Methods for identifying and treating diseases characterized by allele specific expression

Abstract

Provided are methods for identifying and treating diseases or disorders characterized by allele specific expression (ASE). Various embodiments provide methods for identifying genes exhibiting ASE associated with a condition, such as a disease. Certain embodiments provide methods of treating such diseases, including the use of gene therapies and by providing therapeutic agents. Gene therapies may include altering expression of an allele associated with a gene exhibiting ASE. Additional embodiments identify a disease associated with a gene exhibiting ASE in a subject. Some embodiments are specific to identifying and / or treating a cancer, such as prostate cancer.

Description

[0001] METHODS FOR IDENTIFYING AND TREATING DISEASES CHARACTERIZED BY ALLELE SPECIFIC EXPRESSION

[0002] CROSS-REFERENCE TO RELATED APPLICATIONS

[0003] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 541 ,193, filed September 28, 2023, which application is incorporated herein by reference in its entirety.

[0004] INTRODUCTION

[0005] Allele specific expression (ASE) is a phenomenon where the maternal and paternal alleles of a gene are expressed at different levels, often caused by gene regulatory variants in cis with, or on the same strand as, the affected allele. Most genes in homeostasis show biallelic expression, or expression of both alleles equally. Although ASE does occur in normal tissue through mechanisms such as X chromosome inactivation, ASE shows increased frequency in tumors and has been identified as an oncogenic mechanism in several cancers. In melanoma and other cancers, recurrent somatic mutations in the promoter of telomerase TERT) create transcription factor binding sites on one allele and result in activation and expression of one allele of TERT. This promotes cellular immortality and tumorigenesis. ASE analysis identifies genes affected by c / s-acting genetic effects that may not be appreciated through bulk RNA sequencing (RNAseq) analyses.

[0006] Because of the role that ASE can have in disease and disease progression and the limitations of RNAseq, there is a need for assays, methods, systems, and devices that are capable of identifying ASE and for treating diseases characterized by ASE.

[0007] SUM ARY

[0008] Provided are methods for identifying and treating diseases or disorders characterized by allele specific expression (ASE). Various embodiments provide methods for identifying genes exhibiting ASE associated with a condition, such as a disease. Certain embodiments provide methods of treating such diseases, including the use of gene therapies and by providing therapeutic agents. Gene therapies may include altering expression of an allele associated with a gene exhibiting ASE. Additional embodiments identify a disease associated with a gene exhibiting ASE in a subject. Some embodiments are specific to identifying and / or treating a cancer, such as prostate cancer.

[0009] BRIEF DESCRIPTION OF THE FIGURES

[0010] FIGs. 1A-1 E provide ASE analysis in normal prostate, localized PCa, and mCRPC identifies recurrent ASE across PCa and specific to each stage. In particular, Fig. 1 A shows ASE definitions and candidate gene identification. Fig. 1 B shows a distribution of per-sample biallelic expression (BAE), allele specific expression (ASE), and monoallelic expression (MAE) proportion in each dataset (for each of BAE, ASE, and MAE: left-“normal”, middle-“localized”, right- “metastatic”). Two-sided Mann-Whitney U test with Bonferroni correction. Fig. 1 C provides a heatmap showing recurrent ASE genes in each dataset (ASE in at least 10% of each dataset and have a testable SNV in at least 10% of each dataset). Fig. 1 D provides an upset plot: Intersection of recurrent ASE (5% or more of samples, have a testable SNV in at least 10% of each dataset) (Normal:*; Localized: **; Metastatic:***). Fig. 1 E illustrates a plot showing ASE frequency of genes with data in both localized PCa and GTEx normal prostate. Dot color indicates significance of results of Fisher’s exact test for each gene.

[0011] FIGs. 2A-2E illustrate ASE is associated with altered expression of cancer genes. Fig. 2A shows genome-wide frequency of ASE across localized prostate tumors. Fig. 2B provides median overall expression of 11601 genes undergoing ASE in at least 1 sample in ASE samples compared to BAE samples. 189 had a significant difference in overall expression between ASE and BAE samples. The majority (140) showed higher expression in ASE samples (green) while 49 showed higher expression in BAE samples (blue). Fig. 2C shows genes undergoing ASE that both show differential expression between tumors and matched normals (y-axis) and significant difference in overall expression of the gene between ASE and BAE samples (x-axis). Fig. 2D illustrates expression levels of TMPRSS2, ERG, and ETV1 , and ACSM1 stratified by allelic expression status. Fig. 2E provides ChlP-seq tracks and peaks for H3K27ac in MDAPCA2B cells showing peaks unique to androgen treated cells at the ACSM1 promoter. Tracks represent the average of two replicates per condition.

[0012] FIGs. 3A-3D provide ASE stratifies subgroups of patients by molecular features and survival. Fig. 3A shows a frequency of ASE for each gene in TMPRSS2-ERG fusion positive and fusion negative PCa samples in localized PCa. Colored dots are significant results of Fisher’s exact test for each gene with a testable SNV in both groups. Fig. 3B shows a frequency of ASE for each gene in localized tumors from EA and AA patients. Colored dots are significant results of Fisher’s exact test for each gene with a testable SNV in both groups. Fig. 3C shows expression of HLA-DMB, GPR116, and ALDH3B2 stratified by allelic expression status. Fig. 3D provides Kaplan Meier plot showing difference in progression-free survival in localized tumors with low and high ALDH3B2 expression.

[0013] FIGs. 4A-4F provides a comparison of genes undergoing ASE in normal prostate tissue identifies genes enriched for ASE in localized tumors. Fig. 4A provides a categorization of allele expression patterns in 43 matched normal-tumor pairs from the TCGA localized PCa dataset. Fig. 4B provides genes showing recurrent (>=10% of pairs) switch from BAE to ASE in matched normal-tumor pairs. Fig. 4C provides genes showing recurrent switch from no expression to ASE in matched normal-tumor pairs. Fig. 4D provides expression of DNAH8 in ASE compared to BAE samples and across datasets. Fig. 4E provides overall expression of DNAH8 in 9 matched normal and tumor pairs showing no expression to ASE pattern. Fig. 4F illustrates Kaplan Meier plot showing difference in progression-free survival in localized tumors with low and high DNAH8 expression.

[0014] FIGs. 5A-5F: Genes undergoing ASE in mCRPC are enriched for developmental pathways and oncogenes. Fig. 5A provides a plot showing ASE frequency of genes with data in both GTEx normal prostate and mCRPC. Dot color indicates significant results of Fisher’s exact test for each gene. Fig. 5B provides a plot showing ASE frequency of genes with data in both localized and mCRPC. Fig. 5C illustrates a HALLMARK gene set enrichment analysis of 896 genes enriched for ASE in mCRPC compared to localized PCa. Fig. 5D illustrates an enrichment of gene sets among recurrent genes undergoing ASE for both localized and mCRPC using Fisher’s exact test. Fig. 5E illustrates a Kaplan Meier plot showing progression-free survival for localized TCGA tumors stratified by mCRPC MAE signature score. Fig. 5F illustrates -Iog10(p- adj) for allele specific methylation stratified by MAE status for NUDT12.

[0015] FIGs. 6A-6K: Allele-specific expression analysis identifies novel dysregulated genes in prostate tumors in African-American men. A) Schematic of hypothesis. B) Schematic of analysis pipeline. C) Genome-wide frequency of ASE for genes in the localized PCa tumor and normal prostate datasets. D) Volcano plot showing results of enrichment tests for ASE frequency of each gene in tumors compared to normal samples. E) HALLMARK pathway enrichment of 1011 genes enriched for ASE in tumors. F) Frequency of monoallelic expression (MAE) for each gene in localized tumors from EA and AA men. Colored dots are significant results of a two-sided Fisher’s exact test for each gene with a testable SNV in both groups. G) Correlations between androgen receptor (AR) expression and expression of genes enriched for MAE in AA men. H) Expression of genes in all matched normal and tumor samples. I) Expression of genes in all tumors grouped by allelic expression status. J) Kaplan Meier plot showing difference in progression-free survival in tumors with low and high ALDH3B2 expression. K) Cox proportional hazard regression for progression-free survival including race and ALDH3B2 expression as covariates.

[0016] FIG. 7: Schematic depicting ASE identification and candidate ASE driver identification workflow.

[0017] FIGs: 8A-8D: Distribution of testable heterozygous SNVs and genes across samples A) Histogram of total detected heterozygous SNVs per sample. B) Histogram of testable heterozygous SNVs per sample. C) Histogram of testable genes per sample. D) Histogram of DNA reference allele fraction for each SNV.

[0018] FIGs. 9A-9B: Proportion of genes meeting threshold for ASE under varying allele fold-change cutoffs A) Total proportion. B) Median per-sample proportion.

[0019] FIG. 10: Proportion of genes meeting threshold for ASE under varying allele fold-change cutoffs (For each of 1 %, 3%, 5%, and 10%: left-“normal”, middle-“localized”, right-“metastatic”).

[0020] FIGs. 11A-11 C: Per sample count of BAE, ASE, and MAE genes A) GTEx normal prostate. B) TCGA-PRAD Localized Pea. C) WCDT mCRPC. FIGs. 12A-12D: Correlation of ASE count and molecular features A) Correlation of number of ASE, BAE, and MAE genes with tumor features in localized Pea. B) Bar plot showing ASE frequency in localized tumors with low and high Gleason scores. Mann-Whitney U test. C) Bar plot showing ASE frequency for different mCRPC biopsy sites. Mann-Whitney U test D) Correlation between number of ASE, BAE, and MAE genes with tumor features in mCRPC.

[0021] FIGs. 13A-13B: Top 50 genes showing recurrent ASE. A) localized PCa. B) mCRPC.

[0022] FIGs. 14A-14B: Enrichment of ASE in eQTL genes. A) Localized PCa B) mCRPC.

[0023] FIGs. 15A-15D: Copy number and ASE A) Histogram of proportion of genes showing ASE and deep deletion or strong amplification. Top: Localized PCa, bottom: mCRPC. B) Histogram of proportion of genes showing MAE and deep deletion or strong amplification. Top: Localized PCa, bottom: mCRPC. C) Stacked bar plot showing proportion of total gene-sample pairs showing BAE, ASE, and MAE with a concurrent deep deletion or strong amplification. Top: Localized PCa, bottom: mCRPC D) Bar plot showing proportion of genes showing BAE (middle bar), ASE (left bar), and MAE (right bar) with allele-specific copy number (asCN) for localized PCa.

[0024] FIGs. 16A-16B: ASE of TMPRSS2 and ERG A) Pie chart displaying ASE data for TMPRSS2 and ERG in tumors with a TMPRSS2-ERG fusion B) Bar plot showing ASE frequency for TMPRSS2 (top bar) and ERG (bottom bar) for fusion positive and fusion negative samples with testable SNVs.

[0025] FIGs 17A-17B: ChlP-seq for H3K27ac in MDPCA2B cells. A) Tornado plots for control and R1881 treated cells, with two replicates per condition B) Volcano plot showingdifferential peaks in control vs R1881 treated cells. Differential peaks were identified using an FDR of 5% and log2(Fold change) of + / - 1 .

[0026] FIGs 18A-18D: Genome-wide comparison of ASE frequency for other molecular subtypes of PCa. A) Results of enrichment tests in Gleason low and Gleason high samples for ASE genes. B) Results of enrichment tests in SPOP mutant and SPOP wildtype samples for ASE genes. C) Results of enrichment tests in FOXA1 mutant and FOXA1 wildtype samples for ASE genes. D) Results of enrichment tests in PTEN deleted samples and PTEN wildtype samples for ASE genes.

[0027] FIGs 19A-19B: Somatic allele bias in localized PCa. A) Count of samples showing reference vs alternate allele bias for somatic mutations showing ASE. B) Allele frequencies in DNA and RNA for somatic mutations in TP53 that show ASE.

[0028] FIGs 20A-20B: Genome-wide comparison of ASE frequency for other molecular subtypes of PCa. A) violin plot of ASE frequency. B) Bar graphs of ASE frequency across PCa subtypes.

[0029] FIGs 21A-21C: depicts mCRPC MAE signature score in localized tumors.

[0030] FIG. 22: Frequency of ASM of the gene body in imprinted genes from the Geneimprint database. FIG. 23: Genes with significant association between MAE status and gene body ASM.

[0031] DETAILED DESCRIPTION

[0032] Before the methods of the present disclosure are described in greater detail, it is to be understood that the methods are not limited to particular embodiments described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the methods will be limited only by the appended claims.

[0033] Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limit of that range and any other stated or intervening value in that stated range, is encompassed within the methods. The upper and lower limits of these smaller ranges may independently be included in the smaller ranges and are also encompassed within the methods, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the methods.

[0034] Certain ranges are presented herein with numerical values being preceded by the term “about.” The term “about” is used herein to provide literal support for the exact number that it precedes, as well as a number that is near to or approximately the number that the term precedes. In determining whether a number is near to or approximately a specifically recited number, the near or approximating unrecited number may be a number which, in the context in which it is presented, provides the substantial equivalent of the specifically recited number.

[0035] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the methods. Although any methods similar or equivalent to those described herein can also be used in the practice or testing of the methods, representative illustrative methods are now described.

[0036] All publications and patents cited in this specification are herein incorporated by reference as if each individual publication or patent were specifically and individually indicated to be incorporated by reference and are incorporated herein by reference to disclose and describe the materials and / or methods in connection with which the publications are cited. The citation of any publication is for its disclosure prior to the filing date and should not be construed as an admission that the present methods are not entitled to antedate such publication, as the date of publication provided may be different from the actual publication date which may need to be independently confirmed.

[0037] It is noted that, as used herein and in the appended claims, the singular forms “a”, “an”, and “the” include plural referents unless the context clearly dictates otherwise. It is further noted that the claims may be drafted to exclude any optional element. As such, this statement is intended to serve as antecedent basis for use of such exclusive terminology as “solely,” “only” and the like in connection with the recitation of claim elements, or use of a “negative” limitation.

[0038] It is appreciated that certain features of the methods, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the methods, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable subcombination. All combinations of the embodiments are specifically embraced by the present disclosure and are disclosed herein just as if each and every combination was individually and explicitly disclosed, to the extent that such combinations embrace operable processes and / or compositions. In addition, all sub-combinations listed in the embodiments describing such variables are also specifically embraced by the present methods and are disclosed herein just as if each and every such sub-combination was individually and explicitly disclosed herein.

[0039] As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present methods. Any recited method can be carried out in the order of events recited or in any other order that is logically possible.

[0040] DEFINITIONS

[0041] By “small molecule” compound is meant a compound having a molecular weight of 1000 atomic mass units (amu) or less. In some embodiments, the small molecule is 900 amu or less, 750 amu or less, 500 amu or less, 400 amu or less, 300 amu or less, or 200 amu or less. In some instances, the small molecule is not made of repeating molecular units such as are present in a polymer.

[0042] The term “conjugation” or “conjugated” generally refers to a chemical linkage, either covalent or non-covalent, usually covalent, that proximally associates one molecule of interest with a second molecule of interest. In certain embodiments, the mucin-active protease is conjugated to the targeting moiety via a linker. If present, the linker molecule(s) may be of sufficient length to permit the mucin-active protease and targeting moiety to allow some flexible movement between the mucin-active protease and targeting moiety. Linker molecules may be, e.g., about 6-50 atoms long. Linker molecules may also be, e.g., aryl acetylene, ethylene glycol oligomers containing 2-10 monomer units, diamines, diacids, amino acids, or combinations thereof.

[0043] The term “antibody” may include an antibody or immunoglobulin of any isotype (e.g., IgG (e.g., lgG1 , lgG2, lgG3, or lgG4), IgE, IgD, IgA, IgM, etc.), whole antibodies (e.g., antibodies composed of a tetramer which in turn is composed of two dimers of a heavy and light chain polypeptide); single chain antibodies (e.g., scFv); fragments of antibodies (e.g., fragments of whole or single chain antibodies) which retain specific binding to the cell surface molecule of the target cell, including, but not limited to single chain Fv (scFv), Fab, (Fab’)2, (scFv’)2, and diabodies; chimeric antibodies; monoclonal antibodies, human antibodies, humanized antibodies (e.g., humanized whole antibodies, humanized half antibodies, or humanized antibody fragments, e.g., humanized scFv); and fusion proteins comprising an antigen-binding portion of an antibody and a non-antibody protein. According to some embodiments, the antibody is selected from an IgG, Fv, single chain antibody, scFv, Fab, F(ab')2, or Fab'. In certain embodiments, the antibody is a nanobody (an antibody fragment consisting of a single monomeric variable antibody domain - also known as a single-domain antibody (sdAb)), a monobody (a synthetic binding protein constructed using a fibronectin type III domain (FN3) as a molecular scaffold), or a Bi-specific T- cell engager (BiTE).

[0044] As used herein, a “therapeutic agent” is a physiologically or pharmacologically active substance that can produce a desired biological effect in a targeted site in an animal, such as a mammal or in a human. The therapeutic agent may be any inorganic or organic compound. A therapeutic agent may decrease, suppress, attenuate, diminish, arrest, or stabilize the development or progression of disease, disorder, or cell growth in an animal such as a mammal or human. Examples include, without limitation, peptides, proteins, nucleic acids (including siRNA, miRNA and DNA), polymers, and small molecules. In various embodiments, the therapeutic agents may be characterized or uncharacterized.

[0045] By “treat” or “treatment” is meant at least an amelioration of the symptoms associated with the disease state of the subject, where amelioration is used in a broad sense to refer to at least a reduction in the magnitude of a parameter, e.g. symptom, associated with the disease state being treated. As such, treatment also includes situations where the disease state, or at least symptoms associated therewith, are completely inhibited, e.g. prevented from happening, or stopped, e.g. terminated, such that the subject no longer suffers from the disease state, or at least the symptoms that characterize the disease state.

[0046] The term “allele” refers to a genetic variant that exists at a particular locus within the genome. Generally, each locus possesses two alleles in diploid organisms. A “locus” may encompass a specific nucleotide or an entire gene. In certain instances, both alleles have the same sequence, while in other instances each allele is different.

[0047] The terms “individual,” “subject,” “host,” and “patient,” used interchangeably herein, refer to an individual organism, e.g., a mammal, including, but not limited to, murines, simians, humans, non-human primates, ungulates, felines, canines, bovines, ovines, mammalian farm animals, mammalian sport animals, and mammalian pets. In some cases, an “individual,” “subject,” “host,” or “patient” is a human. ALLELE SPECIFIC EXPRESSION

[0048] The present disclosure provides methods to identify a gene exhibiting allele specific expression (ASE) from a disease. ASE exists when the two alleles (e.g., two different alleles at a heterozygous locus) are expressed unequally— for example, if one allele is expressed at a higher rate than the other allele. In contrast, biallelic expression (BAE) exists when the two alleles are equally, or substantially equally, expressed. In certain instances, the allele with higher expression is expressed at 1.5 times, 2 times, 3 times, 4 times, 5 times, or more than the rate that the other allele is expressed. In certain instances, ASE can be considered monoallelic expression (MAE) when one allele is expressed exclusively or at a much higher rate than the other allele. ASE may be considered MAE when one allele is expressed 5 times, 10 times, or more than the rate that the other allele is expressed.

[0049] Various instances identify a single gene, a plurality of genes, and / or a set of genes exhibiting ASE — a set of genes can be identified as any number of genes, including (but not limited to) 1 gene, 2 genes, 3 genes, 4 genes, 5 genes, 10 genes, 15 genes, 20 genes, 25 genes, 50 genes, or more. In various instances, a gene or set of genes exhibiting ASE can be indicative of, associated with, and / or causative of a condition — “condition” in this context is used to differentiate different characteristics, such as a tissue type, a disease, a disorder, and / or any other condition. An association with a disease relates to a correlation or correlative effect between the disease and gene. Such effects may have an unknown cause or effect but have some relationship (known or unknown) between the gene and the disease. The resulting genes showing ASE differences between the condition may be considered an ASE signature that is associated with the condition.

[0050] To make such determinations, samples may be obtained from multiple conditions, such as (but not limited to) healthy and diseased, different tissue types, multiple stages of a disease, score (e.g., Gleason score), histology, severity, prognosis, any other differentiation, and combinations thereof. ASE analysis can compare ASE that exists between the samples to identify when ASE exists in one or more samples. As a non-limiting example, some samples may be from a cancer, while other samples from healthy tissue; ASE analysis may reveal when cancerous tissue possesses genes exhibiting ASE when healthy tissue has biallelic expression (BAE) and vice versa.

[0051] In instances identifying a cancer, the cancer can be selected from one or more of prostate cancer, breast cancer, pancreatic cancer, skin cancer, colorectal cancer, testicular cancer, lung cancer, esophageal cancer, uterine cancer, ovarian cancer, lymphoma, liver cancer, renal cancer, oral cancer, brain cancer, thyroid cancer, urogenital cancer, including individual varieties, subtypes, and stages thereof. Tumor types may be resistant and / or non-resistant, where resistance is resistance to a therapeutic agent, such as a chemotherapeutic, a hormone, radiation, and / or any other therapy. Stages of cancer can include localized or primary tumors and / or metastatic variations of cancer — as a non-limiting example, tissue types may include healthy tissue, localized prostate cancer, and metastatic castration-resistant prostate cancer.

[0052] To identify ASE, various embodiments utilize genomic data capable of identifying or differentiating alleles and / or expression of the alleles. Such genomic data can include sequencing data and / or expression data. Sequencing data can include whole genome sequencing, exome sequencing (including whole exome sequencing), RNA sequencing, cDNA sequencing, and / or any other applicable method to obtain sequencing data. Expression data can include microarray data, RNA blotting (e.g., northern blot), RNA sequencing, and / or any other applicable method to obtain expression data from a gene and / or individual alleles of the gene.

[0053] To identify alleles, certain instances use sequencing data to identify one or more variants present in a gene. Sequencing depth may be any level of depth for confidence in a call. “Sequencing depth” describes the number of unique sequencing reads that align to a region in a reference genome or de novo assembly. In certain instances, the sequencing depth is 2x, 3x, 4x, 6x, 8x, 10x, 20x, 50x, 100x, or more. In certain instances, the variant may be identified de novo (e.g., against the existing sequence information) or by reference (e.g., a variant compared to a reference sequence). Variants may be any known type of variant, such as a single nucleotide variant (SNV), a single nucleotide polymorphism (SNP), an insertion / deletion (indel), a simple sequence repeats (SSR, e.g., trinucleotide expansion), and / or any relevant type of sequence variant. Single nucleotide variants (SNVs) reflect a difference in a single nucleotide at a given position of a sequence (e.g., a given position in one or more alleles). SNVs can include single nucleotide differences in a given sequence position that are rare or common in a given population of individuals. In some cases, SNVs that occur at a frequency of at least 1 % in a population of individuals may be referred to as a single nucleotide polymorphism. In some cases an SNV may exist in only some cells or tissues (e.g., a tumor) within an individual. Indels reflect insertions and / or deletions of multiple nucleotides in a given sequence. In some cases, the insertion or deletion may involve 50 or fewer nucleotides.

[0054] In certain instances, two or more alleles are identified for each gene. Certain instances may reveal multiple variants for a gene and may perform haplotyping to identify which variants form a single allele.

[0055] Some embodiments filter genes showing copy number variation (CNV). CNV can occur due to duplication or deletion of an entire gene or genomic region (e.g., multiple genes, chromosomal arm, entire chromosome, etc.). CNV can include aneuploidy. CNV may be identified through sequencing data or via cytogenetic methodologies. Cytogenetic methodologies include (but are not limited to) fluorescence in situ hybridization, karyotyping, flow cytometry, chromosome sorting, hybridization chip, and / or any other methodology that can identify CNV without sequencing data. Sequencing may be performed using any of a variety of available high throughput nucleic acid sequencing machines and systems. Illustrative sequencing systems include those available from: Illumina, Inc. (San Diego, Calif.), non-limiting examples of which include the Illumina iSeq 100, Miniseq, MiSeq series, NextSeq series (e.g., NextSeq 500 series, NextSeq 1000, NextSeq 2000), and NovaSeq sequencing systems; MGI Tech Co. Ltd. (or “MGI”), non-limiting examples of which include the DNBSEQ T series or DNBSEQ T series G series nucleic acid sequencing systems; Oxford Nanopore Technologies (Oxford, UK), non-limiting examples of which include the MinlONTM, GridlONx5TM, PromethlONTM, and SmidglONTM nanopore-based sequencing systems; Pacific Biosciences (“PacBio”, Menlo Park, Calif.), nonlimiting examples of which include the REVIO, ONSO, and SEQUEL lie sequencing systems. Sequencing data can be used to identify CNV by a statistically significant difference in sequence counts between alleles. For example, if a first allele has 5x sequencing depth, while a second allele has 15x sequencing depth, there may be a duplication of the second allele. Certain embodiments identify CNV based on the ratio of one allele represented in the genomic sequencing data. In numerous embodiments, CNV is identified when one allele is represented at a rate of greater than 0.75 or less than 0.25 in the sequencing data.

[0056] As noted above, expression data may come from RNA sequencing, including bulk RNA sequencing or single cell RNA sequencing (scRNA-seq). RNA sequencing (RNA-seq) is a genomic approach for the detection and quantitative analysis of messenger RNA molecules in a biological sample and is useful for studying cellular responses. As a proxy for studying the proteome, some research has turned to protein-encoding, mRNA molecules (collectively termed the “transcriptome”), whose expression correlates well with cellular traits and changes in cellular state. scRNA-seq permits comparison of the transcriptomes of individual cells. A variety of suitable approaches for scRNA-seq are available, non-limiting examples of which include C1 (SMARTer) (e.g., see Pollen et al. (2014) Nat Biotechnol. 32:1053-8), Smart-seq2 (e.g., see Picelli et al. (2013) Nat Methods 10:1096-8), MATQ-seq (e.g., see Sheng et al. (2017) Nat Methods 14:267-70), MARS-seq (e.g., see Jaitin et al. (2014) Science 343:776-9), CEL-seq (e.g., see Hashimshony et al. (2012) Cell Rep. 2:666-73), Drop-seq (e.g., see Macosko et al. (2015) Cell 161 :1202-14), InDrop (e.g., see Klein et al. (2015) Cell 161 :1 187-201 ), Chromium (e.g., see Zheng et al. (2017) Nat Commun. 8:14049), SEQ-well (e.g., see Gierahn et al. (2017) Nat Methods 14:395-8), SPLIT-seq (e.g., see Rosenberg et al. (2017) BioRxiv doi.org / 10.1 101 / 105163), and others. Further details regarding single-cell RNA-sequencing can be found, e.g., in Haque et al. (2017) Genome Med 9, 75. Various methods exist in the art to generate RNA sequencing libraries and for sequencing the library using platforms as previously described.

[0057] Once genes exhibiting ASE are identified, many embodiments prioritize genes that may drive disease progression. Such prioritization can identify enrichment of genes exhibiting ASE in one condition over other conditions (e.g., enrichment of such genes in cancerous tissue versus healthy tissue). Such variation can be qualitative, such that all enrichment is treated equally, and / or quantitative, such that the expression levels are also utilized as a factor. Quantitation may be more relevant when assessing more than two tissue types, such as healthy tissue, localized tumors, and metastatic cancer.

[0058] ASE signatures may provide a score based on the identified and / or prioritized genes. Such signatures may be formed by filtering genes based on certain conditions, such as a minimum amount of MAE present (e.g., recurrent MAE in at least 5% of tumors). Concurrent CNV may also be factored, to identify ASE caused by a c / s-acting element — for example, recurrent MAE in at least 5% of tumors and does not contain concurrent CNV in >10% of tumors. Allelespecific methylation may also be determined using bisulfite sequencing, such as on whole genome sequencing. Methods for determining methylation, including software-based tools and methods for bisulfite conversion and sequencing.

[0059] It should be noted the types of data listed above (e.g., expression data and / or sequencing data) can be obtained from existing databases or repositories, previously sequenced or analyzed samples, and / or de novo sequencing and analysis. Previously performed data can be obtained as raw data (e.g., raw reads), alignment files, assemblies, and / or any other data format or structure. File formats can include traces, FASTA, FASTQ, SAM (Sequence Alignment / Map), BAM (Binary Alignment / Map), and / or any other relevant format.

[0060] A non-limiting example of the above process of identifying ASE in a disease or other condition is illustrated in Figure 7. In this figure, a collection of samples from a localized prostate cancer (PCa), metastatic castration-resistant prostate cancer (mCRPC), and normal prostate tissue (obtained from the GTEx database). These sample types provided data from RNA sequencing and one or more of WGS and WES. Genic alleles can be identified based on heterozygous exonic SNVs. Allele counts can identify sufficient coverage or sequencing depth as well as copy number variation. Using the RNA sequencing data, gene level ASE can be determined, resulting in identification of which genes exhibit ASE, MAE, or BAE.

[0061] GENOMIC SEQUENCE DATA & EXPRESSION DATA

[0062] As noted above, genomic data and / or expression data can include whole genome sequencing, exome sequencing (including whole exome sequencing), RNA sequencing, cDNA sequencing, and / or any other applicable method to obtain sequencing data. Sequencing may be performed using any of a variety of available high throughput nucleic acid sequencing machines and systems. Illustrative sequencing systems include those available from: Illumina, Inc. (San Diego, Calif.), non-limiting examples of which include the Illumina iSeq 100, Miniseq, MiSeq series, NextSeq series (e.g., NextSeq 500 series, NextSeq 1000, NextSeq 2000), and NovaSeq sequencing systems; MGI Tech Co. Ltd. (or “MGI”), non-limiting examples of which include the DNBSEQ T series or DNBSEQ T series G series nucleic acid sequencing systems; Oxford Nanopore Technologies (Oxford, UK), non-limiting examples of which include the MinlON™, GridlONx5TM, PromethlON™, and SmidglON™ nanopore-based sequencing systems; Pacific Biosciences (“PacBio”, Menlo Park, Calif.), non-limiting examples of which include the REVIO, ONSO, and SEQUEL lie sequencing systems.

[0063] Illumina sequencing technology leverages clonal array formation and reversible terminator technology for large-scale sequencing. For cluster generation, sequencing templates are immobilized on a flow cell surface designed to present the DNA in a manner that facilitates access to enzymes while ensuring high stability of surface-bound template and low non-specific binding of fluorescently labeled nucleotides. Solid-phase amplification creates up to 1 ,000 identical copies of each single template molecule in close proximity (diameter of one micron or less). Because this process does not involve photolithography, mechanical spotting, or positioning of beads into wells, densities on the order of ten million single-molecule clusters per square centimeter are achieved. The next phase involves sequencing by synthesis (SBS) utilizing four fluorescently-labeled nucleotides to sequence the tens of millions of clusters on the flow cell surface in parallel. During each sequencing cycle, a single labeled deoxynucleoside triphosphate (dNTP) is added to the nucleic acid chain. The nucleotide label serves as a terminator for polymerization, so after each dNTP incorporation, the fluorescent dye is imaged to identify the base and then enzymatically cleaved to allow incorporation of the next nucleotide. Since all four reversible terminator-bound dNTPs (A, C, T, G) are present as single, separate molecules, natural competition minimizes incorporation bias. Base calls are made directly from signal intensity measurements during each cycle.

[0064] In some embodiments, a flow cell for clustering in the Illumina platform is a glass slide with lanes. Each lane is a glass channel coated with a lawn of two types of oligos (e.g., P5 and P7' oligos). Hybridization is enabled by the first of the two types of oligos on the surface. This oligo may be complementary to the first completed sequencing adapter or the second completed sequencing adapter. A polymerase creates a compliment strand of the hybridized sequencing template. The double-stranded molecule is denatured, and the original template strand is washed away. The remaining strand, in parallel with many other remaining strands, is clonally amplified through bridge amplification.

[0065] In bridge amplification and other sequencing methods involving clustering, a strand folds over, and a second adapter region on a second end of the strand hybridizes with the second type of oligos on the flow cell surface. A polymerase generates a complementary strand, forming a double-stranded bridge molecule. This double-stranded molecule is denatured resulting in two single-stranded molecules tethered to the flow cell through two different oligos. The process is then repeated iteratively, and occurs simultaneously for millions of clusters resulting in clonal amplification of all the sequencing templates. After bridge amplification, the reverse strands are cleaved and washed off, leaving only the forward strands. The 3' ends are blocked to prevent unwanted priming.

[0066] After clustering, sequencing starts with extending a first sequencing primer to generate the first read. With each cycle, fluorescently tagged nucleotides compete for addition to the growing chain. Only one is incorporated based on the sequence of the template. After the addition of each nucleotide, the cluster is excited by a light source, and a characteristic fluorescent signal is emitted. The number of cycles determines the length of the read. The emission wavelength and the signal intensity determine the base call. For a given cluster all identical strands are read simultaneously. Hundreds of millions of clusters may be sequenced in a massively parallel manner. At the completion of the first read, the read product is washed away.

[0067] In the next step of protocols involving two index primers, an index 1 primer is introduced and hybridized to an index 1 region on the template. Index regions provide identification of fragments, which is useful for de-multiplexing samples in a multiplex sequencing process. The index 1 read is generated similar to the first read. After completion of the index 1 read, the read product is washed away and the 3' end of the strand is de-protected. The template strand then folds over and binds to a second oligo on the flow cell. An index 2 sequence is read in the same manner as index 1 . Then an index 2 read product is washed off at the completion of the step.

[0068] After reading two indices, read 2 initiates by using polymerases to extend the second flow cell oligos, forming a double-stranded bridge. This double-stranded DNA is denatured, and the 3' end is blocked. The original forward strand is cleaved off and washed away, leaving the reverse strand. Read 2 begins with the introduction of a read 2 sequencing primer. As with read 1 , the sequencing steps are repeated until the desired length is achieved. The read 2 product is washed away. This entire process generates millions of reads, representing all the fragments. Sequences from pooled sample libraries are separated based on the unique indices introduced during sample preparation. For each sample, reads of similar stretches of base calls are locally clustered. Forward and reversed reads are paired creating contiguous sequences. These contiguous sequences are aligned to the reference genome for variant identification.

[0069] The sequencing by synthesis may involve paired end reads. Paired end sequencing involves 2 reads from the two ends of a fragment. Paired end reads are used to resolve ambiguous alignments. Paired-end sequencing allows users to choose the length of the DNA to be sequenced and sequence either end of the DNA, generating high-quality, alignable sequence data. Because the distance between each paired read is known, alignment algorithms can use this information to map reads over repetitive regions more precisely. This results in better alignment of the reads, especially across difficult-to-sequence, repetitive regions of the genome. Paired-end sequencing can detect rearrangements, including insertions and deletions (indels) and inversions.

[0070] DNA nanoball sequencing (e.g., employing a sequencing system available from MGI Tech Co., Ltd. (“MGI”)) involves the amplification of genomic DNA into nanoballs, followed by sequencing by synthesis (SBS) using fluorescently labeled nucleotides. In nanoball sequencing, DNA fragments are amplified by rolling circle amplification. The original circular DNA fragment serves as a template for the amplification of each clonal copy of DNA. This results in a spherical "nanoball" of amplified DNA. The negatively charged nanoballs are then hybridized to positively charged binding spots on a patterned flow cell. The sequencing process then proceeds in a similar fashion to standard SBS sequencing. The nucleotides (A, C, G, or T) are added one at a time to the flow cell, and the incorporated nucleotides are detected by a camera. Fluorescently labeled nucleotides, or alternatively, nucleotides labeled with fluorescently labeled antibodies, can be used.

[0071] In nanopore sequencing (e.g., implemented using a sequencer available from Oxford Nanopore Technologies), the nanopore serves as a biosensor and provides the sole passage through which an ionic solution on the cis side of the membrane contacts the ionic solution on the trans side. A constant voltage bias (trans side positive) produces an ionic current through the nanopore and drives ssDNA or ssRNA in the cis chamber through the pore to the trans chamber. A processive enzyme (e.g., a helicase, polymerase, nuclease, or the like) may be bound to the polynucleotide such that its step-wise movement controls and ratchets the nucleotides through the small-diameter nanopore, nucleobase by nucleobase. Because the ionic conductivity through the nanopore is sensitive to the presence of the nucleobase’s mass and its associated electrical field, the ionic current levels through the nanopore reveal the sequence of nucleobases in the translocating strand. A patch clamp, a voltage clamp, or the like, may be employed. Details for obtaining raw sequencing reads of nucleic acid molecules using nanopores are described, e.g., in Feng et al. (2015) Genomics, Proteomics & Bioinformatics 13(1 ):4-16. Nanopore-based sequencing systems are available and include the MinlON™, GridlONx5TM, PromethlON™, and SmidglON™ nanopore-based sequencing systems available from Oxford Nanopore Technologies Limited. Detailed design considerations and protocols for performing nucleic acid sequencing are provided with such systems.

[0072] In zero mode waveguide (ZMW)-based sequence analysis (e.g., using a sequencer available from Pacific Biosciences (PacBio), the ZMW is a nanoscale-sized well that serves as an optical confinement that allows observation of individual polymerase molecules. As a result, nucleotide incorporation events provide observation of an incorporating nucleotide analog that is readily distinguishable from non-incorporated nucleotide analogs. For a description of ZMWs and their application in nucleic acid sequencing, see, e.g., U.S. Patent Application Publication No. 2003 / 0044781 and U.S. Pat. No. 6,917,726, each of which is incorporated herein by reference in its entirety for all purposes. See also Levene et al. (2003) “Zero-mode waveguides for single-molecule analysis at high concentrations” Science 299:682-686, Eid et al. (2009) “Realtime DNA sequencing from single polymerase molecules” Science 323:133-138, and U.S. Pat. Nos. 7,056,676, 7,056,661 , 7,052,847, 7,033,764, and 7,907,800, the full disclosures of which are incorporated herein by reference in their entirety for all purposes.

[0073] In embodiments wherein a sample is obtained from a subject, a sequencing library may be prepared from nucleic acids present in the sample (e.g., genomic DNA or mRNA). By way of eample, methods for preparing a sequencing library can include methods that comprise amplifying nucleic acids of the sample using a primer pair comprising a forward primer and a reverse primer. The forward primer comprises a 3’ domain complementary to nucleic acids in the sample and a 5’ domain comprising a first sequencing adapter. The reverse primer comprises a 3’ domain complementary to the nucleic acids in the sample and a 5’ domain comprising a second sequencing adapter. The amplification produces amplicons, each amplicon comprising the the first sequencing adapter at a first end and the second sequencing adapter at the second end.

[0074] As used herein, a “sequencing adapter” refers generally to an oligonucleotide sequence added to a nucleic acid which is desired to be sequenced, where the oligonucleotide sequence is required for sequencing of the nucleic acid using a particular nucleic acid sequencing system. In some embodiments, sequencing on the sequencing system of choice comprises solid-phase amplification (e.g., for cluster generation), and the first and / or second sequencing adapters are required for capture of the library molecules to the solid phase (e.g., by hybridization) and / or for amplification of the library molecules subsequent to capture. By way of example, when the nucleic acid sequencing system is an Illumina sequencing system, the first and second sequencing adapters may be the P5 and P7 adapters (or a complement thereof) for capture on the flow cell employed by Illumina sequencing system.

[0075] In some instances, the first and second sequencing adapters may be those employed by an MGI Tech Co. Ltd. (or “MGI”) sequencing system, such as a DNBSEQ T series or DNBSEQ T series G series nucleic acid sequencing system. By way of example, the first and second sequencing adapters may be required for amplification of library molecules into DNA nanoballs (DNBs). In other embodiments, the first and second sequencing adapters may be those employed by a nanopore-based sequencing system, non-limiting examples of which include the MinlON, GridlON, and PromethlON nanopore sequencing systems available from Oxford Nanopore Technologies. In still other embodiments, the first and second sequencing adapters may be those employed by a zero-mode waveguide (ZMW) -based sequencing system, such as a REVIO, ONSO, or SEQUEL He sequencing system by Pacific Biosciences (PacBio).

[0076] Methods for preparing a sequencing library can comprise amplifying nucleic acids of the sample using the primer pair comprising the forward primer and the reverse primer. As used herein, “amplify”, “amplifying” or “amplification reaction” and their derivatives, refer generally to any action or process whereby at least a portion of a nucleic acid molecule is replicated or copied into at least one additional nucleic acid molecule. The additional nucleic acid molecule includes sequence that is complementary to at least some portion of the template nucleic acid molecule. The template nucleic acid molecule can be single-stranded or double-stranded and the additional nucleic acid molecule can independently be single-stranded or doublestranded. Amplification optionally includes linear or exponential replication of a nucleic acid molecule. In some embodiments, such amplification can be performed using isothermal conditions; in other embodiments, such amplification can include thermocycling. In some embodiments, the amplification is a multiplex amplification that includes the simultaneous amplification of a plurality of target sequences in a single amplification reaction. In some embodiments, “amplification” includes amplification of at least some portion of DNA and RNA based nucleic acids alone, or in combination. The amplification reaction can include any of the amplification processes known to one of ordinary skill in the art. In some embodiments, the amplification reaction includes polymerase chain reaction (PCR).

[0077] As used herein, the term “primer” and its derivatives refer generally to any polynucleotide that can hybridize to a sequence of interest, which may be targeted or non-targeted (e.g., random primers may be employed). Typically, the primer functions as a substrate onto which nucleotides can be polymerized by a polymerase; in some embodiments, however, the primer can become incorporated into the synthesized nucleic acid strand and provide a site to which another primer can hybridize to prime synthesis of a new strand that is complementary to the synthesized nucleic acid molecule. The primer may be comprised of any combination of nucleotides or analogs thereof. In some embodiments, the primer is a single-stranded oligonucleotide or polynucleotide.

[0078] In various implementations, a primer has a free 3'-OH group that can be extended by a nucleic acid polymerase. For a template-dependent polymerase, generally at least the 3'-portion of the primer oligo is complementary to a portion of a template nucleic acid, to which the oligo “binds” (or “complexes,” “anneals,” or “hybridizes”), by hydrogen bonding and other molecular forces, to the template to give a primer / template complex for initiation of synthesis by a DNA polymerase, and which is extended (i.e., “primer extended”) by the addition of covalently bonded bases linked at its 3'-end which are complementary to the template in the process of DNA synthesis. The result is a primer extension product. Template-dependent DNA polymerases (including reverse transcriptases) generally require complexing of an oligonucleotide primer to a single-stranded template to initiate DNA synthesis (“priming”), but RNA polymerases generally do not require a primer for synthesis of RNA that is complementary to a DNA template (transcription).

[0079] A “template” is a nucleic acid molecule that is being copied by a nucleic acid polymerase, such as a DNA polymerase. Whether the nucleic acid molecule comprises two strands (i.e., is “double-stranded”) or only one strand (i.e., is “single-stranded”), the strand of the nucleic acid molecule that serves to specify the sequence of nucleotides exhibited by a nucleic acid that is synthesized is the “template” or “the template strand.” The nucleic acid synthesized by the nucleic acid polymerase is complementary to the template. Both RNA and DNA are always synthesized in the 5'-to-3' direction, beginning at the 3'-end of the template strand, and the two strands of a nucleic acid duplex always are aligned so that the 5' ends of the two strands are at opposite ends of the duplex (and, by necessity, so then are the 3' ends). A primer is required for both RNA and DNA templates to initiate synthesis by a DNA polymerase, but a primer is not required to initiate synthesis by a DNA-dependent RNA polymerase, which is usually called simply an “RNA polymerase.”

[0080] The terms “nucleic acid”, “polynucleotide” and “oligonucleotide” are used interchangeably herein to refer to a polymeric form of nucleotides of any length, and may comprise ribonucleotides, deoxyribonucleotides, analogs thereof, or mixtures thereof. In some context, the term “nucleic acid” or “polynucleotide” may refer to nucleotide polymers having a relatively large number of nucleotide monomers, while the term “oligonucleotide” may refer to nucleotide polymers having a relative small number of nucleotide monomers. However, that distinction does not apply herein unless specified. Instead, the terms “nucleic acid”, “polynucleotide” and “oligonucleotide” should be understood to include, as equivalents, analogs of either DNA or RNA made from nucleotide analogs and to be applicable to single stranded (such as sense or antisense) and double stranded polynucleotides. The term as used herein also encompasses cDNA, that is complementary or copy DNA produced from an RNA template, for example by the action of reverse transcriptase. This term refers only to the primary structure of the molecule. Thus, the term includes triple-, double- and single-stranded deoxyribonucleic acid (“DNA”), as well as triple-, double- and single-stranded ribonucleic acid (“RNA”).

[0081] As noted above, in some embodiments the genomic sequence data includes wholegenome sequencing (WGS). In WGS, the whole genome, including coding (e.g., exons) and noncoding (e.g., intergenic) sequences, are sequenced. By way of example, sequencing libraries for WGS may be prepared using un-targeted primers (e.g., random primers). In some cases, the genomic sequence data includes whole exome sequencing (WES). In WES, the coding sequences (i.e., the exome) of the genome are sequenced. By way of example, sequencing libraries for WES may be prepared using a plurality of targeted primers specific for the coding sequencies of the genome of interest.

[0082] In some cases, expression data can include RNA sequencing (RNAseq) data. RNA sequencing (RNA-seq) is a genomic approach for the detection and quantitative analysis of messenger RNA molecules in a biological sample and is useful for studying cellular responses. As a proxy for studying the proteome, some research has turned to protein-encoding, mRNA molecules (collectively termed the “transcriptome”), whose expression correlates well with cellular traits and changes in cellular state. In some cases, the RNAseq may be single-cell RNAseq (scRNA-seq). scRNA-seq permits comparison of the transcriptomes of individual cells. A variety of suitable approaches for scRNA-seq are available, non-limiting examples of which include C1 (SMARTer) (e.g., see Pollen et al. (2014) Nat Biotechnol. 32:1053-8), Smart-seq2 (e.g., see Picelli et al. (2013) Nat Methods 10:1096-8), MATQ-seq (e.g., see Sheng et al. (2017) Nat Methods 14:267-70), MARS-seq (e.g., see Jaitin et al. (2014) Science 343:776-9), CEL-seq (e.g., see Hashimshony et al. (2012) Cell Hep. 2:666-73), Drop-seq (e.g., see Macosko et al. (2015) Cell 161 :1202-14), InDrop (e.g., see Klein et al. (2015) Cell 161 :1 187-201 ), Chromium (e.g., see Zheng et al. (2017) Nat Commun. 8:14049), SEQ-well (e.g., see Gierahn et al. (2017) Nat Methods 14:395-8), SPLIT-seq (e.g., see Rosenberg et al. (2017) BioRxiv doi.org / 10.1 101 / 105163), and others. Further details regarding single-cell RNA-sequencing can be found, e.g., in Haque et al. (2017) Genome Med 9, 75. In some cases, the genomic sequence data and / or expression data may include unique molecular identifiers (UMIs). The term “unique molecular identifier (UMI)” or “UMI” as used herein refers to a sequence of nucleotides which can be used to identify and / or distinguish one or more first molecules to which the UMI is attached from one or more second molecules. As used herein, a UMI may include one or more nucleotides at one or both ends of the identifying / distinguishing sequence of nucleotides, e.g., to facilitate attachment (e.g., ligation) of the UMI to a different nucleic acid (e.g., stem structure, nucleic acid of interest, and / or the like). UMIs are typically short, e.g., about 5 to 20 bases in length, and may be conjugated to one or more target molecules of interest or amplification products thereof (e.g., nucleic acids in a sample taken from a subject). Generally, a UMI is used to distinguish between molecules of a similar type within a population or group, whereas a barcode sequence is used to distinguish between populations or groups of molecules. In some embodiments, where both a UMI and a nucleic acid barcode sequence are utilized, the UMI is shorter in sequence length than the nucleic acid barcode sequence. Attaching a UMI to the stem structures of a solid support finds use, e.g., in further increasing the diversity of the barcoded solid supports, tracking the number of copies of concatemers per solid support, and / or the like.

[0083] In some cases, the genomic sequence data and / or expression data may include unique barcodes. As used herein, a “barcode” or “barcode sequence” refers to an identifiable nucleotide sequence that can be coupled to a target nucleic acid (directly or indirectly). In some embodiments, a barcode is uniquely identifiable and may be used to identify the solid support to which the target nucleic acid is / was attached. Barcode sequences may vary widely in length and composition. According to some embodiments, the barcode has a degenerate sequence of from 4 to 120 nucleotides in length, e.g., from 4 to 100, 4 to 80, 4 to 60, 4 to 40, 6 to 30, 8 to 20 nucleotides, or 10 to 15 nucleotides in length. In certain embodiments, the barcode has a degenerate sequence of up to 20 nucleotides in length, e.g., 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 1 1 , 12, 13, 14, 15, 16, 17, 18, 19 or 20 nucleotides in length. The barcode may include one or more mixed bases (e.g., every 3 bases, every 4 bases, or the like) of only three possible base combinations instead of four to prevent homopolymeric barcodes.

[0084] As noted above, in some cases the expression data may be microarray data. Microarray technology is known in the art and described, for example, in: Schena, Editor, Microarrays: A Practical Approach (IRL Press, Oxford, 2000); Southern, Current Opin. Chem. Biol., 2: 404-410 (1998); Nature Genetics Supplement, 21 :1 -60 (1999); and Fodor et al, U.S. Pat. Nos. 5,424,186; 5,445,934; and 5,744,305.

[0085] SAMPLES FROM A SUBJECT

[0086] A Sample from a subject as used in the methods of the present disclosure may be collected by any convenient means. In some instances, useful cellular samples may be or may be derived from a biopsy. Biopsy tissues may be obtained from healthy or diseased tissues, including e.g., cancer tissues. Depending on the type of cancer and / or the type of biopsy performed the sample may be prepared from a solid tissue biopsy or a liquid biopsy.

[0087] In some instances, a sample may be prepared from a surgical biopsy. Any convenient and appropriate technique for surgical biopsy may be utilized for collection of a sample to be employed in the methods described herein including but not limited to, e.g., excisional biopsy, incisional biopsy, wire localization biopsy, and the like. In some instances, a surgical biopsy may be obtained as a part of a surgical procedure which has a primary purpose other than obtaining the sample, e.g., including but not limited to tumor resection, mastectomy, lymph node surgery, axillary lymph node dissection, sentinel lymph node surgery, and the like.

[0088] Various other biopsy techniques may be employed to obtain biopsy tissue, for use as a sample as described herein. As a non-limiting example, a sample may be obtained by a needle biopsy. Any convenient and appropriate technique for needle biopsy may be utilized for collection of a sample including but not limited to, e.g., fine needle aspiration (FNA), core needle biopsy, stereotactic core biopsy, vacuum assisted biopsy, and the like.

[0089] IDENTIFYING A DISEASE ASSOCIATED WITH AN ASE SIGNATURE IN A SUBJECT

[0090] Numerous embodiments can identify a subject as being affected by or having a disease that is associated with an ASE signature. Such embodiments can perform a similar process as described above in identifying an ASE signature that is associated with a disease. In many such embodiments, the ASE was identified as described above to identify an ASE signature in a disease or other condition. In some instances, the ASE signatures were previously identified, while other instances perform the ASE identification de novo.

[0091] In many instances, a sequencing and / or expression data is obtained from the subject. Such data can be obtained as previously sequenced or analyzed data (e.g., obtained as sequencing reads, alignment files, etc.), while other embodiments obtain a sample from the subject. Such samples can be obtained from one or more of a blood sample, liquid biopsy, a tumor biopsy, and a biopsy of a tissue suspected of being cancerous, a buccal swab, a skin swab, a skin scraping, a throat swab, a nasal swab, a urine sample, and / or any other relevant sample type.

[0092] Once a disease associated with an ASE signature is identified, the subject can be treated with one or more therapies, such as will be described in depth below.

[0093] Additionally, it should be noted that the foregoing method of identifying a disease associated with an ASE signature can be used against known positive and negative samples to validate or assess the accuracy of the ASE signature. Such validation can determine a receiver operating characteristic (ROC) and / or produce a receiver operating characteristic curve. A metric for accuracy can include an area under ROC curve (AUC or AUROC). TREATING A DISEASE ASSOCIATED WITH AN ASE SIGNATURE

[0094] Additional embodiments treat an individual for a disease characterized by one or more genes exhibiting ASE. In many such embodiments, the ASE was identified as described above to identify an ASE signature in a disease or other condition. In some instances, the ASE signatures were previously identified, while other instances perform the ASE identification de novo.

[0095] Various embodiments provide one or more therapies to an individual possessing the disease. Such therapies can include small molecule, large molecule, biologic (e.g., an antibody, a trap, a hormone, a protein, an enzyme, a nucleic acid, an engineered cell), radiation, resection, gene therapy, and any combination thereof. Gene therapy can include methods to alter gene expression. Altering gene expression can include transient expression, such as by supplementing messenger RNA (mRNA), gene silencing (e.g., RNA interference (RNAi)), and / or gene editing, such as to alter a c / s-acting element that may be affecting expression (e.g., increasing or decreasing expression) of an allele. Altering expression can comprise one or more of equalizing expression of both alleles, increasing expression of one allele, and / or decreasing expression of one allele. In this context, equalizing is used to describe allelic expression below a threshold used to define ASE. For example, if ASE is defined as a first allele is expressed at least 2x more than the second allele, equalization can indicate a situation where the first allele is expressed less than 2x and more than 0.5x than the second allele. In altering gene expression, the overall expression of the gene (i.e., combined expression of both alleles) can be increased, decreased, or kept equal.

[0096] Any convenient and appropriate method for altering gene expression may be employed. In some embodiments, gene expression may be altered in an allele-specific manner. For example, the RNA transcript of a specific allele may be targeted for degradation or to otherwise inhibit translation of the allele-specific RNA transcript.

[0097] In some embodiments, gene expression (e.g., allele-specific gene expression) may be altered with the use of an ASO. ASOs are typically small (-15-30 nucleotides), synthetic, singlestranded nucleic acid polymers. In some instances, the ASOs comprise nucleotide modifications. Such modifications may impart useful properties, e.g. increase the biological stability of the ASOs (e.g. nucleases resistance), enhance target binding, increase tissue uptake and / or increase the physical stability of the duplex formed between the ASOs and target nucleic acids, etc. In certain embodiments, the ASO induces steric block of a target sequence, and in such a way that it does not induce target cleavage via RNase H recruitment. For example, an ASO may comprise a chemistry which does not support RNase H cleavage (e.g., does not generate consecutive runs of DNA or DNA-like bases). For example, an ASO may comprise a “mixmer” pattern in which the ASO may comprise two or more different nucleic acid chemistries, but runs of more than 2 or 3 DNA or DNA-like bases (which would support RNase H-mediated cleavage) are avoided. In certain embodiments, the ASO of the present disclosure may comprise DNA, RNA, and / or nucleotide analogues. The nucleotide analogues may be peptide nucleic acid (PNA), FANA, DANA, LNA, and other branched nucleic acids (ENA, cEt), phosphorodiamidate morpholino oligomer (PMO), and / or tricyclo DNA. According to some embodiments, the ASO comprises an abasic site, i.e., the absence of a purine (adenine and guanine) or a pyrimidine (thymine, uracil and cytosine) nucleobase. In certain embodiments, the ASO comprises a 3' to 5' phosphodiester (PO) linkage as naturally found in DNA or RNA. The ASO may comprise a modified internucleoside linkage, e.g. a phosphotriester linkage, a phosphorothioate (PS) linkage, a boranophosphate linkage, a phosphorodiamidate linkage, a phosphoamidate linkage, and / or a thiopho sphoramidate linkage. The modified internucleoside linkage may be other modifications known in the art. According to some embodiments, the ASO comprises one or more asymmetric centres and thus give rise to enantiomers, diasteromers, and other stereoisomeric configurations, e.g. R, S. For example, stereochemistry may be constrained at one or more modified internucleoside linkages. For example, the oligonucleotide may comprise repeated left-left-right (or SSR) chiral PS centers. In some instances, the ASO comprises a sugar moiety as found in naturally occurring RNA (e.g., a ribofuranosyl) or a sugar moiety as found in naturally occurring DNA (e.g., a deoxyribofuranosyl). The ASO may comprise a modified sugar moiety, i.e. a substituted sugar moiety or a sugar surrogate. Substituted sugar moieties include furanosyls comprising substituents at the 2'-position, the 3'-position, the 5 '-position and / or the 4'-position. A substituted sugar moiety may be a bicyclic sugar moiety (BNA). Sugar surrogates include morpholino, cyclohexeynl and cyclohexitol. The modified sugar moiety may comprise a 2' 0- methyl, 2'-O-methoxyethyl (2'-O-MOE), 2'-O-aminopropyl, 2'-deoxy, 2'-O- propyl (2'-O-AP), 2'-O- dimethylaminoethyl (2'O-DMAOE), 2'-O-dimethylaminopropyl (2'-O-DMAP), 2'-O- dimethylaminoethyloxyethyl (2'O-DMAEOE), or 2'0-N-methylacetoamido (2'0-NMA) modification or a locked or bridged ribose conformation (e.g., LNA, cEt or ENA). The modified sugar moiety may comprise other modifications known in the art. According to some embodiments, the ASO comprises a terminal modification at its 5' and / or 3' end, such as a vinyl phosphonate, and / or inverted terminal bases. In certain embodiments, the ASO comprises a nucleobase as found in naturally occurring RNA and DNA (i.e. adenine (A), thymine (T), uracil (U), guanine (G), cytosine (C), inosine (I), and 5-methyl C). The oligonucleotide may comprise a modified nucleobase, e.g. 5-hyrdoxymethylcytosine, 5-formylcytosine, and 5-carboxycytosine. The inclusion of 5'methylcytosine may enhance base pairing by modifying the hydrophobic nature of the oligonucleotide. In some instances, the ASO comprises a single type of nucleic acid chemistry (e.g. full PS -MOE, or full PMO) or combinations of different nucleic acid chemistries. For example, each of the sugar moieties in the ASO may comprise a 2'-O-methoxyethyl (2'MOE) modification and each of the internucleoside linkages may be a phosphorothioate (i.e. a fully PS- MOE oligonucleotide). PS modifications are known to result in resistance to a broad spectrum of nucleases and increase protein binding, which also improves tissue uptake. 2'MOE modifications are known to enable enhanced binding affinity to the target mRNA with minimal toxicity and reduce plasma protein binding. According to some embodiments, the ASO comprises a combination of PO and PS internucleoside linkages. This may facilitate fine tuning of the pharmacokinetics of the oligonucleotide. In certain embodiments, the ASO is produced using chemical synthesis and / or enzymatic ligation reactions using procedures known in the art. Alternatively, An ASO may be produced biologically using an expression vector into which the oligonucleotide is sub-cloned in an antisense orientation (e.g., RNA transcribed from the inserted oligonucleotide will be of an antisense orientation to the target nucleic acid of interest).

[0098] In some embodiments, gene expression (e.g., allele-specific gene expression) may be altered with the use of siRNA, miRNA, or morpholinos. Approaches for designing and delivering siRNAs, miRNAs, morpholinos, etc. for targeting a particular mRNA are known and described, e.g., in Monsoori et al. (2014) Adv Pharm Bull. 4(4) :313-321 ; Xin et al. (2017) Mol Cancer 16:134; Chakraborty et al. (2017) Mol Ther Nucleic Acids 8:132-143; and Ahmadzada et al. (2018) Biophys Rev. 10(1 ):69-86. siRNAs, miRNAs, morpholinos, etc. may be designed based on the known sequence of an mRNA to be targeted and using available tools, e.g., siRNA Wizard from Invivogen, siDESIGN Center from Dharmacon, BLOCK-iT™ RNAi Designer from Invitrogen, miR-Synth available at microrna.osumc.edu / mir-synth, WMD3 - Web MicroRNA Designer, a morpholino design tool provided by Gene Tools, etc.

[0099] Any convenient and appropriate gene therapy methodology may be employed to introduce one or more of the therapies (e.g., altering expression, genetic editing, etc.) described herein. Methods of site-directed introduction of a desired edit will vary and may include introducing one or more site directed cleavage events, e.g., through the use of one or more site- directed nucleases (e.g, a CRISPR / Cas9 nuclease, a TALEN nuclease, a ZFN, and the like). Site-directed cleavage may include double and / or single strand breaks where applicable. In some instances, site-directed cleavage is followed by a specific repair event at the site cleaved by the site-directed nuclease, e.g., to introduce a desired edit, such as e.g., a substitution, insertion, deletion, or the like. Such methods of specific repair may include, e.g., homologous recombination, including homology directed repair (HDR), e.g., in the presence of a nucleic acid that includes homology regions to guide the repair. In some instances, site-directed cleavage may be employed to introduce a gene disruption and / or knock-out, e.g., without employing a specific repair event, e.g., through cellular processes following site-directed cleavage such as e.g., non-homologous end joining (NHEJ). In some instances, site-directed introduction of a desired edit may employ a base editing system that does not introduce a double strand cleavage event, such as but not limited to e.g., CRISPR protein-guided based editing systems, such as e.g., dCas9-deaminase fusion protein systems including cytosine base editor (CBE) and adenine base editor (ABE) systems. In some instances, useful base editing systems introduce a single base change, e.g., without cleavage of the phosphodiester nucleic acid backbone.

[0100] Various editing compositions may be employed and such compositions will vary, e.g., based on the editing-system employed, the type of edit desired, the sequence of the targeted locus or loci, etc. Useful editing compositions may include e.g., CRISPR / Cas9 editing compositions, e.g., including a Cas9 protein, or a nucleic acid encoding a Cas9 protein, and gRNAs or a sgRNA or a nucleic acid encoding the gRNAs or sgRNA; TALEN editing compositions, including e.g., a TALEN nuclease or TALEN nuclease pair, or a nucleic acid encoding a TALEN nuclease or TALEN nuclease pair; ZFN editing compositions, including e.g., a ZFN nuclease or ZFN nuclease pair, or a nucleic acid encoding a ZFN nuclease or ZFN nuclease pair; base-editing editing compositions e.g., including a CRISPR-protein-guided-base- editing protein, or a nucleic acid encoding a CRISPR-protein-guided-base-editing protein, and gRNAs or a sgRNA or a nucleic acid encoding the gRNAs or sgRNA; and the like.

[0101] CRISPR-Cas based editing compositions, and methods of employing CRISPR-Cas based editing compositions will be described in more detail. However, such description, as well as the compositions and methods, are not so limited and it will be readily understood that elements, targets, and / or concepts of such description may be correspondingly adapted or applied to the use of other editing systems where appropriate.

[0102] In some instances, useful editing compositions will include a CRISPR-Cas protein, such as e.g., a Cas9 protein, or a polynucleotide encoding a CRISPR-Cas protein and guide RNA (gRNA) or a polynucleotide encoding gRNA. As used herein, the term “gRNA” generally encompasses either two-component guide systems (e.g., two gRNAs) as well as single guide RNA (sgRNA) systems, unless inappropriate and / or denoted otherwise. In some instances, the gRNA or multiple gRNAs may be configured and employed to target a desired locus as described herein or one or more elements thereof such as one of more exons of a gene present at the locus. For example, in some instances, a gRNA or multiple gRNAs may be configured and employed to target a selected gene or locus (e.g., a gene identified as above) or one or more elements thereof, such as e.g., one or more exons (e.g., one or more of exon 1 , exon 2, or exon 3) of a selected gene or locus.

[0103] In some instances, an instant method of editing may include the use of a Cas9 nuclease, including natural and engineered Cas9 nucleases, as well as nucleic acid sequences encoding the same. Useful Cas9 nucleases include but are not limited to e.g., Streptococcus pyogenes Cas9 and variants thereof, Staphylococcus aureus Cas9 and variants thereof, Actinomyces naeslundii Cas9 and variants thereof, Cas9 nucleases also include those discussed in PCT Publications Nos. WO 2013 / 176772 and W02015 / 103153 and those reviewed in e.g., Makarova et al. (201 1 ) Nature Reviews Microbiology 9:467-477, Makarova et al. (2011 ) Biology Direct 6:38, Haft et al. (2005) PLOS Computational Biology 1 :e60 and Chylinski et al. (2013) RNA Biology 10:726-737, the disclosures of which are incorporated herein by reference in their entireties. In some instances, a non-Cas9 CRISPR nuclease (or engineered variant thereof) may be employed, including but not limited to e.g., Cpf1 or Cpf1 variant.

[0104] Cas9 nucleases are used in the CRISPR / Cas9 system of gene editing and modified Cas9 proteins (e.g., Cas9 nickases and dCas9 proteins, with or without added functionalities) may be employed in various editing methodologies. In the CRISPR / Cas9 system two separate guide components (i.e., crRNA and a tracrRNA) or a chimeric RNA containing the target sequence (i.e. , the “guide RNA” or “single guide RNA (sgRNA)”, which collectively contains a crRNA and a tracrRNA) guides the Cas9 nuclease to cleave the DNA at a specific target sequence defined by the gRNAs or sgRNA. Where employed, the specificity, efficiency and versatility of targeting and replacement by HDR is greatly improved through the combined use of various homology-directed repair strategies and CRISPR nucleases (see e.g., Gratz et al. (2014) Genetics. 196(4)961 -971 ; Chu et al. (2015) Nature. 33:543-548; Hisano et al. (2015) Scientific Reports 5: 8841 ; Farboud & Meyer (2015) Genetics, 199:959-971 ; Merkert & Martin (2016) Stem Cell Research 16(2):377- 386; the disclosures of which are incorporated herein by reference in their entireties).

[0105] The CRISPR system offers significant versatility in gene editing in part because of the small size and high frequency of necessary sequence targeting elements within host genomes. CRISPR guided Cas9 nuclease requires the presence of a protospacer adjacent motif (PAM), the sequence of which depends on the bacteria species from which the Cas9 was derived (e.g. for Streptococcus pyogenes the PAM sequence is "NGG") but such sequences are common throughout various target nucleic acids. The PAM sequence directly downstream of the target sequence is not part of the guide RNA but is obligatory for cutting the DNA strand. Synthetic Cas9 nucleases have been generated with novel PAM recognition, further increasing the versatility of targeting, and may be used in the methods described herein. Cas9 nickases (e.g., Cas9 (D10A) and the like) that cleave only one strand of target nucleic acid as well as endonuclease deficient (i.e., “dead”) dCas9 variants with additional enzymatic activities added by an attached fusion protein have also been developed.

[0106] In some instances, a method of gene editing may include the use of a zinc-finger nuclease (ZFN). ZFNs consist of the sequence-independent Fokl nuclease domain fused to zinc finger proteins (ZFPs). ZFPs can be altered to change their sequence specificity. Cleavage of targeted dsDNA involves binding of two ZFNs (designated left and right) to adjacent half-sites on opposite strands with correct orientation and spacing, thus forming a Fokl dimer. Dimerization increases ZFN specificity significantly. Three or four finger ZFPs target about 9 or 12 bases per ZFN, or about 18 or 24 bases for the ZFN pair. The specificity, efficiency and versatility of targeting and replacement of homologous recombination is greatly improved through the combined use of various homology-directed repair strategies and ZFNs (see e.g., Urnov et al. (2005) Nature. 435(7042):646-5; Beumer et al (2006) Genetics. 172(4):2391-2403; Meng et al (2008) Nat Biotechnol. 26(6):695-701 ; Perez et al. (2008) Nat Biotechnol. 26(7):808-816; Hockemeyer et al. (2009) Nat Biotechnol. 27(9):851 -7; the disclosures of which are incorporated herein by reference in their entireties). In general, one ZFN site can be found every 125-500 bp of a random genomic sequence, depending on the assembly method. Methods for identifying appropriate ZFN targeting sites include computer-mediated methods e.g., as described in e.g., Cradick et al. (201 1 ) BMC Bioinformatics. 12:152, the disclosure of which is incorporated herein by reference in its entirety. In some instances, a method of gene editing may include the use of a transcription activator-like effector nuclease (TALEN). Similar in principle to the ZFN nucleases, TALENs utilize the sequence-independent Fokl nuclease domain fused to Transcription activator- like effectors (TALEs) proteins that, unlike ZNF, individually recognize single nucleotides. TALEs generally contain a characteristic central domain of DNA-binding tandem repeats, a nuclear localization signal, and a C-terminal transcriptional activation domain. A typical repeat is 33-35 amino acids in length and contains two hypervariable amino acid residues at positions 12 and 13, known as the "repeat variable di-residue" (RVD). An RVD is able to recognize one specific DNA base pair and sequential repeats match consecutive DNA sequences. Target DNA specificity is based on the simple code of the RVDs, which thus enables prediction of target DNA sequences. Native TALEs or engineered / modified TALEs may be used in TALENs, depending on the desired targeting. TALENs can be designed for almost any sequence stretch. Merely the presence of a thymine at each 5' end of the DNA recognition site is required. The specificity, efficiency and versatility of targeting and replacement of homologous recombination is greatly improved through the combined use of various homology-directed repair strategies and TALENs (see e.g., Zu et al. (2013) Nature Methods. 10:329-331 ; Cui et al. (2015) Scientific Reports 5:10482; Liu et al. (2012) J. Genet. Genomics. 39:209-215, Bedell et al. (2012) Nature. 491 :1 14- 118, Wang et al. (2013) Nat. Biotechnol. 31 :530-532; Ding et al. (2013) Cell Stem Cell. 12:238- 251 ; Wefers et al. (2013) Proc. Natl. Acad. Sci. U.S.A, 110:3782-3787; the disclosures of which are incorporated herein by reference in their entireties).

[0107] In some instances, a method of gene editing may include the use of a base editor system, including but not limited to e.g., base editor systems employing a fusion protein comprising a programable DNA binding protein, a nucleobase editor and gRNA, and the like. Base editing generally does not rely on HDR and / or NHEJ and generally does not result in or require the cleavage of phosphodiester bonds on both backbones of dsDNA. Thus, based editing may, in some instances, employ RNA-guided (i.e., “programable”) DNA binding proteins, such as Cas nucleases, that do not cause double-strand breaks, such as e.g., nuclease-deficient or nucleasedefective Cas proteins, such as e.g., a dCas9 or a Cas9 nickase. Useful examples of base editors and base editing systems, including base editor encoding nucleic acids, include but are not limited to BE1 , BE2, BE3 (Komor et al., 2016); Target-AID (Nishida et al., 2016); SaBE3, BE3 PAM variants, BE3 editing window variants (Kim et al., 2017); HF-BE3 (Rees et al., 2017); BE4 and BE4-Gam; AID, CDA1 and APOBEC3G BE3 variants (Komor et al., 2017); BE4max, ArcBe4max, ABEmax (Koblan et al., 2018); Adenine base editors (ABE7.10) (Gaudelli et al., 2017); ABE8 (Richter et al., 2020); ABE8e (Gaudelli et al., 2020); A&C-BEmax (Zhang et al., 2020); SPACE (Grunewald et al., 2020); and the like; the preceding references being incorporated by reference herein in their entireties.

[0108] Non-limiting examples of useful base editor systems, and the components thereof, include but are not limited to e.g, those describe in PCT Patent App. Pub. Nos. WO2020236936A1 , WO2020231863A1 , WO2020168135A1 , WO2020168122A1 , W02020168088A1

[0109] WO2020168132A9, WO2020168133A1 , W02020168075A9, W02020168051 A9

[0110] W02020160514A1 , W02020160517A1 , W02020150534A9, W02020051562A3

[0111] W02020051562A3, W02020028823A1 , WO2019217941 A1 , WO2019217942A1 , and

[0112] WO2019217943A1 ; as well as US. Pat. App. Pub. No. US20200399626A1 ; the disclosures of which are incorporated herein by reference in their entireties.

[0113] In some instances, the presence of a desired edit may be verified, e.g., by an assay to test whether the edit is present (or the desired deletion is absent) at the target locus, by an assay to test whether the gene product encoded at the locus targeted for disruption is absent, that the gene product encoded by an introduced sequence is present, or the like. Useful methods to perform such assays include but are not limited to e.g., methods based on PCR (e.g., PCR, qPCR, rt-PCR, etc.) of the locus and / or an RNA encoded at the locus, methods based on Western blot of cells lysates probed with antibodies to a protein encoded at the locus, flow cytometry based methods, sequencing (e.g., single cell sequencing), and the like.

[0114] Other useful components, e.g., of transgenes, of expression cassettes, of editing compositions, of vectors, or the like, may include promoter sequences (e.g., constitutive, tissuespecific, etc.), signal peptide sequences, poly(A) sequences, terminators, translational regulatory sequences such as ribosome binding sites and internal ribosome entry sites, enhancers, silencers, insulators, boundary elements, replication origins, matrix attachment sites and / or locus control regions. Furthermore, multiple gene products can be expressed from one nucleic acid, for example by linking individual components (transgenes) in one open reading frame separated, for example, by a self-cleaving 2A peptide or IRES sequence.

[0115] Examples of useful promoters include, for example, viral simian virus 40 (SV40) (e.g., early or late), cytomegalovirus (CMV) (e.g., immediate early), Moloney murine leukemia virus (MoMLV), MND (myeloproliferative sarcoma virus enhancer, negative control region deleted, dl587rev primer-binding site substituted), Rous sarcoma virus (RSV), herpes simplex virus (HSV), spleen focus-forming virus (SFFV) promoters and the like. In certain embodiments, the promoter may be inducible, such that transcription of all or part of the viral genome will occur only when one or more induction factors are present. Induction factors include, but are not limited to, one or more chemical compounds or physiological conditions, e.g., temperature or pH, in which the host cells are cultured. In some instances, the promoter may be constitutive. In some instances, the promoter may cause preferential expression in a desired cell-type or tissue, e.g., the promoter may be cell-type or tissue specific.

[0116] In some instances, a transgene, an expression cassette, a vector, etc., may include sequence encoding a signal peptide. Signal peptides are short peptides located in the N-terminal of proteins. Functioning in protein localization, signal peptides are useful in directing the associated protein to the secretory pathway and driving secretion of the protein. Vectors, including retroviral vectors, e.g., lentivirus vectors, may include (or exclude as desired where appropriate) various elements, including cis-acting elements, such as promoters, long terminal repeats (LTR), and / or elements thereof, including 5’ LTRs and 3’ LTRs and elements thereof, central polypurine tract (cPPT) elements, DNA flap (FLAP) elements, export elements (e.g., rev response element (RRE), hepatitis B virus post-transcriptional regulatory element (HPRE), etc.), posttranscriptional regulatory elements (e.g., woodchuck hepatitis virus posttranscriptional regulatory element (WPRE), hepatitis B virus regulatory element (HPRE), etc.), polyadenylation sites, transcription termination signals, insulators elements (e.g., p-globin insulator, e.g., chicken HS4), and the like. Other elements that may be present or absent in various vectors include but are not limited to enhancers, untranslated regions (UTRs), Kozak sequences, polyadenylation signals, additional restriction enzyme sites, multiple cloning sites, internal ribosomal entry sites (IRES), recombinase recognition sites (e.g., LoxP, FRT, and Att sites), termination codons, transcriptional termination signals, and polynucleotides encoding selfcleaving polypeptides, epitope tags, homology regions useful in homology directed repair (HDR), and the like.

[0117] Useful LTRs include but are not limited to e.g., those containing U3, R and / or U5 regions, and portions thereof. LTRs provide functions for the expression of retroviral genes (e.g., promotion, initiation and polyadenylation of gene transcripts) and for viral replication. An LTR can contain numerous regulatory signals including transcriptional control elements, polyadenylation signals and sequences needed for replication and integration of the viral genome. A U3 region may contain enhancer and promoter elements. A U5 region may contain a polyadenylation sequence. The R (repeat) region is generally flanked by the U3 and U5 regions. An LTR composed of U3, R and U5 regions may appear at both the 5’ and 3' ends of a viral genome. A viral genome may include sequence adjacent to a 5' LTR that functions in reverse transcription of the genome (e.g., the tRNA primer binding site), for efficient packaging of viral RNA into particles (e.g., the Psi site), and the like.

[0118] Useful LTRs include modified 5' LTR and / or 3' LTRs. Modifications of the 3' LTR are often made to improve the safety of lentiviral or retroviral systems by rendering viruses replicationdefective. As used herein, the term “replication-defective” refers to virus that is not capable of complete, effective replication such that infective virions are not produced (e.g., replicationdefective lentiviral progeny). The term “replication-competent” refers to wild-type virus or mutant virus that is capable of replication, such that viral replication of the virus is capable of producing infective virions (e.g., replication-competent lentiviral progeny).

[0119] In some embodiments, useful vectors may be self-inactivating. The term “self-inactivating” (SIN) with regards to vectors refers to replication-defective vectors, e.g., retroviral or lentiviral vectors, in which the right (3') LTR enhancer-promoter region, including e.g., the U3 region, has been modified (e.g., by deletion and / or substitution) to prevent viral transcription beyond the first round of viral replication. In further embodiments, the 3' LTR may be modified such that the U5 region is replaced, for example, with a heterologous or synthetic poly(A) sequence, one or more insulator elements, and / or an inducible promoter. It will be readily apparent to the ordinarily skilled artisan where reference to an LTR, e.g., 3’ LTR or 5' LTR, may include modified LTRs or modifications to LTRs, such as modifications to the 3' LTR, the 5' LTR, or both 3' and 5' LTRs.

[0120] In some embodiments, viral vectors may comprise a TAR element. The term “TAR” refers to the “trans-activation response” genetic element located in the R region of lentiviral (e.g., HIV) LTRs. This element interacts with the lentiviral trans-activator (tat) genetic element to enhance viral replication. In some embodiments, a vector may not include a TAR element, including e.g., wherein the U3 region of the 5' LTR is replaced by a heterologous promoter.

[0121] In some instances, a vector may be a pseudotyped vector. The terms “pseudotype” or “pseudotyping” as used herein, refer to a virus that has one or more viral envelope proteins that have been substituted with those of another virus possessing preferable characteristics. For example, HIV can be pseudotyped with vesicular stomatitis virus G-protein (VSV-G) envelope proteins. In some embodiments, lentiviral envelope proteins are pseudotyped with VSV-G. In some embodiments, packaging cells which produce recombinant retrovirus, e.g., lentivirus, pseudotyped with the VSV-G envelope glycoprotein may be employed.

[0122] Vectors, both viral and nonviral, may include structural and / or genetic elements, or potions thereof, derived from viruses. Retroviral vectors may include structural and / or genetic elements, or portions thereof, derived from retroviruses. Lentiviral vectors may include structural and functional genetic elements, or portions thereof, including LTRs that are primarily derived from a lentivirus. In some instances, hybrid vectors may be employed, including e.g., where a hybrid vector includes an LTR or other nucleic acid containing both retroviral, e.g., lentiviral, sequences and non-retroviral, e.g., non-lentiviral viral, sequences. In some embodiments, a hybrid vector may include a vector comprising retroviral e.g., lentiviral, sequences for reverse transcription, replication, integration and / or packaging.

[0123] As noted previously, additional therapeutic agents can include one or more of a small molecule, a large molecule, a biologic molecule, a radionuclide. Many biologies qualify as large molecules and many large molecules are also biologic molecules. Biologies can include an antibody, a trap, a hormone, a protein, an enzyme, a nucleic acid, and / or an engineered cell. Such therapies can be provided as a therapeutically effective amount. Additionally, certain therapeutics can include conjugated molecules, where two molecules are linked together, such as an antibody-drug conjugate. “Therapeutically effective amount” is meant to describe a dosage sufficient to produce a desired result, e.g., an amount sufficient to effect beneficial or desired therapeutic (including preventative) results, such as a reduction in a symptom of the disease state.

[0124] Various drugs and / or antibodies can be used as a treatment. Non-limiting examples of antibodies that specifically bind to tumor antigens include Adecatumumab, Ascrinvacumab, Cixutumumab, Conatumumab, Daratumumab, Drozitumab, Duligotumab, Durvalumab, Dusigitumab, Enfortumab, Enoticumab, Figitumumab, Ganitumab, Glembatumumab, Intetumumab, Ipilimumab, Iratumumab, Icrucumab, Lexatumumab, Lucatumumab,

[0125] Mapatumumab, Narnatumab, Necitumumab, Nesvacumab, Ofatumumab, Olaratumab,

[0126] Panitumumab, Patritumab, Pritumumab, Radretumab, Ramucirumab, Rilotumumab,

[0127] Robatumumab, Seribantumab, Tarextumab, Teprotumumab, Tovetumab, Vantictumab,

[0128] Vesencumab, Votumumab, Zalutumumab, Flanvotumab, Altumomab, Anatumomab, Arcitumomab, Bectumomab, Blinatumomab, Detumomab, Ibritumomab, Minretumomab, Mitumomab, Moxetumomab, Naptumomab, Nofetumomab, Pemtumomab, Pintumomab, Racotumomab, Satumomab, Solitomab, Taplitumomab, Tenatumomab, Tositumomab, Tremelimumab, Abagovomab, Igovomab, Oregovomab, Capromab, Edrecolomab, Nacolomab, Amatuximab, Bavituximab, Brentuximab, Cetuximab, Derlotuximab, Dinutuximab, Ensituximab, Futuximab, Girentuximab, Indatuximab, Isatuximab, Margetuximab, Rituximab, Siltuximab, Ublituximab, Ecromeximab, Abituzumab, Alemtuzumab, Bevacizumab, Bivatuzumab, Brontictuzumab, Cantuzumab, Cantuzumab, Citatuzumab, Clivatuzumab, Dacetuzumab, Demcizumab, Dalotuzumab, Denintuzumab, Elotuzumab, Emactuzumab, Emibetuzumab, Enoblituzumab, Etaracizumab, Farletuzumab, Ficlatuzumab, Gemtuzumab, Imgatuzumab, Inotuzumab, Labetuzumab, Lifastuzumab, Lintuzumab, Lorvotuzumab, Lumretuzumab, Matuzumab, Milatuzumab, Nimotuzumab, Obinutuzumab, Ocaratuzumab, Otlertuzumab, Onartuzumab, Oportuzumab, Parsatuzumab, Pertuzumab, Pinatuzumab, Polatuzumab, Sibrotuzumab, Simtuzumab, Tacatuzumab, Tigatuzumab, Trastuzumab, Tucotuzumab, Vandortuzumab, Vanucizumab, Veltuzumab, Vorsetuzumab, Sofituzumab, Catumaxomab, Ertumaxomab, Depatuxizumab, Ontuxizumab, Blontuvetmab, Tamtuvetmab, or a tumor antigenbinding variant thereof. As used herein, “variant” is meant the antibody specifically binds to the particular antigen (e.g., HER2 for trastuzumab) but has fewer or more amino acids than the parental antibody (e.g., is a fragment (e.g., scFv) of the parental antibody), has one or more amino acid substitutions relative to the parental antibody, or a combination thereof.

[0129] In some embodiments, an antibody is an antibody approved by the United States Food and Drug Administration and / or the European Medicines Agency (EMA) for use as a therapeutic antibody (e.g., for targeting certain disease-associated cells in a patient, etc.), or a fragment thereof (e.g., a single-chain version of such an antibody, such as an scFv version of the antibody) that retains the ability to specifically bind the target antigen.

[0130] Some drugs used in various embodiments include cytotoxic agents, including (but not limited to) a cytotoxic agent selected from an enediyne, a lexitropsin, a duocarmycin, a taxane, a puromycin, a dolastatin, a maytansinoid, and a vinca alkaloid. According to certain embodiments, the cytotoxic agent is paclitaxel, docetaxel, CC-1065, CPT-11 (SN-38), topotecan, doxorubicin, morpholino-doxorubicin, rhizoxin, cyanomorpholino-doxorubicin, dolastatin-10, echinomycin, combretastatin, calicheamicin, maytansine, maytansine DM1 , maytansine DM4, DM-1 , an auristatin or other dolastatin derivatives, such as auristatin E or auristatin F, AEB (AEB-071 ), AEVB (5-benzoylvaleric acid-AE ester), AEFP (antibody-endostatin fusion protein), MMAE (monomethylauristatin E), MMAF (monomethylauristatin F), pyrrolobenzodiazepines (PBDs), eleutherobin, netropsin, or any combination thereof.

[0131] Various instances may target a gene product of a selected gene. Such gene targets can include a protein, an enzyme, or other peptide encoded by gene. Such targeting can include providing an inhibitor of an enzyme, such as an allosteric inhibitor and / or a competitive inhibitor. In some embodiments, a protein interaction is disrupted. The interaction can be internal to a single protein or between two or more proteins or peptides. When the interaction is between two or more proteins or peptides, the proteins or peptides can be the same peptide (e.g., homopolymer) or between different peptides (e.g., heteropolymer).

[0132] Various methods for RNAi or otherwise silencing RNA can be used. Certain embodiments use short interfering RNAs (siRNAs), microRNAs (miRNA), and / or any other form of small RNA that can be used in an RNAi pathway. Approaches for designing and delivering siRNAs, miRNAs, morpholinos, etc. for targeting a particular mRNA are known and described, e.g., in Monsoori et al. (2014) Adv Pharm Bull. 4(4):313-321 ; Xin et al. (2017) Mol Cancer 16:134; Chakraborty et al. (2017) Mol Ther Nucleic Acids 8:132-143; and Ahmadzada et al. (2018) Biophys Rev. 10(1 ):69- 86; the disclosure of which is hereby incorporated by reference in its entirety. siRNAs, miRNAs, morpholinos, etc. may be designed based on the known sequence of an mRNA to be targeted and using available tools, e.g., siRNA Wizard from Invivogen, siDESIGN Center from Dharmacon, BLOCK-iT™ RNAi Designer from Invitrogen, miR-Synth available at microrna.osumc.edu / mir-synth, WMD3 - Web MicroRNA Designer, a morpholino design tool provided by Gene Tools, etc.

[0133] ASE SIGNATURES IN CANCER

[0134] Certain embodiments provide an ASE signature based on the foregoing methods in one or more cancers. The subject methods may be employed for the treatment of a large variety of cancers. “Tumor”, as used herein, refers to all neoplastic cell growth and proliferation, whether malignant or benign, and all pre-cancerous and cancerous cells and tissues. The terms “cancer” and “cancerous” refer to or describe the physiological condition in mammals that is typically characterized by unregulated cell growth / proliferation. Examples of cancers that may be treated using the subject methods include, but are not limited to, carcinoma, lymphoma, blastoma, and sarcoma. More particular examples of such cancers include renal cancer; kidney cancer; glioblastoma multiforme; metastatic breast cancer; breast carcinoma; breast sarcoma; neurofibroma; neurofibromatosis; pediatric tumors; neuroblastoma; malignant melanoma; carcinomas of the epidermis; leukemias such as but not limited to, acute leukemia, acute lymphocytic leukemia, acute myelocytic leukemias such as myeloblastic, promyelocytic, myelomonocytic, monocytic, erythroleukemia leukemias and myelodysplastic syndrome, chronic leukemias such as but not limited to, chronic myelocytic (granulocytic) leukemia, chronic lymphocytic leukemia, hairy cell leukemia; polycythemia vera; lymphomas such as but not limited to Hodgkin's disease, non-Hodgkin's disease; multiple myelomas such as but not limited to smoldering multiple myeloma, nonsecretory myeloma, osteosclerotic myeloma, plasma cell leukemia, solitary plasmacytoma and extramedullary plasmacytoma; Waldenstrom's macroglobulinemia; monoclonal gammopathy of undetermined significance; benign monoclonal gammopathy; heavy chain disease; bone cancer and connective tissue sarcomas such as but not limited to bone sarcoma, myeloma bone disease, multiple myeloma, cholesteatoma-induced bone osteosarcoma, Paget's disease of bone, osteosarcoma, chondrosarcoma, Ewing's sarcoma, malignant giant cell tumor, fibrosarcoma of bone, chordoma, periosteal sarcoma, soft- tissue sarcomas, angiosarcoma (hemangiosarcoma), fibrosarcoma, Kaposi's sarcoma, leiomyosarcoma, liposarcoma, lymphangio sarcoma, neurilemmoma, rhabdomyosarcoma, and synovial sarcoma; brain tumors such as but not limited to, glioma, astrocytoma, brain stem glioma, ependymoma, oligodendroglioma, nonglial tumor, acoustic neurinoma, craniopharyngioma, medulloblastoma, meningioma, pineocytoma, pineoblastoma, and primary brain lymphoma; breast cancer including but not limited to adenocarcinoma, lobular (small cell) carcinoma, intraductal carcinoma, medullary breast cancer, mucinous breast cancer, tubular breast cancer, papillary breast cancer, Paget's disease (including juvenile Paget's disease) and inflammatory breast cancer; adrenal cancer such as but not limited to pheochromocytom and adrenocortical carcinoma; thyroid cancer such as but not limited to papillary or follicular thyroid cancer, medullary thyroid cancer and anaplastic thyroid cancer; pancreatic cancer such as but not limited to, insulinoma, gastrinoma, glucagonoma, vipoma, somatostatin-secreting tumor, and carcinoid or islet cell tumor; pituitary cancers such as but limited to Cushing's disease, prolactinsecreting tumor, acromegaly, and diabetes insipius; eye cancers such as but not limited to ocular melanoma such as iris melanoma, choroidal melanoma, and ciliary body melanoma, and retinoblastoma; vaginal cancers such as squamous cell carcinoma, adenocarcinoma, and melanoma; vulvar cancer such as squamous cell carcinoma, melanoma, adenocarcinoma, basal cell carcinoma, sarcoma, and Paget's disease; cervical cancers such as but not limited to, squamous cell carcinoma, and adenocarcinoma; uterine cancers such as but not limited to endometrial carcinoma and uterine sarcoma; ovarian cancers such as but not limited to, ovarian epithelial carcinoma, borderline tumor, germ cell tumor, and stromal tumor; cervical carcinoma; esophageal cancers such as but not limited to, squamous cancer, adenocarcinoma, adenoid cyctic carcinoma, mucoepidermoid carcinoma, adenosquamous carcinoma, sarcoma, melanoma, plasmacytoma, verrucous carcinoma, and oat cell (small cell) carcinoma; stomach cancers such as but not limited to, adenocarcinoma, fungating (polypoid), ulcerating, superficial spreading, diffusely spreading, malignant lymphoma, liposarcoma, fibrosarcoma, and carcinosarcoma; colon cancers; colorectal cancer, KRAS mutated colorectal cancer; colon carcinoma; rectal cancers; liver cancers such as but not limited to hepatocellular carcinoma and hepatoblastoma, gallbladder cancers such as adenocarcinoma; cholangiocarcinomas such as but not limited to papillary, nodular, and diffuse; lung cancers such as KRAS-mutated non-small cell lung cancer, non-small cell lung cancer, squamous cell carcinoma (epidermoid carcinoma), adenocarcinoma, large-cell carcinoma and small-cell lung cancer; lung carcinoma; testicular cancers such as but not limited to germinal tumor, seminoma, anaplastic, classic (typical), spermatocytic, nonseminoma, embryonal carcinoma, teratoma carcinoma, choriocarcinoma (yolk-sac tumor), prostate cancers such as but not limited to, androgen-independent prostate cancer, androgendependent prostate cancer, adenocarcinoma, leiomyosarcoma, and rhabdomyosarcoma; penal cancers; oral cancers such as but not limited to squamous cell carcinoma; basal cancers; salivary gland cancers such as but not limited to adenocarcinoma, mucoepidermoid carcinoma, and adenoidcystic carcinoma; pharynx cancers such as but not limited to squamous cell cancer, and verrucous; skin cancers such as but not limited to, basal cell carcinoma, squamous cell carcinoma and melanoma, superficial spreading melanoma, nodular melanoma, lentigo malignant melanoma, acrallentiginous melanoma; kidney cancers such as but not limited to renal cell cancer, adenocarcinoma, hypernephroma, fibrosarcoma, transitional cell cancer (renal pelvis and / or uterer); renal carcinoma; Wilms' tumor; and bladder cancers such as but not limited to transitional cell carcinoma, squamous cell cancer, adenocarcinoma, carcinosarcoma. In some embodiments, the cancer is myxosarcoma, osteogenic sarcoma, endotheliosarcoma, lymphangioendotheliosarcoma, mesothelioma, synovioma, hemangioblastoma, epithelial carcinoma, cystadenocarcinoma, bronchogenic carcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary carcinoma, or papillary adenocarcinomas.

[0135] A specific and non-limiting example includes prostate cancer. For example a prostate cancer ASE signature can include one or more of the genes provided in Table 1 . Certain embodiments may target a subset of genes, which may show a causative effect in cancer, such as in tumorigenesis or cancer progression. In some embodiments, such a subset of genes may be selected from one or more genes selected from ACSM1 (NCBI Gene ID: 1 16285), ALDH3B2 (NCBI Gene ID: 222), DNAH8 (NCBI Gene ID: 1769), MTUS1 (NCBI Gene ID: 57509), RAD52 (NCBI Gene ID: 5893), SLC25A37 (NCBI Gene ID: 51312), EPHX2 (NCBI Gene ID: 2053), TMPRSS2 (NCBI Gene ID: 71 13), HLA-DRB6 (NCBI Gene ID: 3128), BANK1 (NCBI Gene ID: 55024), NKX3-1 (NCBI Gene ID: 4824), SLC7A2 (NCBI Gene ID: 6542), TMBIM4 (NCBI Gene ID:51643), NQO2 (NCBI Gene ID: 4835), ABAT (NCBI Gene ID: 18), HCP5 (NCBI Gene ID: 10866), NCAM2 (NCBI Gene ID: 4685), ZNF717 (NCBI Gene ID: 100131827), DOCK1 (NCBI Gene ID: 1793), FARP1 (NCBI Gene ID: 10160), and FDFT1 (NCBI Gene ID: 2222). In other embodiments, the subset of genes may be selected from one or more genes selected from ACSM1 , ALDH3B2, DNAH8, MTUS1 , RAD52, SLC25A37, EPHX2, TMPRSS2, HLA-DRB6, and BANK1 . Identifying such an ASE signature is described in detail in the Experimental section herein. While such an embodiments is specific to prostate cancer, it should be noted that the methods and procedures are applicable to any cancer, disease, or other condition. Furthermore, the specific treatments or therapies that can be provided to an individual can include generally accepted therapies for prostate cancer, including hormones, antibodies, chemotherapy, etc. Certain embodiments treat prostate cancer by altering one or more of the genes identified in the ASE signature (e.g., the genes listed in Table 1 ). Certain embodiments may target a subset of genes, which may show a causative effect in cancer, such as in tumorigenesis or cancer progression. In some embodiments, such a subset of genes may be selected from one or more genes selected from ACSM1 , ALDH3B2, DNAH8, MTUS1 , RAD52, SLC25A37, EPHX2, TMPRSS2, HLA-DRB6, BANK1 , NKX3-1 , SLC7A2, TMBIM4, NQO2, ABAT, HCP5, NCAM2, ZNF717, DOCK1 , FARP1 , and FDFT1. In other embodiments, the subset of genes may be selected from one or more genes selected from ACSM1 , ALDH3B2, DNAH8, MTUS1 , RAD52, SLC25A37, EPHX2, TMPRSS2, HLA-DRB6, and BANK1 .

[0136] For purposes of completeness, various aspects of the present disclosure are set out in the following numbered clauses.

[0137] Aspect 1. A method for identifying an allele specific expression (ASE) signature in a disease, the method comprising: obtaining genomic sequence data and expression data from a collection of tissue, wherein the collection of tissue includes normal tissue and abnormal tissue, wherein the abnormal tissue is associated with the disease; and identifying a gene exhibiting ASE that is indicative of the disease using the genomic sequence data and expression data, wherein the gene is heterozygous and its alleles are differentially expressed in either healthy tissue or unhealthy tissue. Aspect 2. The method of Aspect 1 , wherein the genomic sequence data includes one or more of whole genome sequencing (WGS) data and whole exome sequencing (WES) data, and wherein the expression data includes one or more of RNA sequencing (RNASeq) data and microarray data.

[0138] Aspect 3. The method of Aspect 1 or 2, wherein identifying a gene exhibiting ASE, comprises: identifying the alleles based on a heterozygous single nucleotide variant (SNV) located in an exonic region of the gene using the genomic sequence data; and determining expression of the alleles based on the expression data; wherein ASE is indicated by one allele being expressed at a greater rate than the other allele.

[0139] Aspect 4. The method of Aspect 3, wherein ASE is indicated by one allele being expressed at a rate of at least 2x as compared to the other allele or when only one allele is expressed.

[0140] Aspect 5. The method of Aspect 3 or 4, wherein each SNV is present in at least eight sequencing reads in the genomic sequence data. Aspect 6. The method of any one of Aspects 3-5, further comprising removing genes exhibiting copy number variation (CNV).

[0141] Aspect 7. The method of Aspect 6, wherein CNV is identified based on one allele being overrepresented in the genomic sequencing data.

[0142] Aspect 8. The method of Aspect 7, wherein CNV is identified based on one allele being represented at a rate of greater than 0.75 or less than 0.25 in the genomic sequencing data.

[0143] Aspect 9. The method of any one of Aspects 18, wherein the genomic sequence data includes one or more of whole genome sequencing (WGS) data and whole exome sequencing (WES) data, and wherein the expression data includes one or more of RNA sequencing (RNASeq) data and microarray data.

[0144] Aspect 10. The method of any one of Aspects 1-9, wherein the disease is selected from a cancer, an infectious disease, a deficiency disease, a hereditary disease, and a physiological disease.

[0145] Aspect 11 . The method of any one of Aspects 1 -10, wherein the abnormal tissue includes tissue from more than one type, stage, score, histology, severity, or prognosis.

[0146] Aspect 12. The method of any one of Aspects 1-9, wherein the disease is a cancer.

[0147] Aspect 13. The method of Aspect 12, wherein the cancer is selected from prostate cancer, breast cancer, pancreatic cancer, skin cancer, colorectal cancer, testicular cancer, lung cancer, esophageal cancer, uterine cancer, ovarian cancer, lymphoma, liver cancer, renal cancer, oral cancer, brain cancer, thyroid cancer, urogenital cancer, including individual varieties, subtypes, and stages thereof.

[0148] Aspect 14. The method of Aspect 12 or 13, wherein the abnormal tissue includes tissue from localized cancer and metastatic cancer.

[0149] Aspect 15. The method of Aspect 12 or 13, wherein the abnormal tissue includes resistant tumors and non-resistant tumors.

[0150] Aspect 16. The method of Aspect 12, wherein the cancer is prostate cancer and the abnormal tissue includes localized prostate cancer and metastatic castration-resistant prostate cancer.

[0151] Aspect 17. The method of any one of Aspects 1 -16, further comprising validating the gene exhibiting ASE.

[0152] Aspect 18. The method of Aspect 17, wherein validating the gene exhibiting ASE comprises determining a receiver operating characteristic.

[0153] Aspect 19. A method for treating a disease in a subject in need thereof, the method comprising: altering expression of or targeting the product of a gene exhibiting allele specific expression (ASE) in the disease, wherein the ASE was identified by the method of any one of Aspects 1 -17. Aspect 20. The method of Aspect 19, further comprising performing the method of any one of Aspects 1 -18.

[0154] Aspect 21 . The method of Aspect 19 or 20, wherein altering expression of a gene exhibiting ASE comprises equalizing expression between the alleles associated with the gene exhibiting ASE.

[0155] Aspect 22. The method of Aspect 19 or 20, wherein altering expression of the gene exhibiting ASE comprises increasing expression of one allele associated with the gene exhibiting ASE.

[0156] Aspect 23. The method of Aspect 19 or 20, wherein altering expression of the gene exhibiting ASE comprises reducing expression of one allele associated with the gene exhibiting ASE.

[0157] Aspect 24. The method of any one of Aspects 21 -23, wherein altering expression of the gene exhibiting ASE comprises utilizing a CRISPR system to alter expression of the gene exhibiting ASE.

[0158] Aspect 25. The method of Aspect 24, wherein the CRISPR system alters a regulatory element of the gene exhibiting ASE.

[0159] Aspect 26. The method of Aspect 24, wherein the CRISPR system alters a coding region of the gene exhibiting ASE.

[0160] Aspect 27. The method of any one of Aspects 21 -23, wherein altering expression of the gene exhibiting ASE comprises utilizing RNA interference to alter expression of the gene exhibiting ASE.

[0161] Aspect 28. The method of Aspect 19 or 20, wherein targeting the product of a gene exhibiting ASE comprises providing a therapeutic agent to the subject.

[0162] Aspect 29. The method of Aspect 28, wherein the therapeutic agent is selected from a biologic molecule and a small molecule.

[0163] Aspect 30. The method of Aspect 29, wherein the biologic molecule is selected from an antibody, a trap, a hormone, a protein, an enzyme, a nucleic acid, a cell.

[0164] Aspect 31 . The method of Aspect 29, wherein the small molecule is selected from an antibiotic, an antiviral, a chemotherapeutic agent, a radioactive nuclide, an allosteric enzyme inhibitor, and a competitive enzyme inhibitor.

[0165] Aspect 32. The method of any one of Aspects 19-31 , further comprising resecting tissue that is diseased.

[0166] Aspect 33. A method of identifying a subject as having a disease associated with allele specific expression (ASE) of a gene, the method comprising: assessing a sample from the subject for ASE of the gene, wherein the ASE was identified by the method of any one of Aspects 1 -17.

[0167] Aspect 34. The method of Aspect 31 , further comprising performing the method of any one of Aspects 1 -18. Aspect 35. The method of Aspect 33 or 34, wherein the sample is obtained from one or more of a blood sample, liquid biopsy, a tumor biopsy, and a biopsy of a tissue suspected of being cancerous, a buccal swab, a skin swab, a skin scraping, a throat swab, a nasal swab, and a urine sample.

[0168] Aspect 36. The method of any one of Aspects 19-31 , further comprising providing a therapy to the subject.

[0169] Aspect 37. The method of Aspect 36, wherein the therapy comprises altering expression of or targeting the product of a gene exhibiting allele specific expression (ASE) in the disease.

[0170] Aspect 38. The method of Aspect 37, wherein altering expression of a gene exhibiting ASE comprises equalizing expression between the alleles associated with the gene exhibiting ASE.

[0171] Aspect 39. The method of Aspect 37, wherein altering expression of the gene exhibiting ASE comprises increasing expression of one allele associated with the gene exhibiting ASE.

[0172] Aspect 40. The method of Aspect 37, wherein altering expression of the gene exhibiting ASE comprises reducing expression of one allele associated with the gene exhibiting ASE.

[0173] Aspect 41 . The method of any one of Aspects 37-40, wherein altering expression of the gene exhibiting ASE comprises utilizing a CRISPR system to alter expression of the gene exhibiting ASE.

[0174] Aspect 42. The method of Aspect 41 , wherein the CRISPR system alters a regulatory element of the gene exhibiting ASE.

[0175] Aspect 43. The method of Aspect 41 , wherein the CRISPR system alters a coding region of the gene exhibiting ASE.

[0176] Aspect 44. The method of any one of Aspects 37-40, wherein altering expression of the gene exhibiting ASE comprises utilizing RNA interference to alter expression of the gene exhibiting ASE.

[0177] Aspect 45. The method of Aspect 37, wherein targeting the product of a gene exhibiting ASE comprises providing a therapeutic agent to the subject.

[0178] Aspect 46. The method of Aspect 45, wherein the therapeutic agent is selected from a biologic molecule and a small molecule.

[0179] Aspect 47. The method of Aspect 46, wherein the biologic molecule is selected from an antibody, a trap, a hormone, a protein, an enzyme, a nucleic acid, a cell.

[0180] Aspect 48. The method of Aspect 46, wherein the small molecule is selected from an antibiotic, an antiviral, a chemotherapeutic agent, a radioactive nuclide, an allosteric enzyme inhibitor, and a competitive enzyme inhibitor. Aspect 49. The method of any one of Aspects 35-48, further comprising resecting tissue that is diseased.

[0181] Aspect 50. A method of treating prostate cancer, the method comprising: altering expression of or targeting the product of one or more genes selected from ACSM1 , ALDH3B2, DNAH8, MTUS1 , RAD52, SLC25A37, EPHX2, TMPRSS2, HLA-DRB6, BANK1 , NKX3-1 , SLC7A2, TMBIM4, NQO2, ABAT, HCP5, NCAM2, ZNF717, DOCK1 , FARP1 , and FDFT1.

[0182] Aspect 51 . The method of Aspect 50, wherein the one or more genes are selected from ACSM1 , ALDH3B2, DNAH8, MTUS1 , RAD52, SLC25A37, EPHX2, TMPRSS2, HLA- DRB6, and BANK1 .

[0183] Aspect 52. The method of Aspect 50 or 51 , wherein the prostate cancer is selected from localized prostate cancer, metastatic castration resistant prostate cancer (mCRPC), and metastatic hormone-sensitive prostate cancer (mHSPC).

[0184] Aspect 53. The method of any one of Aspects 50-52, wherein altering expression of the one or more genes comprises equalizing expression between the alleles associated with the one or more genes.

[0185] Aspect 54. The method of any one of Aspects 50-52, wherein altering expression of the one or more genes comprises increasing expression of one allele associated with the one or more genes.

[0186] Aspect 55. The method of any one of Aspects 50-52, wherein altering expression of the one or more genes comprises reducing expression of one allele associated with the one or more genes.

[0187] Aspect 56. The method of any one of Aspects 53-55, wherein altering expression of the one or more genes comprises utilizing a CRISPR system to alter expression of the one or more genes.

[0188] Aspect 57. The method of Aspect 56, wherein the CRISPR system alters a regulatory element of the one or more genes.

[0189] Aspect 58. The method of Aspect 56, wherein the CRISPR system alters a coding region of the one or more genes.

[0190] Aspect 59. The method of any one of Aspects 50-52, wherein altering expression of the one or more genes comprises utilizing RNA interference to alter expression of the one or more genes.

[0191] Aspect 60. The method of any one of Aspects 53-55, wherein targeting the product of a one or more genes comprises providing a therapeutic agent to the subject.

[0192] Aspect 61 . The method of Aspect 60, wherein the therapeutic agent is selected from a biologic molecule and a small molecule.

[0193] Aspect 62. The method of Aspect 61 , wherein the biologic molecule is selected from an antibody, a trap, a hormone, a protein, an enzyme, a nucleic acid, a cell. Aspect 63. The method of Aspect 61 , wherein the small molecule is selected from an antibiotic, an antiviral, a chemotherapeutic agent, a radioactive nuclide, an allosteric enzyme inhibitor, and a competitive enzyme inhibitor.

[0194] Aspect 64. The method of any one of Aspects 50-63, further comprising resecting tissue that is diseased.

[0195] Aspect 65. A method for identifying prostate cancer in a subject, the method comprising: assessing a sample from a subject for allele specific expression (ASE) exhibited in one or more genes selected from: ACSM1 , ALDH3B2, DNAH8, MTUS1 , RAD52, SLC25A37, EPHX2, TMPRSS2, HLA-DRB6, BANK1 , NKX3-1 , SLC7A2, TMBIM4, NQO2, ABAT, HCP5, NCAM2, ZNF717, DOCK1 , FARP1 , and FDFT1.

[0196] Aspect 66. The method of Aspect 65, wherein the one or more genes are selected from ACSM1 , ALDH3B2, DNAH8, MTUS1 , RAD52, SLC25A37, EPHX2, TMPRSS2, HLA- DRB6, and BANK1 .

[0197] Aspect 67. The method of Aspect 65 or 66, wherein the subject has or is suspected of having prostate cancer.

[0198] Aspect 68. The method of any one of Aspects 65-67, wherein the sample is selected from one or more of a liquid biopsy, a tumor biopsy, and a tissues suspected of being cancerous.

[0199] Aspect 69. The method of any one of Aspects 65-68, wherein assessing the sample for ASE comprises assessing expression levels of alleles associated with the one or more genes.

[0200] Aspect 70. The method of Aspect 69, wherein assessing expression levels comprises performing RNA sequencing or a microarray assay.

[0201] The following examples are offered by way of illustration and not by way of limitation.

[0202] EXPERIMENTAL

[0203] Example 1 - Methods

[0204] Data Acquisition

[0205] WES, WGS, and RNAseq BAM files for TCGA PRAD and WCDT mCRPC samples were downloaded from the GDC Portal using the GDC Data Transfer Tool. DNA and RNA counts at heterozygous SNVs for normal prostate tissue were downloaded from the GTEx Portal. The TCGAbiolinks R package was used to download raw count and TPM expression data. Imprinted genes were downloaded from the Geneimprint database. Cell line WES and RNAseq BAM files were downloaded from the CCLE database. Estimation of SNV-level ASE

[0206] In order to differentiate reads from different gene alleles, heterozygous SNVs in genes we identified first. Somatic and germline heterozygous SNVs were called using Mutect2 and HaplotypeCaller from GATK (V4.2.2.0), with a filter of 8 reads per allele. Both DNA and RNA BAM files were filtered using the WASP pipeline to correct for SNV mapping bias that could result in false positive ASE calls. RNA read counts for each allele were called using GATK ASEReadCounter. Heterozygous SNVs that had at least 8 total RNA reads and were located in exonic regions were used for subsequent analysis. SNVs with a DNA reference fraction of greater 0.75 or less than 0.25 were removed to account for bias introduced by large-scale changes in DNA content such as aneuploidy. In order to identify and remove SNVs that mapped to more than one gene, blast queries were conducted for each SNV and its surrounding context against Gencode protein coding transcripts. SNVs were filtered that showed a reference:alternate foldchange strongly favoring one direction in multiple samples, which shows evidence of mapping bias. Assuming that a SNV is neutral, the geometric mean of these fold-changes across samples should be approximately 1 . Extreme cases showing a geometric mean of 10 or greater were removed.

[0207] Gene-level allele-specific expression

[0208] Allele-specific expression was tested for at each heterozygous SNV using the binomial test and an allele fold-change threshold. Sequencing read counts are overdispersed, and it was observed that the average DNA reference read fraction across heterozygous SNVs was slightly higher than 0.5 (Fig. 8D). To account for this, the DNA reference fraction of each SNV was used as the null ratio for the binomial test instead of 0.5. The Benjamini-Hochberg correction with FDR of 5% was applied to the p-values in each tumor to control the FDR. To measure the magnitude of ASE, an allele fold-change was computed for each SNV by dividing the reference allele fraction alternate allele fraction ratio in the RNA by the reference allele fractiomalternate allele fraction ratio in the DNA. To avoid division by zero, a pseudocount of 0.001 was added to each allele fraction. A fold-change greater than two was used for the major allele to classify SNVs showing ASE. Of those SNVs, those SNVs showing a fold-change greater than five were further denoted as MAE. This threshold was determined by applying several different fold-change thresholds and finding that the number of MAE genes per patient plateaued in each dataset after five (Figs. 9A-9B). To obtain gene level estimates, the SNV with the greatest RNAseq coverage in the gene was used.

[0209] MDAPCA2B cell culture, androgen treatment, and ChlP-seq

[0210] MDA PCa 2b cells (ATCC CRL-2422) were cultured in BRFF-HPC-1 media (Athena #0403). MDA PCa 2b were seeded at 4 million cells in a 15 cm dish per immunoprecipitation. Cells were hormone deprived for 3 days in BRFF-HPC-1 media with 10% charcoal-stripped serum before treatment for 16 hours with either 1 % ethanol (control) or 10nM of methyltrienolone (R1881 ) dissolved in ethanol. Cells were harvested in suspension and prepared for ChlP-seq according to the SimpleChIP® Enzymatic Chromatin IP Kit (Cell Signaling Technology #9003). 0.75ul of micrococcal nuclease and 5 sonication cycles of 125W, 20khz, and 20s intervals were used to digest chromatin. AR, H3K27ac, and IgG ChIP was performed in paired R1881 -treated and ethanol-treated samples. ChlPs were run in duplicate. 4ug AR (sc-816), 5ug H3K27ac (Active Motif 39133), and 1 ug Rabbit IgG (Cell Signaling Technology #2729) were used as ChIP antibodies. 20ng samples were submitted to Novogene for DNA library preparation with Illumina PE150 NovaSeq 6000.

[0211] ChlP-seq analysis

[0212] Fastq alignment, QC, and peak-calling were performed using the nf-core Nextflow pipeline for ChlP-seq data29. Differential peak calling was performed using DESeq230. ChlP- seq tracks and peaks were visualized using SparK (v2.6.2)31 ,32.

[0213] Enrichment analysis

[0214] To test for enrichment of ASE and MAE genes between two groups of samples, we used a two-sided Fisher’s exact test. We tested each gene that was ASE or MAE in at least one sample and had testable SNVs in both groups. We used the Benjamini-Hochberg procedure with an FDR of 5% to adjust p-values for multiple hypothesis testing. Genes with p-adj < 0.05 and a log2(Odds Ratio) > 1 or < -1 were considered significantly enriched. Gene ontology and enrichment analysis were performed using the clusterProfiler package in R33. The HALLMARK gene set was obtained from MSigDB.

[0215] Candidate ASE gene prioritization

[0216] Several criteria were developed to identify candidate ASE genes driving tumorigenesis and metastasis in PCa (Fig. 7). First, genes were prioritized that were significantly enriched for ASE in tumors compared to normal prostate. Furthermore, genes were identified showing significant differences in expression between samples showing ASE and BAE. Genes for which stratifying tumors by ASE status or expression level showed a significant difference in patient prognosis were prioritized by the log-rank test. To nominate disease-relevant genes, genes enriched for ASE in known molecular subtypes and subgroups of patients were identified. These subgroups included patients with mutations in SPOP, FOXA1 , and PTEN, TMPRSS2-ERG fusions, AA patients, patients with differing Gleason grades, and biopsy location in mCRPC patients. ASE gene signatures and signature score

[0217] To select for genes dysregulated by cis-acting genetic variation, the first requirement was that genes must show recurrent MAE in >5% of tumors and not contain concurrent CNV in >10%. Known imprinted genes from the Geneimprint database were also removed. For the PCa signature, it was required that genes must be significantly enriched for MAE in both localized tumors and mCRPC compared to the GTEx normal prostates via Fisher’s exact test. The localized signature contains genes enriched for MAE in localized tumors compared to GTEx normal prostates. The mCRPC signature contains genes enriched for MAE in mCRPC compared to localized tumors.

[0218] WGBS processing and allele specific methylation calling

[0219] WGBS of mCRPC biopsies was performed by the WCDT SU2C project, as described previously. DMNTools was used to convert WGBS bam files into epiread format. Genes with allelic expression data for each patient were split into the gene body region and 2kb upstream of the TSS. These regions were tested for allele specific methylation (ASM) using DNMtools amrtester, which fits reads containing CpGs to single-allele and two-allele models and outputs a p-value for ASM.

[0220] Example 2 - Identification of ASE Across Prostate Cancer Stages

[0221] In order to determine the role of ASE in PCa tumorigenesis and metastasis, the landscape of ASE was characterized in normal prostate, localized tumors, and mCRPC. DNA sequencing and RNA sequencing data from 495 tumor samples and 43 matched normal samples were obtained from The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA PRAD) dataset and 98 mCRPC biopsies from the West Coast Prostate Cancer Dream Team / Stand Up to Cancer (WCDT / SU2C) study. ASE calls from 221 normal prostate samples from the GTEx consortium were utilized as an additional comparison dataset. Briefly, ASE was estimated by obtaining RNA read counts at heterozygous SNVs within genes and testing for a significant difference in allele frequency in the RNA reads compared to the DNA reads (Methods, Fig. 7). SNVs with RNA allele counts significantly imbalanced by binomial test (FDR 5%) and displaying an allele fold-change of at least 2-fold were classified as showing ASE. Since ASE exists on a continuum of slight imbalance to monoallelic expression (MAE), an additional fold-change criteria of at least 5-fold was applied to identify SNVs showing MAE (Fig. 1 A).

[0222] Across tumors, a total of 2.4 million heterozygous SNVs in localized and more than 468,000 SNVs in mCRPC passed QC and had sufficient expression to be tested for ASE (Methods, Fig. 8B). On the gene level, a total of 15,474 genes in localized and 17,805 genes in mCRPC contained a testable SNV. We observed that the majority of genes tested can demonstrate ASE in at least one tumor, but only a fraction of genes recurrently show ASE in 10% or more samples (Fig. 10). This suggests that most genes showing imbalance are specific to each prostate tumor. A median of 7.9% of genes per tumor showed ASE in localized disease compared to a median of 13% per tumor in mCRPC (Fig. 1 B, Fig 1 1 ). The frequency of MAE was markedly increased in mCRPC compared to localized tumors (Mann-Whitney U p=2.517e-49). Furthermore, the range of MAE frequency amongst tumors was wide, suggesting a heterogeneous landscape of allelic imbalance.

[0223] To investigate the increase in MAE in mCRPC, it was asked whether the frequency of ASE in a tumor was correlated with any known molecular features. Advanced PCa has previously been associated with higher tumor mutational burden (TMB), copy number burden, and structural variant burden. An expected correlation between the number of tested SNVs and ASE genes detected per patient was observed. Non-synonymous TMB was positively correlated with the number of genes showing ASE and MAE (Spearman rho = 0.11 and 0.19, Figs. 12A-12D). Fraction of genome altered (FGA), the percentage of the genome that has been affected by copy number gains or losses, showed a positive correlation with the number of genes showing MAE specifically (Spearman rho = 0.19). In mCRPC, the proportion of ASE or MAE per sample was not significantly correlated with mutation count, sequencing depth, chromothripsis, or chromoplexy within the dataset. Notably, patients with liver biopsies showed an increased frequency of ASE compared to all other biopsy sites in the dataset. Previous studies report that mCRPC patients with liver metastases have shorter median overall survival and show higher FGA compared to other sites. This suggests that an increased burden of mutations and copy number changes is associated with increased MAE events in PCa.

[0224] Across samples, we observed ASE of genes that are known to be imprinted in prostate tissue and genes that are associated with prostate c / s-eQTLs. Among genes showing the most recurrent ASE across the cohort was the maternally imprinted gene necdin (NDN), showing ASE in 152 of 153 tumors with allelic expression data (Figs. 13A-13B). Additionally, roughly a quarter of genes in both the localized and mCRPC datasets that showed ASE in at least one sample were identified as significant c / s-eQTL genes in GTEx normal prostate tissue. c / s-eQTL genes showed significantly higher frequency of ASE compared to genes that were not detected as cis- eQTLs (Mann-Whitney U p = 9.4e-11 , Figs. 14A-14B). Prostate stem cell antigen (PSCA), a known prostate-specific eQTL gene, showed highly recurrent ASE in normal, localized, and mCRPC.

[0225] To account for copy number variation (CNV) being a major source of ASE / MAE in cancers, SNVs showing evidence of large-scale deletions or amplifications were flagged and excluded them from analysis (Methods). Additionally, genes showing ASE that concurrently showed CNV in the same sample were identified. A median of 4% of genes showing MAE in localized tumors and 2.3% in mCRPC had a deep deletion or strong amplification (Figs. 15A- 15C). Amplifications in 8q as well as deletions in 6q and 13q are frequently observed in PCa, resulting in altered expression of oncogenes and tumor suppressors. Indeed, the most recurrent genes showing MAE and CNV were located on chromosome 8, 6, and 13. Among these recurrent genes, MAE of SLC25A37, PEBP4, CHRNA2 likely resulted from deletion of chr8p, PSCA from amplification of chr8q, and C0G3 and CAB39L from deletion of chr13q. Furthermore, available allele-specific copy number data was used in the localized dataset and found that 7% of ASE events were co-occurring with a hemizygous deletion, or loss of one allele, in the same gene (Fig. 15D). The fraction was higher among MAE events only (10%). In summary, genes undergoing ASE that concurrently show CNV were captured, particularly in major CNV hotspots in PCa. The most common pattern was a hemizygous deletion of one allele. However, the majority of genes undergoing ASE included in our analysis do not show strong CNV, enriching for events that may be caused by alternate c / s-regulatory mechanisms.

[0226] It was next asked whether genes showing ASE were shared across datasets. Given that most genes showing ASE in tumors were patient-specific, the most recurrent genes (>5%) were focused on and those that were testable for ASE in at least 10% of each dataset. It was found that most genes recurrently undergoing ASE in normal prostates were also recurrent in tumors, but more than 2300 genes were recurrent for ASE in tumors only with the majority being unique to mCRPC (Fig. 1 C-D). Among the most recurrent genes, known drivers of PCa we identified, including TMPRSS2, as well as multiple novel genes previously unassociated with PCa tumorigenesis. Overall, a distinct set of genes recurrently undergoing ASE in tumors as well as stage-specific genes were identify.

[0227] The frequency of ASE for all testable genes in the localized TCGA samples that were also testable in the GTEx normal prostates were compared. In total, 1055 genes recurrently showing ASE in the tumors were significantly enriched for ASE by Fisher’s exact test (Fig. 1 E). Gene ontology analysis of these genes showed enrichment of multiple metabolic processes including fatty acid and carboxylic acid metabolism. Enrichment analysis using HALLMARK gene sets showed enrichment in EMT transition, androgen response, and cholesterol homeostasis. Among these tumor enriched genes, several genes that have been previously implicated in human cancers were identified. The top gene was CYB561 , where 122 of 125 assessable tumors showed ASE compared to 0 of 136 normal samples. 109 of the 122 tumors showed MAE. Increased expression of CYB561 has been associated with lower survival in breast cancer and associated with metastatic and neuroendocrine PCa. Overall, the landscape of allelic imbalance in localized PCa is characterized by dysregulation of several cancer-driving pathways including altered metabolism and hormone signaling.

[0228] Example 3 - ASE is associated with changes in overall gene expression in oncogenes and tumor suppressors

[0229] Allelic imbalance can alter the overall expression level of tumor suppressors and oncogenes, leading to tumorigenesis. It was sought to identify genes that show evidence of this mechanism in localized PCa. First, whether samples showing ASE for a given gene had a difference in overall expression level compared to samples showing BAE were tested. Of the 11 ,601 genes showing ASE in at least one sample, 2% (189) showed significant differences in expression between ASE and BAE samples (Mann-Whitney U, FDR 5%). ASE was associated with both increased and decreased expression, with the majority showing an increase in ASE samples (Figure 2B). Next, whether these significant genes were also differentially expressed in tumors compared to matched normal tissue were determined. Thirty-two of the significant genes were also DEGs, 21 of which were upregulated in tumors overall and 1 1 were downregulated. (Fig. 2C). This finding indicates that in a subset of ASE genes, ASE is associated with changes to overall expression, and concurrently, differential expression in tumors compared to normal tissue. This suggests that ASE drives activation or repression of these genes in tumors.

[0230] Among these genes, androgen-regulated TMPRSS2 and ETS transcription factors ERG and ETV1 were identified and which are fused together in roughly half of localized prostate tumors and drive prostate tumorigenesis. TMPRSS2-ERG fusion may cause ASE of TMPRSS2 and / or ERG if the fusion occurs on one allele. Of 195 tumors with TMPRSS2-ERG fusions, -50% had allelic expression data for either TMPRSS2 or ERG (Fig. 16A). Roughly 80% of tumors with a heterozygous SNV in TMPRSS2 showed TMPRSS2 ASE, and similarly for ERG (Fig. 16B). Twenty-one tumors had SNVs in both genes, 7 of which showed ASE in both genes. In patients showing MAE for ERG and ETV1 significantly increased expression of those genes were observed, as compared to patients with biallelic expression (Fig. 2D).

[0231] Acyl-CoA Synthetase Medium Chain Family Member 1 (ACSM1 ) showed highly recurrent ASE in localized tumors (188 / 259 vs 8 / 100 in GTEx normal), where the majority of samples showing ASE showed MAE (107 / 188). ACSM1 shows significantly increased expression in samples showing ASE and is upregulated in tumors (Fig. 2D). ACSM1 also showed recurrent ASE in mCRPC (17 / 33). Expression of ACSM1 has been shown to be upregulated in PCa tumors and associated with worse prognosis. Previous studies suggest that ACSM1 is regulated by the androgen receptor (AR) and may contribute to tumorigenesis via metabolic and the extracellular matrix signaling pathways. Only one sample concurrently showed ASE and strong amplification of ACSM1 , suggesting that the majority of the ASE occurs through mechanisms other than CNV. No statistically significant differences in Gleason score, overall survival or progression-free survival between MAE and BAE patients for ACSM1 (Fisher’s exact p=0.75, log rank p=0.32, 0.92) was observed. ACSM1 was testable for ASE in 23 out of 43 matched tumor normal pairs. Interestingly, ACSM1 MAE is not restricted to the tumor, with 7 patients showing MAE in both normal and tumor. Increased expression in the tumor is observed regardless of the status of the matched normal and tumor. This suggests that ACSM1 ASE may be a feature of diseased prostate, including surrounding normal tissue.

[0232] Given evidence that ACSM1 is AR-regulated and contains allele-specific binding sites for AR, it was hypothesized that differences in chromatin conformation near ACSM1 may be detectable in the setting of androgen deprivation compared to androgen treatment that could allow access to these AR binding sites. To test this, cell line whole exome sequencing and RNA sequencing data from the Cancer Cell Line Encyclopedia (CCLE) were utilized. Of the 6 PCa cell lines in CCLE, only MDAPCA2B cells showed MAE for ACSM1 . As there is no ChlP-seq data for MDAPCA2B, ChlP-seq for H3K27ac was performed in the setting of androgen deprivation and androgen treatment (Methods, Figs. 17A-17B). Differential peaks and unique peaks between the conditions were identified. Among 5320 peaks unique to androgen-treated cells, a peak directly upstream of the TSS of ACSM1 and in the promoter of neighboring gene ACSM3 was identified (Fig. 2E). This supports prior evidence that ACSM1 is regulated by androgen signaling and suggests that MAE of ACSM1 may arise via altered chromatin conformation.

[0233] Example 4 - TMPRSS2, ERG, and ERG-associated genes recurrently undergo ASE in tumors with TMPRSS2-ERG fusion

[0234] Next, it was asked whether different molecular subtypes of PCa showed unique ASE profiles. First, it was hypothesized that the TMPRSS2-ERG fusion may drive ASE due to the overexpression of the ERG transcription factor. The frequency of ASE and MAE was compared for each gene with testable SNVs in TMPRSS2-ERG fusion positive and fusion negative patients using Fisher’s exact test (Fig. 3A). As expected, a significantly increased frequency of ASE for both TMPRSS2 and ERG in fusion positive patients was identified, increased frequency of MAE for G protein-coupled receptor 1 16 (GPR1 16) and major histocompatibility complex class II, DM beta (HLA-DMB, data not shown) were also identified. Previous studies have shown that GPR116 is overexpressed in ERG+ tissue. HLA-DMB is co-expressed with ERG and an ERG target gene. It was observed that both genes were expressed significantly higher in samples showing ASE for these genes compared to those showing BAE (Fig. 3C). This finding indicates that fusion positive patients show both dysregulated expression of ERG and of ERG associated genes.

[0235] Additionally, enrichment of ASE in tumors with PTEN deletions (Fig. 18D) was tested. Nore frequent ASE of TMPRSS2, GPR116, and AZGP1 was identified in PTEN deleted tumors. Given that 61 of the 95 PTEN deleted samples also harbored TMPRSS-ERG fusions, ASE of TMPRSS2 and GPR116 was not surprising. Enrichment of ASE in tumors harboring somatic mutations in SPOP, FOXA1 , and in tumors with high Gleason scores (Figs. 18B-18D) were also tested. However, no significant hits were observed.

[0236] Example 5 - AA patients show recurrent MAE of genes implicated in castration resistance, aggressive disease, and poor survival

[0237] AA men have twice the mortality rate of PCa compared to EA men. However, the role of gene dysregulation in promoting worse outcomes in AA men is unclear. Ancestry-specific ASE sites in AA individuals have been identified previously compared to EA individuals. To investigate whether tumor ASE is associated with this disparity, an unbiased comparison of the frequency of ASE and MAE events was performed between 60 AA patients and 408 EA patients in the localized cohort. A Fisher’s exact test was performed for each gene showing ASE or MAE in at least 1 sample to determine if any were enriched for imbalance in either group. It was identified that ALDH3B2, POM121 C, NUDT8, and RPS20 more frequently undergo MAE in AA samples while MAE of C1 orf56 and MRPL55 was more frequent in EA samples (Fig. 3B). None of these genes were previously identified as population-based eQTLs in GTEx normal prostate. After adjusting for age and Gleason score, it was seen that race remained a significant predictor for MAE in ALDH3B2, NUDT8, RPS20, and C1 orf56.

[0238] Next several criteria were assessed to determine whether any of these genes could be considered candidate drivers that are functionally related to prognosis. Aldehyde dehydrogenases have previously been associated with the growth of cancer stem cells. ALDH3B2 showed lower expression in tumors showing MAE compared to BAE (Fig. 3C). Stratifying samples by those showing MAE or BAE did not result in a significant difference in survival or progression free survival. However, using the entire TCGA dataset, patients with median or lower expression of ALDH3B2 had a lower progression-free survival rate than patients with above median expression (Fig. 3D). Of 6 available cell lines, MAE of ALDH3B2 in MDAPCA2B, a PCa cell line derived from a 63 year old AA male with metastatic and androgenindependent disease, was identified. These findings suggest that differences in ASE exist between racial / ethnic groups, and ASE may be one mechanism that alters expression of prognostic genes in AA men.

[0239] Example 6 - Mutant TP53 allele is preferentially expressed in localized PCa

[0240] It was hypothesized that preference for a certain allele in tumors may serve as a mechanism to enhance survival and proliferation. Identifying instances where ASE was biased toward a somatic allele were prioritized. In total, 101 1 somatic SNVs showed ASE across the localized tumors. Fifty-five percent of these mutations showed a bias towards the reference allele, while 44% showed a bias toward the alternate allele. Twelve tumors were identified with a somatic mutation in TP53 and showed ASE of TP53. Eleven out of 12 showed biased RNA expression toward the alternate allele (Figs. 19A-19B). Recurrent ASE of TP53 has also been observed in colorectal and breast cancers 21 ,54 . It is possible that preferential expression of the mutated TP53 allele results in a selective advantage for the cancer cell.

[0241] Example 7 - Comparison of tumors and normal tissue reveals tumor-specific ASE genes

[0242] To distinguish tumor-associated ASE with ASE present in normal tissue, first ASE in 43 available matched normal samples from the localized cohort were assessed. In order to properly identify any difference in allelic expression status in the matched normal and tumor, the same heterozygous SNV in both samples were tested. In total, 12,337 genes were able to be tested which contained a heterozygous SNV and had allele expression data in either the tumor or normal. A median of 3508 genes could be assessed for ASE per pair. The proportion of genes showing ASE and MAE was higher in the matched tumors (median 7.9%, 1 .8%) compared to the normals (median 6.7%, 1.4%) overall (Fig. 20A). This is consistent with findings from a previous study of ASE in matched tumors and normal tissues from TCGA breast invasive carcinoma, head and neck squamous cell carcinoma, lung adenocarcinoma, and thyroid carcinoma.

[0243] Next the allelic expression status in the normal and tumor for each gene was identified. It was found that in each pair, most genes showed BAE in both the normal and tumor (Fig. 4A). Genes turned off and turned on biallelically were the next most common (median 8.3% and 6.7% respectively). Interestingly, the next most common changes were BAE to ASE and ASE to BAE (median 5% and 4.2% respectively). Amongst the genes undergoing ASE in the tumors, most were unique to the tumor (median 81 %, Fig. 20B). The same finding was observed in the normals (median 80%). This suggests the landscape of allelic imbalance in tumors is distinct from adjacent normal tissue, and that during tumorigenesis alleles are commonly activated and repressed.

[0244] From this data, the genes showing allele activation or repression in the tumors were prioritized. One hundred eighty-four 184 genes that showed recurrent BAE in normals and ASE in tumors (Fig. 4B) were identified. Gene set enrichment analysis using the MSigDB C2_CGP geneset showed enrichment of MYC target, prostate development, and 4EBP1 / 4EBP2 target genesets (Fig. 4C). It was confirmed that 88% of these genes were significantly enriched for ASE in the larger cohort of localized tumors compared to the GTEx normal prostates. Next, instances of monoallelic activation of genes, or genes recurrently showing no expression in normal and ASE in tumors were explored (Fig. 4D). Dynein axonemal heavy chain 8 (DNAH8) showed no expression in normal and ASE in tumor for 9 of 24 matched normal-tumor pairs with a testable SNV, with the majority showing no expression to MAE (Fig. 4E). It was hypothesized that DNAH8 is activated in tumors via MAE. In the larger TCGA cohort, 1 16 of 258 localized PCa samples tested showed MAE for DNAH8. This was significantly more frequent compared to 3 of 24 tested normal prostates from GTEx (Fisher’s exact test OR = 5.71 , p-adj = 0.038). In the localized cohort, low expression of DNAH8 was also associated with worse progression-free survival (Fig. 4F). DNAH8 has previously been identified as an AR target gene associated with PCa progression.

[0245] Example 8 - mCRPC shows enrichment of ASE in oncogenes and developmental pathway genes

[0246] To investigate the role of ASE in the transition from localized to metastatic disease, it was tested whether any genes were significantly enriched for ASE or MAE in each stage (data not shown). Eight hundred ninety-six genes were identified in mCRPC that were enriched for ASE (Fig. 5B). GO analysis showed significant enrichment developmental pathways and Wnt- signaling, which are implicated in more aggressive disease with metastatic potential (Fig. 5C). Furthermore, enrichment of known PCa pathways, oncogenes, and tumor suppressors amongst genes showing recurrent ASE in both localized tumors and mCRPC were tested. Interestingly, a unique enrichment of fatty acid metabolism genes was identified within the localized genes and oncogenes in the mCRPC genes (Fig. 5D). This suggests that oncogenes may be activated via ASE to facilitate the transition from a more indolent, localized form of PCa to a more aggressive and metastatic form. Example 9 - mCRPC MAE signature score identifies a subset of localized PCa patients with shorter progression-free survival

[0247] To nominate strongly imbalanced genes that are hallmarks of PCa, both a PCa-wide and an mCRPC-specific MAE gene signature were developed using several criteria (data not shown, Methods). In total, a 35 gene PCa signature and 428 gene mCRPC signature was identified that met the inclusion criteria. Among the mCRPC signature genes was mitochondrial Tumor suppressor 1 1 (MTUS1 ), a tumor suppressor which showed MAE in 16 of 46 mCRPC tumors compared to 5 of 324 in localized tumors. Radiation sensitive 52 (RAD52), involved in homologous DNA recombination, showed MAE in 22 of 51 mCRPC tumors. Altered expression of RAD52 has been implicated in tumor progression and resistance in prostate and several other cancers, yet the transcriptional regulation of this gene is poorly understood.

[0248] It was hypothesized that scoring tumors by this signature could measure the tumor’s propensity for metastasis and aggressive disease based on gene dysregulation. An MAE score was developed which represents the proportion of the signature showing MAE in the tumor, normalizing for the number of genes in the signature with testable SNVs. This scoring system was applied to the localized TCGA tumors and found that tumors with greater than median scores showed shorter progression-free survival (Fig. 5E). MAE score was also higher amongst tumors with higher Gleason scores (Mann-Whitney U test, p=2.4e-7, Figs. 21A-21 C). These high-scoring tumors had higher frequencies of MAE for SLC25A37, EPHX2, TMPRSS2, HLA-DRB6, and BANK1 among other genes. Ultimately, these findings show that we can define a molecular subtype of tumors with worse prognosis based on dysregulated genes in advanced PCa.

[0249] Example 10 - Genes undergoing MAE are enriched for allele-specific methylation in mCRPC

[0250] Changes to DNA methylation are widespread in PCa. It was hypothesized that allelespecific methylation (ASM), which is increased in cancers, is one mechanism that causes ASE of cancer genes in mCRPC59. To identify ASM, methylated CpGs were first identified using whole genome bisulfite sequencing. DNMTools was used to compute p-value scores for ASM in promoters and gene body regions across the genome (Materials and methods). As a control, we first tested for ASM in the gene body of known imprinted genes. Of 97 imprinted genes that were tested in the dataset, 90% showed evidence of ASM. These genes showed high frequency of ASM within the dataset (Fig. 22). Across the genome, ASM was prevalent, with a median of 34% of promoters and 42% of gene body regions showing ASM per sample. I was then tested whether genes showing ASE were enriched for ASM and found that promoter (Fisher’s exact OR = 1 .48, p = 3.69e-293) and gene body (Fisher’s exact OR = 1 .29, p = 1 ,74e-1 10) ASM were enriched in samples showing ASE compared to BAE. The association was stronger for genes showing MAE (promoter OR = 1 .33, p = 9.21 e-89 and gene body OR = 1 .56, p = 1 .06e-237).

[0251] Next an association between MAE and ASM was tested for on an individual gene level among genes that showed recurrent MAE in mCRPC. Of 722 genes that showed MAE in greater than 5 tumors, 7 genes showed a significant association (Mann-Whitney U FDR 15%, Fig 23). Tumors with MAE of NUDT12 showed increased levels of ASM in the gene body (Fig 5F). The NUDT (nudix hydroxylase) family of enzymes has been previously linked to breast cancer progression. Integration of ASE and ASM data at the same gene provides a potential mechanism for gene dysregulation.

[0252] Example 11 - Somatic non-coding mutations lie in mutational hotspots near genes undergoing ASE in mCRPC

[0253] A recent preprint used the WCDT / SU2C WGS data to identify somatic mutational hotspots in mCRPC61 . For a subset of these hotspot regions, the flanking genes showed differential expression in samples harboring mutations in the regions. It was hypothesized that mutations in these regions, which were termed candidate driver regulatory regions (CDRRs), could potentially cause ASE of flanking genes. These CDRRs were used to nominate candidate non-coding mutations linked to ASE. Somatic mutations were identified that were both located in one of the 98 CDRRs and occurred in tumors showing ASE for these genes. There were 332 mutations that were located in CDRRs, 38 of which the CDRRs had testable SNVs in the flanking genes. Six mutations within CDRRs near TNFSFI O, HNRNPF, ZNF544, ZNF512B, and ADNP co-occurred with ASE (data not shown). Interestingly, only 2 tumors showed MAE for ADNP and both harbored non-coding mutations in that CDRR. ASE of ADNP was found at a frequency of 2% in localized tumors compared to 12% of mCRPC tumors. A SNP in ADNP or activity-dependent neuroprotective protein was previously identified as a PCa susceptibility locus through GWAS62. As demonstrated, ASE analysis can prioritize rare non-coding variants that may contribute to tumorigenesis.

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[0319] Example 12 - Allele-specific expression analysis identifies novel dvsrequlated genes in prostate tumors in African-American men

[0320] Background and Methods: African-American (AA) men are twice as likely to die from prostate cancer (PCa) than European-American (EA) men. In PCa, AA men show fewer ERG rearrangements (27.6% AA, 42.5% EA) and PTEN deletions (6.9% AA, 19.8% EA) which are known drivers of PCa. Tumor cis-regulatory alterations can disturb gene regulation and drive tumorigenesis, but these effects have not been fully explored in the context of PCa disparities. Allele specific expression (ASE) analysis identifies genes showing imbalanced expression of alleles, often due to altered gene regulation on one allele. ASE has been identified as a driver mechanism in cancer. It is hypothesized that ASE analysis can identify novel dysregulated genes involved in PCa disparities (FIG. 6A). A schematic of the analysis pipeline is depicted in FIG. 6B.

[0321] Results are shown in FIGs. 6C-6K and indicate that ASE occurs more frequently in prostate tumors and affects genes in prostate cancer pathways such as androgen response and epithelial to mesenchymal transition. Novel genes that are enriched for MAE in tumors from AA men are identified, some which have been previously implicated in castration resistance, aggressive disease, and poor survival. Tumors showing MAE of ALDH3B2 show lower overall expression, which is associated with worse progression-free survival.

[0322] Accordingly, the preceding merely illustrates the principles of the present disclosure. It will be appreciated that those skilled in the art will be able to devise various arrangements which, although not explicitly described or shown herein, embody the principles of the invention and are included within its spirit and scope. Furthermore, all examples and conditional language recited herein are principally intended to aid the reader in understanding the principles of the invention and the concepts contributed by the inventors to furthering the art, and are to be construed as being without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, and embodiments of the invention as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents and equivalents developed in the future, i.e., any elements developed that perform the same function, regardless of structure. The scope of the present invention, therefore, is not intended to be limited to the exemplary embodiments shown and described herein.

[0323] Table 1 : Top 15 genes in mCRPC MAE signature

Claims

WHAT IS CLAIMED IS:1 . A method for identifying an allele specific expression (ASE) signature in a disease, the method comprising: obtaining genomic sequence data and expression data from a collection of tissue, wherein the collection of tissue includes normal tissue and abnormal tissue, wherein the abnormal tissue is associated with the disease; and identifying a gene exhibiting ASE that is indicative of the disease using the genomic sequence data and expression data, wherein the gene is heterozygous and its alleles are differentially expressed in either healthy tissue or unhealthy tissue.

2. The method of claim 1 , wherein the genomic sequence data includes one or more of whole genome sequencing (WGS) data and whole exome sequencing (WES) data, and wherein the expression data includes one or more of RNA sequencing (RNASeq) data and microarray data.

3. The method of claim 1 or 2, wherein identifying a gene exhibiting ASE, comprises: identifying the alleles based on a heterozygous single nucleotide variant (SNV) located in an exonic region of the gene using the genomic sequence data; and determining expression of the alleles based on the expression data; wherein ASE is indicated by one allele being expressed at a greater rate than the other allele.

4. The method of claim 3, wherein ASE is indicated by one allele being expressed at a rate of at least 2x as compared to the other allele or when only one allele is expressed.

5. The method of claim 3 or 4, wherein each SNV is present in at least eight sequencing reads in the genomic sequence data.

6. The method of any one of claims 3-5, further comprising removing genes exhibiting copy number variation (CNV).

7. The method of claim 6, wherein CNV is identified based on one allele being overrepresented in the genomic sequencing data.

8. The method of claim 7, wherein CNV is identified based on one allele being represented at a rate of greater than 0.75 or less than 0.25 in the genomic sequencing data.

9. The method of any one of claims 18, wherein the genomic sequence data includes one or more of whole genome sequencing (WGS) data and whole exome sequencing (WES) data, and wherein the expression data includes one or more of RNA sequencing (RNASeq) data and microarray data.

10. The method of any one of claims 1 -9, wherein the disease is selected from a cancer, an infectious disease, a deficiency disease, a hereditary disease, and a physiological disease.11 . The method of any one of claims 1 -10, wherein the abnormal tissue includes tissue from more than one type, stage, score, histology, severity, or prognosis.

12. The method of any one of claims 1 -9, wherein the disease is a cancer.

13. The method of claim 12, wherein the cancer is selected from prostate cancer, breast cancer, pancreatic cancer, skin cancer, colorectal cancer, testicular cancer, lung cancer, esophageal cancer, uterine cancer, ovarian cancer, lymphoma, liver cancer, renal cancer, oral cancer, brain cancer, thyroid cancer, urogenital cancer, including individual varieties, subtypes, and stages thereof.

14. The method of claim 12 or 13, wherein the abnormal tissue includes tissue from localized cancer and metastatic cancer.

15. The method of claim 12 or 13, wherein the abnormal tissue includes resistant tumors and non-resistant tumors.

16. The method of claim 12, wherein the cancer is prostate cancer and the abnormal tissue includes localized prostate cancer and metastatic castration-resistant prostate cancer.

17. The method of any one of claims 1 -16, further comprising validating the gene exhibiting ASE.

18. The method of claim 17, wherein validating the gene exhibiting ASE comprises determining a receiver operating characteristic.

19. A method for treating a disease in a subject in need thereof, the method comprising:altering expression of or targeting the product of a gene exhibiting allele specific expression (ASE) in the disease, wherein the ASE was identified by the method of any one of claims 1 -17.

20. The method of claim 19, further comprising performing the method of any one of claims 1-18.21 . The method of claim 19 or 20, wherein altering expression of a gene exhibiting ASE comprises equalizing expression between the alleles associated with the gene exhibiting ASE.

22. The method of claim 19 or 20, wherein altering expression of the gene exhibiting ASE comprises increasing expression of one allele associated with the gene exhibiting ASE.

23. The method of claim 19 or 20, wherein altering expression of the gene exhibiting ASE comprises reducing expression of one allele associated with the gene exhibiting ASE.

24. The method of any one of claims 21-23, wherein altering expression of the gene exhibiting ASE comprises utilizing a CRISPR system to alter expression of the gene exhibiting ASE.

25. The method of claim 24, wherein the CRISPR system alters a regulatory element of the gene exhibiting ASE.

26. The method of claim 24, wherein the CRISPR system alters a coding region of the gene exhibiting ASE.

27. The method of any one of claims 21-23, wherein altering expression of the gene exhibiting ASE comprises utilizing RNA interference to alter expression of the gene exhibiting ASE.

28. The method of claim 19 or 20, wherein targeting the product of a gene exhibiting ASE comprises providing a therapeutic agent to the subject.

29. The method of claim 28, wherein the therapeutic agent is selected from a biologic molecule and a small molecule.

30. The method of claim 29, wherein the biologic molecule is selected from an antibody, a trap, a hormone, a protein, an enzyme, a nucleic acid, a cell.31 . The method of claim 29, wherein the small molecule is selected from an antibiotic, an antiviral, a chemotherapeutic agent, a radioactive nuclide, an allosteric enzyme inhibitor, and a competitive enzyme inhibitor.

32. The method of any one of claims 19-31 , further comprising resecting tissue that is diseased.

33. A method of identifying a subject as having a disease associated with allele specific expression (ASE) of a gene, the method comprising: assessing a sample from the subject for ASE of the gene, wherein the ASE was identified by the method of any one of claims 1-17.

34. The method of claim 31 , further comprising performing the method of any one of claims 1-18.

35. The method of claim 33 or 34, wherein the sample is obtained from one or more of a blood sample, liquid biopsy, a tumor biopsy, and a biopsy of a tissue suspected of being cancerous, a buccal swab, a skin swab, a skin scraping, a throat swab, a nasal swab, and a urine sample.

36. The method of any one of claims 19-31 , further comprising providing a therapy to the subject.

37. The method of claim 36, wherein the therapy comprises altering expression of or targeting the product of a gene exhibiting allele specific expression (ASE) in the disease.

38. The method of claim 37, wherein altering expression of a gene exhibiting ASE comprises equalizing expression between the alleles associated with the gene exhibiting ASE.

39. The method of claim 37, wherein altering expression of the gene exhibiting ASE comprises increasing expression of one allele associated with the gene exhibiting ASE.

40. The method of claim 37, wherein altering expression of the gene exhibiting ASE comprises reducing expression of one allele associated with the gene exhibiting ASE.41 . The method of any one of claims 37-40, wherein altering expression of the gene exhibiting ASE comprises utilizing a CRISPR system to alter expression of the gene exhibiting ASE.

42. The method of claim 41 , wherein the CRISPR system alters a regulatory element of the gene exhibiting ASE.

43. The method of claim 41 , wherein the CRISPR system alters a coding region of the gene exhibiting ASE.

44. The method of any one of claims 37-40, wherein altering expression of the gene exhibiting ASE comprises utilizing RNA interference to alter expression of the gene exhibiting ASE.

45. The method of claim 37, wherein targeting the product of a gene exhibiting ASE comprises providing a therapeutic agent to the subject.

46. The method of claim 45, wherein the therapeutic agent is selected from a biologic molecule and a small molecule.

47. The method of claim 46, wherein the biologic molecule is selected from an antibody, a trap, a hormone, a protein, an enzyme, a nucleic acid, a cell.

48. The method of claim 46, wherein the small molecule is selected from an antibiotic, an antiviral, a chemotherapeutic agent, a radioactive nuclide, an allosteric enzyme inhibitor, and a competitive enzyme inhibitor.

49. The method of any one of claims 35-48, further comprising resecting tissue that is diseased.

50. A method of treating prostate cancer, the method comprising: altering expression of or targeting the product of one or more genes selected from ACSM1 , ALDH3B2, DNAH8, MTUS1 , RAD52, SLC25A37, EPHX2, TMPRSS2, HLA-DRB6, BANK1 , NKX3-1 , SLC7A2, TMBIM4, NQO2, ABAT, HCP5, NCAM2, ZNF717, DOCK1 , FARP1 , and FDFT1.51 . The method of claim 50, wherein the one or more genes are selected from ACSM1 , ALDH3B2, DNAH8, MTUS1 , RAD52, SLC25A37, EPHX2, TMPRSS2, HLA-DRB6, and BANK1 .

52. The method of claim 50 or 51 , wherein the prostate cancer is selected from localized prostate cancer, metastatic castration resistant prostate cancer (mCRPC), and metastatic hormone-sensitive prostate cancer (mHSPC).

53. The method of any one of claims 50-52, wherein altering expression of the one or more genes comprises equalizing expression between the alleles associated with the one or more genes.

54. The method of any one of claims 50-52, wherein altering expression of the one or more genes comprises increasing expression of one allele associated with the one or more genes.

55. The method of any one of claims 50-52, wherein altering expression of the one or more genes comprises reducing expression of one allele associated with the one or more genes.

56. The method of any one of claims 53-55, wherein altering expression of the one or more genes comprises utilizing a CRISPR system to alter expression of the one or more genes.

57. The method of claim 56, wherein the CRISPR system alters a regulatory element of the one or more genes.

58. The method of claim 56, wherein the CRISPR system alters a coding region of the one or more genes.

59. The method of any one of claims 50-52, wherein altering expression of the one or more genes comprises utilizing RNA interference to alter expression of the one or more genes.

60. The method of any one of claims 53-55, wherein targeting the product of a one or more genes comprises providing a therapeutic agent to the subject.61 . The method of claim 60, wherein the therapeutic agent is selected from a biologic molecule and a small molecule.

62. The method of claim 61 , wherein the biologic molecule is selected from an antibody, a trap, a hormone, a protein, an enzyme, a nucleic acid, a cell.

63. The method of claim 61 , wherein the small molecule is selected from an antibiotic, an antiviral, a chemotherapeutic agent, a radioactive nuclide, an allosteric enzyme inhibitor, and a competitive enzyme inhibitor.

64. The method of any one of claims 50-63, further comprising resecting tissue that is diseased.

65. A method for identifying prostate cancer in a subject, the method comprising: assessing a sample from a subject for allele specific expression (ASE) exhibited in one or more genes selected from: ACSM1 , ALDH3B2, DNAH8, MTUS1 , RAD52, SLC25A37, EPHX2, TMPRSS2, HLA-DRB6, BANK1 , NKX3-1 , SLC7A2, TMBIM4, NQO2, ABAT, HCP5, NCAM2, ZNF717, DOCK1 , FARP1 , and FDFT1.

66. The method of claim 65, wherein the one or more genes are selected from ACSM1 , ALDH3B2, DNAH8, MTUS1 , RAD52, SLC25A37, EPHX2, TMPRSS2, HLA-DRB6, and BANK1 .

67. The method of claim 65 or 66, wherein the subject has or is suspected of having prostate cancer.

68. The method of any one of claims 65-67, wherein the sample is selected from one or more of a liquid biopsy, a tumor biopsy, and a tissues suspected of being cancerous.

69. The method of any one of claims 65-68, wherein assessing the sample for ASE comprises assessing expression levels of alleles associated with the one or more genes.

70. The method of claim 69, wherein assessing expression levels comprises performing RNA sequencing or a microarray assay.

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