-fold, or 3.0-fold to 4.0-fold, optionally where the statistical significance of the increase or decrease is at least 5e-2, le-2, 5e-3, le-3, 5e-4, le-4, 5e-5, le-5, 5e-6, or le-6.Differential MeDIP modification

[0176] Genomic loci demonstrating differential DNA methylation in basal subtype vs. classical subtype pancreatic cancer are provided in Table 3 which shows the chromosomal coordinates of each genomic locus and whether they are correlated with basal subtype or classical subtype pancreatic cancer (genomic loci in columns with “MeDIP - Basal Locus Up” in the header correlate with basal subtype pancreatic cancer while genomic loci with “MeDIP- Classical Locus Up” in the header correlate with classical subtype pancreatic cancer). The genomic loci are sorted based on their chromosomal coordinates which are based on human genome build GRCh37 / hgl9 (NCBI RefSeq assembly GCF_000001405.13).

[0177] A person of skill in the art will recognize that the methods disclosed herein do not require that every genomic locus listed in Table 3 be assessed for MeDIP modification. Instead, a subset of loci may be assessed for MeDIP modification. Subsets of the genomic loci of Table 3 can be selected (e.g., for use in determining basal / classical subtype status) based on various performance criteria, e.g., to select genomic loci that demonstrate differential modification with a particular level of statistical significance and / or a particular threshold of differential between relevant states (e.g., a measured log2(fold-change)). Subsets of the genomic loci may also be selected based on an algorithm, e.g., during the process of obtaining a classifier. Those of skill in the art will appreciate that such subsets of loci of Table 3, and loci included in such subsets, are together, individually, and / or in randomly selected subsets, at least as informative (e.g., as statistically significant and / or reliable) for uses disclosed herein, e.g., for determining basal / classical subtype status. The present disclosure particularly includes, among other things, subsets of the genomic loci of Table 3, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 or higher, 5.0 or higher, 4.5 or higher, 4.0 or higher, 3.5 or higher, 3.0 or higher, 2.5 or higher, 2.0 or higher, 1.9 or higher, 1.8 or higher, 1.7 or higher, 1.6 or higher, 1.5 or higher, 1.4 or higher, 1.3 or higher, 1.2 or higher, 1.1 or higher, 1.0 or higher, 0.9 or higher, 0.8 or higher, 0.7 or higher, 0.6 or higher, or 0.5 or higher. The present disclosure also includes subsets of the genomic loci of Table 3, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 to less than 6.0, 5.0 to less than 5.5, 4.5 to less than 5.0, 4.0 to less than 4.5, 3.8 to less than 4.0, 3.6 to less than 3.8, 3.4 to less than 3.6, 3.2 to less than 3.4, 3.0 to less than 3.2, 2.8 to less than 3.0, 2.6 to less than 2.8, 2.4 to less than 2.6, 2.2 to less than 2.4, 2.0 to less than 2.2, 1.8 to less than 2.0, 1.6 to less than 1.8, 1.4 to less than 1.6, 1.2 to less than 1.4, 1.0 to less than 1.2, 0.8 to less than 1.0, or 0.6 to less than 0.8.

[0178] In various embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 1, 2, 3, 4, 5, 6, 7, 8,Attorney Docket No.: DFS-34525 (DFCI 3605)9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, or 274 loci identified in Table 3 (or any subset thereof) are differentially MeDIP modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer). In certain embodiments, a subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status (e.g., basal subtype status) if at least a number of loci identified in a Table 3 (or any subset thereof) having a lower bound selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, or 200 and an upper bound selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, or 274 is found to be differentially MeDIP modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer).

[0179] In some embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 120, or 142 loci identified in Table 3 as classical locus up are differentially MeDIP modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer). In some embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 120, or 132 loci identified in Table 3 as basal locus up are differentially MeDIP modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer).

[0180] In certain particular embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 1, 2, 3, 4, 5, 10, 20, 30, 40, or 50 loci identified in Table 3 (e.g., about 1 to about 270, about 5 to about 200, about 10 to about 150, about 25 to about 100, about 5, about 10, about 20, or about 50 loci) are differentially MeDIP modified as compared to a reference (e.g., a sample from a healthy subject or a subject with classical subtype cancer). In various embodiments a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% of loci identified in Table 3 are differentially MeDIP modified as compared to a reference (e.g., a sample from a healthy subject, a subject with classical subtype cancer, or a subject with basal subtype cancer). In certain embodiments, a sample or subject from which the sample is obtained or derived, is determined to have a particular basal / classical subtype status if at least a percent of loci identified in Table 3 having a lower bound selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10%, and an upper bound selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% is found to be differentially MeDIP modified as compared to a reference (e.g., a sample from a healthy subject or a subject with classical subtype cancer).Attorney Docket No.: DFS-34525 (DFCI 3605)

[0181] In various embodiments, differentially MeDIP modified refers to a methylation status characterized by an increase or decrease in a value measuring methylation (e.g., of read counts and / or normalized read counts for a given genomic locus), and / or a mean, median and / or mode thereof, and / or a log thereof (e.g., log base 2 (log2)), of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40-fold, 45-fold, 50-fold, or greater, or any range in between, inclusive, such as 1% to 50%, 50% to 2-fold, 25% to 50-fold, 25% to 30-fold, 25% to 20-fold, 25% to 16-fold, 30% to 16-fold, 50% to 16-fold, 70% to 16-fold, 2-fold to 16-fold, 2.2-fold to 16-fold, 2.6-fold to 16-fold, 3-fold to 16-fold, 3.4-fold to 16-fold, 4-fold to 16-fold, 4.5-fold to 16-fold, 5.2-fold to 16-fold, 6-fold to 16-fold, 7-fold to 16-fold, or 8-fold to 16-fold, as compared to a reference, optionally where the statistical significance of the increase or decrease is at least 5e-2, le-2, 5e-3, le-3, 5e-4, le-4, 5e-5, le-5, 5e-6, or le-6. In various embodiments, an increase or decrease in a value measuring methylation can be, or is expressed as, a log2(fold-change), e.g., a log2(fold-change) of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, or greater, or any range in between, inclusive, such as an increase or decrease of 0.1-fold to 10-fold, 0.2-fold to 5-fold, 0.2-fold to 4.0-fold, 0.4-4.0-fold, 0.4-fold to 4.0-fold, 0.6-fold to 4.0-fold, 0.8-fold to 4.0-fold, 1.0-fold to 4.0-fold. 1.2-fold to 4.0-fold. 1.4-fold to 4.0-fold, 1.6-fold to 4.0-fold, 1.8-fold to 4.0-fold, 2.0-fold to 4.0-fold, 2.2-fold to 4.0-fold, 2.4-fold to 4.0-fold, 2.6-fold to 4.0-fold, 2.8-fold to 4.0-fold, or 3.0-fold to 4.0-fold, optionally where the statistical significance of the increase or decrease is at least 5e-2, 1e-2, 5e-3, 1e-3, 5e-4, 1e-4, 5e-5, 1e-5, 5e-6, or 1e-6.Differential chromatin accessibility or transcription factor binding

[0182] Genomic loci provided in Tables 1-3 can also demonstrate differential chromatin accessibility or transcription factor binding in basal subtype vs. classical subtype pancreatic cancer.

[0183] In various embodiments, without wishing to be bound by any particular scientific theory, histone methylation (e.g., H3K4me3) corresponds and / or is correlated with chromatin accessibility. In various embodiments, without wishing to be bound by any particular scientific theory, histone acetylation (e.g., H3K27ac) corresponds and / or is correlated with chromatin accessibility. In various embodiments, without wishing to be bound by any particular scientific theory, DNA methylation corresponds and / or is correlated with chromatin accessibility.

[0184] In some embodiments, without wishing to be limited to any particular scientific theory, chromatin accessibility corresponds and / or is correlated with H3K4me3 modifications. As a result, in some embodiments, basal / classical subtype status may be determined by detecting and quantifying chromatin accessibility at one or more genomic loci in Table 1 in accordance with the section above discussing exemplary genomic loci with differential H3K4me3 modifications.Attorney Docket No.: DFS-34525 (DFCI 3605)

[0185] In some embodiments, without wishing to be limited to any particular scientific theory, chromatin accessibility corresponds and / or is correlated with H3K27ac modifications. As a result, in some embodiments, basal / classical subtype status may be determined by detecting and quantifying chromatin accessibility at one or more genomic loci in Table 2 in accordance with the section above discussing exemplary genomic loci with differential H3K27ac modifications.

[0186] In some embodiments, without wishing to be limited to any particular scientific theory, chromatin accessibility corresponds and / or is correlated with MeDIP modifications. As a result, in some embodiments, basal / classical subtype status may be determined by detecting and quantifying chromatin accessibility at one or more genomic loci in Table 3 in accordance with the section above discussing exemplary genomic loci with differential MeDIP modifications.

[0187] In various embodiments, without wishing to be bound by any particular scientific theory, histone methylation (e.g., H3K4me3) corresponds and / or is correlated with transcription factor binding. In various embodiments, without wishing to be bound by any particular scientific theory, histone acetylation (e.g., H3K27ac) corresponds and / or is correlated with transcription factor binding. In various embodiments, without wishing to be bound by any particular scientific theory, DNA methylation corresponds and / or is correlated with transcription factor binding.

[0188] In some embodiments, without wishing to be limited to any particular scientific theory, binding of RNA pol II corresponds and / or is correlated with H3K4me3 modifications. As a result, in some embodiments, basal / classical subtype status may be determined by detecting and quantifying binding of RNA pol II at one or more genomic loci in Table 1 in accordance with the section above discussing exemplary genomic loci with differential H3K4me3 modifications.

[0189] In some embodiments, without wishing to be limited to any particular scientific theory, binding of p300, mediator complex, cohesin complex or RNA pol II corresponds and / or is correlated with H3K27ac modifications. As a result, in some embodiments, basal / classical subtype status may be determined by detecting and quantifying binding of p300, mediator complex, cohesin complex or RNA pol II at one or more genomic loci in Table 2 in accordance with the section above discussing exemplary genomic loci with differential H3K27ac modifications.Applications

[0190] Methods and compositions encompassed by the present disclosure include analysis of differentially modified genomic loci to determine transcriptional subtype of a pancreatic cancer in subject. Methods and compositions encompassed by the present disclosure can be used in any of a variety of applications. For example, methods and compositions encompassed by the present disclosure can be used in detecting and / or treating pancreatic cancer based on classical / basal subtype status.Attorney Docket No.: DFS-34525 (DFCI 3605)

[0191] In various embodiments, methods, kits and systems encompassed by the present disclosure can be applied to an asymptomatic human subject. As used herein, a subject can be referred to as “asymptomatic” if the subject does not report, and / or demonstrate by non-invasively observable indicia (e.g., without one, several, or all of device-based probing, tissue sample analysis, bodily fluid analysis, surgery, or cancer screening), sufficient characteristics of cancer to support a medically reasonable suspicion that the subject is likely suffering from cancer, e.g., pancreatic cancer. Detection of early-stage cancer can be achieved using methods, kits and systems encompassed by the present disclosure, with attendant medical benefits including potential for early treatment and attendant improvement in therapeutic outcomes.

[0192] In various embodiments, methods, kits and systems encompassed by the present disclosure can be applied to a symptomatic human subject. As used herein, a subject can be referred to as “symptomatic” if the subject report, and / or demonstrates by non-invasively observable indicia (e.g., without one, several, or all of device-based probing, tissue sample analysis, bodily fluid analysis, surgery, or cancer screening), sufficient characteristics of cancer to support a medically reasonable suspicion that the subject is likely suffering from pancreatic cancer. For example, in various embodiments a sample from a subject, optionally where the subject has a pancreatic cancer that is of unknown transcriptional status, can be assayed according to one or more embodiments encompassed by the present disclosure to determine if the pancreatic cancer is classical or basal subtype. In various embodiments a sample from a subject, where the subject has a pancreatic cancer that is known or suspected of having a basal subtype, can be assayed according to one or more embodiments encompassed by the present disclosure to determine if the pancreatic cancer is in fact basal subtype or classical subtype.

[0193] Those of skill in the art will appreciate that regular, preventative, and / or prophylactic screening to detect classical / basal subtype of pancreatic cancer improves diagnosis, prognosis, and / or treatment of pancreatic cancer. Thus, the present disclosure provides, among other things, methods and compositions particularly useful for the diagnosis and treatment of pancreatic cancer (e.g., basal subtype pancreatic cancer). Generally, and particularly in embodiments in which transcriptional subtype detection in accordance with the present disclosure is carried out annually, and / or in which a subject is has recently been diagnosed with pancreatic cancer, methods, kits, and systems encompassed by the present disclosure are especially likely to detect early stages of disease, which can be useful, e.g., for treatment selection and improved therapeutic outcomes.

[0194] In various embodiments basal / classical subtype determination in accordance with the present disclosure is performed once for a given subject or multiple times for a given subject. In various embodiments, basal / classical subtype determination in accordance with the present disclosure is performed on a regular basis, e.g., every six months, annually, every two years, every three years, every four years, every five years, or every ten years.Attorney Docket No.: DFS-34525 (DFCI 3605)

[0195] In various embodiments, methods, kits and systems disclosed herein provide a determination of basal / classical subtype status. In other instances, methods, kits and systems disclosed herein will be indicative of basal / classical subtype status but not definitive for basal / classical subtype status. In various instances in which methods, kits and systems encompassed by the present disclosure are used to determine basal / classical subtype status, the same can be followed by a further confirmatory assay, which further assay can confirm, support, undermine, or reject a determination resulting from a prior determination, e.g., a determination in accordance with the present disclosure. As used herein, a confirmatory assay can be a test that is currently recognized by medical practitioners, e.g., based on tissue-based profiling.

[0196] In various embodiments, basal / classical subtype status determination according to one or more methods, kits and / or systems disclosed herein is followed by treatment of cancer. In various embodiments, treatment of cancer includes administration of a therapeutic regimen including one or more cancer therapies provided herein, including without limitation one or more of a basal subtype targeted therapy or a classical subtype targeted therapy, surgery, radiation, endocrine therapy, chemotherapy, and / or immunotherapy. In various embodiments, treatment of cancer includes administration of a therapeutic regimen including one or more treatments provided herein as available, appropriate, and / or preferred for a particular basal / classical subtype status.

[0197] In various embodiments, methods, kits and systems can be used to determine whether a particular subject and / or cancer is likely to be and / or is characterized as responsive to a basal subtype therapeutic agent (e.g., a KRAS inhibitor) or a classical subtype therapeutic agent. In some such embodiments, methods, kits and systems can be followed by treatment of the subject with a basal subtype or a classical subtype therapeutic agent.

[0198] In various embodiments, methods, kits and systems can be used to determine whether a particular subject is likely to be and / or is characterized as resistant to, non-responsive to, or not recommended treatment with a basal subtype-targeted agent or a classical subtype-targeted agent. In some such embodiments, methods, kits and systems can be followed by treatment with a therapeutic agent to a different target.

[0199] Responsiveness can refer to the ability or likelihood of a therapy to cause a reduction in tumor size or inhibit tumor growth or metastasis. Responsiveness can refer to improvement in prognosis (e.g., increased time to cancer recurrence or increased life expectancy, e.g., overall survival, recurrence-free survival, metastasis-free survival, or disease-free survival). Responsiveness can refer to achievement of a treatment benefit, including e.g., improvement in one or more symptoms of cancer, e.g., pancreatic cancer. Responsiveness can be measured quantitatively (e.g., as in the case of tumor size; as in the case of measurement of histone modification, chromatin accessibility, or transcription factor binding at one or more genomic loci; or as in the calculation of clinical benefit (CBR)), or qualitatively (e.g., by measures such as “pathological complete response” (pCR), “clinicalAttorney Docket No.: DFS-34525 (DFCI 3605)complete remission” (cCR), “clinical partial remission” (cPR), “clinical stable disease” (cSD), “clinical progressive disease” (cPD), or other qualitative criteria). Resistance can refer to the inability or unlikelihood of a therapy to achieve a desired therapeutic effect (e.g., a reduction in tumor size, improvement in prognosis, or other treatment benefit such as, e.g., improvement in one or more symptoms of cancer) in a subject and / or cancer. Resistance includes both acquired and natural resistance. In certain embodiments, resistance includes the extent to which one or more desired therapeutic benefits results from administration of a therapy to a subject and / or cancer is less than that expected and / or achieved in a reference (e.g., less than 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, or 10% of benefit achieved in a reference).

[0200] In some embodiments, methods, kits and systems for basal / classical subtype status determination provided herein can inform treatment and / or payment (e.g., reimbursement for or reduction of cost of medical care, such as detecting or treatment) decisions and / or actions, e.g., by individuals, healthcare facilities, healthcare practitioners, health insurance providers, governmental bodies, or other parties interested in healthcare cost.

[0201] In some embodiments, methods, kits and systems for basal / classical subtype status determination provided herein can inform decision making relating to whether health insurance providers reimburse a healthcare cost payer or recipient (or not), e.g., for (1) basal / classical subtype status determination itself (e.g., reimbursement for detecting otherwise unavailable, available only for periodic / regular detecting, or available only for temporally- and / or incidentally- motivated detecting); and / or for (2) treatment, including initiating, maintaining, and / or altering therapy, e.g., based on the determined basal / classical subtype status. For example, in some embodiments, methods, kits and systems for basal / classical subtype status determination provided herein are used as the basis for, to contribute to, or support a determination as to whether a reimbursement or cost reduction will be provided to a healthcare cost payer or recipient. In some instances, a party seeking reimbursement or cost reduction can provide results of basal / classical subtype status determination conducted in accordance with the present disclosure together with a request for such reimbursement or reduction of a healthcare cost. In some instances, a party making a determination as to whether or not to provide a reimbursement or reduction of a healthcare cost will reach a determination based in whole or in part upon receipt and / or review of results of basal / classical subtype status determination conducted in accordance with the present disclosure.

[0202] In various embodiments, basal / classical subtype status determination using methods, kits and systems disclosed herein can be used in classifying subjects, samples, and / or tumors (e.g., pancreatic cancer subjects, samples, and / or tumors). In various embodiments, methods, kits and systems disclosed herein can be used to generate a set of subjects, samples, and / or tumors identified according to the present methods, kits and systems each classified as corresponding to a particular basal / classical subtype status, and optionally using two or more of such classified subjects, samples,Attorney Docket No.: DFS-34525 (DFCI 3605)and / or tumors to identify biomarkers that distinguish the classes (i.e., distinguish the subjects, samples, and / or tumors according to their class, e.g., according to their basal / classical subtype status).

[0203] For illustration purposes and without limitation, in an exemplary assay encompassed by the present disclosure, samples obtained from a subject (e.g., a liquid biopsy sample including cfDNA, e.g., a plasma sample including cfDNA) is analyzed by ChlP-seq for a histone modification (e.g., H3K4me3 and / or H3K27ac). ChlP-seq sequence reads are aligned to human genome build GRCh37 / hgl9 (NCBI RefSeq assembly GCF_000001405.13), e.g., using the Burrows-Wheeler Aligner (BWA). Non-uniquely mapping and redundant reads are optionally discarded. To provide one example of peak calling, MACS v2.1.1.20140616 can be used for ChlP-seq peak calling with aq-value (FDR) threshold of 0.01. ChlP-seq data quality can optionally be evaluated by any of one or more of a variety of measures, including total peak number, FRiP (fraction of reads in peak) score, number of high-confidence peaks (e.g., enriched > ten-fold over background), and percent of peak overlap with “blacklist” DHS peaks derived from the ENCODE project (Amemiya et al., Sci Rep (2019) 9(1): 9354). If the ChlP-seq data quality is below a particular threshold the data may be discarded and the assay repeated. ChlP-seq peaks that overlap with selected genomic loci that are differentially modified as provided herein for the relevant histone modification (Tables 1-2) can then be used to determine basal / classical subtype status. The number of reads overlapping the selected genomic loci for the relevant histone modification are summed, e.g., in some embodiments all the genomic loci that are differentially modified with an absolute log2(fold-change) > 4.0 are selected. In some embodiments, the average number of reads in the local background of each ChlP-seq peak is subtracted to improve signal to noise. The data is then log2 -transformed and quantile normalized to match the distribution of the data used to train the classifier.

[0204] For the avoidance of any doubt, those of skill in the art will appreciate from the present disclosure that methods, kits and systems for basal / classical subtype status determination encompassed by the present disclosure are at least for in vitro use. Accordingly, all aspects and embodiments encompassed by the present disclosure can be performed and / or used at least in vitro.

[0205] Those of skill in the art will also appreciate that, in certain embodiments, methods encompassed by the present disclosure can be implemented on and / or in conjunction with a computer program and computer system. In some embodiments, methods encompassed by the present disclosure can be implemented on and / or in conjunction with a non-transitory computer readable storage medium encoded with the computer program, wherein the program comprises instructions that when executed by one or more processors cause the one or more processors to perform operations to perform the method. A computer system can also store and manipulate data generated by methods encompassed by the present disclosure that comprise a plurality of genomic locus modification status and / or accessibility status changes / profiles, which data can be used by a computer system in implementing methods disclosed herein. In certain embodiments, a computer system (i) receivesAttorney Docket No.: DFS-34525 (DFCI 3605)modification status and / or accessibility status data; (ii) stores the data; and (iii) compares the data in any number of ways described herein (e.g., analysis relative to appropriate references), e.g., to determine basal / classical subtype status. In certain embodiments, a computer system (i) compares the genomic locus modification and / or accessibility status to a reference; and (ii) outputs an indication of whether the modification status and / or accessibility status of the genomic locus is significantly different from the reference and / or provides a determination regarding basal / classical subtype status.

[0206] Numerous types of computer systems can be used to implement methods encompassed by the present disclosure according to knowledge possessed by a skilled artisan in the bioinformatics and / or computer arts. Several software components can be loaded into memory during operation of such a computer system. The software components can comprise both software components that are standard in the art and components that are special to the present disclosure (e.g., dCHIP software described in Lin et al., Bioinformatics (2004) 20: 1233-1240, incorporated herein by reference in its entirety; radial basis machine learning algorithms (RBM) known in the art). Methods encompassed by the present disclosure can also be programmed or modeled in mathematical software packages that allow symbolic entry of equations and high-level specification of processing, including specific algorithms to be used, thereby freeing a user of the need to procedurally program individual equations and algorithms. Such packages include, e.g., Matlab from Mathworks (Natick, MA), Mathematica from Wolfram Research (Champaign, IL), S-Plus from MathSoft (Seattle, WA), R from R Foundation for Statistical Computing (Vienna, Austria), Python from Python Software Foundation (Wilmington, DE), or Perl from Perl Foundation (Holland, MI). In certain embodiments, a computer system comprises a database for storage of genomic locus modification status and / or accessibility status data. Such stored profiles can be accessed and used to perform comparisons of interest at a later point in time. In addition to the exemplary program structures and computer systems described herein, other, alternative program structures and computer systems will be readily apparent to the skilled artisan.

[0207] Various algorithms can be applied to the comparison, between samples and references, of the modification status and / or accessibility status of genomic loci that are differentially modified in basal and classical subtype pancreatic cancers. In various embodiments, an algorithm can be a single learning statistical classifier system. Other suitable statistical algorithms are well known to those of skill in the art. For example, learning statistical classifier systems include a machine learning algorithmic technique capable of adapting to complex data sets (e.g., a panel of genomic loci of interest) and making decisions based upon such data sets. In some embodiments, a single learning statistical classifier system such as a classification tree (e.g., random forest) is used. In other embodiments, a combination of 2, 3, 4, 5, 6, 7, 8, 9, 10, or more learning statistical classifier systems are used, preferably in tandem. Examples of learning statistical classifier systems include, but are not limited to, those using inductive learning (e.g., decision / classification trees such as random forests,Attorney Docket No.: DFS-34525 (DFCI 3605)classification and regression trees (C& RT), boosted trees, etc.), Probably Approximately Correct (PAC) learning, connectionist learning (e.g., neural networks (NN), artificial neural networks (ANN), neuro fuzzy networks (NFN), network structures, perceptrons such as multi-layer perceptrons, multilayer feed-forward networks, applications of neural networks, Bayesian learning in belief networks, etc.), reinforcement learning (e.g., passive learning in a known environment such as naive learning, adaptive dynamic learning, and temporal difference learning, passive learning in an unknown environment, active learning in an unknown environment, learning action-value functions, applications of reinforcement learning, etc.), and genetic algorithms and evolutionary programming. Other learning statistical classifier systems include support vector machines (e.g., Kernel methods), multivariate adaptive regression splines (MARS), Levenberg-Marquardt algorithms, Gauss-Newton algorithms, mixtures of Gaussians, gradient descent algorithms, and learning vector quantization (LVQ). In certain embodiments, methods encompassed by the present disclosure can include sending classification results to a medical practitioner, e.g., an oncologist.Formulation and Administration of Therapeutic Agents

[0208] The present disclosure includes methods where a therapeutic agent or regimen is administered to a subject based on the basal / classical subtype status of a pancreatic cancer. In general, the therapeutic agent or regimen provided herein will be available, appropriate, and / or preferred for the determined basal / classical subtype status. Those of skill in the art will be aware of recommended and / or governmentally approved formulations and / or dosages for various therapeutic agents provided herein.

[0209] The present disclosure includes pharmaceutical compositions for delivery of one or more therapeutic agents to a subject. As disclosed herein, a pharmaceutical composition may be in any form known in the art, including formulations for administration according to any route known in the art. A suitable means of administration can be selected based on the age and condition of a subject.

[0210] Pharmaceutical composition forms encompassed by the present disclosure can include, e.g., liquid, semi-solid and solid dosage forms. Pharmaceutical composition forms encompassed by the present disclosure can include, e.g., liquid solutions (e.g., injectable and infusible solutions), dispersions or suspensions, tablets, pills, powders, and liposomes. Selection or use of any particular form may depend, in part, on the intended mode of administration and therapeutic application. Accordingly, the compositions can be formulated for administration by a parenteral mode (e.g., intravenous, subcutaneous, intraperitoneal, or intramuscular injection) or a non-parenteral mode. As used herein, parenteral administration refers to modes of administration other than enteral and topical administration, usually by injection or infusion.Attorney Docket No.: DFS-34525 (DFCI 3605)

[0211] In some embodiments, the compositions provided herein are present in unit dosage form, which unit dosage form can be suitable for self-administration. Such a unit dosage form may be provided within a container, e.g., a pill, vial, cartridge, prefdled syringe, or disposable pen.

[0212] A pharmaceutical composition encompassed by the present disclosure can be in an injectable or infusible form. For example, the present disclosure includes sterile formulations for injection or infusion, which can be formulated in accordance with conventional pharmaceutical practices. Sterile solutions can be prepared by incorporating a composition described herein in the required amount in an appropriate solvent with one or a combination of ingredients enumerated above, as required, followed by filter sterilization. Solutions can be formulated, e.g., using distilled water, physiological saline, or an isotonic solution containing glucose and other supplements such as D-sorbitol, D-mannose, D-mannitol, or sodium chloride as an aqueous solution for injection, optionally in combination with a suitable solubilizing agent, for example, an alcohol such as ethanol and / or a polyalcohol such as propylene glycol or polyethylene glycol, and / or a nonionic surfactant such as polysorbate 80™ or HCO-50, and the like. In the case of sterile powders for the preparation of sterile injectable solutions, methods for preparation include vacuum drying and freeze-drying that yield a powder of a composition described herein plus any additional desired ingredient (see below) from a previously sterile-filtered solution thereof. The proper fluidity of a solution can be maintained, for example, by the use of a coating such as lecithin, by the maintenance of the required particle size in the case of dispersion and by the use of surfactants. Prolonged absorption of injectable compositions can be brought about by including in the composition a reagent that delays absorption, for example, monostearate salts, and gelatin. In particular instances, a pharmaceutical composition can be formulated, for example, as a buffered solution at a suitable concentration and suitable for storage, e.g., at 2-8°C (e.g., 4°C).

[0213] In various embodiments, a pharmaceutical composition encompassed by the present disclosure can be formulated as a solution, microemulsion, dispersion, liposome, or other ordered structure suitable for stable storage at high concentration. Generally, dispersions are prepared by incorporating a composition described herein into a sterile vehicle that contains a basic dispersion medium and the required other ingredients from those enumerated above.

[0214] In various instances, a pharmaceutical composition can be formulated to include a pharmaceutically acceptable carrier or excipient. Examples of pharmaceutically acceptable carriers include, without limitation, any and all solvents, dispersion media, coatings, antibacterial and antifungal agents, isotonic and absorption delaying agents, and the like that are physiologically compatible.

[0215] In certain embodiments, compositions can be formulated with a carrier that will protect the therapeutic agent against rapid release, such as a controlled release formulation, including implants and microencapsulated delivery systems. Biodegradable, biocompatible polymers can beAttorney Docket No.: DFS-34525 (DFCI 3605)used, such as ethylene vinyl acetate, polyanhydrides, polyglycolic acid, collagen, polyorthoesters, and polylactic acid. Many methods for the preparation of such formulations are known in the art. See, e.g., J. R. Robinson (1978) “Sustained and Controlled Release Drug Delivery Systems,” Marcel Dekker, Inc., New York.

[0216] Route of administration can be parenteral, for example, administration by injection. Administration by injection can be by intravenous injection, intramuscular injection, intraperitoneal injection, subcutaneous injection. Administration can be systemic or local. In certain embodiments, a composition described herein can be therapeutically delivered to a subject by way of local administration. As used herein, “local administration” or “local delivery,” can refer to delivery that does not rely upon transport of the composition or therapeutic agent to its intended target tissue or site via the vascular system. For example, the composition may be delivered by injection or implantation of the composition or therapeutic agent or by injection or implantation of a device containing the composition or therapeutic agent. In certain embodiments, following local administration in the vicinity of a target tissue or site, the composition or therapeutic agent, or one or more components thereof, may diffuse to an intended target tissue or site that is not the site of administration.

[0217] A pharmaceutical composition can be administered parenterally in the form of an injectable formulation comprising a sterile solution or suspension in water or another pharmaceutically acceptable liquid. For example, a pharmaceutical composition can be formulated by suitably combining the therapeutic molecule with pharmaceutically acceptable vehicles or media, such as sterile water and physiological saline, vegetable oil, emulsifier, suspension agent, surfactant, stabilizer, flavoring excipient, diluent, vehicle, preservative, binder, followed by mixing in a unit dose form required for generally accepted pharmaceutical practices. Examples of oily liquid include sesame oil and soybean oil, and it may be combined with benzyl benzoate or benzyl alcohol as a solubilizing agent. Other items that may be included are a buffer such as a phosphate buffer, or sodium acetate buffer, a soothing agent such as procaine hydrochloride, a stabilizer such as benzyl alcohol or phenol, and an antioxidant. The formulated injection can be packaged in a suitable ampule.

[0218] In various embodiments, subcutaneous administration can be accomplished by means of a device, such as a syringe, a prefilled syringe, an auto-injector (e.g., disposable or reusable), a pen injector, a patch injector, a wearable injector, an ambulatory syringe infusion pump with subcutaneous infusion sets, or other device for combining with a therapeutic agent for subcutaneous injection.

[0219] An injection system encompassed by the present disclosure may employ a delivery pen as described in U. S. Pat. No. 5,308,341. Pen devices, most commonly used for self-delivery of insulin to patients with diabetes, are well known in the art. Such devices can include at least one injection needle, are typically pre-filled with one or more therapeutic unit doses of a solution that includes the therapeutic agent and are useful for rapidly delivering solution to a subject with as little pain as possible. One medication delivery pen includes a vial holder into which a vial of a therapeuticAttorney Docket No.: DFS-34525 (DFCI 3605)or other medication may be received. The pen may be an entirely mechanical device or it may be combined with electronic circuitry to accurately set and / or indicate the dosage of medication that is injected into the user. See, e.g., U. S. Pat. No. 6,192,891. In some embodiments, the needle of the pen device is disposable and the kits include one or more disposable replacement needles. Pen devices suitable for delivery of any one of the presently featured compositions are also described in, e.g., U. S. Pat. Nos. 6,277,099; 6,200,296; and 6,146,361, the disclosures of each of which are incorporated herein by reference in their entirety. A microneedle-based pen device is described in, e.g., U. S. Pat. No. 7,556,615, the disclosure of which is incorporated herein by reference in its entirety. See also the Precision Pen Injector (PPI) device, MOLLY™, manufactured by Scandinavian Health Utd.

[0220] In certain embodiments, administration of a therapeutic agent as described herein is achieved by administering to a subject a nucleic acid encoding a therapeutic agent described herein. Nucleic acids encoding a therapeutic agent described herein can be incorporated into a gene construct to be used as a part of a gene therapy protocol to deliver nucleic acids that can be used to express and produce therapeutic agent within cells. Expression constructs of such components may be administered in any therapeutically effective carrier, e.g., any formulation or composition capable of effectively delivering the component gene to cells in vivo. Approaches include insertion of the subject gene in viral vectors including recombinant retroviruses, adenovirus, adeno-associated virus, lentivirus, and herpes simplex virus-1 (HSV-1), or recombinant bacterial or eukaryotic plasmids. Viral vectors can transfect cells directly; plasmid DNA can be delivered with the help of, for example, cationic liposomes (lipofectin) or derivatized, polylysine conjugates, gramicidin S, artificial viral envelopes or other such intracellular carriers, as well as direct injection of the gene construct or CaPO₄ precipitation. Examples of suitable retroviruses include adenovirus-derived vectors, adeno-associated virus (AAV), pLJ, pZIP, pWE, and pEM which are known to those skilled in the art.

[0221] In some embodiments, a composition can be formulated for storage at a temperature below 0°C (e.g., -20°C or -80°C). In some embodiments, the composition can be formulated for storage for up to 2 years (e.g., one month, two months, three months, four months, five months, six months, seven months, eight months, nine months, 10 months, 11 months, 1 year, or 2 years) at 2-8°C (e.g., 4°C). Thus, in some embodiments, the compositions described herein are stable in storage for at least 1 year at 2-8°C (e.g., 4°C).

[0222] A pharmaceutical composition can include a therapeutically effective amount of a therapeutic agent described herein. Such effective amounts can be readily determined by one of ordinary skill in the art. A therapeutically effective amount can be an amount at which any toxic or detrimental effects of the composition are outweighed by therapeutically beneficial effects. In some embodiments, a dose can also be chosen to reduce or avoid production of antibodies or other host immune responses against a therapeutic agent. Those of skill in the art will appreciate that data obtained from cell culture assays and animal studies can be used in formulating a range of dosage forAttorney Docket No.: DFS-34525 (DFCI 3605)use in humans. In various embodiments, the amount of active ingredient included in a pharmaceutical composition is such that a suitable dose within the designated range can be administered to subjects. The dose and method of administration can vary depending on weight, age, condition, and other characteristics of a patient, and can be suitably selected as needed by those skilled in the art.

[0223] Pharmaceutical compositions including certain therapeutic agents, e.g., therapeutic antibodies, can be administered as a fixed dose, or in a milligram per kilogram (mg / kg) dose. While in no way intended to be limiting, an exemplary single dose of certain pharmaceutical compositions described herein can include certain therapeutic agents as described herein in an amount equal to, e.g., 0.001 to 1000 mg / kg, 1-1000 mg / kg, 1-100 mg / kg, 0.5-50 mg / kg, 0.1-100 mg / kg, 0.5-25 mg / kg, 1-20 mg / kg, and 1-10 mg / kg body weight. Exemplary dosages of a composition described herein include, without limitation, 0.1 mg / kg, 0.5 mg / kg, 1 mg / kg, 2 mg / kg, 4 mg / kg, 8 mg / kg, or 20 mg / kg. The present disclosure is not limited to such ranges or dosages.

[0224] The present disclosure further includes methods of preparing pharmaceutical compositions encompassed by the present disclosure and kits including pharmaceutical compositions encompassed by the present disclosure.

[0225] In various embodiments, therapeutic agents encompassed by the present disclosure can be administered to a subject in a course of treatment that further includes administration of one or more additional therapeutic agents or therapies that are not therapeutic agents (e.g., surgery or radiation). Combination therapies encompassed by the present disclosure can include simultaneous exposure of a subject to therapeutic agents of two or more therapeutic regimens.

[0226] In certain embodiments, a therapeutic agent as described herein can be administered together with (e.g., at the same time and / or in the same composition as) an additional agent or therapy. In certain embodiments, a therapeutic agent encompassed by the present disclosure can be administered separately from an additional therapeutic agent or therapy (e.g., at a different time and / or in a different composition than the additional therapeutic agent or therapy). Dosing regimens of a therapeutic agent and one or more additional therapeutic agents with which it is administered in combination can be coordinated or independently determined. In various embodiments, an additional therapeutic agent or therapy administered in combination with a therapeutic agent as described herein can be administered at the same time as therapeutic agent, on the same day as therapeutic agent, or in the same week as therapeutic agent. In various embodiments, an additional therapeutic agent or therapy administered in combination with a therapeutic agent as described herein can be administered such that administration of the therapeutic agent and the additional therapeutic agent or therapy are separated by one or more hours before or after, one or more days before or after, one or more weeks before or after, or one or more months before or after administration of the therapeutic agent. In various embodiments, the administration frequency and / or dosage of one or more additional therapeutic agents can be the same as, similar to, or different from the administration frequency of aAttorney Docket No.: DFS-34525 (DFCI 3605)therapeutic agent. In some embodiments, the two or more regimens can be administered simultaneously; in some embodiments, such regimens can be administered sequentially (e.g., all “doses” of a first regimen are administered prior to administration of any doses of a second regimen); in some embodiments, such therapeutic agents are administered in overlapping dosing regimens.

[0227] In certain embodiments, administration of a therapeutic agent can be to a subject having previously received, scheduled to receive, or in the course of a treatment regimen including an additional cancer therapy. Administration of a therapeutic agent can, in some instances, improve delivery or efficacy of another therapeutic agent or therapy with which it is administered in combination.

[0228] It is contemplated that therapeutic agent combination therapies can demonstrate synergy and / or greater-than-additive effects between a therapeutic agent and one or more additional therapeutic agents with which it is administered in combination. A therapeutic agent can be administered in any effective amount as determined independently or as determined by the joint action of therapeutic agent and any of one or more additional therapeutic agents or therapies administered. Administration of the therapeutic agent may, in some embodiments, reduce the therapeutically effective dosage, required dosage, or administered dosage of the additional therapeutic agent or therapy relative to a reference regimen for administration of additional therapeutic agent or therapy or therapy absent the therapeutic agent. In certain embodiment, a composition described herein can replace or augment other previously or currently administered therapy. For example, upon treating with therapeutic agent, administration of one or more additional therapeutic agents or therapies can cease or diminish, e.g., be administered at lower levels.Kits

[0229] The present disclosure includes kits for detecting modification and / or accessibility of one or more genomic loci. In some embodiments, the present disclosure provides kits for quantifying one or more histone modifications and / or chromatin accessibility at one or more genomic loci. Kits encompassed by the present disclosure can include, e.g., reagents such as buffers and / or antibodies useful in the detection and quantification of histone modifications. In certain embodiments, a kit encompassed by the present disclosure can include at least one antibody that selective binds a histone modification selected from H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, or H3K4me3, or pan acetylation. In certain embodiments, a kit encompassed by the present disclosure can include at least one antibody that selective binds H3K4me3 modifications. In certain embodiments, a kit encompassed by the present disclosure can include at least one antibody that selective binds H3K27ac modifications. A kit encompassed by the present disclosure can include instructional materials disclosing or describing the use of the kit in a method of determining basal / classical subtype status of a pancreatic cancer and / or treatment disclosed herein. In variousAttorney Docket No.: DFS-34525 (DFCI 3605)embodiments, a kit encompassed by the present disclosure can include one or more therapeutic agents useful in the treatment of pancreatic cancer, e.g., as disclosed herein, optionally in combination with instruction materials for treatment of pancreatic cancer based on basal / classical status.

[0230] In some embodiments, a kit encompassed by the present disclosure comprises reagents for quantifying one or more histone modifications and / or chromatin accessibility at one or more genomic loci, wherein the one or more genomic loci are selected from Tables 1-2.

[0231] In some embodiments, the kit comprises reagents for quantifying H3K4me3 for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1. In some embodiments, the kit comprises reagents for quantifying H3K27ac for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2. In some embodiments, the kit comprises one or more antibodies for use in ChlP-seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac-modified histones.

[0232] In some embodiments, the kit comprises reagents for isolation of cell-free DNA (cfDNA) from a liquid biopsy sample. In some embodiments, the kit comprises reagents for library preparation for sequencing. In some embodiments, the kit comprises reagents for sequencing. In some embodiments, the kit comprises instructions for determining if a subject has a basal subtype or classical subtype pancreatic cancer.Systems

[0233] The present disclosure includes systems for detecting modification and / or accessibility of one or more genomic loci. In some embodiments, the present disclosure provides systems for quantifying one or more histone modifications and / or chromatin accessibility at one or more genomic loci. Systems encompassed by the present disclosure can include a sequencer configured to generate a sequencing data set from a sample; and a non-transitory computer readable storage medium and / or a computer system.

[0234] In some embodiments, the non-transitory computer readable storage medium is encoded with a computer program, wherein the program comprises instructions that when executed by one or more processors cause the one or more processors to perform operations to perform a method encompassed by the present disclosure.

[0235] In some embodiments, the computer system comprises a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform a method encompassed by the present disclosure.

[0236] In some embodiments, the sequencer is configured to generate a Whole Genome Sequencing (WGS) data set from the sample. In some embodiments, the system also includes a sample preparation device configured to prepare the sample for sequencing from a biological sample, optionally a liquid biopsy sample. The sample preparation device may include reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or moreAttorney Docket No.: DFS-34525 (DFCI 3605)transcription factors, and / or DNA methylation at one or more genomic loci in cell-free DNA (cfDNA) from the biological sample, optionally the liquid biopsy sample.

[0237] Systems encompassed by the present disclosure can include, e.g., reagents such as buffers and / or antibodies useful in the detection and quantification of histone modifications. In certain embodiments, a system encompassed by the present disclosure can include at least one antibody that selective binds H3K4me3 modifications. In certain embodiments, a system encompassed by the present disclosure can include at least one antibody that selective binds H3K27ac modifications. A system encompassed by the present disclosure can include instructional materials disclosing or describing the use of the system in a method of determining basal / classical subtype status of pancreatic cancer and / or treatment disclosed herein.

[0238] In some embodiments, a system encompassed by the present disclosure comprises reagents for quantifying one or more histone modifications and / or chromatin accessibility at one or more genomic loci, wherein the one or more genomic loci are selected from Tables 1-2.

[0239] In some embodiments, the system comprises reagents for quantifying H3K4me3 for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1. In some embodiments, the system comprises one or more antibodies for use in ChlP-seq, optionally wherein the one or more antibodies specifically bind H3K4me 3 -modified histones.

[0240] In some embodiments, the system comprises reagents for quantifying H3K27ac for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2. In some embodiments, the system comprises one or more antibodies for use in ChlP-seq, optionally wherein the one or more antibodies specifically bind H3K27ac-modified histones.

[0241] In some embodiments, the system comprises reagents for measuring chromatin accessibility via an ATAC-seq assay.

[0242] In some embodiments, the system comprises reagents for isolation of cell-free DNA (cfDNA) from a liquid biopsy sample. In some embodiments, the sequencer comprises reagents for library preparation for sequencing. In some embodiments, the sequencer comprises reagents for sequencing. In some embodiments, the system comprises instructions for determining if a subject has a basal or classical subtype of pancreatic cancer.

[0243] EXAMPLES

[0244] The present Examples demonstrate the identification and use of differentially modified and / or differentially accessible genomic loci in cfDNA in plasma samples obtained from subjects with basal and classical subtypes of pancreatic cancer. The present Examples show that differentially modified and / or differentially accessible genomic loci encompassed by the presentAttorney Docket No.: DFS-34525 (DFCI 3605)disclosure can be used to determine basal / classical status from cfDNA in plasma samples obtained from subjects with basal subtype pancreatic cancer and classical subtype pancreatic cancer.

[0245] The following examples are set forth so as to provide those of ordinary skill in the art with a complete disclosure and description of how to make and use the presently disclosed embodiments, and are not intended to limit the scope of what the inventors regard as their invention. It will be appreciated that the scope of the invention is to be defined by that which may be understood from the embodiments disclosed herein and the claims rather than by the specific embodiments that have been presented by way of example.Example 1: Materials and Methods

[0246] The present Example describes the materials and methods that were used to generate sequencing data that was then used in Example 2 to identify differentially modified genomic loci in basal subtype and classical subtype pancreatic cancers.Patient-derived xenografts acquisition

[0247] Patient-derived xenografts (PDX) were derived from patients with pancreatic ductal adenocarcinoma (PDAC) from 2 institutions: Dana-Farber Cancer Institute (DFCI) and MD Anderson Cancer Center (MDACC). Tumors were established by subcutaneous implantation of patient tumor samples and expanded through serial transplantation in mice. Briefly, tumors were collected from patients, sectioned into small fragments (2x2x2mm), and implanted subcutaneously into 6-8-week-old female nude mice (Charles River Laboratories). Tumor growth was monitored, and when tumors reached around 2cm, they were excised, fragmented, and re-implanted. This process was repeated to expand the model in vivo across multiple generations. PDX models provided by MDACC were developed and established as previously described (Carugo A, et al. In Vivo Functional Platform Targeting Patient-Derived Xenografts Identifies WDR5-Myc Association as a Critical Determinant of Pancreatic Cancer. Cell Reports. 2016 Jun; 16(1): 133-47) by implanting tissue fragments at 4x4x4 mm3fragment volume subcutaneously into the right flank of 6-8 week old NSG mice. Tumor volumes were captured by serial caliper measurements weekly. Tumor volume (TV) was calculated as TV = (D × d2 / 2), where “D” is the larger and “d” is the smaller superficial visible diameter of the tumor mass. All measurements were documented as mm3. At the endpoint of the study, tumors were collected and fixed in 10% neutral buffered formalin overnight and then processed and embedded in paraffin for histology analysis or snap frozen in liquid nitrogen for sequencing analysis.PDX tissue chromatin immunoprecipitation followed by sequencing (ChlP-seq)

[0248] Frozen tissue was pulverized using the Covaris cryoPREP® system and fixed with 2 mmol / L disuccinimidyl glutarate for 10 minutes followed by 1% formaldehyde for 10 minutes and quenched with glycine. Chromatin was sheared using the Covaris E220 ultrasonicator and then incubated overnight with the following antibodies coupled with 40 pL protein A and protein G beadsAttorney Docket No.: DFS-34525 (DFCI 3605)(Invitrogen) at 4°C overnight: H3K27ac (Abeam #ab4729), H3K4me3 (Thermo Fisher Scientific #PA5-27029). Five percent of the sample was not exposed to antibody and was used as a control “input”. Beads were washed three times each with Low-Salt Wash Buffer (0.1% SDS, 1% Triton X- 100, 2 mmol / L EDTA, 20 mmol / L Tris-HCl pH 7.5, 150 mmol / L NaCl), High-Salt Wash Buffer (0.1% SDS, 1% Triton X-100, 2 mmol / L EDTA, 20 mmol / L Tris-HCl pH 7.5, 500 mmol / L NaCl), and LiCl Wash Buffer (10 mmol / L Tris pH 7.5, 250 mmol / L LiCl, 1% NP-40, 1% Na-Doc, 1 mmol / L EDTA) and rinsed with TE buffer (pH 8.0) once. Samples were then de-cross-linked, treated with RNase and proteinase K, and DNA was extracted using MinElute® PCR Purification Kit (Qiagen). DNA sequencing libraries were prepared from the purified immunoprecipitated and input DNA using the ThruPLEX® DNA-seq Kit (TakaraBio). Libraries were sequenced on an Illumina HiSeq 4000 to generate 150 bp paired-end reads (Novogene Corporation).PDX tissue assay for transposase-accessible chromatin sequencing (ATAC-seq)

[0249] Frozen tissue was resuspended and dounce homogenized in 1,000 pL of homogenization buffer. Nuclei were filtered using a 70-pm Flowmi strainer, isolated using iodixanol density-gradient centrifugation method, and washed with RSB buffer (10 mmol / L Tris-HCl pH 7.4, 10 mmol / L NaCl, and 3 mmol / L MgCl2in water). Approximately fifty thousand nuclei were resuspended in 50 pL of transposition mix [2.5 pL transposase (100 nmol / L), 16.5 pL PBS, 0.5 pL 1% digitonin, 0.5 pL 10% Tween-20, and 5 pL water]. Transposition reactions were incubated at 37°C for 30 minutes in a thermomixer shaking at 1,000 rpm. Reactions were cleaned with Qiagen columns. Libraries were amplified using the Omni-ATAC protocol and sequenced on an Illumina platform (Novogene Corporation) using 150-base paired-end reads. See Corces MR, et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat Methods. 2017 Oct 1; 14( 10): 959— 62 and Buenrostro JD, et al. ATAC-seq: A Method for Assaying Chromatin Accessibility Genome-Wide. CP Molecular Biology [Internet]. 2015 Jan [cited 2025 Mar 19]; 109(1). PDX tissue Methylated DNA immunoprecipitation followed by sequencing (MeDIP-seq)

[0250] Methylated DNA immunoprecipitation sequencing (MeDIP-seq) was performed on tissue and plasma following published methods. See Shen SY, et al. Sensitive tumour detection and classification using plasma cell-free DNA methylomes. Nature. 2018 Nov;563(7732):579-83; Shen SY, et al. Preparation of cfMeDIP-seq libraries for methylome profiling of plasma cell-free DNA. Nat Protoc. 2019 Oct;14(10):2749-80; Nuzzo PV, et al. Detection of renal cell carcinoma using plasma and urine cell-free DNA methylomes. Nat Med. 2020 Jul 1;26(7): 1041-3; and Berchuck JE, et al. Detecting Neuroendocrine Prostate Cancer Through Tissue-Informed Cell-Free DNA Methylation Analysis. Clinical Cancer Research. 2022 Mar l;28(5):928-38. Library preparation was performed on 10 ng of DNA using the KAPA HyperPrep® Kit (KAPA Biosystems). Then end-repair, A-tailing, and ligation of NEBNext® adaptors (NEBNext® Multiplex Oligos for Illumina kit, New England BioLabs) were performed. Libraries were digested using the USER enzyme (New England BioLabs).Attorney Docket No.: DFS-34525 (DFCI 3605)X DNA, consisting of unmethylated and in vitro methylated DNA, was added to prepared libraries to achieve a total amount of 100 ng DNA. Methylated and unmethylated Arabidopsis thaliana DNA (Diagenode) was added for quality control. MeDIP was performed using the MagMeDIP Kit (Diagenode) following the manufacturer’s protocol. Samples were purified using the iPure Kit v2 (Diagenode). Success of the immunoprecipitation was confirmed using qPCR to detect recovery of the spiked-in Arabidopsis thaliana methylated and unmethylated DNA. KAPA HiFi Hotstart ReadyMix (KAPA Biosystems) and NEBNext® Multiplex Oligos for Illumina (New England Biolabs) were added to a final concentration of 0.3 pmol / L and libraries were amplified. Samples were pooled and sequenced (Novogene Corporation) on Illumina HiSeq 4,000 to generate 150 bp paired-end reads. PDX tissue RNA sequencing

[0251] RNA was extracted from frozen tumor samples using the Qiagen RNeasy Mini Kit (CatNo. / ID: 74104). RNA sequencing (RNA-seq) libraries were constructed from 1 pg RNA using the Illumina TruSeq® Stranded mRNA LT Sample Prep Kit. Barcoded libraries were pooled and sequenced on the Illumina Novaseq X plus platform. FASTQ files were processed using the VIPER workflow. Cornwell M, et al. VIPER: Visualization Pipeline for RNA-seq, a Snakemake workflow for efficient and complete RNA-seq analysis. BMC Bioinformatics. 2018 Dec;19(l):135. Read alignment to human genome build GRCh37 / hgl9 (NCBI RefSeq assembly GCF_000001405.13) was performed with STAR (RRID: SCR_004463). Dobin A, et al. STAR: ultrafast universal RNA-seq aligner.Bioinformatics. 2013 Jan 1;29(1): 15— 21. Cufflinks (RRID: SCR_014597) was used to assemble transcript-level expression data from filtered alignments. Trapnell C, et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc. 2012 Mar;7(3):562-78.Plasma samples acquisition

[0252] Plasma samples from patients with metastatic pancreatic cancer were obtained from (A) a randomized phase II trial (NCT03520790), (B) a prospective nonrandomized clinical trial MOSCATO-01 / 02, (C) a retrospective collection of plasma samples from patients at DFCI under protocol 03-189. All patients provided written informed consent. Studies were conducted in accordance with recognized ethical guidelines.Circulating tumor (ct)DNA estimation in plasma samples

[0253] Cell-free (cf)DNA extraction and low-pass whole-genome sequencing (LPWGS) were performed on plasma samples using previously published methods. See El Zarif T, et al.Detecting Small Cell Transformation in Patients with Advanced EGFR Mutant Lung Adenocarcinoma through Epigenomic cfDNA Profding. Clinical Cancer Research. 2024 Sep 3;30(17):3798— 811. The ichorCNA R package (RRID: SCR_024768) was used to infer copy-number profdes and cfDNA tumor content from read abundance across bins spanning the genome using default parameters.Attorney Docket No.: DFS-34525 (DFCI 3605)Adalsteinsson VA, et al. Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors. Nat Commun. 2017 Nov 6;8( 1): 1324.Cell-free chromatin immunoprecipitation followed by sequencing (cfChlP-seq)

[0254] An example protocol for cfChlP-seq used for initial analysis (e.g., as shown in FIG.6A) is as follows. One microgram of antibody was coupled with 10 pL protein A (Invitrogen, cat #10002D) and 10 pL protein G (Invitrogen, cat #10004D) for at least 6 hours at 4°C with rotation in 0.5% BSA (Jackson Immunology, cat #001-000-161) in PBS (Gibco, cat #14190250), followed by blocking with 1 % BSA in PBS for 1 hour at 4°C with rotation. The following antibodies were used: H3K27ac (Abeam #ab4729) and H3K4me3 (Thermo Fisher Scientific #PA5-27029). A total of 800 pL of thawed plasma was centrifuged at 3,000 g for 15 minutes at 4°C. The supernatant was precleared with the magnetic beads with 20 pL protein A and 20 pL protein G for 2 hours at 4°C. Then, the precleared and conditioned plasma was subjected to antibody-coupled magnetic beads overnight with rotation at 4°C. The reclaimed magnetic beads were washed with 1 m of each washing buffer twice. Three washing buffers were used in following order: low salt washing buffer (0.1% SDS, 1% Triton X-100, 2 mmol / L EDTA, 150 mmol / L NaCl, 20 mmol / L Tris-HCl pH 7.5), high salt buffer (0.1% SDS, 1% Triton X-100, 2 mmol / L EDTA, 500 mmol / L NaCl, 20 mmol / L Tris-HCl pH 7.5), and LiCl washing buffer (250 mmol / L LiCl, 1% NP-40, 1% Na Deoxycholate, 1 mmol / L EDTA, 10 mmol / L Tris-HCl pH 7.5). Subsequently, the beads were rinsed with TE buffer (Thermo Fisher Scientific, cat #BP2473500) and resuspended and incubated in 100 pL of DNA extraction buffer containing 0.1 mol / L NaHCO3, 1% SDS, and 0.6 mg / mL Proteinase K (Qiagen, cat #19131) and 0.4 mg / mL RNaseA (Thermo Fisher Scientific, cat #12091021) for 10 minutes at 37°C, for 1 hour at 50°C and for 90 minutes at 65°C. DNA was purified through phenol extraction (Invitrogen, cat #15593031) and ethanol precipitation was performed with 3 mol / L NaOAc (Ambion, cat #AM9740) and glycogen (Ambion, cat #AM9510). Cell-free ChlP-seq (cfChlP-seq) libraries were prepared with ThruPLEX DNA-Seq Kit (Takara Bio, cat #R400675) following the manufacturer’s instructions. After library amplification, the DNA was purified by AMPure XP (Beckman coulter, cat# A63880). The library was submitted for the 150 base-pair paired-end sequencing on an Illumina NovaSeq6000 system (Novogene Corporation). Baca SC, et al. Liquid biopsy epigenomic profiling for cancer subtyping. Nat Med. 2023 Nov;29(l 1):2737— 41.

[0255] cfChlP-seq analysis for the Examples below was performed according to the following protocol. Twenty-five micrograms of antibody were conjugated to 5mg of Dynabeads M-270 Epoxy (Invitrogen, cat # 1431 ID) according to the manufacturer instructions. After coupling, beads were stored at 4 °C and pre-cleared in 0.1% BSA in PBS for 5 min at 4 °C prior to use. The following antibodies were used: H3K27ac (Abeam #ab4729) and H3K4me3 (Thermo Fisher Scientific #711958). 810 pl of thawed plasma was supplemented with protease inhibitor cocktail (Roche, 11873580001), centrifuged at 3,000g for 15 min at 4 °C, and combined with 90 pl of salt-Attorney Docket No.: DFS-34525 (DFCI 3605)detergent. The resulting 900uL of plasma was incubated with lug of antibody-coupled magnetic beads at 4°C with rotation. Beads were washed three times each with Low-Salt Wash Buffer (0.1% SDS, 1% Triton X-100, 2 mmol / L EDTA, 150 mmol / L NaCl, 20 mmol / L Tris-HCl pH 7.5), High-Salt Wash Buffer (0.1% SDS, 1% Triton X-100, 2 mmol / L EDTA, 500 mmol / L NaCl, 20 mmol / L Tris-HCl pH 7.5), and LiCl Wash Buffer (250 mmol / L LiCl, 1% NP-40, 1% Na Deoxycholate, 1 mmol / L EDTA, 10 mmol / L Tris-HCl pH 7.5) and rinsed with TE buffer once (Thermo Fisher Scientific, cat #BP2473500). Subsequently, beads were resuspended and incubated in 100 pL of DNA extraction buffer containing 0.1 mol / L NaHCO3, 1% SDS, and 0.6 mg / mL Proteinase K (Qiagen, cat #19131) and 0.4 mg / mL RNaseA (Thermo Fisher Scientific, cat #12091021) for 10 minutes at 37°C, for 1 hour at 50°C and for 2 hours at 65°C. DNA was purified using the ChIP DNA Clean & Concentrator Kit (Zymo Research, cat #D5205). Cell-free ChlP-seq (cfChlP-seq) libraries were prepared with ThruPLEX DNA-Seq Kit (Takara Bio, cat #R400675) following the manufacturer’s instructions. After library amplification, the DNA was purified by AMPure XP (Beckman coulter, cat# A63880). The library was submitted for the 150 base-pair paired-end sequencing on an Illumina NovaSeq6000 system (Novogene Corporation).Refinement of enhancer-centric (ATAC and H3K27ac) epigenomic signature

[0256] Sites that were both differentially marked by H3K27ac and differentially accessible were classified as “intersection” sites. Their performance was compared to regions that were exclusively differentially accessible (“ATAC-only”), exclusively differentially marked by H3K27ac (“H3K27ac-only”), as well as the complete sets of differential ATAC peaks and differential H3K27ac peaks. For each site set, an aggregate signal per sample was computed by summing the values across all sites and normalizing by the number of sites in the set. To quantify subtype separation, exhaustive pairwise comparisons between all classical and basal-like samples was performed. For each classical-basal sample pair, we calculated the absolute difference in normalized aggregate signal, generating a distribution of pairwise subtype separation values for each site set. The mean separation across these pairwise comparisons was then used to evaluate the discriminatory capacity of each region category using a Wilcoxon signed-rank test.Refinement of promoter-centric (H3K4me3) epigenomic signature

[0257] Promoter regions were defined across a range of log fold-change (LFC) thresholds, and for each threshold we calculated the per-sample normalized aggregate signal across selected promoters. Similar to the framework described above, subtype separation was then quantified as the absolute difference in normalized signal across all pairwise combinations of classical and basal-like samples. For each classical-basal sample pair, the absolute difference in normalized aggregate signal, generating a distribution of pairwise subtype separation values for each site set was calculated. The mean separation across these pairwise comparisons was then used to evaluate the discriminatory capacity of each region category using a Wilcoxon signed-rank test.Attorney Docket No.: DFS-34525 (DFCI 3605)Data Analysis and Statistics

[0258] Unless differently stated, all pairwise tests are unpaired and two-tailed Wilcoxon rank sum tests. All reported boxplot are based on first quartile, median, and third quartile, with whiskers extending up to 1.5 IQR. Unless otherwise stated, all correlation coefficients are Spearman R rounded to the second digit. Survival data was extracted from the MOSCTAO-02 trial (NCT01566019), a evaluating the use of high throughput molecular analysis to treat patients with metastatic cancer with targeted therapeutics, a randomized phase I / II study evaluating the use paricalcitol plus gemcitabine and nab-paclitaxel in patients with metastatic pancreatic cancer (NCT03520790), and collected retrospectively for patients treated at Dana-Farber Cancer Institute. Kaplan-Meier curves and log-rank P values were computed and plotted using the survival and survminer R packages. Reported analyses and plots were created with R 4.4.0 with tidyverse packages. Given the retrospective nature of this study, no randomization was applied. No power analysis was conducted, and size was dictated by sample availability.Data availability

[0259] Raw human sequencing data generated and analyzed in this study are being deposited in dbGaP under controlled access to protect participant privacy (accession pending). These datasets include (1) tissue ChlP-seq profiling of histone modifications (H3K4me3, and H3K27ac), ATAC-seq, MeDIP-seq, and RNA-seq for all PDX models, (2) plasma cfChlP-seq profiling of histone modifications (H3K4me3, and H3K27ac), cfMeDIP-seq, and low-pass whole-genome sequencing. Code availability

[0260] Scripts to reproduce analyses from this study are available on the World Wide Web at github.com / Baca-Lab / scripts-cfChlP-PDAC).Example 2: Determining classical-basal transcriptional subtypes of pancreatic ductal adenocarcinoma using circulating tumor DNA epigenomic profiling

[0261] Classical (C) and basal (B) transcriptional subtypes are key prognostic biomarkers of pancreatic cancers such as, e.g., pancreatic ductal adenocarcinoma (PDAC). Current subtyping methods rely on tissue biopsies, which may not capture subtype heterogeneity, and are difficult to implement clinically. The present example describes a novel non-invasive approach for PDAC subtyping using circulating tumor DNA (ctDNA) epigenomic profiling.

[0262] To characterize the epigenetic landscape of classical and basal PDAC, bulk RNA-seq, chromatin immunoprecipitation and sequencing (ChlP-seq) for H3K27ac and H3K4me3, assay for transposase-accessible chromatin sequencing (ATAC-seq), and methylated DNA immunoprecipitation sequencing (MeDIP-seq) were performed on PDAC patient derived xenografts (PDXs), as depicted in FIG. 1. PDXs were selected over primary pancreatic tumors because primary tumors have a high stromal content making epithelial tumor characterization challenging. Moreover,Attorney Docket No.: DFS-34525 (DFCI 3605)larger tumor volumes can be obtained from PDX models. To determine the PDX transcriptional subtypes, we performed bulk RNA-sequencing and employed PurlST, which is a single-sample classifier for tumor subtyping in pancreatic cancer, and categorizes tumors along a spectrum of strong, likely, and lean (Rashid NU, et al. Purity Independent Subtyping of Tumors (PurlST), A Clinically Robust, Single-sample Classifier for Tumor Subtyping in Pancreatic Cancer. Clinical Cancer Research. 2020 Jan l;26(l):82-92.). Chromatin immunoprecipitation and sequencing (ChlP-seq) was performed for two histone post-translational modifications: H3K27ac and H3K4me3. H3K27ac is enriched at active gene promoters and enhancers (Creyghton MP, et al. Histone H3K27ac separates active from poised enhancers and predicts developmental state. Proc Natl Acad Sci USA. 2010 Dec 14; 107(50):21931- 6.), and H3K4me3 is enriched at active or bivalent gene promoters (O’Geen H, et al. Using ChlP-Seq Technology to Generate High-Resolution Profiles of Histone Modifications. In: Tollefsbol TO, editor. Epigenetics Protocols [Internet]. Totowa, NJ: Humana Press; 2011 [cited 2025 Mar 30], p. 265-86. (Methods in Molecular Biology)). Assay of transposase accessible chromatin (ATAC-seq) was also performed to profile chromatin accessibility (Buenrostro JD, et al.Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat Methods. 2013 Dec;10(12): 1213-8; Corces MR, et al. The chromatin accessibility landscape of primary human cancers. Science. 2018 Oct 26;362(6413):eaavl898.) and methylated CpG dinucleotide immunoprecipitation and sequencing (MeDIP-seq) for DNA methylation (Mohn F, Weber M, Schiibeler D, Roloff TC. Methylated DNA Immunoprecipitation (MeDIP). In: Tost J, editor. DNA Methylation [Internet]. Totowa, NJ: Humana Press; 2009 [cited 2025 Mar 30], p. 55-64. (Walker JM, editor. Methods in Molecular Biology); Jones PA. Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat Rev Genet. 2012 Jul;13(7):484-92).

[0263] Specifically, 28 PDAC PDXs (C = 18, B = 10) were profiled with ChlP-seq (H3K27Ac, H3K4me3), ATAC-seq and MeDIP-seq as described in Example 1 above. Specifically, among these 28 PDX models, 28 were analyzed by RNA-seq, H3K27ac, and MeDIP-seq; 27 were analyzed by ATAC-seq (18 classical and 9 basal -like) and by H3K4me3 (17 classical and 10 basal-like), and 26 were analyzed by H3K27me3 (17 classical and 9 basal-like).

[0264] Classical PDAC tumors were confirmed to exhibit a gain of signals at promoters of canonical classical subtype marker genes, including CLDN18, GATA6, and HNF1A (FIG. 2). In contrast, basal tumors demonstrated increased signal in key regulators of EMT and basal-like genes including KRT6A, PTGES, and SNAI2 (FIG. 2).Subtype calling of PDAC PDXs

[0265] Classical and basal transcriptional subtypes were identified using bulk RNA-seq and the purity-independent subtyping (PurlST) algorithm. See Rashid NU, et al. Purity Independent Subtyping of Tumors (PurlST), A Clinically Robust, Single-sample Classifier for Tumor Subtyping inAttorney Docket No.: DFS-34525 (DFCI 3605)Pancreatic Cancer. Clinical Cancer Research. 2020 Jan l;26(l):82-92. Briefly, PurlST is a singlesample classifier that compares the expression of eight gene pairs to develop a probability of classical and basal tumors. PurlST classifications were also compared with Moffitt subtype assignments and showed complete concordance across all 28 PDX models used in the subsequent analyses.Epigenomic peak calling

[0266] Chromatin immunoprecipitation sequencing (ChlP-seq) reads were aligned to the human genome build GRCh37 / hgl9 (NCBI RefSeq assembly GCF_000001405.13) using the Burrows-Wheeler Aligner version 0.7.17 (RRID: SCR_010910. Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009 Mar 4;10(3): R25. Non-uniquely mapped and redundant reads were discarded. MACS v2.1.1.20140616 (RRID: SCR_013291) was used for ChlP-seq peak calling with a q-value threshold of 0.01. Zhang Y, et al. Model-based Analysis of ChlP-Seq (MACS). Genome Biol.2008 Sep 17;9(9): R137. IGV v2.8.2 was used to visualize normalized ChlP-seq read counts at specific genomic loci. Robinson JT, et al. Integrative genomics viewer. Nat Biotechnol. 2011 Jan;29(l):24-6. ChlP-seq heatmaps were generated with deepTools v3.3.1 (RRID: SCR_016366) and show normalized read counts at the peak center ±2 kb unless otherwise noted. Ramirez F, et al. deepTools: a flexible platform for exploring deep-sequencing data. Nucleic Acids Research. 2014 Jul 1;42(W1): W187-91. Overlap of ChlP-seq peaks was assessed using BEDTools v2.26.0. Peaks were considered overlapping if they shared one or more base pairs. For plasma data including cfChlP-seq profiling of histone modifications (H3K4me3, and H3K27ac), cfMeDIP-seq, low-pass whole-genome sequencing we used the SNAPIE (Streamlined Nextflow Analysis Pipeline for Immunoprecipitationbased Epigenomics) with default parameters.Defining set of genomic loci to distinguish classical vs. basal-like PDAC

[0267] H3K27ac and H3K4me3 ChlP-seq, and ATAC-seq from classical and basal-like PDAC PDX were compared to identify genomic loci (peaks) with significant enrichment in the two above groups referred as “classical-up” and “basal-up” peaks. A union set of peaks was created using BEDTools, and narrowPeak calls from MACS were used for H3K27ac, H3K4me3 and ATAC. The number of unique aligned reads overlapping each genomic locus (peak) in each sample is calculated from BAM files using BEDtools, to create a count matrix in which each row represents a peak, and each column represents a sample. Read counts for each peak were normalized to the total number of mapped reads for each sample. Differential features between C-B PDXs for various epigenetic features were identified using DESeq2. Using DESeq2, subtype-enriched peaks are identified at a defined false discovery rate (FDR)-q value and log2 fold-change (LFC) thresholds (for H3K27ac and ATAC: FDR-q < 0.05, |LFC| > 0; for H3K4me3: FDR-q < 0.05, |LFC| > 0).

[0268] Unsupervised hierarchical clustering was performed based on Spearman correlation between samples. Principal component analysis was performed using the prcomp R function (data notAttorney Docket No.: DFS-34525 (DFCI 3605)shown). The GREAT analysis (V4.0.4) was used to assess enrichment of Gene Ontology (GO) annotations among genes near differential ChlP-seq peaks, assigning each peak to the nearest gene within 500 kb. Results are shown in FIGs. 3A-3E. Classical and basal-like PDAC models clearly separated when analyzing activated regions marked by H3K27ac, H3K4me3 and ATAC-seq peaks, whereas global DNA methylation was less discriminatory.

[0269] Differential regions associated with classical and basal-like subtype for each epigenetic feature were investigated. Using DESeq2, the following sites were identified: 54,922 differentially marked H3K27ac regions (22,136 enriched in classical PDAC; “classical-up”; FDR-q<0.05; data not shown), 8,754 differential H3K4me3 regions (3,808 classical-up; FDR-q<0.05), 48,088 differentially accessible ATAC-seq regions (21,479 classical-up peaks; FDR-q<0.05) and 752 differentially methylated regions on MeDIP-seq (442 classical-up; FDR-q<0.05). The H3K27ac classical-up sites were enriched for regions related to pancreas embryonic development and function and with motifs for transcription factors important for pancreatic lineage determination and known relevance to classical subtype biology, such as GATA6 and HNF4A (data not shown). Conversely, H3K27ac sites upregulated in the basal-like subtype were enriched for pathways associated with epithelial-mesenchymal transition (EMT) and epidermal development and p63 binding motifs (data not shown), consistent with earlier reports.Validation on a Published PDX cohort

[0270] The ability of these differential epigenomic regions to distinguish classical and basal-like PDAC subtypes in an independent set of previously published PDAC PDX models was investigated (Lomberk G, et al. Distinct epigenetic landscapes underlie the pathobiology of pancreatic cancer subtypes. Nat Commun. 2018 May 17;9( 1): 1978.). RNA-seq and ChlP-seq data from 24 external PDAC PDXs was reanalyzed, identifying 17 strong classical PDAC and 3 strong basal -like PDXs, with the remainder categorized as “likely” or “lean” classical using PurlST (data not shown). Unsupervised hierarchical clustering and PCA of combined internal and previously published PDAC PDXs using H3K27ac signal clearly segregated the models by transcriptional subtype, despite technical variations in protocols and reagents utilized between our cohort and the external cohort. Furthermore, in the external validation PDX cohort, clear on-off patterns were observed across the differentially marked and accessible sites identified using our in-house PDX dataset (data not shown). These results indicate highly recurrent epigenomic differences between PDAC transcriptional subtypes.Refinement of peaks ATAC with H3K27ac

[0271] For the differential regions identified by H3K4me3 ChlP-seq, a stringent threshold of FDR-q < 0.01 and |LFC| > 3 was applied, thereby retaining 465 highly specific sites. Setting the stringency for the differential H3K4me3 ChlP-seq sites (FDR-q < 0.01 and log2 fold-change (LFC) >Attorney Docket No.: DFS-34525 (DFCI 3605)2), retained 2,737 highly specific sites (977 classical-up and 1,760 basal-up sites), led to the highest signal discrimination between the two subtypes compared to other LFC thresholds (all p<10-10; data not shown). These 2,737 H3K4me3differentially accessible sites are provided in Table 1 below.

[0272] To refine this epigenomic signature by reducing the number of sites used to stratify PDAC subtypes, which could facilitate the development of hybrid capture assays in the future, the intersection of H3K27ac and ATAC-seq differential regions were explored with the aim to capture the biologically relevant enhancers with higher accuracy. See FIG. 4A. Sites were categorized as both differentially marked by H3K27ac and differentially accessible as “intersection” (10,498 classical -up and 11,484 basal -up sites) and compared their power of separation to that of regions that were either exclusively differentially accessible (which are not differentially marked by H3K27ac; “ATAC-only”; 11,199 classical-up and 15,432 basal-up sites) or exclusively marked by H3K27ac (which are not differentially accessible, “H3K27ac-only”; 12,633 classical-up and 19,602 basal-up sites). As expected, although the “intersection” sites were smaller in number, they demonstrated the most separation between classical and basal-like PDAC subtypes, outperforming both the “ATAC-only” and “H3K27ac-only” sites, respectively, in classical-up and basal-up sites (all p<10-11). See FIG. 4B and FIG. 4C

[0273] Limiting the stringency of these intersection sites to only those H3K27ac and ATAC-seq differential regions having a p<10-8resulted in a subset of 2,274 and 1,789 classical-up and basal-up sites, respectively. These high stringency H3K27ac differentially accessible sites are provided in Table 2, below.

[0274] The loci identified in Tables 1 and 2 can be useful, e.g., for determining a basal or classical subtype of pancreatic cancer.

[0275] For differentially methylated regions (DMRs) identified via MeDIP-seq, a more modest threshold of FDR-q < 0.01 and LFC > 1 was chosen given fewer differential regions overall, thereby retaining 274 subtype-specific DMRs (142 basal-like and 132 classical DMRs). These differential MeDIP sites are provided in Table 3 below. Of note, the evaluation of MeDIP performance in the external PDX cohort may have been limited by data availability. Unlike the ChlP-seq datasets, raw DNA methylation sequencing data were not publicly accessible, so read alignment and extraction fragment-level signals were not performed. Instead, methylation information was obtained as summarized scores at predefined genomic loci. As a result, the methylation signal was estimated by overlapping these loci with our subtype-specific DMRs, which led to the loss of a portion of sites.

[0276] The loci identified in Tables 1, 2, and / or 3 can be useful for determining a basal or classical subtype of pancreatic cancer.Attorney Docket No.: DFS-34525 (DFCI 3605)

[0277] To internally normalize the signature score for each individual mark, the signal ratio at classical: basal (C: B) sites was calculated. All three C: B epigenetic signature scores (H3K27ac, H3K4me3, MeDIP) were significantly different between classical and basal-like PDXs and were significantly correlated with each other in the external validation cohort (FIG. 4D). Hence, tumor-informed epigenetic signatures derived from the discovery PDAC PDX cohort described herein can broadly capture and distinguish classical and basal -like PDAC subtypes.Epigenomic characterization of plasma samples from PDAC patients

[0278] Whether these tumor-informed epigenomic signatures could be recovered from plasma of patients with PDAC to discern their transcriptional subtype was assessed according the experimental approach shown in FIG. 5. H3K27ac and H3K4me3 ChlP-seq, MeDIP-seq and low pass whole genome sequencing (LPWGS) were performed on plasma of patients with metastatic PDAC from two clinical cohorts where C-B subtypes were previously determined as described above. ctDNA fraction was estimated using ichorCNA. A classical / basal (C / B) score was derived for each epigenetic feature in individual patients by calculating the ratio of aggregate signal at classical:basal regions.

[0279] Specifically, 73 plasma samples (C = 47, B = 26 by tissue RNA analysis) from patients with metastatic PDAC were profiled by H3K27ac cfChlP-seq and H3K4me3 cfChlP-seq. The median ctDNA fraction was comparable between the two subtypes (3.2% vs. 3.7%; p=0.8). The H3K27ac and H3K4me3 C / B scores were significantly higher in plasma from patients with classical PDAC (p<0.001) compared to basal PDAC. See FIG. 6A. The methylation signature did not distinguish the two subtypes (p=0.2).

[0280] Cell-free DNA utilizing cell-free ChlP-seq (cfChlP-seq) for H3K27ac and H3K4me3 and cfMeDIP-seq was profiled on plasma of 82 patients with metastatic PDAC where tissue-based transcriptional subtype calls were available. The samples included patients from three distinct cohorts: A clinical trial of paricalcitol in combination with chemotherapy (NCT03520790, n=29), the MOSCATO 02 trial (NCT01566019, n=27), and an institutional cohort of patients treated with standard of care at the Dana-Farber Cancer Institute (n=26). The median age was 65 (IQR: 57-70), 58% were male, 97% had stage IV PDAC (two patients had stage III), and 68% were previously untreated. The cohort included 50 classical and 32 basal-like samples based on RNA analysis of temporally matched tumor biopsy to the plasma collection. The median interval between the plasma draws and the tissue biopsy was 7 days (IQR: 1-15), with 97% of the biopsies obtained from a metastatic site, most commonly the liver. cfChlP-seq was performed for H3K27ac and H3K4me3 and cfMeDIP-seq on each patient’s plasma and generated a total of 242 cell-free epigenomic libraries. Circulating tumor DNA (ctDNA) fraction was estimated by applying ichorCNA. The median (IQR) ctDNA tumor fraction across these samples was 3.3% (0-9%), consistent with previous studies, and was comparable between classical and basal-like PDAC (3.2% vs. 4.8%, respectively; p=0.3) (dataAttorney Docket No.: DFS-34525 (DFCI 3605)not shown). Notably, plasma H3K27ac, H3K4me3, and MeDIP signals were elevated at classical-up sites in classical PDAC samples and elevated at basal-like-up sites in basal-like PDAC samples (data not shown). Similar to the analysis conducted on the PDX data, the normalized epigenetic signature scores (C: B ratios) was calculated at predefined signature sites from our PDX analysis for each epigenomic mark. C: B ratios were consistently higher in classical plasma samples compared to basal-like plasma samples for H3K27ac (p=1.1x10-3), H3K4me3 (p=6.4x10-5), and MeDIP (p=9.1x10-6)(FIG. 6B). C: B signal ratios derived from cfMeDIP-seq, H3K4me3 cfChlP-seq, and H3K27ac cfChlP-seq in plasma samples from patients with metastatic PDAC revealed only a moderate correlation between marks (data not shown). This contrasts with the observations described above in the PDX models where the three marks were more highly correlated and may reflect variations in epitope accessibility, epigenetic mark stability, and capture efficiencies of antibodies in plasma vs. tissue. However, since of the 23,944 differential sites across the three epigenomic features, the vast majority (90%; n=21,631) were unique to one epigenomic datatype, the moderate correlation may also suggest that each mark contributes orthogonal information.Generation of the pancreatic integrated epigenomic score (PIES) for plasma samples

[0281] A plasma integrated epigenomic score (PIES) was developed by combining various epigenetic features and its performance was assessed using the area under the receiver operating characteristic (AUROC) curve. For both H3K4me3 and H3K27ac cfChlP-seq and for each plasma sample, reads overlapping with the previously defined "classical-up" and "basal-up" peaks were counted. For both histone marks and for each plasma sample, an epigenomic score was calculated as the ratio of reads mapping at the "classical-up" sites over reads mapping at the "basal-up" sites. To generate the pancreatic integrated epigenomic score, the H3K4me3 and H3K27ac epigenomic scores were log -transformed and summed, for each plasma sample.

[0282] For cfChlP-seq (both H3K4me3 and H3K27ac) and cfMeDIP-seq, and for each plasma sample, reads overlapping with the previously defined "classical-up" and "basal-up" peaks were counted. For each epigenomic mark, and for each plasma sample, a ratio of reads mapping at the "classical-up" sites over reads mapping at the "basal-up" sites was calculated. To generate the pancreatic integrated epigenomic score, each of the 3 ratios was log-transformed and Z-score normalized and summed, for each plasma sample.

[0283] Since "classical-up" reads are the numerator of the ratio and "basal-up" reads are the denominator, a higher integrated epigenomic score indicates a higher likelihood of categorizing the plasma sample as classical PDAC. Conversely, a lower score suggests a higher likelihood of categorizing the sample as basal-like PDAC. Finally, a classifier for the subtyping of pancreatic cancer in plasma was built and its performance was evaluated by measuring the area under the receiver operating characteristic (ROC) curve as previously described. McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat Biotechnol. 2010 May;28(5):495-Attorney Docket No.: DFS-34525 (DFCI 3605)501. The resulting pancreatic integrated epigenomic score (PIES) shows high discriminatory power between classical and basal samples, with an AUC of 0.84 for all samples regardless of ctDNA fraction. See FIG. 7.

[0284] These results support that the identified epigenomic loci can be used to characterize pancreatic cancer classical / basal subtype in plasma samples. These can be applied as a non-invasive approach for determining classical-basal subtypes of PDAC using ctDNA chromatin epigenomic profiling which could allow rapid and broad adoption of transcriptional subtyping for clinical use. Example 3: Multianalyte integration improves non-invasive pancreatic cancer subtyping

[0285] Compared to tumor tissue RNA-based classical / basal-like labels, plasma epigenetic signal from H3K27ac, H3K4me3, and MeDIP distinguished the two PDAC subtypes with an area under the receiver operating characteristic curve (AUROC) of 0.71, 0.76, and 0.81, and area under the precision-recall curve (AUPRC) of 0.79, 0.83, and 0.86, respectively (data not shown). Interestingly, cfMeDIP showed numerically higher performance compared to H3K27ac and H3K4me3 individually, which contrasts with the above observations in PDX models. This likely reflects the relative stability of DNA methylation as an epigenetic mark compared with histone post-translational modifications leading to its improved recovery in cell -free ctDNA assays. Since each epigenomic feature contributes orthogonal information, integrating these signals may enhance their discriminatory power. Similar to previously described approaches, each individual C: B ratio prior to simple summation was log-transformed and z-score normalized to obtain a singular pancreatic integrated epigenomic score, or PIES (FIG. 8). As expected, PIES values were significantly higher in classical compared to basal -like PDAC plasma (p=6.4x10-8; FIG. 9A). Additionally, PIES values were calculated for all plasma samples with the loci that includes the high stringency subset of H3K27ac loci in Table 2, and compared with PIES using the full set of differential loci (FIG. 9B). Specifically, scores from the full set of loci (H3K27ac, H3K4me3 and MeDIP) correspond to the PIES scores shown in FIG. 9A.Scores from the high stringency subset of loci utilized only H3K27ac peaks that were significantly differential at high stringency (p < 1x10-8) recited in Table 2 in addition to the full set of differential H3K4me3 and MeDIP sites of Tables 1 and 3, respectively. Pearson correlation coefficient and corresponding p-value are shown. As shown in FIG. 9B, there is a high correlation (R = 0.95) between PIES calculated on all loci and the PIES on the high stringency subset of loci.

[0286] To ensure unbiased performance estimates, performance metrics were evaluated using leave-one-out cross-validation (LOO-CV). LOO-CV was performed on all available plasma samples, consisting of 49 classical and 31 basal-like samples (total n=80). For each iteration, the holdout sample was excluded from all preprocessing steps. For each iteration, one plasma sample was left out, and Youden’s index (True positive rate - False positive rate) was calculated on the remaining 79 samples to identify the optimal threshold that maximized the index. Normalization parameters used toAttorney Docket No.: DFS-34525 (DFCI 3605)compute the PIES were estimated exclusively from the training samples in each fold and subsequently applied to the held-out sample to generate an out-of-fold prediction. This threshold was then applied to the PIES score of the left-out sample to assign a prediction: samples with scores above the threshold were classified as classical, and those below as basal-like. After all 80 samples were individually evaluated, the PIES labels were compared to the RNA subtype labels, and performance metrics, including recall (sensitivity), precision, and specificity, were calculated.

[0287] LOO-CV yielded an AUROC of 0.84 (FIG. 10A) and an AUPRC of 0.89 regardless of ctDNA fraction (FIG. 10B), an improvement compared to any individual mark alone. The performance of PIES further improved with AUROC of 0.9 and AUPRC of 0.92 when focusing on plasma samples with detectable ctDNA levels (>3%, the sensitivity threshold for ichorCNA (FIGs.10A-10B). LOO-CV achieved a precision of 88%, a recall of 76%, and a specificity of 84%. The optimal actionable cut-off maximizing the difference between true positive and false positive rates using the Youden index (J), estimated within each training fold and averaged across LOO iterations, was -0.4.Example 4: Tumoral subtype heterogeneity may underlie plasma-tissue discordance

[0288] The overall accuracy of PIES (compared to tumor tissue RNA labels) was 79% and there was no significant bias in the directionality of inaccurate results (12 out of 49 tissue classical labeled plasma basal-like, and 5 out of 31 tissue basal-like labeled plasma classical subtype;McNemar’s test: p=0.15). Pancreatic ductal adenocarcinoma is a biologically heterogeneous disease, with prior single-cell and spatial profiling studies demonstrating that classical and basal-like transcriptional programs can coexist within the same tumor and even within single malignant cells. This heterogeneity might partly explain the observed plasma-tissue discordance. To explore this discordance further, 15 cases in the cohort were identified where extra tissue was available from the same site as used for RNA-sequencing and subtype determination. A validated and orthogonal assay was applied utilizing a six-marker multiplex immunofluorescence (mIF) panel which measures quantitative expression levels of classical (GATA6, CLDN18.2, TFF1) and basal-like (KRT5, KRT17, S100A2) proteins in individual tumor cells, categorizing each tumor cell as classical, basal-like or co-expressor as previously described.

[0289] mIF was performed using a previously developed and validated tumor epithelial subtype panel. Briefly, 4 pm FFPE tissue sections were stained with a six-marker epithelial subtype panel comprising basal markers (KRT17, KRT5, S100A2) and classical markers (GATA6, TFF1, CLDN18.2), together with DAPI for nuclear identification and pan-cytokeratin for epithelial cell identification. Multiplex staining was performed on a Leica BOND RX Research Stainer (Leica Biosystems, Buffalo, IL), and imaging was conducted using the Vectra Polaris system (PhenoImager HT) (Akoya Biosciences, Waltham, MA). Multispectral images were unmixed and analyzed usingAttorney Docket No.: DFS-34525 (DFCI 3605)machine-learning-based tissue and cell segmentation in inForm software (inForm 3.0, Akoya Biosciences), followed by single-cell-level data export and downstream analysis in R (v4.3.2, R Foundation for Statistical Computing; Vienna, Austria).

[0290] Four cases included in this subset were originally discordant between plasma PIES and tissue RNA derived labels (PANFR3025, PANFR3298, and P23 noted to be classical on the plasma PIES and basal -like using tissue RNA; PANFR3130 noted as basal -like by plasma PIES and classical using tissue RNA. Interestingly, two of the cases above which were noted as classical by plasma PIES, and basal by tissue RNA (PANFR 3025, and PANFR 3298) were noted as classical on the mIF panel (>50% classical cells on mIF panel as defined previously but had elements of hybrid co-expressing, and basal-like cells. On the other hand, PANFR3130 and P23 remained discordant on plasma and tissue testing even after the mIF analysis. PANFR3130 was uniformly classical with 89% classical cells, and P23 was uniformly basal with 92% basal cells on the mIF panel, both concordant with the tissue label determined on bulk RNA-sequencing performed on the same biopsy.Interestingly, and of note, P23 had a PFS of 9 months and OS of 15 months, substantially higher than expected for a purely basal tumor. Similarly, PANFR3130 exhibited a PFS of 2.3 months and OS of 9.3 months, consistent with a poorer prognosis.

[0291] To understand discordance more systematically, univariate logistic regression was conducted to identify predictors of plasma PIES and tissue subtype discordance. Biological variables such as ctDNA tumor fraction, the proportion of co-expressor cells, and the proportion of PIES-discordant subtype cells (i.e. frequency of cell type discordant to plasma PIES determination on tumor mIF panel analysis) were included as independent variables. Interestingly, increasing representation of the PIES-discordant subtype on mIF panel analysis by two-group (i.e. only counting classical and basal cells as denominator to assess discordant cell type frequency) and three-group classifications (counts classical, basal and co-expressor cells as denominator to assess discordant cell type frequency) were associated with an increased likelihood of discordance across platforms (two-group odds ratio per 10% increase [OR]=2.25, 95% CI: 1.2-16, p=0.003; three-group OR=3.23, 95% CI: 1.2-86, p=0.003; respectively). ctDNA tumor fraction and the proportion of co-expressor cells by mIF were not associated with an increased likelihood of discordance between plasma and tissue-based subtyping platforms (OR=0.66, 95% CI: 0.25-1.38, p=0.28; OR=0.83, 95% CI: 0.33-1.72, p=0.62; respectively). Marginal effects analysis demonstrated a monotonic increase in the predicted probability of discordance across the observed range of discordant cell type in tumors. Tumors with low proportions of PIES-discordant cells exhibited a low predicted probability of discordance, whereas tumors in which the discordant subtype predominated showed a markedly higher predicted probability (data not shown). These findings indicate that increasing dominance of the PIES-discordant subtype is associated with progressively greater discordance across classification platforms, whereas more homogeneous tumors are more likely to be concordant between tissue andAttorney Docket No.: DFS-34525 (DFCI 3605)blood-based approaches. Interestingly, mixed tumors, previously defined as those with <90% of classical or basal-like cells on mIF did not have intermediate-range PIES scores compared to more pure tumors, and hence the score threshold alone may not allow identification of such cases.Example 5: Plasma subtypes improve clinical outcome prediction compared to tumor tissue subtyping

[0292] The present example shows that plasma-based subtype determination can better predict clinical outcomes compared to standard tissue subtyping methods. For this, survival data from patients who had plasma collected prior to the initiation of the first-line treatment for pancreatic cancer (n=50) was analyzed. The median (IQR) age was 65 (58-70), 31 were male (62%), 35 (70%) had liver metastases, and 32 (64%) had ECOG greater than or equal to 1. The first-line regimens administered were FOLFIRINOX (FFX; n=17) or Gemcitabine + nab-paclitaxel (GnP; n=33). Patients were categorized into two groups: low and high PIES using a cut-off of -0.4 derived using the Youden index (J) across all LOO iterations. In a multivariable Cox regression model accounting for ctDNA fraction (continuous), the presence vs. absence of liver metastasis, ECOG (0 vs. 1-2), CA19-9 levels (continuous), and the chemotherapy regimen administered (FFX vs. GnP), low PIES (vs. high PIES) but not tissue transcriptomic subtype (basal-like vs. classical) emerged as an independent determinant of worse progression-free survival (PFS) in patients with metastatic PDAC (Low PIES: adjusted HR=2.99; 95% CI: 1.3-6.9; p=0.01; FIG. 11; basal-like tissue RNA subtype: adjusted HR=2; 95% CI: 0.94-4.24; p=0.07). Patients with low PIES had a significantly worse PFS compared to patients with high PIES, with a median (95% CI) PFS of 4.7 (2.3-NA) vs. 6.9 (4.8-11.2) months (logrank p=0.046; FIG. 12A), and, similar to the results of the multivariable Cox analysis, PFS among classical and basal-like PDAC determined using tissue-based transcriptomic analysis did not reach statistical significance (5.4 vs. 6.4 months; log-rank p=0.25; FIG. 12B).

[0293] Given prior evidence that classical and basal-like PDAC exhibit differential responses to FFX and GnP, with basal-like tumors faring poorly on FFX compared to GnP, a sensitivity analysis was performed stratified by treatment regimen to assess whether the prognostic impact of PIES varied across therapeutic subgroups. Interestingly, among patients treated with FFX, patients with low PIES had a more pronounced poor prognosis compared to patients with high PIES, with a median (95% CI) PFS of 2.1 (0.4-NA) vs. 6.7 (5.7-NA) months (p<0.001; FIG. 12C. In contrast, no differences were observed in outcomes among patients with PDAC receiving FFX according to tissue-based transcriptomic analysis with a median (95% CI) PFS of 5.2 (0.4-NA) vs. 6.1 (3.4-NA) months (p=0.91; FIG. 12D). These differences were not observed among patients treated with GnP.Moreover, when stratified by treatment arms (FFX vs. GnP), among patients with low PIES, patients treated with GnP had better outcomes compared to patients treated with FFX, with a median (95% CI) PFS of 6.2 (4.7-NA) vs. 2.1 (0.4-NA) months (p<0.01; FIG. 12E). Conversely, no differences wereAttorney Docket No.: DFS-34525 (DFCI 3605)observed in outcomes among regimens in patients with a basal-like subtype per tissue transcriptomics (p=0.7; FIG. 12F). An interaction term between chemotherapy regimen (FFX vs. GnP) and PIES group (high vs. low) in the Cox regression model for PFS was included, adjusting for ctDNA fraction and the presence of liver metastases. A significant interaction between chemotherapy regimen and PIES group was observed (interaction p=0.04), with patients with low PIES appearing to derive greater benefit from GnP compared with FFX. Overall, these results suggest that PIES may better capture underlying tumor biology and be more representative of cancer behavior than tissue transcriptomics, which can be limited by PDAC intratumoral and intermetastatic heterogeneity.

[0294] The examples herein describe, inter alia, a Pancreatic Integrated Epigenomic Score (PIES), a novel non-invasive approach for inferring pancreatic cancer transcriptional subtypes based on circulating tumor epigenomic profiles. Leveraging a large PDAC PDX cohort, highly recurrent gene regulatory programs were identified that distinguish classical and basal-like subtypes and validated these findings in an independent PDAC PDX cohort. Subsequently, subtype-specific epigenomic signals in plasma of patients with advanced metastatic PDAC were captured and PIES developed by integrating three distinct epigenetic analytes. These examples show that PIES accurately discriminates between classical and basal-like PDAC in patients with metastatic disease, with low PIES indicating a basal -like subtype and high PIES indicating a classical subtype. These examples also show that PIES improves prognostication and treatment response prediction over tissue-based RNA subtyping by providing a readout of the overall tumoral transcriptional subtype better accounting for prevalent intratumoral and intermetastatic lesion subtype heterogeneity.

[0295] PIES was associated with clinical outcomes in patients with PDAC. Patients with low PIES had significantly worse outcomes than those with high PIES when treated with FFX, whereas no difference in outcomes was observed among patients treated with GnP. Interestingly, among patients with low PIES, those treated with GnP had significantly better outcomes than patients treated with FFX. This finding supports that patients with basal-like PDAC may derive better outcomes with GnP.Tables

[0296] The following tables are included in the present application in connection with this Example. Table 1 provides differentially H3K27ac modified loci - first presenting those genomic loci where H3K4me3 modification is up in basal PDAC, followed by loci where H3K4me3 modification is up in classical PDAC, as indicated at the top of each page. Loci in Table 1 are ordered by chromosomal location, down each column and then from left to right. Table 2 provides differentially H3K27ac modified loci - first presenting those genomic loci where H3K27ac modification is up in basal PDAC, followed by loci where H3K27ac modification is up in classical PDAC, as indicated at the top of each page. Differentially modified loci are sorted by p-value, with the most significant (lowest) p-value at the top of the left most column, and p-value increasing down the column and thenAttorney Docket No.: DFS-34525 (DFCI 3605)moving left to right. For H3K27ac - basal up, chromosomal locations from chrl:209567573-209610436 to chr4: 132300347-132301753 have p-value of 10-10or more significant; chromosomal locations chr6: 161828322-161829414 to chrl:85308640-85309938 have a p-value from 10-9up to 10-10, and chromosomal locations chrl9: 15319074-15334170 to chr4: 189032848-189036984 have ap-value from 10-8up to 10-9. For H3K27ac - classical up, chromosomal locations from chrl:54557790-54562885 to chrl2:98964445-98974633 have p-value of 10-10or more significant; chromosomal locations chr2:36620792-36625142 to c chr8: 1876548-1882511 have ap-value from 10'9up to 10-10, and chromosomal locations chrl8:8329446-8332261 to chr4:79299926-79303037 have ap-value from 10'8up to 10'9. In some embodiments, loci encompassing any range of p-values within Table 2 may be assessed. Table 3 provides differentially MeDIP modified loci - first presenting those genomic loci where MeDIP modification is up in basal PDAC, followed by loci where MeDIP modification is up in classical PDAC, as indicated at the top of each page. Loci in Table 3 are ordered by chromosomal location, down each column and then from left to right.Attorney Docket No.: DFS-34525 (DFCI 3605)Table 1 - Differentially H3K4me3 Modified Loci - Basal UpH3Kta»3 - Basal Ueu# Up H3K4tne3 - Basal Locus Up H3K4me3 - Basal laicus lip M3K-3me.3 - Basal IXKWS Up chrl:2358984-2364949 chr4:11207389l-f 12074414 cM:110985903-110988412 dul3:49854987-4985566’ dii'l:23S2115-2380215 dirt: 112257978- 112258882 chr8: 1136()619O-.l 13607034 chrl 3:49971 W-4997SS64 chd:2396275-’403i73 chi4;l 12439976-112440729 dw8:334058308-114058796 chrl 3:52828294-5’82939.5 dirl:360636G-3609639 chl4:l 13683717-113684878 cht8:l 14849807-114850444 chrl.3:53O55248-53O55912 chrl:3624j07-36260J7 d«4:l 17326665- H 7327706 chr8:115017705-. E15018914 chrl3:5S<>46558-5864743’ dul;6445«)8-64469l8 dn4.121662619-121663453 chrSd 15029410-115021329 chrl 3:61283887-61284692 chrl: S197079-81?%34 cht4: 123030734- 123032288 chrS:! 15028608-115029106 chrl 3:62131555-6’132959 chrl: JOOX842M 0089639 chr4: 125038409- f 25039178 cfafcl15125103-115126128 du-13:6464X513-64653’13 chrl:12525D4 Ji-12525489 chr4:l’6I49792-1’6I5O54i drr8:ii5515482-il55l 7181 chrl3:0750S095-6750S677 chd:i6536111-16539684 chi4; 127849098- 127850081 dw8: 335597500-135599718 chrl 3:67673385-67674538 chrl: 168711846.16873193 chr4: 128 $09573- 138 $ 11065 chr8:l 15604527-115605640 d»rt3;6767471(W<5755ll chrl:?"248106-l724X738 dw4: 129240730- 129241437 cJ>r8:l 15648593-115650193 diT13:67675774-6767M’3 dir1:l7536697-17S443<» d«4.130774423-130776010 dirS: 115794459- H 5795282 chrl 3: ^73184331-73185306 chrl: 17574512-17579473 chf4:l309~23!6-131)973~54 dtrt:i 160047U-116005369 dir! 3:74072079-74074234 chrl:27144725-27145733 chr4:133129684-132131277 chi8: 116506314- 116507257 chrl.3:75000 J 78-75001039 chrl:30IS0665-30l 82763 cte4;13227. U27-132274230 clirS: 118203319- 118204683 chrl3:816438J 1-81644348 c6jrl:; U22S305-3U3U®4 chi4; 132300297- 132302282 dw8:339937793-139918502 chrl 3:82619338-8’629331 chrl:38941765-38942639 chr4:13314S7’9-13314915’ dir8:121205649-121206528 dir! 3:83499924-83500384 chrl:457X150^5784515 chr4: 138974052-138974657 chi8: 123874682- 123875491 chrl 3: N367498’-S3<>76735 did;49747S42-49749050 dn4: 142470396- 142471162 dirS:!23875767-lZ3876155 chr 13:91503496-91506420 chrl:504002S6-5040l3«J cht4: 146290386- 14629144 J dwS:324190631-124204055 chrl 3:95024329-95025147 chrl:5H 69528-51171524 chi4: 147584363- 147 $85532 du«: 127304672- 127305223 chrl3:96983407-9fl98446’ chrl:56555169-56555982 chr4:15O836353-f 50837497 ch I'S: 128322952- 128324832 chrl 3:97636495-97637768 chd: S8739981-5874f)793 cht4:l53641227-l536419J5 chr8: 328X72153-128873137 chrl 3: 100647773-100648399 chrl:58844122-58844952 chr4:15728812S-157289263 dir8:329908734-l 29910321 dir! 3: 103174374- 103174929 chrl:6353938O-63539933 did: 160099488-160100020 chrX: 129934403 - 129934740 dul3:l 10874’76-110874698 did;656: L5732-6563f>34<5 dn4: 160303417- 160303938 chrS: 330169653- 130170602 chr 33: 112592.339-112592519 clirl 169346791 -69348455 chi4; 160310906-160312941 chrS:l30368 $67-13036938$ chrl 3:113394667-113395317 dirl:695X54274595X6’64 cfw4.160636199- 160636875 du«; 130744934- 130745787 chr!3:l 13407’25-113407746 chri:719791I8-719S0!37 chr4: 164133249- 164134312 c}w'8:130795866-I39799613 chrl3:li424985’-114251454 chrl 172353518-72354526 chr4: 165021497-165022710 chrS: 33’647102-1326482$$ chrl 3:114523475-114524730 chri:73363515-73365172 chr4: 165062841- 165063725 chr8:i32782929-l 32784993 chr i 4: 19065521 - 19067234 chrl:79735216-79737181 chj4:170789H5-J70789280 chr8:133779747.i33780074 chrl4:21:510441-21511735 chrl:80549196 -86549711 dir4: 186842003-! 86842978 chrS: 135088399- 135089355 chrl 4:22763739-22764170 chd:82165313-82167383 dn4: 187302548- 187302958 dwS:336’7O9O3-l 36’72336 Chrl4:23896%9-’2897314 chrl:826(U704-8260’635 chr4.187405962- 187407251 chi«:140W>699-140908430 chr!4:25679011-25680029 chrl: S3633363-83633920 dt4:188592613-188593999 chr8:142047003-. E42048103 chri4::2<>253380-20254226 did;84995277 -84995889 d»4; 188783225- 188784429 chrS: 34’065570- • 42066322 chr 14:27147846-27149439 chrl 186392706-86393466 chr4:188858637-188859300 chr8: 1420665 H - 142067003 chrl 4:27312278-27313415 dirl:86889673-S6892224 did: 188897469-188898006 dirt?; 143404736- 143405435 chrl4:2904?164-290509f 3 chrl 188807194-88808370 dir4: 189139390- 189141080 chrS: 143863718443871264 chrl 4:29052835-29053237 chrl189829317-89831052 dirf;957262-9575S4 dw8:143875t}41-143875475 chrl 4:39056311 -29056825 chrl:92398’02-923W67 dirX;143875549-143877080 chrl4:29226133-29226502chr5:1611S77-1612558Attorney Docket No.: DFS-34525 (DFCI 3605)Table 1 - Differentially H3K4me3 Modified Loci - Basal Upchd:94235358-94236393 dw5:5764186- 1764432 <*18:1-44256633-144257154 chrl4:29227771-2922897.3 *rl:94237133-9424 )093 <hd 1805974-1808764 d 8:144544255- 1 45 5715 dwl4:2999311 -29993? f 5 chrl:9533{»604J533O714 ch)5:1 09298-i8H»I5 chr9:84l27l-843I61 dwH:30765«3-30767347 ci l:9S763024-95763966 S: 1850946- 1852217 dw5» 1083142- 1083918 cbrl 4:30878523-30 80335 *rl:99054041-9W5-S966 chr5:25376S9-25 8] 57 *19:3574323-1575351 chrl 4:30940173-399443 1 chri:1033990i 8403399901 chr5:4501853-4502797 ciw9:5 10397-55.11031 chr!4:33194263-33194626 l l: 103572127- J 03573162 ehi5:5l45929-514Sll2 dw9:5629621-562126 chr!4:35i 17283-35118503 chrl: 505206542- 105207958 cht5:7130543-7131575 <*19:6134973-6136378 dwi4:358 8l81-35839199 dwl: 505318375- 1053! 9273 chi 9: 193731-7194755 dw9:l 2 3789-12334917 dwl4:364OI 774-3<54O2 67 cM:t0539J693-105392671 chr5:8090148-8090332 chO*13443803-13444639 chrl4:3S24f269-3824224J cJwl:112763874- J 12764815 w5:l0632280-i0632778 dw* ) 8649979- 18650504 cbrl:418)58086-41X159915 eiwl:i2I315453421317086 chr5:13986083-13986325 <*19:22508054-22509628 chrl 4:40108185 -40108913 clwl:}49058005-149059J 38 chr5: 1527142245272392 ciw9:2384953 -23851665 clwl 4:42380095-42381305 c)wl:149l93 [82-149194819 dw5 1.5912045-15912826 d 9:28347857-2 348708 chr 1:44167 1 -44168599 ci l: 1 1008760-151010075 chf5:l63354-4J-16336327 *B»i29)88526- 5>t8Wl iw! 4:44467887-44408864 clwl:152538309452538811 chr5: 17663246-17664746 <*19:29449467-29451292 clwl4:45951437-4595253l chrl: J 53265424- 153266119 hrS: 17951763-37952004 ciw9:30074918-30075838 clwl4:46977766-4697S3f2 cJwl:153284467-J532S5Ol3 clu5:2l701443-2l701688 dir9:31848508-31850287 cbri 4:48655911-48656902 ciwl 1153329928-153332896 chr5:23413306-23412067 <*t9: 34766939- 34767074 clwl4:5I422951-51424297 chrl ■ 55 i; 33045- 153333521 chr5:250 29 2-250840 7 c:hs:3809l'i442-38997484 clwl 4:51955437-51960 f 75 l l; 153362446-153363642 ehi5:26'W.3264-26943578 dw9:43376481-43377438 dull ^52032240-52032793 ci l: 15885574O-158SS65S4 w5:319358)9-31938576 dw9:66033197-66033532 cbrl 4:5 123OOS-52J 2 652 clwl: 159043448-159047519 chr5:33I22130-33123423 <*i9:78712 15-7 71 4‘iO clw!4:52266511-52268087 clwl: 160737778- 160738206 hr5:33858905-33859785 ciw*i: 81717790- 17191 8 dwl4:5329071 i-53291035 ciwl:16l972855- 161973719 w5:3389O277-3 S928O3 dw99 372715-90373574 ch;: 4:54460913-54461196 ciwl: 17507581 S-I75076618 chr5: 4147228-34148925 dw9:9i 605619-91 07662 lwl 4:6w96347-60098068 clwl: 17391493 M 78915481 chi5:36lXrfs236-?.6O67237 chi9:91S4924 -9 499W clwl4:622i i795-622!2f27 l l;181973070-181973900 elw537 36339-37841159 dw9:94976553-9 977589 chr 14:64580832-64581691 ciwl:186l52855- 186153265 *15:39216963-39219883 dw5*: 96960472 -96960838 chrl 4:65834858-65835403 clwl: 186675890- 1 6681529 chr5:39272425-39273747 *19:98332277-98332830 clwl4:66560348-66561096 chrl: 386885930- 186886342 cfw5:42943309-42945282 ciw9:98527l24-98527655 clwl 4:7124S490- 71249068 clwl:187318259-1873191 W> clwS:437l 8002-337189 3 1*1**99063603- 064488 chr) 4:71698684-716 9572 cl l: 1875666-44-187567373 ehr5:43748979-43749699 <*19:101013177-101013544 l l 4:73925992-73026469 *1:! WJ J846-19O4J29J8 chr5:45748570-45749476 dw9:l0l70 749-101707084 chrl4:7:5082052-750S3563 clirl:l 96193759-196194735 c!w5:49884O64-49884544 ciw** 102130 48-102131452 d l 4: 75447042-75448465 clwl: 200 80558-200 81977 elu5:55l 6624-55l48708 dw9: 103452830-103453980 chr J 4:76880139-76880797 clwl:2O1251225-2O1257849 <*(5:58330207-583311)91 <*i9: i059*W643-10600W>37 clwl4:77510248-77510937 dwl:201258060-20) 258533 chr5:62099935-6210I259 *(9:1090 9242-109049827 chrl4:77736713-77737897 clwl: 2033650 0-203365797 5;640l 0263-64011391 dw9:ll 1205736-111207062 chr 1:79597832-79598511 ciwl:2O3866084-2O3867032 ehr5:66254230-66255332 clw9:i i2294975-l 12296112 clwl 4:80554558-80555899 clwl:2O938O78S-2O9381857 chr5:67J84i 644171 6044 *1:11229980 - 112300798 clwl4:82717729-82718582 clwl;209586517-209587251 c!wS:70746266-70747274 ciw9: 113120208- 113120510 cl l 4:84104719-84106519 ciwl: 209600460-20960771 clu5:76l07028-7f, 109052 d 9:113i 78953-113180179 chr) 4:86351159-86352640 clwl:209989094-20999tXn9 <*(5:76904422-76905308 dw9:113553123-I l 35538 7 *114:86567831-86568365Attorney Docket No.: DFS-34525 (DFCI 3605)Table 1 - Differentially H3K4me3 Modified Loci - Basal Up cM:21(i32563Ml0225994 <*<•5:78514871 -78515606 <*•9:114618868-114619813 chd 4:89779320-89770723 dir I:2I 0439479-210440127 <*<5:788425116-78844486 <*r9;11595012?-i 15951251 <*<14:89876250-89876701 chri -2)4926618-214927213 c!»-5:79234634-~923499i chr9:ii 6412917-116-113567 di<14:90909855-9091067S <*<1:217869249-217870695 <*<5:85801858-85802756 dir9: I 17050678-117051582 <*£14:92111695-92113130 chri:226213921-226213809 ch<5:8598S3704S5989O42 du9:l 17877258-117877794 chrl 4:93540681 -93541 (d 7 <*<1:231264843-23)265115 <*r5:863O8682-S63O8988 <*19:117877929-117878192 <*<14:93884536-93885679 dul 1232427099-332427643 ehi5: S6577063-86577772 *i9: 117878330-117881381 dir 14:94345W)2-94346895 chrl:237338005-237339380 ch<5:873l0514-873ll428 <*<9:118506120-11 S 5066: 4 chrl 4:97092709-970937g 1 dirl:239792190-239795135 chr5:89503999-89505000 <*<9:118915628- 118918443 dal 4:101543434-101544493 chri 343893293-243894760 <*r5:90 II 7504-90118634 <*<9:119833526-119834316 chrl4:105j7j416-105372795 cJurl:244499S33-2445fn 147 <*<5:90605874-90611130 <*<9: 122817436-122818261 <*rl 4: 10S490567-10S491068 chri:2445344O4-244535066 <*<5:91598035-91598960 <*<9:123156281-123156559 cbrt5;2364< M54-2364ll29 did:245768996-245769J 86 <*£5:94413137.94413947 <*r9: 123698305- 123698835 dui5:250J7750-25019045 di<1:24833.5093-24833.5938 <*<5.95117264-95117546 chrf): 126778961-126781256 dir 15:28759906-28760557 chr2:481407-4818O7 <*<5:95195497-95195680 <*<9:127105405-127105779 d5r!5:3M83846-30484957 ch>2:5593339-5593858 dir596528261-96529590 <*<9:132044557- 132047023 dirl5:305j7944-30538689 ch<2:)0230952-l0232I89 chr5:96854906-96855814 <*<9:133044652-133045217 <*<15:32584487-32585063 <*<2:15012542-15013637 <*<5:97882249-97883267 <*<9: 135290569-135290975 <*£15:32638171-32639572 <*<2: 15996625-15997339 <*<5:99799242-99800042 <*<9: i 35931588-135933250 <*<15:339(14967-33005659 16780539-1678 f 349 <*r5: 100 f 58412-100 f 59209 <*<9: 135936123- 135937711 dnl 5:33404637-33406600 dir2;17622266-176234Sl eh<5:l00225627-l00226544 *<9: 136791286- 136792690 dir 15:33445281-33447202 ch<2:1942S0l2-19428926 ch<5:101467O51-101467476 <*<9:137532686-137539080 <*£15:35363190-35363581 chr2:24S86t)23-24l 86307 did 102005767- 102007540 <*i9; 137834400-137834767 dirl5:377I9251-37720117 dir2:2439745I -24398940 <*r5:102028312-102029429 <*<9: 138780579- 13878141 S dirl 5:38421865-38422883 cJii’2:2S524598-2552492S <*t5: W2382427-l«23832H <*<9: 339513293- 139515996 cbrl 5:40368664-40369624 <*<2:25932788-25933451 <*<5:103854267-103854710 <*<9: 140709015-140709373 <*<15:423126-18-42313196 <*<2:40240966-4(1242888 <*r5; 104726394-! 04729230 chdO:1272744-1273502 dul5:42327198-42328096 du2:4O3325264O333O90 <*<5: 105263243- 10526.3721 elwlO:! 381300-1382175 dir! 5:43558728-43559103 <*<2:41016642 -41017454 <*<5:105766385-105767450 <*<10:1568687-1569609 dui 5:47210773-47211481 <*<2:45291866-45293059 ch<5: 105963811-105964525 did 0:2256456- 3356931 di<15:48594457-48594993 <*<2:45302383-45303701 <*r5: 1059789(17-105979288 <*<10:2619859-2621106 (*<15:491 S38 J 1-49184396 <*<•2:54009601-54010273 <*<■5: 106054579- 106055559 <*rlO:2786738-2787764 dir 15:49252115-49252908 463:55506679-55507105 <*<5:108594568-108595355 did 0:5222484-5223091 <*rI5:5<»75716-5W76979 <*12:56369395-56370405 <*r5;10907322l-i09073f>43 <*rJ 0:5506741 -5568149 dirl 5:51894570-51895939 <*<2:57605645-57606356 did; 10292042-110292766 <*<10:5657676-5660237 chri 5:55356119-55356977 ch<2:57645557-57646625 d«3:l 10321203-110322229 <*<10:8635569-8636842 <*£l 5:56307649-56209452 4113:57835926-57836643 <*<5.110636344-110638562 did 0:9315459-9316344 dnl5:56441683-56442634 <*12:58613881-58614875 <*r5: 111326843-111327938 d)d0:l 2394756-.12395589 chrl5:63180020-63180287 <*r2;61885338-61886217 ehr5; 113324929- 113325769 <*<10:14850924-14851807 dir 15:64480173-64480930 4113:62938009-62938-165 ch<5:l 16739916-116741403 dtrlO: 15963257-15963721 chri 5:71W 1843-71902347 <*3:62939159-62939840 dsr5: 116868379- 116869380 dirlO:17331451-1.7332332 dnl5;73805662-73$07244 chr2:63033211-63033577 <*r5:l 19115637-119116807 <*<10:18324804-18325611 chri 5:76078627-76079302 ch3:6640430-4-66405095 di<5: 119799191-119802246 <*<10: 19382646-19383739 did 5:78171493-78171724<*<2:67583146-67584018 <*r 5: 1201 ’.'7034- 120038047 did0:19875381-19870357 dwl5: S3955647-83956402Attorney Docket No.: DFS-34525 (DFCI 3605)Table 1 - Differentially H3K4me3 Modified Loci - Basal Upchr2:69026880-69927213 *15: 120153894- 120153694 *rt&21045823-21047022 chrl 5:84748360-84749588 ch<2:70993733-70995679 chr 5: 120565081- 129565458 *(•10:21719060-21719741 clw.l5:84«22918-S4923735 chr2:7H 62776-71164255 *r5:121718419-12172O142 *rlO:22417989-22419364 dirl5:88O53(»l-S8OS3S0J <*r2: 72290740-72291900 *<■5:122620896-122621775 *rl 0:22922336-22922830 dwl 5:89102859-89103721 chr2:76577436-76578480 chr5: 126097808- 126098727 *r10:23293761-23294288 <*<•15:93779388-93779851 <*12:76880356-76881492 *<5:126103191-126103717 **0:24543805-24546366 chrl 5:94749089-94749919 clir2:76934467-76935246 *r5: 1276351611- 127635523 dwl0:2454657i-24546992 dwl5:95217590-95217985 c*r2:77008103-77009077 *<•5:129140204- 129141362 dtrl 0:24548293-24548712 <*rl 5:95739079-95740570 ch<2:83315594-83316811 dw 5: 133682025-133682621 durlO: 25034603- 25035479 dal 5: 101067800-101069539 *<2:84451875-84452680 *r5:134844156-134844710 chdO:2554133O-25542661 chrlSdOl 873455- 101 S75424 <*r2:8S 594689-85505330 *t5:l36123701-l 36124871 dwl 0:25606719-25606923 <*1:56:1582018-1587306 chr2:85623409-85624064 *r5: 136385730- 136386557 dtrl 0:2580949! -25810329 <*rt6;}?34427-}?348lO *r2:8" O4842I -87049108 <*<•5:136833181-136835112 <*rJ 0:26061938-26063107 dai6:1735868-1736586 clir2:8872S702-88729007 ehrS.137945436-137946173 *>10:26464703-26465572 dir 16: 1793216-1797800 *r2:88849192-8884%93 chr5:1389597S4-138%0370 dtrl 0:27846497-27847485 dir!6:1921323-J92r?52 *<2:89370935-89372751 clw5: 140456697- 140457677 <31110:28671012-38671514 <*<•16:3237517-3242294 *r2:*?3 Sf 6535-91816739 <*>5:140887347-140889339 did 0:29921825-29922540 chrl6:5>i6()4J8-916246f dw2:92109218-92109683 *r5: 141094933- 141095605 **0:29923134-29924184 djd6:107K)745-107ii6l6 *r2:95527033-95527749 chr5:141743512-1417447H dtrl 0:30403973-30404377 <*rl6:lI712208-11712981 *<■2:95536896-95537910 *r5: 141783036-141784490 <*rl 0:30818193-30818873 chrl 6:237822! 0-237825 f 1 vhr2;95540l<50-955405S6 *r5: 142064169- 142065958 *>10:43970712-42972154 <*<46:24682135-24682571 chr2196996452-96996946 *r5: 146762212-146763260 dtl 0:44162897-44163226 <*rt 6:26828009-26829063 ch<2:9863«)40-98630264 *r5.147100570- J 47102211 dwl 0:47745864-47750492 clnl6:28677041-28678366 dir2: 106938150- 106938801 *r5: 147283279-147284371 dir! 0:48600971-4860148S chri6:2S70S845-2871H 15 <*r2: 108321179- J 08322143 chtS: 150950054- 150950527 dwl 0:51555745-51556270 rhd 6:29228725-29232824 *r2: 108362474-198365043 *<5: 150966959- 15097173S dtrl 0:53706549-55707686 <*rl 6:29754398-29758404 *<2:115761856-115762700 <*<5:151011731-151012583 <*rl 0:54211037-54215060 rial 6:31313867-31314051 dn'2; 120441263 - J 20441933 *r5: 1 ’ 1064488- 151066964 dir 10:57658897-57660135 dirl6:31540122-31541846 <*r2: 120934659- J 20935739 *<■5:152147451-152148385 dirl 0:66683473-66684753 du • 6:46488471 -46489438 dir2: 122775475-122776275 dw5: 152703580- 152705649 did 0:67025989-67026672 <*r16:468<1296M6S03732 *<2:123f945Il-l23f9513I <*<5: 153850677- 153850885 <*110:69318298-69319031 chrl6:4SS07741-4880S723 dir2;125l 19237-125119893 chrS; }67000124- 167001460 dirlO:" 1097424-71098400 dirl6:5(1511933-50513019 chr2: 1’5165440-125166145 chr5:167181S57-167183155 dtrl 0:73729783-73733764 chrl 6:50913771-50914526 *12:126940884-126941738 <*r5;16736i35?-167362087 <*rl 0:74060304-74064663 <*<■16:53801955-53802550 *r2: 129062849-129064658 <*r5; 167378212- 167379995 <*1-10:77872914-77873763 <*<•16:53825614-53826536 <*r21131966238- 1319f, 8999 *r5: 169671996- 169673064 <*rl0:"9472464-79472987 cfw J 6: 54407643-54408155 *>2:138072316-138073359 chr5:l 70362592-179364010 did0:79698863-79700689 <*<16:55404732-55405123 *<2:14 j 558919-141559869 *<5:170516110-170517289 <*110:79847903-79849046 chrl6:555!27O7-5551569! dw2; 143370455- 143371859 *<5; 171606458- 171607245 dirl0:81024839-SR)25164 dwl6;556f)9526-556O3525 *r2: 144618144- 144619190 c hr5: 172664414- 172666186 dtrl 0:81860067-81861125 ehrl 6:55689338-55690653 *<2:147149535-147159468 *r5: 173925809- 172936167 dirl0:824S7778-82488624 chr16:57661497-57665743 *r2: 149085686-149086458 <*<5:173446463-173447605 <*rlO:83<}56406-83057488 chrl 6:59016689-590! 7664 chi-2: 153646485-153646917 *<5:174135417-174116375 dirl 0:85546278-85546826 chrl 6:59598750-59599217*<2:153869516-153879968 dw5: 176372117-! 76372421 did0:85930513-85931850 chrl 6:60556047-60557532Attorney Docket No.: DFS-34525 (DFCI 3605)Table 1 - Differentially H3K4me3 Modified Loci - Basal Up chr2: i5407889^ l54079735 chr5:17731O423'177313:213 dirl 0:86521780-86522883 dtrl 6:61815598-61816790 dtr2: 154113205-154H 4036 <*rt>:6096495-6096847 <*rlft8653S24!-86S39149 dal 6:61833849-61836107 <.«:t54727708-454730503 <*i6:7447468-7447943 ciw! O:86885240-86886l9l dirl6:6!937J61 -61937686 <*r2:i55700885-1557Ol338 da6:8725772-8726669 <*rl 0:87114890-87115483 cbd6:6195l252-61953l66 <*r2: 156553575- 15655438$ cl«6:877$911-877751$ did 0:88711659-88721614 dirl 6:62016071 -62016564 dtr2: 159590557- 159590022 <*>6:9971476-9972502 did 0:90466055-90467344 chrl6:64927J 10-64927763 dit'2: 159639251 - J 59640049 ehi6: 10480937-10481325 dirl0:9l77(}534'9177r.573 dir 16:65723496-65724753 chr2:15965l4l 3-159653822 elit6:152834i4-15283983 dirl 0:92010226-920! 0951 dtrl 6:7(3603315-70603781 dw2:162357106-162358063 chrtl: 19654119-39654601 <*rlft93236404-93X36963 dirl 6:71459707-71460436 chr2:}67041583-167042150 <*r6:197648l2-J9765269 <*110:99309688-99309903 rfa-16:73200427-73200842 dur2: 16S4(W74- J 68402058 cl»6;2481745f-248l8472 dtrl 0: 300548213-100549249 du • 6:73863452-73864460 chi2:171036576-171037032 tbir. 26745220-26747597 ^10:100912362-100913353 cbrf 6:75192823-75193238 dtr2: 172243038-172243433 <*r6:27017764-27018384 did 0: 101244657- 101245060 da-16: 75525930-75526839 <*r2:172265939-172266477 el«6:27300581 -27303493 dtrl 0: 102473125- 162473981 dir 16: 75861197-75862286 ciw2:17273l538-I727325l3 tht6:27528929-27530188 dtrl ft 104389953- 104390310 dtr! 6:76838856-76839112 cltr2: 174025048-174026459 <*r<>:27551377-27551911 did 0:105498416-105500328 dni6;79623238-79623950 dtr2: 575711694- 1757! 2287 <*>6:27631137-27632237 did 0: 106086785- 106090296 dir!6:81105680-81106677 cJu2: 176352097- 176352928 clii6:27652566-2765.3.325 dtrl 0: 106293388-106294286 du • 6:81678772-81679549 chr2:17694012S-I76941434 <*16:28442335-28443679 dtrl Or! 07142626-107143134 dirl 6:84228017-84231994 L'1W2: 379303203-179304158 c: W>: 28565116-28566646 did ft 107309620-107330547 dirl 6:84262008-8426228:1 dir2: 181556075- 181557237 ein6:2S58870J -28590203 dir 10: 107540906- 107541276 dir 16:84675790-84677022 dw2:18lS573S3-J81SSS075 <*<6:28641704-28642708 dtrl 0: 108609280-108610975 ebrl 6:86750508-86752047 cltr2: 384714060- 184714998 c3w6.28663936-2«664657 did 0:11 l5<5!j490-i 11561288 dirl6: S7739459-S7740097 du2:l 85675063- 185675680 <*>6:28? O9907-2S711471 <*dft 111585244- 111586648 dirl 6:87803020.87803671 <*r2: 186271515 - J 86272956 dw6:2S714849-28716162 dtrl 0: 1! 6045753-116046323 cbrl6;88216735-8822i l47 chr2: i87401950-i87402565 t*<6:28723956-28726917 dtrl0::i l7i77464-:l:17128368 dirl 6:89524486-89524950 cli 1'2:387766511'187767386 da6:28731623-287339O9 <*rJ 0:117295503-117296269 dal 7:875894-876537 dir2; 189469489- J 89472012 ein6:2S756720-28759346 dtrl 0:117346678-117347291 dirl 7:876934-877575 <*r2: 192626602- J 926271 S3 c*t6:2S769853-28772054 dtrl 0: 118843300- 118845051 cbrl 7:2466403-2467296 cW: 394082482- 194083417 4*16:28775598-28776963 diriO:120O3l436-120032033 dtrl7:3055904-3056701 dtr2: 394701123- 194701731 <*16:28777188-28778862 dirl ft 123845298 ■ 123845716 dal 7:3079306-3080779 chr2:39476820bi94770347 dw6:30951722-30953006 chrlft 126920078-126921259 dirl 7:4762095-4764601 cbr2: 195937261-195938614 ehr6:33712581-33715298 dtrl 0: 128364955-128365752 <*r17:6674l 16-6674722 Ar2:198456204-l 98456900 <*>6:37533552-37534276 did 0:129630961 - 129631207 dirl 7:7489530-7494288 dtrl: 1984637! 4-198464564 <*16:48077191-48078350 dwl 0: 131843458- 131844029 chri 7:8299640-8301254 chi-2: 198504557-198506159 dil6:48078640-48078875 dirl0:1351O5I8O.135JO5441 chrl7:8X19179-8819S76 dn2: 399666302-199666555 cbr6:48704629-48705630 did I:232l575-2326639 dnl7:9066O26-9066845 cht2:200094176-200094662 <*36:53270106-53270978 did.1:4552621-4553574 dirl 7:9518976-9520152 «1M2;200523841-200524491 elit6;55233562-S5234364 dirl 1:5498370-5499523 dirl 7:13574915-13575249 cbt2:2O4190294-204191069 <*16:56502845-56507790 dtrl 1:5640791-5642212 <*rl7:157C2754-157O37(M 28933'207139253 chr6:67340724-67341331 <*ri l:6164634-616S74S dal 7: 16569958- 16570970 dtr2:20S 104227-208107443 <*16:67743405-67742238 cferl 1:9554440-9554824 dal 7: 17345336- 17349268 chr2:2O9993253-2O999391O «hi6;7l 653807-71654380 dtrl 1:13010457-13011889 cbrl7:l«491889-18493697dtr2:230798481 ~210798754 c*f6:73279586-73280788 dirl 1:17742300-17743616 dnl7:185!4286-l851463(lAttorney Docket No.: DFS-34525 (DFCI 3605)Table 1 - Differentially H3K4me3 Modified Loci - Basal Updir2:2i4437i80-2 438256 cht6:74299915-74300489 *11:22550116-22550931 chd 7:20754717-20756827 dit2:214607422-214607926 *6:74879612-74879968 *11:24776371-24777156 dirl 7:20773358-20773978 di 7:220177562-220179492 *6:76820 53-7682.1320 *11:26985645-26987683 *17:21837625-21837971 *2:220795975-2207973S3 *6:79492823-79493374 dirl 1:28399451-28400387 *17:25416580-25418126 *2:221805222-221 0555$ *6:79680992«79682057 *11:34533035-34536459 *17:25431457-25432439 dtr2:221989275-221990129 *6:81368354-81369145 did 1:355 6943-35547853 chrl 7:28973248-2897 186 du-2:223019674-2230204 7 *6.81557319-81558287 clwl 1:41075731- 1076396 *17:2930771 -29308314 *2:2294 1633-229433776 cht6:8l 924403-81925419 dirl 1:465420%-46542454 *i 7:30360995-30301761 *2:233019403-233020109 *6:82288069-82288866 did J;488744S2-48875472 *17:31010385-31011677 ll2:233i 24545-233124885 *6:84512531-84513949 <*111:49199088-49199691 *17:31161598-311623-47 *: 233754444-233756502 *6:85823903 -85824466 dirl 1:49212238-49213154 *57:3914000.3-39140676 *2236663 $05-23666 880 *:8676692S-8676789$ *11:49801789-49802779 *17:3965595 -39662866 dir2:239344006-239344552 *6:87607444-87608205 *11:60202898-60203431 *17:39739254-39744053 *2:240582393-340582714 *6.876319.17-876314 3 dirl 1:61486001-61486542 * 17:39765469- 39769884 *2:242604730-242605739 w6:88 458S2-88446590 dirt 1:65523421-65524490 *17:40803763-40804289 *3:4515900-4516465 *6:89116246-89117149 dii11;67440488-67442502 *17:41496180-41497637 *3:6811065-6812342 *6:89946117-899421 8 <*111:72912370-72 12734 dirl 7:42589532-42590405 *3:9906193-9906965 *6:94580843-94581849 dirl 1:79263698-7926447S *17:43303284-43303924 *3: 10057201 -10 57550 chr6:‘ 1913314-94914128 irl 1:81866745-81867388 ehri 7:45949555-45959389 *3:32798517-12801288 *6:95560784-9556 f 841 irl 1:83539176-83S39484 *17:47072538-47078053 vh; >.14415240-34 16257 *6:95966432-95968146 di l 1:84430917-84432527 dir 17: 722733 -47228092 *3:15835295-15835521 *6:96205958-96207035 di l 1:88719947-88720958 *17:47354846-47355223 *3: 35836435-15836937 <:bn> 9842671 -98427488 did 1:88798740-88799384 *17:47571922-47575737 *3:20090054-10690701 <h<6 M 150709-99151607 <*rl 1:89O51543-89053244 *17:55057576-55038080 *3:22029761 -22031327 *6: 102536084-102536863 dirl 1:89867404-89868786 *17:56234202-56234996 *3:26286174-26286717 chr6: 103168939-103170676 dtrl 1:9042 131-90424963 *17:56365577-36366322 *3:26431657-26432436 *6: 103944339- 103945224 did L94307552-943O7S93 du 17:57386! 99-57386955 *3:26445079-26445734 *6.107978897- 107981X141 <*rl 1:94439248-94441072 * 1:58159626-581 $9984 *3:27862507-27864615 *6: W9571877- 10957362 f dwl 1:95854886-95855253 * • 7:60746855-60748270 *328341703-28242609 *6: 110804675- 111)804871 did 1:96278144-96278911 *17:60802327-60802479 *3:29326660- 9327675 *6: 111354982- 111355394 <*111:96916427-96917339 *17:61517360-61517878 *3:38992198-38993452 dw6: 112229355- 112230564 dwl 1:9753884S-9?539394 dirl 7:66770547-66771149 *3:42132748-42133717 ehr6: 113009497- 113011079 irl 1:9S294896-98295533 did 7:71537556-71538007 *3:43735418-43735740 *6; J 17137589-} 17138503 dwJ J:100156066- 100157208 d rl 7: 73864862-73866896 d ir3;4 100056-14100226 <hi;>:1174 3161-1174241 9 dwl 1: 100 22 18- 160323274 dirl 7: 74696437-74697315 *34620493046206726 *6:11 "565925-117566673 dirl 1:100351637-1003525 4 di l 7:75524445-75525380 *3:46830063 6830838 *6.117763417-117763740 did 1: 104886769-104887972 dir!7 ^75612833-75613585 *3:48533251-48533607 *6:117937084-117938104 <*rl 1: 105830892-1958 1895 *17:76771103-76771602 *3;55170008-5S171063 dit6;ll8l50934-USl5U04 irl 1:112752164-112752914 dirl 7:78887869-78889801 *3:55865650-55866291 chr6: 122369992- 122370751 irl 1:113145684-113146123 *17:86793134-80798817 *3:58512007-58533432 < M: 12257426 -122574802 di J J:! 14 09438-114510340 *18:975864-977969 *:58916562-5891703 <hi;> 123793097- 123793936 did 1:119557008-119558725 dirl 8: 1508235- 1 10(K)0 *3:670SW63 -67080404 *6: 125033 i 44- 125034040 dwl I: ■ 22049404-122051081 *18:22296030-22297615 *3: 85653572-85554564 <;bi6 125125587-125126253 dull: 122310635- 122312424 irl 8:23770424-23770823Attorney Docket No.: DFS-34525 (DFCI 3605)Table 1 - Differentially H3K4me3 Modified Loci - Basal Upd)r3:88247694-88348024 cte6: 126647743- 126648608 etel 1: 3: 23228582-323229623 chr?8:24O2<) 11-24031610 chr3: S9401X)06-S9460927 cte6: 130181944-13 182523 dud 1:124952619-124954330 ctel 8:24859251-24860420 ii'3:895l5225-89516274 ehrt>:141887076- 141888188 w 11: 125405126 - 1 5-107474 chrl 8:25322190-25324228 cte:89923664-89924224 chi*; 142066 16-142068005 dirl 1:326188300-126188577 did 8:26001680-26003829 chr3:9O382791-903842O6 chi6: 1 23691 8- 142369815 etel 1: 127232749-127233859 ctel 8:26202159-26292918 cte3 ^3526677 -93527526 chrti: 145244299- 145249117 did 1:130817493-130818339 ctel 8:28736350-28737542 ic:94463974-94464954 ehi*:l48499847-l4S50H22 <*rl2:739654-740716 dirl8:28932467-28935114 cte31947840 "0-94785092 cht6: 148679528- 148680388 etel2:798968-799852 <*rt 8:29027^8-290 2865 te3:97 6tnj44.»7361113 cte6: 149353316-149353878 dtrl 2:1868 23-18*9176 ctel 8:29034586-29035 f 61 cte3:97962877 *97963600 chrti: 152667-117-152668268 etel2:2392901-2393857 ctel8:299!4023-29914886 cte3:98274333-98275145 chi*: 153196745-1531 7380 <*112:323949 -3240800 <*r?8:33S98305-33598S43 cte3:98593541-98593846 chr6:153336559-I53337158 etel2:3323695-3324296 ctel 8:3851 421 -38529096 chr3:98610854-986? 1475 Cte6: 153897265- 153898078 did2:3506440-3507579 ehrl 8:39211504-39212500 cte3:986l2468-98615lS9 ete*!-<•<• 82197-156683317 etel2:4*l 7*74-46187*0 dir 18:39354972-39355458 chrS: 8615523-98616111 chf6:15775569O-15775635$ etel2:4781138-4782507 chr! 8:42262157-42263353 chr3198685812-98686489 cte6.158383646-158384032 did 2:5068935-5069716 ctel 8:46359426-46361317 c 3:9S6998I -98700388 dirtk J 5967 115-159674474 di 2:5230740-5232515 ctel 8:48661326-48661 SS8 cte3:98700985-98701670 ch*; 163264954-163265670 *112:5399128-5400965 *£18:51037286-51038631 chrS 198702046-98702802 chr6; 165200674- 165201606 etel 2:6253820-6254 8} chrl 8:53559893-53561561 chr31987335 3-9 733895 c 6: 1 *5596165- 1 *5597377 <*rl 2:7403457-7404875 ctei 8:57702371-57703379 <*r3:98753655-987S45l9 ehl*; 168396579- 168398390 <*rl2:7991798-7992J59 dir 18:58983125-58984046 cte3:99355561 -99358090 hi*; 169067993- 169068278 ctel 2: 8089169-8690317 ctel 8:66457209-66459571 cteS:99457337-9'W58523 cte6.17O55525l-J7O55*725 did 2:8146707-8147305 ctelS:66483632-66484009 liri: 102938846- 102949075 chr7:643647-64S083 did 2:86 1104-8*02094 ctel 8:67136615-67137326 cte3: 19325 043-10325 832 chr7:«52955-6S4152 *rl2:8720305 -8721238 ctel8:70210049-70211961 cte31103281035-103281915 chr7:680077-68i233 etel 2:8975202-8979538 ctel 8:73920642-73921413 ch r3:?0357HX>fi-103571631 chi":!597342-1600980 <*112: 785445-9785920 chi 18:74396039-74396507 <*r3; 1041 0364- 104164553 elu7 196169M962347 <*rl2;9835038-9835512 dir 18:75026665-75027370 cte: 109232532- 109133280 ch7:2306574- 2309915 etel2: 10015406-100157*0 <*£18:75333632-75334898 chr3: HO158832-11O159733 cte?:2348992-2350391 did 3:10025270-10025732 ctelS:76584632-76585263 ir. Ml 1851509-1 US52OI4 cte?:2850911-2S5222I <*rl2:10G9522S-I0096525 ctel9:2079948-208709f cM 1115036390- 115037655 chr7;4S33744-48354SS ctel2:10253385-UQ53977 ctel 9:5260293-5261343 chr3: 118632540-118633823 chi: 1: 60491 -5161112 etel 2:10280756-10282802 cte?9:5 17675-5418360 cte.^ll 8725655-118726541 cte7:5685874-5686453 cteJ2:10548489-10551079 ctel9:5436315-.5437124 dH-3:ri 9357977-119357709 chi7;5732090-S732661 ctel 2: 1 561002- 1056-1318 dirl9:6?17940-672128O chi311202 1871 -120292411 chr7:5734626»5735282 *112:10634326-10634915 ctel9:10246001-102472l9 cte3:?20737753-l20738026 drr? 9443405-9444*66 did 3: 11101507-11101876 ctel9:10626051-l06298J3 cte3:12i378923*121379809 cte7:18977859-18978122 <*112:12818254-12818758 chr!9: 1 <148275- 1404973 J 3;12l 964643-121965599 ehi; 19233891 -19234786 <*rl2:14427I85-1442«a)3 dir 1; 14097036- 1 097362 cte3: 1220 3700- 122047645 chr7: 19699842- 19700459 ctel 2: i 5037443-15037633 ctel9:14636879-14637864 cte3:1225086 3-122509012 chr? 2258S957-22590234 did3:150 714?- O57859 chil9:14885710-14888261 cte3: 323549419-123550647 chr7;22896981-228977?6 chr12:15081016-15081479 dirl 9: 16043024- 16043291 did:125889417-125890339 du7:23285934-232S7 30 etel2:150815. E 4-15082188 cte!9:3H60138-311M338 lw3: 326788344- 126789338 ^7:276 5534-27*86943 did 3: 15248078- 15348772 ctel9:31183345-31184352Attorney Docket No.: DFS-34525 (DFCI 3605)Table 1 - Differentially H3K4me3 Modified Loci - Basal Upchr3:126854055-126854917 dir7:3356663S-33567669 ctel 2: 15500654- 15502100 chd9:31942814 -3194323.3 chr3:128372992-12S373777 chr7:35132062-35133424 did 2:17356474- 17357896 chrl9:32595627-325958?3 e«d2S6542HM2S655037 chr7:35.163933-351644® chd2:17926672-.1792750? dirl9:.344SS909-.34489742 d«3: 1318.5.5667-131856550 chr7:37392725-37393337 dirl2:18008275-l 8009239 did 9:37838611-37839076 ehr3: 132484717~ 132486044 chr7:390S2365-3905471S dirt 2:18937691-18939027 chrt 9:38539405-38540291 chd:1326704n-1326715«2 chr":41734203-41734899 did 2: 19927798- 19930704..lirio:39528765-39529432 did: 132723574- J 32724543 chr7:41735229-41742734 dir!2: 19931984- 19933794 cht 19:39572374-39572752 chr3:135l57250-135158798 cht7.-42532923-42533936 dirt2:20014641-200J6067 chd 9:39572920-39576308 chr3: J 35377423-135378255 chr7: 43097785-4 >999759 d«’12:20056224- 20057012 dirl9:39685995-396899jt) chr3:t36726152-136726788 chr7:43152996-43153857 ehrl2:20413278-20413873 chrl9:39737?57-.?973S675 chr3:i37432006-I37433925 chr7:43455604 -434.57619 dirl2:20572747-20573693 du 59:40005166-40006921 chr3:138866395-138867267 chr7:43685476-43687673 dirl 2:20930401-20930862 dirl9:41118786-4} 122009 clw3: 140771356-14-0772000 chr“:44025465-44030901 chr!2:20936655-20937052 chr19:43278396-43279528 du.3: 145051816- 145052770 ehr7:45981387-45981829 dir 12:20943214-20943533 ^119:43356247-43357102 cfet3:145734410-1457348S»7 chr7:53099325-53100252 dirl2:21366724-21368741 dir! 9:43709335-43709718 chr3: 148936034-148938278 <*17:55119950-55123043 did 2:21547121-21548896 chrl9:46929381 -46930609 did: } 50365012- 150365360 chr7;55l774i0"55179819 clw'12:21680016-21681205 chrl9:46957669.4695S4f4 chr3:iS295S503-152960484 dir7:557687?5-55769182 dw!2:21889587-21890669 did 9:47021302-47922787 chr3:153O10544- 153010757 drf7:77129619-77129979 dtrl2:21927241-21928347 ehrl 9:48082034-48082430 '. W<-: >0 S-M;'..: 54040188 chr7:80543060-80543318 dirl 2:22052350-22053291 chrl 9:5(18 f 5043-5(1816595 dir3: 153080859-153000508 chr784878817-84879992 dwl2:22289319-22290255 dir 19:51070573-51071981 ch: 3; 153258791 -1532S9212 ehr7: S4964262-84%5290 dwl 2:22299292-22299635 d)rt9:514S2S35-5}457l60 chr3:155229312-155230132 Chr7:90802620-9080342.1 dirl 2:22486411-22488968 chrl9:56806599-56807968 «: 155935841 ■ 155936145 chr7: H3O769330-H»773267 <*rl 2:22561652-22562270 dir20:l 10065- 111665 chr3: 156001989- 156002783 chr7: 101360787- 101361734 dwl2:22562756-22563425 du:20: 1458329- 1459480 chr3:15744253O-157443O17 chr?:10218W57-l0218S625 dtrl 2:22987133-22987988 chr20:3526702-3527515 dis’3:157614567-157615198 du7: 102274493-102276295 chrl2:23298805-23299675 chl20:3993?72-3999O44 dir3:1588lS592-1588l9734 ehr7.104869519- 104876407 dwl2:23541676-23542557 ^120:6301965-6303875 d«’3:1594.5O173-J5945O791 chr7:lO7148325-lO7149135 dwl2:24S 91902-24104326 du:20:lI612539-lJ6i4083 clw3: 159570728-159571092 dw7: 109284172- 109287469 dii12:2564}640-25643789 chr20:13881162-13882029 dw.3: 362564952- 162564859 dir? d 10202506- 110293935 clirl 2: 25685*507-25690488 chr20: 19387264- 193 $8 f 93 dii'3:i62583472-162583771 chi-7.112556405-112557479 dwl2:27700178-2??00759 dir20: 20247814-20249147 chr3: 164009253-164010178 chrM 15347526-115347871 dtrl2:27745499-27746<»6 chr20:21683712-21684429 cta-3:164239069-l 64239349 chr": J 15793021-115793644 dwJ2:37846859-32847319 chr20:21S965J 8-21897800 did; 1655921 «>- 165593861 dir?: 119546189-119548962 ciwl2:33484934-33485366 dir20:2316S546-23169314 ch 13: 166162329- 166162648 div’: 121591799-121592494 dwl2:33925845-3392674O dw:20:26214119-26215197 clw3: 169615848-169616386 did 128601897- 128602429 did 3:34001083-34001812 chr20:30662583-3(WJ823 chr3:17J580868-171531278 chr7:130872180-130872734 chrl2:34217946-34218805 chr2O:3O3! 5466-3031610 J chi3; 172385733-172386274 dir?; 133316974-133.318250 dwl2:34224307-34226190 du2O:3O615851 -30617039 chr3: 172395413-172395686 chr?: 134233825- 134234552 dtrl2:3444235i-34M4123 ehr20:37719059-32721779 dw3:172727067.172728677 djr?:136103968-l 36105260 dirr2:344880O?-34491475 dir20:32792422-32794197 chr3; 173982422-1739S35O5 dir?: 137027756- 137028678 chrl 2:34498475-34504238 dir20:3669S948-36699716 dlr3:17444l211-174441546 dir?: 138456920- 138459027 <*>112:34515565-34517046 <*<20:36700693-36701313clw3: 175609249- 175609892 did 140766775- 140768257 did 2:39190341-39l91221 chr20:36780575-36794674Attorney Docket No.: DFS-34525 (DFCI 3605)Table 1 - Differentially H3K4me3 Modified Loci - Basal UpchrS: 178822284- 178822971 *<7:141387161-141387699 did2:39193046-39193950 ch^20:36847594-36848864: 179659858-179660557 <*<7:144550819- f 44551350 did 2:40372098-40372887 clt20:368$8327-36889785 <*<3:180585974-180588515 <*r7:1571O223 l-l 57102508 did2:41221695-41222429 dir2(};36932390-36933320 dud: 18140.513- J 81467006 <*<8:2590828- 2592089 *<12:41239584-41240196 chr20;42073365-42073864 <*r3: 183842013- 183842758 chr8: 15419003 d 5419733 did2:43863573-43865783 chr20:44321844-44322745 chr5: T $4432854- 184434662 <hr$: 1652725$M 6528335 chd2:44507376-445G801O:chr20:45525892-4553OO42 vhi3: 184458747- J 84459057 <*<8:23201095-23202025 clwl2:45325591-45326150 chr20:45583273-45584065 chr3: 184472350- 184472652 eht8:29970646-2997H37 diH2:453445<>4-4534553t> <*<20:45754606-45754967 dw3: 1857849 J 5-165785560 <*r8;33489965-33490936 cfcjrl 2:45638175-45638408 cta20:46O6O216-46061 f 38 <*r3:l$6371557-186372141 <*<$□7349515-37351702 chd2:4834049M8340765 cht20:478H 904-47812517 <*<3:188693813-188694337 <*<8:37767691 -37768028 ehrl2:48914444-48915297 <*<29:4«857316-488S7646 <*<3:189507323-189510904 chr$:4028S945-4O29O548 did 2:52334472-52335573 <*m;48902. M8-48902692 clw3: 1 $9559592-189559809 <*r$:40673245-40673613 did2:52679447-52682619 dtT20:48954995-4S9558? J did; 192506664- 192507316 <*<8:40863909-40864425 dirl2:52843156-5284640«> dit20:49045390-4904»556 ch<3: 196062473-196066062 thr8:41121612-41122097 dirl2:52S82957-52887755 <*<20:49067531-4!»<58. W8 clw3: 196069658-196071X173 <;*:> 47882286-47882551 du12:52910061-52914980 <*d!0:49112309-49112992 dt<3: 196290383- 196290719 chr$:47929950-4793 II 51 <*112:53205452-53207857 ch<20:52i I9303-5212146J <*JC3:197121033-197121562 <*<8:48011380-48013360 ehrl2:548W395-54S0972i <*<20:52341437-52342273 chr4:1106803-1198902 ehr8:48091042-48091497 dtrl 2:55480232-55481504 ch<20:5236O75O-52361171 dw4: 1542656- 1544316 chr8:49375128-49375821 chrl 3:554951(15-55496453 cht20:5286674S-528676O6 <*<4;2922669-2933352 <*<8:49611949-4961243? <*rl2:5556O37O-5556J539 chr2O:53399O30-533*>888 616'4:3086626-3087117 eh<8:496208984%22443 dwl2:557J9407-557!9898 <*<20:5503.3420-55033876 <*<4:5445458-5446502 <*<8.52361872-52363635 <*rl2: S6060530-5606l557 <*<20:55379073-55379505 <*<4:5595300-5596124 <*r$:52520483-S2521893 did 2:56468682-56476922 ch<20: 553 $9696-553909S5 <*<4:7919438-7921042 <*<8:52892671 -52893006 ehrl2:59234144-59235563 <*<20:55401866-55402658 <*<4:16023413-10024045 chix Sun 77O-54-M23O5 dtrl2:6168754{i-616SS339 <*<20:55405009-55405501 <*<4:55385630-11386719 <*<8:54870083-54870676 did2:62335230-623360l0 du2053349735-55550290 dirfri 2725616-! 3726295 <*<8:56979?9O-S69S05O8 <*rl2:645«936i-64590200 dir20:55646333-55646780 du4: 144811*88-14483487 <*<8:57327614-57328638 ehrl2:64686677-64687359 <*<20:55754124-55755102 <*<4:54756238-14757159 <*<8:59244411-59244890 dirl 2: 70861517 -70863404 <*<20:56000346-56006845 <*r4: 15280239- 152$ 1070 <*<8:60086519-60087259 <*1-12:71327435-71327863 <*<20:56749997-56751463 da4;13936612-! 5940397 <*r8:62l85?’3-621S6738 <*rl2:74371529-74372697 <*120:57088905-57093190 dw4: 1694421 &- 16945226 ch<8:63713089-6371'4094 dtrl 2:74564056-74565504 <*<20:58532315-58537554 chpl:17730033-1773J 142 <*<8:64071839-64072817 <*rl 2: 75268457-75269216 <*<20:5 $629730-58633802 dtr-l: 19456860- 194SS912 <*<8:64287292-64288099 <*rl 2:75876274-75876749 <*<20:58638816-58642923 <*<4:27382681-27383724 elu8:6'l402157-64403125 <*rl2:76848684-76848968 <*<29:5M91600-58692369 chr4:37003359-37004389 chr8 65OM622-65Ol 5734 did 2:77572286-77573600 £*■20:60378749-60379667 *(4:37074301 -37075583 <*r$:66472695-66472962 <*112:78227268-78228102 <*<20:607338 J 3-60737000 du4;38754l99-38754502 chi8;<59931041 -69932034 <*rl2:80847889-80848340 <*120:62085295-62086249 <*<4:47296149-47297129 chr8:70164S 17-70167296 dt-12:80871206-8O872055 <*<20:62281620-62286265 <*<4:47566696-47567423 chr8:72726936-72727226 did 2:81471090-81473455 *<20:627 < 3! 46-62734604 dtpl:48059464 -’18060027 <*<8:75417584-75418850 <*<■12:85509796-85510254 ch<21: 15068879- 1506975! <*<4:48712902-48714234 «h<8:75776$38-75779653 dwl2:89108.1.17-89108523 <*<21: 15077020-15077904clw4:48730849-48731294 <*<8.75896272-75897629 tftl2:950375l8-9S038629 <*<21:15095333-15096671Attorney Docket No.: DFS-34525 (DFCI 3605)Table 1 - Differentially H3K4me3 Modified Loci - Basal Upd)r-4:54430-1.39-54431608 cht8:7800053 b7800l6S1 <*712:95961966-95962746 ch^h 15435723-15437574 chr4:54743108-54743875 chr8:78851773-?«8537O8 dirl 2:96387802-96390465 dir21:17791772-17794652 chr4: 5 $400195 -55401457 ch)-S;79O25109-79027229 did 2:96431539-96431827 chr2l:m$0444-t8700(538 clu4: S8433785-58434504 cl»8; Sl 143786-81144521 dwl2:96820522-96821297 £0121:19063441-19064175 chr4:62811117-62812118 chr*:83170490-83] 70880 <*r] 2:99714626-99715630 C1H'2!: I927<621-19275112 chr4:63467752-03463754 chrS:84358584-84360231 did 2:99856707-99*58009 chr21:2"6j77 j 1-27638165 dirt;64127757-64128471 ehi8: S7255753-87257l74 dwl2: 100109301-100110144 dir21:27777943-27778664 dw4:£4398047-64399015 cht8:88339267-88340424 <*rt2: W27067*5-i 02797745 dn-2!:30472079-30472577 dir4:6573013J-6573W39 chr8:88437999-8«439385 dirl 2:193226445- 103227035 du-21:34395002-3439:5726 chi-4:66 J 59436-66160306 chrS:89160961-S9161978 did2: 103293269- 19329398! chr21:3448f 562-34482458 du'4:684l5576-68416l63 cht8:8S*697652-896S*9274 dirl2: I03888992-I03890047 d)l21:41404935-41405850 dir4:6*838326-6**39371 chr*:90702815-90703:265 <*rl 2: 114842932-114843779 chr21:44612985-44615940 ^^4:68993127-68995549 d)r8:907I030S-907J 1320 dal 2:131363457-121364618 du-21:4478J 121-44782556 dirf;69313l2S-69316093 ehi-8.91101123-91107977 dirl2: 1:23183734-1:23188191 chr21:44863597-44864740 ciw4:69316431-69316937 dir*:91109540-9511110! <*rl2:!23193O50-i23J93S39 dir2J:46977541-4607*062 chr4:69326288-69326953 £018:94241395-94242536 dill 2: 123 J 96905-:l 23198173 du-2l:46129012-46129677 dir4:70529588-7G530512 d)rS:944I7994-94418893 did 2: 123198320- 12320153 S chr2l:46t 31091-46131 S93 did: 71584405 -71584869 chi8:97128l43-97l30120 dir 12: 323408957-123410468 chi21:46385169-46385852 chr4: 73459452 -73460615 chr*:971572!9-97158360 dtrl 2: 125102241 -125103720 chr21:46422316-46425249 rfw4:76200933-762i!2038 chr8:97166980-97168424 dir! 2: 130621531-1:30622616 d»-21:46874206-46877599 clir4:76326286-76327202 einS:973506 J 5-97351030 dir 12: 132689659- 132690630 chr21:47294510-47295201 91)1'4:76373006-76373757 cht8:97431708-974323 "8 dir!2: 133441659-1: 33444334 djj2J 147405266-47406488 dir4:76486777-764*7866 £018:97536318-97536572 did 2:133446049-133447273 du-21:474*4931-47485952 dir4:?6972849-7697jj23 chrSOWm 14-98844313 did 3: 19683017- 19684647 dir22: 17378422- 17379395 clii'4:80625752-80626161 cht8:‘.»9626 J 18-99627522 dirl3:39790080-19791141 cfo22d.77SO570-17753755 chr4:*4878577-84*79808 chr*:99662556-99663390 dtrl3:20070642-2007195I dir22: 17*30088-17839428 chs4:85219098 -85221021 £108:99750434-99751652 dirl3:22601377-22601918 dir22:17848129-l'7848555 dirt: 869966*7 -869977 *6 ehrS.100956163-100956445 dirl3:23O723Ol-23i)74O86 dir22:21811107-21812017 cJu4:87372689-87375103 chi'S: 101603484- 101603654 dirl3:23147087-23149857 <*122:23586734-23588403 clir4:*7571180-87571559 £bi8 103910509- 103911377 did 3; 24144240- 24147654 dir22:2463*479-24641607 chr4: SSS96583-8S901219 chrS; 104231078- 104232217 dirl 3: 2560814- 1-25608465 cht32:256S0663-25690474 du-4:96835130-96836667 chrS: 104620407- 104621368 dirl 3:27699038-27700612 dir22:316'43S10-31647l3.5 chr4:9*55. V19-98555434 chr*: 104761220- 104763749 dtrl 3:30833244-30834317 chr22:33402068-33492*95 chr4:9S824673 -98825358 chrS: J 04800308- 104801828 dirl3:36587353-36589020 chr22:36290692-36291063 dir4:99SS0204-99880429 ciir8: 105235157-105236652 did3:36589176-36590100 chr22:4(W 1 S620-40-119363 dirt: 10035466:2-100355344 elivS: 105337871-105338371 dirl 3:37052944-3705325 i djr22:4O925914-40929986 dir4: 100926696-100927870 £hr8: 105481048- 105481759 did 3:37150607-37151262 dir22:40937362-4093*OO6 chp1:104477731-104478672 chrS: 105744171-105744400 d)rl3:37729M4-37730795 cht22:45928648-45931394 dirt: 10447*746- 104480305 elirS; 105757064- 10.575*416 dirl3:37824320-37825181 dir22:45947549-45948937 dir4: 194915927-104916586 t hr*: 106200251 - 106200821 dtrl 3:40409533-10410020 chr22:46364264-46365788 dir4: 105613284-105614146 £*18:108251985-108253583 did 3;40930359-40931051 chr22:468 J 1968-46812470 dir4:107497681-107498462 dirS: 108441339-108441827 dwl 3:4440407:1-44404726 dir22:46907245-469il721 dirt: 110820854-110821595 dii-8: 108793943- 10879+463 dirl 3:46754623-46755052 d)r22:49764292-49766390clw4:l l 1614072-H 1614944 dir*: 109942649- 109943395 did 3;48437548-48438360 dir22:50231735-50233075Attorney Docket No.: DFS-34525 (DFCI 3605)Table 1 - Differentially H3K4me3 Modified Loci - Basal Upchr4:l 11797203-111798293 LhtX: U(li6303bll0U'.3553 |d»rU149W639MW?0n ch»22;51180736-511X2027Attorney Docket No.: DFS-34525 (DFCI 3605)Table 1 - Differentially H3K4me3 Modified Loci - Classical UpI-I3Kta»3 - Classical Locus Up H3K4tne3 - Classical Locos Up H3K4me3 - Classical Locus Up «3K4me3 - Classical Locus Up chrl: 5056433- 1070258 chr3: 133756603- 133758864 chr7: 105722422-105723163 chrl 3:41847697-41848336 chrl:2022970-2023%5 chr3:1377O7I65-1377O7723 chr?: 124633096-.124635237 chrl3:-1533S4J M5339556 c5irl:3M4948-31054f« chr3;l377!6302-l37723552 chr7:l28514329-128514932 chrl 3:45890389-45890737 chrl:323688O-324I008 chr 3: 137723757- 137729630 chr7:l29007617-129011548 chrl.3:47162410-47163226 chrl:6420094-6420S99 chr3: 140954611-140955079 chr7:13405670M34059l92 chrl3:47l 81973-47182518 chrl;6882709-6883293 ehr3 142339587-142339826 chr7: 134211584- 134217438 chrl 3:47233469-47235446 ctal: MSI 8483-10822337 chr3: 145939983- 145940905 chr?: 134217632- 134218149 chr!3:50809731-50810572 chrl: 10875420-10875988 chr3:149J 92038-149 J 99783 chr7:138646064-138646301 chrl3:60254935-60255459 chrl:t6660499-16660935 chr3: 150928651-150929084 chr7:i388W655-138811075 chrl3:6lOO76J7-6lO0S57J c5irJ:17083525-J 7087602 chr3:155364442-l55364856 chr7: 341736353-141736813 chrI3:7I8799ll-7188O637 chrl: 17906705-17907768 c hr 3: 168 $45912 - 168 $46270 ^7:141803114-141804128 chrl 3:792.19895-79229131 chrl: T9751549-19752469 c hr 3: 168988462- 168992206 chr7: 141806056-141808602 chrl3:98959739-98960<426 chd; 20064102-20064399 chi$:l6958589< H 69586533 chr7:!41811158-141814351 chr 13:98965497-98966970 chrl:29l375l7-2OI43260 chr3:l695S6537-l69588429 dir7:141S14684-14i8i5128 chr!3: I®12O397-19OI20819 chrl:24338441 -24339103 chr3: 177017952- 177019998 chr7: 141820117-141820742 chrl3:10l I69229-10U7O521 chrl:2?2363O5-27241320 chr3: 182477995- 182478711 clir7:14l82l0l 6-141821275 chrl3: 107128675- 107329366 clirl:27296S92-272972l4 chr3; 182943875-18294442 f dw7: 142939829-142940194 chrl 3: 107302032-107305602 chrl:32134767 -32137228 c hr3: 185043954-1850+W69 chr7; 144421788- 144422126 chrl 3: 199508243 - 109598615 chrl:32?88969-327S9316 chrl: 185046103-185050888 eh <7:150211812-150212522 chrl 3: 1099S4540-K6MS5700 dirl:33772023-3377327S ein-3: 186478758- 186479460 chr7: 350549009- 150550537 chr 13:113759949-113760833 <^1:34042521 -34043644 chr. U 187224519-187225846 dw7:152J66542-152167393 chrl 3: 1I4OS0256...

Claims

Attorney Docket No.: DFS-34525 (DFCI 3605)CLAIMSWhat is claimed is:

1. A method of determining a classical / basal subtype of a pancreatic cancer in a subject, the method comprising quantifying, at one or more genomic loci in a biological sample obtained or derived from the subject:(i) one or more histone modifications;(ii) DNA methylation, and / or(iii) chromatin accessibility,wherein the sample optionally comprises cell-free DNA (cfDNA) from a liquid biopsy sample.

2. A method of demoffitttermining if a subject has basal subtype pancreatic cancer, the method comprising quantifying, at one or more genomic loci in a biological sample obtained or derived from the subject:(i) one or more histone modifications,(ii) DNA methylation; and / or(iii) chromatin accessibility,wherein the sample optionally comprises cell-free DNA (cfDNA) from a liquid biopsy sample.

3. The method of claim 1 or 2, wherein the one or more histone modifications are quantified using a histone modification assay that measures one or more of H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4mel, H3K4me2, H3K4me3, and pan-acetylation.

4. The method of claim 3, wherein the histone modification assay detects H3K4me3 modifications.

5. The method of claim 3 or 4, wherein the histone modification assay detects H3K27ac modifications.

6. The method of any one of claims 3-5, wherein the histone modification assay is selected from ChlP-seq (Chromatin ImmunoPrecipitation sequencing), CUT& RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT& Tag (Cleavage Under Targets and Tagmentation) sequencing.

7. The method of any one of claims 1-6, wherein chromatin accessibility is quantified using a chromatin accessibility assay selected from ATAC-seq (Assay of Transpose Accessible ChromatinAttorney Docket No.: DFS-34525 (DFCI 3605)sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde-Assisted Isolation of Regulatory Elements sequencing), MNase-seq (Micrococcal Nuclease digestion with sequencing), and a DNase hypersensitivity assay.

8. The method of any one of claims 1-7, wherein the sample is blood, plasma, serum, or urine.

9. The method of any one of claims 1-8, wherein the subject has previously been determined to have pancreatic cancer, optionally wherein the pancreatic cancer is pancreatic ductal adenocarcinoma (PDAC).

10. The method of any one of claims 1-9, wherein the subject is a mammal, optionally wherein the mammal is a human.

11. The method of any one of claims 1-10, wherein quantification of one or more histone modifications and / or chromatin accessibility at the one or more genomic loci as compared to a reference indicates that the subject has a basal subtype pancreatic cancer or a classical subtype pancreatic cancer.

12. The method of claim 11, wherein the reference is a predetermined threshold, a measurement from a liquid biopsy sample, and / or a normalized value, optionally wherein the reference is a measurement from a liquid biopsy sample obtained from a cohort of subjects who have previously been determined to have classical subtype pancreatic cancer (e.g., classical subtype PDAC) or basal subtype pancreatic cancer (e.g., basal subtype PDAC).

13. The method of any one of claims 1-12, wherein the method comprises quantifying one or more histone modifications, DNA methylation, and / or chromatin accessibility at one or more genomic loci in Tables 1-3.

14. The method of claim 13, wherein the method comprises quantifying H3K4me3 modifications for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1.

15. The method of claim 13 or 14, wherein the method comprises quantifying H3K27ac modifications for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2.

16. The method of any one of claims 13-15, wherein the method comprises quantifying MeDIP for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 3.

17. A method of treating a subject having pancreatic cancer, the method comprising:Attorney Docket No.: DFS-34525 (DFCI 3605)administering a pancreatic cancer therapy to the subject based on the classical / basal status of the pancreatic cancer, wherein the classical / basal status of the pancreatic cancer has been determined using the method of any one of claims 1-16.

18. A kit comprising reagents for determining histone modification and / or DNA methylation at one or more genomic loci, wherein the one or more genomic loci are selected from Tables 1-3, optionally wherein the kita) comprises reagents for quantifying H3K4me3 for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1;b) comprises reagents for quantifying H3K27ac for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2;c) comprises reagents for quantifying MeDIP for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 3;d) comprises one or more antibodies for use in ChlP-seq, further optionally wherein the antibody specifically binds H3K4me3 -modified histones or H3K27ac-modified histones;e) comprises reagents for isolation of cell-free DNA (cfDNA) from a liquid biopsy sample; and / orf) comprises instructions for determining if a subject has basal or classical subtype of pancreatic cancer.

19. A non-transitory computer readable storage medium encoded with a computer program, wherein the program comprises instructions that when executed by one or more processors cause the one or more processors to perform operations to perform the method of any one of claims 1-16.

20. A computer system comprising a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform operations to perform the method of any one of claims 1-16.

21. A system for determining if a pancreatic cancer is basal transcriptional subtype in a subject, the system comprising a sequencer configured to generate a sequencing data set, epigenomic data set, and / or gene expression data set from a sample; and a non-transitory computer readable storage medium of claim 19 and / or a computer system of claim 20.

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