WO2016196065A1 - Procédés et compositions pour évaluer la réponse de cancers aux inhibiteurs bet - Google Patents

Procédés et compositions pour évaluer la réponse de cancers aux inhibiteurs bet Download PDF

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WO2016196065A1
WO2016196065A1 PCT/US2016/033826 US2016033826W WO2016196065A1 WO 2016196065 A1 WO2016196065 A1 WO 2016196065A1 US 2016033826 W US2016033826 W US 2016033826W WO 2016196065 A1 WO2016196065 A1 WO 2016196065A1
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cancer
erna
subject
expression level
cells
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PCT/US2016/033826
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Mark L. MCCLELAND
Ron Firestein
Kathryn MESH
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Genentech, Inc.
F. Hoffmann-La Roche Ag
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
    • A61P35/00—Antineoplastic agents

Definitions

  • the present disclosure relates to compositions and methods for assessing responsiveness of cancers to BET inhibitors.
  • Cancer is a leading cause of death and results in over $88 billion dollars in healthcare expenses within the U.S. alone (American Cancer Society. Cancer Facts & Figures 2015. Atlanta, Ga. 2015).
  • Colorectal carcinoma (CRC) is one of the most prevalent and fatal types of cancers accounting for over half a million deaths worldwide annually (Haggar, F.A. & Boushey, R.P. Clin Colon Rectal Surg 22, 191-197 (2009)).
  • Genomic analyses of colorectal tumors have uncovered a number of key somatic and germline mutations that drive tumorigenesis at the molecular level and can be linked to well-defined disease stages of tumor progression (Fearon, E.R.
  • Colorectal tumors can be divided into three main subtypes based on these initiating molecular alterations: 1) chromosomal instability (CIN), 2) CpG island methylator phenotype (CIMP) and 3) microsatellite instability (MSI) (Issa, J.P. Clin Cancer Res 14, 5939-5940 (2008); Ogino, S. & Goel, A.
  • CIN chromosomal instability
  • CIMP CpG island methylator phenotype
  • MSI microsatellite instability
  • CIMP colon cancer pathogenesis
  • DNA methylation and histone modification are reversible processes that can be targeted for therapeutic intervention using small molecule inhibitors of the epigenetic writers (methyltransferases, acetyltransferases, kinases), readers (bromodomain- or chromodomain- containing genes) and erasers (demethylases, deacetylases, phosphatases) (Wee, S., et al. Ann NY Acad Sci 1309, 30-36 (2014); Ahuja, N., Easwaran, H. & Baylin, S.B.
  • Cancer including colorectal cancer
  • chemotherapy including chemotherapy, radiation therapy, and surgery depending on the cancer type, location, and severity.
  • these treatments are expensive and are accompanied by significant adverse effects that negatively impact quality of life.
  • the response rates for treating metastatic colorectal cancer with the drug cetuximab ranges between 8.8% when used alone and 22.9% when used in combination with the drug irinotecan (Cunningham et al. (2004) N Engl J Med. 351:337-45; Saltz et al. (2004) Clin Oncol. 22: 1201-8).
  • Cancer biomarkers can include DNA, mRNA, proteins, metabolites, or processes such as apoptosis or angiogenesis. Cancer biomarkers can be utilized for cancer screening, clinical staging, evaluating treatment responses, and tracking disease progression. However, current biomarkers possess a low diagnostic specificity and sensitivity (Kulasingam et al (2008) Nat. Clin. Pract. Oncol. 5(10):588-599). The lack of biomarkers for treatment responsiveness contributes to unnecessary, ineffective, and potentially harmful treatments. Identifying biomarkers that predict how a patient will respond to therapy will lead to individualized cancer therapies, thereby decreasing healthcare costs, increasing cancer therapy efficacy, and increasing the quality of life of cancer patients. Thus, an unmet need exists for novel methods to predict responses to specific cancer treatments. [0009] All references cited herein, including patent applications and publications, are hereby incorporated by reference in their entirety.
  • the present disclosure provides methods of treating a subject having cancer with a BET inhibitor, methods of selecting a subject for treatment with a BET inhibitor, and methods of modulating the treatment of a subject undergoing BET inhibitor treatment for cancer, where the methods include the step of performing a nucleic acid-based detection assay to detect the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from the subject.
  • the teachings herein demonstrate the surprising result that enhancer-derived non-coding RNA can serve as a predictive biomarker and as a
  • one aspect includes methods of treating a subject having cancer with a BET inhibitor, comprising performing a nucleic acid-based detection assay to detect the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from the subject; determining whether the cells in the sample from the subject express the eRNA at a level greater than a reference expression level of the eRNA; and administering an effective amount of the BET inhibitor to the subject if it is determined that the cells in the sample from the subject express the eRNA at a level greater than the reference expression level of the eRNA.
  • Another aspect includes methods of selecting a subject for treatment with a BET inhibitor, comprising performing a nucleic acid-based detection assay to detect the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from the subject; determining whether the cells in the sample from the subject express the eRNA at a level greater than a reference expression level of the eRNA; and selecting the subject for treatment with a BET inhibitor if the cells in the sample from the subject express the eRNA at a level greater than the reference expression level of the eRNA.
  • selecting the subject for treatment comprises selecting the subject for inclusion in a clinical trial.
  • Another aspect includes methods of modulating the treatment of a subject undergoing BET inhibitor treatment for cancer, comprising performing a nucleic acid-based detection assay to detect the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from the subject; determining the expression level of the eRNA in the cells in the sample; comparing the expression level of the eRNA in the cells in the sample to a reference expression level of the eRNA; and modulating the amount of BET inhibitor administered to the subject based on the difference between the expression level of the eRNA in the cells in the sample and the eRNA reference expression level.
  • the reference expression level is based on the expression level of the eRNA in the subject at an earlier timepoint during BET inhibitor treatment. In some embodiments, comparing the expression level of the eRNA in the cancer cells to the reference expression level of the eRNA comprises determining that the expression level of the eRNA in the cancer cells is less than the reference expression level of the eRNA and modulating the amount of BET inhibitor administered to the subject comprises maintaining the same level or decreasing the level of BET inhibitor administered to the subject.
  • comparing the expression level of the eRNA in the cancer cells to the reference expression level of the eRNA comprises determining that the expression level of the eRNA in the cancer cells is the same or more than the reference expression level of the eRNA and modulating the amount of BET inhibitor administered to the subject comprises increasing the level of BET inhibitor administered to the subject.
  • Another aspect includes methods of predicting responsiveness of a subject having cancer to a BET inhibitor, comprising performing a nucleic acid-based detection assay to detect the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from a subject; determining whether the cells in the sample from the subject express the eRNA at a level greater than a reference expression level of the eRNA; and predicting that the subject will be responsive to a BET inhibitor if it is determined that the cells in the sample from the subject express the eRNA at a level greater than the reference expression level of the eRNA.
  • Another aspect includes methods of communicating the likelihood of response of a subject having cancer to a BET inhibitor, comprising: performing a nucleic acid-based detection assay to detect the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from a subject; determining whether the cells in the sample from the subject express the eRNA at a level greater than a reference expression level of the eRNA; and communicating to a treatment provider that the cells in the sample from the subject express the eRNA at a level greater than the reference expression level of the eRNA, wherein the treatment provider administers an effective amount of a BET inhibitor to the subject or selects the subject for treatment with a BET inhibitor based on the communication.
  • Another aspect includes methods of treating a subject having cancer with a BET inhibitor, comprising administering to the subject an effective amount of the BET inhibitor wherein cancer cells contained in a sample from the subject were determined to express an eRNA transcribed from a myc-associated enhancer element at a level greater than a reference expression level of the eRNA.
  • Another aspect includes methods of treating a subject having cancer with a BET inhibitor, comprising administering to the subject an effective amount of the BET inhibitor wherein the subject was selected for treatment based on a determination that cancer cells contained in a sample from the subject express an eRNA transcribed from a myc-associated enhancer element at a level greater than a reference expression level of the eRNA.
  • Another aspect includes methods of treating cancer in a subject comprising administering to the subject an effective amount of a BET inhibitor wherein treatment is based upon the subject having cancer comprising a cancer cell that expresses an eRNA transcribed from a myc-associated enhancer element at a level greater than a reference expression level of the eRNA.
  • Another aspect includes methods of treating a cancer cell, wherein the cancer cell expresses an eRNA transcribed from a myc-associated enhancer element at a level greater than a reference expression level of the eRNA, the method comprising providing an effective amount of a BET inhibitor to the cell.
  • Another aspect includes method of treating cancer in a subject provided that the subject has been found to have cancer comprising a cancer cell that expresses an eRNA transcribed from a myc-associated enhancer element at a level greater than a reference expression level of the eRNA, the method comprising administering to the subject an effective amount of a BET inhibitor.
  • the cancer is selected from the group consisting of colon cancer, lung cancer, pancreatic cancer, bladder cancer, kidney cancer, endometrial cancer, leukemia, prostate cancer, breast cancer, gastric cancer, lung cancer, and ovarian cancer.
  • the cancer is selected from the group consisting of colon cancer, lung cancer, pancreatic cancer, bladder cancer, kidney cancer, and endometrial cancer.
  • the cancer is colon cancer.
  • the colon cancer is CpG island methylator phenotype (CIMP) (+) colon cancer.
  • the eRNA comprises a sequence having at least 80% identity to a sequence selected from the group consisting of SEQ ID NO: 1, SEQ ID NO: 2, and SEQ ID NO: 3.
  • the cancer is leukemia.
  • the eRNA comprises a sequence having at least 80% identity to SEQ ID NO: 4.
  • the cancer is selected from the group consisting of prostate cancer, bladder cancer, kidney cancer, endometrial cancer, breast cancer, gastric cancer, lung cancer, and ovarian cancer.
  • the cancer is prostate cancer.
  • the eRNA comprises a sequence having at least 80% identity to SEQ ID NO: 5.
  • the subject is a human.
  • the BET inhibitor is selected from the group consisting of JQ1, 1-BET 151 (GSK1210151A), I-BET 762 (GSK525762), OTX-015, TEN-010, CPI-203, and CPI-0610.
  • the nucleic acid-based detection assay detects expression of non-coding, nuclear RNA expressed in the cells in the sample from the subject.
  • the nucleic acid-based detection assay is selected from the group consisting of RNAseq, microarray analysis, direct RNA sequencing, in situ hybridization, and quantitative real-time PCR.
  • the myc-associated enhancer element is a myc-associated super enhancer element.
  • the reference expression level is based on the expression level of the eRNA in non-cancer cells.
  • the non-cancer cells are from the same tissue type as the cancer cells.
  • Another aspect includes methods of treating a subject having colon cancer with a BET inhibitor, comprising performing a nucleic acid-based detection assay to detect the expression level of an eRNA comprising a sequence having at least 80% identity to a sequence selected from the group consisting of SEQ ID NO: 1, SEQ ID NO: 2, and SEQ ID NO: 3 in a sample containing colon cancer cells from the subject; determining whether the cells in the sample from the subject express the eRNA at a level greater than a reference expression level of the eRNA; and administering an effective amount of the BET inhibitor to the subject if it is determined that the cells in the sample from the subject express the eRNA at a level greater than the reference expression level of the eRNA.
  • kits comprising reagents for detecting the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample.
  • the kits further comprise instructions for using the reagents.
  • the kits further comprise a BET inhibitor.
  • the kits further comprise instructions for performing any of the methods described herein.
  • FIG. 1 A shows a schematic diagram of lentiviral expression vectors used to express Cas9 and gRNA.
  • FIG. IB shows cell viability measured in parental RKO or RKO- Cas9 stably expressing cells 7 days after transduction with gRNAs targeting luciferase or PLKl.
  • FIG. 1C shows a schematic of a CRISPR negative-selection screen that was conducted in RKO-Cas9 cells using an arrayed gRNA library designed and synthesized to target 211 genes involved in epigenetic regulation and cancer (Epi200). Distribution curve shows Z- scores for cell viability for all gRNAs in the Epi200 CRISPR library.
  • FIG. ID shows a scatter gram depicting Z-score values for each gRNA of the 13 genes that scored as hits. Bars represent individual gRNAs. NTC gRNAs and CTNNB 1 gRNAs were not expected to score and are shown for reference.
  • FIG. IE shows a bar graph demonstrating cell viability effects after BRD4 knockout using 5 independent gRNAs. Error bars indicate standard deviation from three replicates. Accompanying immunoblots display the level of BRD4 depletion 4 days following transduction.
  • FIG. IF shows validation of gRNA-mediated BRD4 knockout using immunofluorescence. Two independent gRNAs are shown. In merged panels, DNA is blue and BRD4 is red.
  • FIGS. 2A-D show bar graphs depicting average cell viability changes conducted on a subset of the top scoring target genes in the primary CRISPR screen. 5 independent gene-specific gRNAs were used per gene. Error bars represent standard deviation from three replicates. Immunoblots beneath bar graphs show the level of protein depletion 4 days following gRNA transduction. Percent protein depletion was quantified using Image J and is displayed under immunoblots.
  • FIG. 2E shows a bar graph demonstrating the range of gRNA mediated protein depletion for 39 gRNAs representing a total of 8 genes.
  • FIGS. 3A&B depict BRD4 immunohistochemistry of normal colon (NL), colonic adenoma and colon carcinoma using either a pan-isoform BRD4 (FIG. 3A) or a BRD4-LF specific (FIG. 3A) antibody.
  • FIG. 3B shows photomicrographs illustrating target specificity using wild type (WT) or BRD4 knockout (KO) RKO cells.
  • FIG. 3C depicts immunoblot analysis of isoform specific BRD4 expression in colon cancer cell lines.
  • FIG. 3D shows generation of BRD4 clonal knockout RKO and HCT116 cells. The schematic illustrates the location of gRNAs co-transfected into cells with Cas9.
  • FIGS. 3E&F show incucyte analysis used to quantify cell proliferation of RKO (FIG. 3E) or HCT116 (FIG. 3F) BRD4 knockout cells.
  • the blue line represents parental wild-type cells
  • gray lines represent an individual clone's growth
  • the red line represents the average clonal growth. Error bars represent SEM.
  • FIG. 3G shows FACS-based cell cycle analysis of RKO and HCT116 parental and BRD4 knock out cells.
  • FIG. 3H&I demonstrate that expression of the BRD4 long isoform (LF-wt) rescued cell proliferation defects in HCT116 BRD4 knockout cells. Expression of a non-specific protein (LacZ) or a BRD4 long isoform containing inactivating mutations in both bromodomains (LF-mut) failed to rescue the phenotype.
  • FIG. 3H shows an immunoblot of stably expressing cell lines in FIG. 31.
  • FIGS. 3J&K show generation of clonal HCT116 cells that lack the C terminal domain of BRD4.
  • FIG. 3J shows a schematic illustrating the location of BRD4 gRNA co-transfected with Cas9 to knock out the BRD4 long isoform.
  • FIG. 3K demonstrates incucyte analysis used to quantify cell proliferation of HCT116 cells containing BRD4 C terminal deletions.
  • the blue line represents parental cells
  • gray lines represent an individual clone's growth
  • the red line represents the average clonal growth. Error bars represent SEM.
  • FIG. 4A shows an immunoblot (left) demonstrating stable BRD4 knockout cells expressing exogenous LACZ (control), exogenous wild-type BRD4 short isoform (BRD4- wt), or BRD4 short isoform containing bromodomain inactivating mutations.
  • Incucyte analysis (right) was utilized to quantify cell proliferation in the corresponding cell lines.
  • FIG. 4B demonstrates inducible BRD4 knockdown reduces cell proliferation of HCT116 and HT29 cells in vitro. Incucyte anaylsis was utilized to quantify cell proliferation following induction of BRD4 shRNAs with 0.5 ⁇ g/ml doxycycline. Error bars represent SEM.
  • FIG. 5 A shows the generation of stable HT-29 and HCT-116 cell lines containing doxycycline inducible BRD4 shRNAs. Immunoblots show BRD4 protein levels following 4 days of doxycycline treatment in vitro.
  • FIG. 5B depicts IHC staining for BRD4 in
  • FIG. 5C shows quantification of BRD4 depletion in xenograft tumors 7 days after
  • FIG. 5E shows quantification of mitotic index using Phospho-histone H3 (Phos H3) IHC following BRD4 knockdown in xenograft tumors.
  • FIG. 5F shows quantification of cMYC by IHC following BRD4 knockdown in xenograft tumors.
  • FIG. 5G shows
  • H&E histological analysis of HT-29 tumors in shNTC or shBRD4 tumors following doxycycline addition. H&E, Alcian Blue, Ki-67, and cMYC staining are shown.
  • FIG. 6A shows relative EC50 values in colon cancer cells following JQ1 treatment for 3 days. Blue and red bars highlight sensitive and resistant cell lines used for predictive analysis in FIG. 6B.
  • FIG. 6B shows a schematic illustrating the genomic tools and features utilized for predicting colon cancer sensitivity to BET inhibition.
  • FIG. 6C depicts the relative JQ1 EC50 values in colon cancer cells sorted by CIMP status. Bar represents the mean, error bars represent SEM, and each dot represents a single cell line.
  • FIG. 6D shows a schematic of RNA-seq and ChlP-seq experiments and analysis pipeline.
  • FIG. 6E depicts a heat map of Brd4 binding at super-enhancers and lOkb flanking regions.
  • FIG. 6G depicts a heatmap of the top 20 genes differentially regulated by JQl in CIMP(+) versus CIMP(-) cell lines.
  • FIG. 6H shows MYC levels examined by immunoblot in colon cancer cell lines treated for 6 or 24 hours with either DMSO or 1 ⁇ JQl.
  • FIG. 61 shows a comparison of MYC protein depletion in CIMP(+) or CIMP(-) colon cell lines following 1 ⁇ JQl treatment for 24 hours. Bars represent average, error bars represent SD, and each dot represents an individual cell line.
  • FIG. 7A shows relative EC50 values calculated for colon cancer cell lines treated with JQl for 3 days. Bar graph shows the EC50 for each cell line. Blue boxes show the 6 most sensitive (ATRFLOX-SW48) and red boxes show the 6 most resistant (COL0741-LS- 180) cell lines that were used for a binomial tail analysis. The features tested are shown on the right.
  • FIG. 7B shows eight gene panel classification for the CIMP-status (defined by Ogino, S., et al. J Mol Diagn 9, 305-314 (2007)). Box plot shows the degree of CpG methylation for the CIMP-gene set in each cell line.
  • JQl sensitivity is denoted below each cell line and is defined based on an arbitrary cut-off of 0.25 ⁇ EC50.
  • FIGS. 7C&D depict features that were significantly associated with JQl sensitivity. Scatter plots show either DNA methylation or expression as a function of the JQl sensitivity per given cell line (each dot is one cell line). Rho values (Spearman correlation) and p- values are indicated for each feature.
  • FIG. 8A demonstrates sensitivity of colon cancer cell lines to iBET-762. Bar graph depicts relative EC50 values.
  • FIG. 8B shows iBET-762 sensitivity profiles binned according to CIMP status. P-values denote statistical significance (Student's t-test).
  • FIG. 8C shows correlation between iBET-762 and JQl EC50 across the entire panel of 20 colon cancer cell lines. Pearson correlation is shown.
  • FIG. 9A shows the overlap of genes downregulated by > 2 fold following 500 nM JQl treatment (24h) relative to DMSO control in CIMP(+) or CIMP(-) cell lines. Overlap of CIMP(+) common and CIMP(-) common JQl -downregulated genes.
  • FIG. 9B shows the overlap of Brd4 super-enhancer associated genes in CIMP(+) or CIMP(-) cell lines. Overlap of CIMP(+) common and CIMP(-) common Brd4 super-enhancer associated genes.
  • FIG. 9C shows GSEA terms enriched in CIMP(+) or CIMP(-) cell lines based on analysis of JQl - regulated genes. An FDR cutoff of 5% was used. ES (enrichment score), NES (normalized enrichment score).
  • FIG. 10A shows quantification of cMYC protein levels at the indicated time points after 1 ⁇ JQl treatment in the indicated cell lines.
  • Bar graph shows cMYC levels normalized to DMSO control. CIMP status is defined per Ogino classification. DMSO is shown on the left, JQl 6 hours in the middle, and JQl 24 hours on the right for each cell line.
  • FIGS. lOB&C show kinetic analysis of cMYC reduction following 1 ⁇ JQl treatment in CJJVIP(+) (FIG. 10B) or CJJVIP(-) (FIG. IOC) colon cell lines. Each connecting line and associated dots represent a single cell line.
  • FIG. 10B shows quantification of cMYC protein levels at the indicated time points after 1 ⁇ JQl treatment in the indicated cell lines.
  • Bar graph shows cMYC levels normalized to DMSO control. CIMP status is defined per Ogino classification. DMSO is shown on the left, JQl
  • 10D demonstrates overexpression of V5- tagged cMYC in BRD4 knockout HCT116 cells partially rescues the cell proliferation phenotype.
  • Cell proliferation was measured by Incucyte analysis and quantified by percent confluence.
  • GFP overexpression was used as control (+GFP).
  • cMYC immunoblot (right) confirmed cMYC transgene expression.
  • FIG. 11 A depicts a Venn diagram showing the overlap of genes downregulated by JQl (>2 fold) and associated with a super-enhancer across CIMP(+) cell lines and CIMP(-) cell lines. Super-enhancer-associated, JQl -regulated genes common to all CIMP(+) cell lines are highlighted.
  • FIG. 11B shows the distribution of Brd4 ChlP-seq signal across enhancers in CIMP(+) cell lines. The y-axis represents input subtracted Brd4 signal. The x-axis represents enhancers ranked by Brd4 signal intensity. Super-enhancers were defined as enhancers that surpassed the inflection point. The CCATl -associated super-enhancer is highlighted.
  • FIG. 1 ID shows basal RNA levels of CCATl in colon cell lines. RNA was measured by RNAseq and presented as Log2 RPKM. CIMP(+) lines are HT-29, HCT 116, COLO 205, and HCT- 15, and CIMP(-) lines are COLO 320 and SW 480.
  • FIG. 1 IF shows relative cMYC expression in colon cancer cells following 500 nM JQl treatment. Data is from RNAseq analysis.
  • FIGS. 12A&B depicts genome browser tracks of ChlP-seq for Brd4 (FIG. 12A) and H3K27ac (FIG. 12B) at the MYC and CCATl genomic region for CIMP(+) (blue) and CIMP(-) (red) cell lines.
  • the y-axis represents ChlP/input coverage values.
  • FIGS. 12C&D show quantification of input-normalized Brd4 (FIG. 12C) and H3K27ac (FIG.
  • FIG. 12D ChlP-seq signal at the CCATl locus. Region was defined by overlap of super-enhancers in CIMP(+) cell lines. The region quantified is highlighted by the dark gray box in FIGS. 12A&B.
  • FIG. 13A depicts genome browser tracks showing H3K27ac signal for colon cancer (HCT-116; blue), prostate cancer (VCaP; red), and leukemia (Jurkat; black) overlapping IncRNA-encoding genes near the Myc locus. The y-axis represents reads per million.
  • FIG. 13B depicts a box and whisker plot of CCATl, PCATl, and LOC728724 RNA expression in a panel of cancers. Data was analyzed using RNAseq datasets from The Cancer Genome Atlas (TCGA) and presented as Log 10 RPKM. CCAT expression is shown on the left, PCATl in the middle, and LOC728724 on the right for each cancer type.
  • FIG. 13A depicts genome browser tracks showing H3K27ac signal for colon cancer (HCT-116; blue), prostate cancer (VCaP; red), and leukemia (Jurkat; black) overlapping IncRNA-encoding genes near the Myc locus. The y-axis represents reads per million.
  • FIG. 13C shows correlation analysis between CCATl expression and c-MYC downregulation following JQ1 treatment.
  • Cells were treated for 24 hours with either DMSO or 1 ⁇ JQ1 and cMYC expression was quantified by qRT-PCR. Each dot represents a single cell line.
  • FIG. 13D shows correlation analysis between CCATl expression and cell line sensitivity to JQ1. Relative EC50 values are calculated based on 3 days of JQ1 treatment. Cell lines with an RPKM ⁇ 0.1 were defined as CCATl low and cell lines with an RPKM >1 were defined as CCATl high. Each dot represents a single cell line. The bar represents the mean, and error bars represent SEM.
  • FIGS. 14A-D shows basal RNA expression of CCATl in colon cancer cells (FIG. 14A), CCATl in gastric, pancreatic, and lung cancer cells (FIG. 14B), PCATl in prostate cancer cells (FIG. 14C), and LOC728724 in blood cancer cells (FIG. 14D).
  • RNA was measured by RNAseq and presented as log2 RPKM.
  • FIGS. 14E-G demonstrate CCAT1(FIG. 14E), PCAT1(FIG. 14F), and LOC728724 (FIG. 14G) expression is dependent on BET activity. Cells were treated for 24 hours with 1 ⁇ JQ1 or DMSO and the indicated IncRNA was quantified by qRT-PCR in the indicated cell lines.
  • FIG. 15A shows quantification of cMYC RNA by qRT-PCR in gastric, pancreatic, lung, and colon cancer cells treated for 24 hours with DMSO or 1 ⁇ JQ1.
  • CCATl high lines were defined by a CCATl RPKM >1 (KATOIII-SNU601 for Gastric; TCCPAN2- CAPAN1 for Pancreatic; NCIH1666-NCIH1944 for Lung; and RKO-SKCOl for Colon), and CCATl low lines were defined by a CCATl RPKM ⁇ 1 (HS746T-HGC27 for Gastric;
  • FIGS. 15B-E show correlation analysis between IncRNA expression and cell line sensitivity to JQ1. Relative EC50 values were calculated based on 3 days of JQ1 treatment. Lung (FIG. 15B), pancreatic (FIG. 15C), gastric (FIG. 15D), and colon (FIG. 15E) cell lines with a CCATl RPKM ⁇ 0.1 were defined as CCATl low and cell lines with a CCATl RPKM > 1 were defined as CCATl high.
  • FIG. 15F-H show quantification of cMYC RNA by qRT- PCR in prostate cancer cells treated for 24 hours with DMSO or 1 ⁇ JQ1. Correlation analysis between IncRNA expression and cMYC downregulation in prostate cancer cells following JQ1 treatment is shown in FIG. 15F. Prostate cells with a PCAT1 RPKM ⁇ 0.1 were defined as PCAT1 low, and cell lines with a PCAT1 RPKM > 0.1 were defined as PCAT1 high (FIG. 15G).
  • FIG. 15H shows a bar graph depicting the level of cMYC reduction per each cell line.
  • FIG. 151 shows quantification of cMYC RNA by qRT-PCR in blood cancer cells treated for 24 hours with DMSO or 1 ⁇ JQ1. Error bars represent SEM.
  • FIG. 15J shows correlation analysis between LOC728724 expression and cMYC
  • Each dot represents an individual cell line.
  • FIG. 16A depicts representative ISH (in situ hybridization) photomicrographs showing CCATl expression in colon tumors. ISH scoring system is indicated.
  • FIG. 16B depicts the ISH score breakdown for a panel of normal colon tissues and colon tumors. Each patient sample was scored from triplicate representative tumor cores and the average CCATl ISH score was recorded as low (0-1), moderate (1-2), or high (2-3).
  • FIG. 16C shows Kaplan- Meier survival data for patients with colon cancer, separated by CCATl ISH score. Patients with high or moderate CCATl expression had a worse overall survival compared with low CCATl expression.
  • FIG. 17A depicts CCATl ISH performed on a CCATl high (HT-29) or a CCATl low (SW620) expressing colon cell line.
  • FIG. 17B demonstrates CCATl expression is sensitive to JQ1 treatment.
  • CCATl ISH was performed on formalin fixed RKO cell pellets. Cells were pre-treated with either DMSO or 1 ⁇ JQ1.
  • FIG. 17C demonstrates CCATl expression in normal human tissues. Box and whisker plots (min to max) highlight CCAT1 expression in normal colon, gastric, lung, and pancreatic human tissue. Results were compiled from TCGA RNAseq data sets.
  • FIG. 17D demonstrates that normal human colon tissue lacks expression of CCAT1, as indicated by CCAT1 ISH.
  • biomarker refers generally to a molecule, including a gene, non-coding RNA, protein, carbohydrate structure, or glycolipid, the expression of which in or on a mammalian tissue or cell or secreted can be detected by known methods (or methods disclosed herein) and is predictive or can be used to predict (or aid prediction) for a mammalian cell's or tissue's sensitivity to, and in some embodiments, to predict (or aid prediction) an individual's responsiveness to treatment regimes based on BET inhibitors.
  • Percent (%) identity with respect to the sequence of a reference RNA is defined as the percentage of nucleotides in a candidate sequence that are identical with the nucleotides in the reference RNA sequence, after aligning the sequences and introducing gaps, if necessary, to achieve the maximum percent sequence identity, and not considering any conservative substitutions as part of the sequence identity. Percentage identity may also refer to the alignment of a complement of the reference or candidate sequence to the other sequence. Alignment for purposes of determining percent nucleotide sequence identity can be achieved in various ways that are within the skill in the art, for instance, using publicly available computer software such as BLAST, BLAST-2, ALIGN or Megalign (DNASTAR) software.
  • ALIGN-2 sequence comparison computer program
  • the ALIGN-2 program is publicly available from Genentech, Inc., South San Francisco, California, or may be compiled from the source code.
  • the ALIGN-2 program should be compiled for use on a UNIX operating system, including digital UNIX V4.0D. All sequence comparison parameters are set by the ALIGN-2 program and do not vary.
  • treatment refers to clinical intervention in an attempt to alter the natural course of the individual or cell being treated during the course of clinical pathology. Desirable effects of treatment include, but are not limited to, decreasing the rate of disease progression, ameliorating or palliating the disease state, and remission or improved prognosis.
  • an individual is successfully “treated” if one or more symptoms associated with cancer are mitigated or eliminated, including, but not limited to, reducing the proliferation of (or destroying) cancerous cells, decreasing symptoms resulting from the disease, increasing the quality of life of those suffering from the disease, decreasing the dose of other medications required to treat the disease, and/or prolonging survival of individuals.
  • delaying progression of a disease means to defer, hinder, slow, retard, stabilize, and/or postpone development of the disease (such as cancer). This delay can be of varying lengths of time, depending on the history of the disease and/or individual being treated. As is evident to one skilled in the art, a sufficient or significant delay can, in effect, encompass prevention, in that the individual does not develop the disease. For example, a late stage cancer, such as development of metastasis, may be delayed.
  • mammals include, but are not limited to, domesticated animals (e.g., cows, sheep, cats, dogs, and horses), primates (e.g., humans and non-human primates such as monkeys), rabbits, and rodents (e.g., mice and rats).
  • domesticated animals e.g., cows, sheep, cats, dogs, and horses
  • primates e.g., humans and non-human primates such as monkeys
  • rabbits e.g., mice and rats
  • rodents e.g., mice and rats
  • pharmaceutical formulation refers to a preparation which is in such form as to permit the biological activity of an active ingredient contained therein to be effective, and which contains no additional components which are unacceptably toxic to a subject to which the formulation would be administered.
  • a “pharmaceutically acceptable carrier” refers to an ingredient in a
  • a pharmaceutically acceptable carrier includes, but is not limited to, a buffer, excipient, stabilizer, or preservative.
  • An "effective amount" of an agent, e.g., a pharmaceutical formulation refers to an amount effective, at dosages and for periods of time necessary, to achieve the desired therapeutic or prophylactic result.
  • an effective amount of a therapeutic agent e.g., a BET inhibitor provided herein
  • drug, compound, or pharmaceutical composition may or may not be achieved in conjunction with another drug, compound, or pharmaceutical composition.
  • an "effective amount" may be considered in the context of administering one or more therapeutic agents, and a single agent may be considered to be given in an effective amount if, in conjunction with one or more other agents, a desirable result may be or is achieved.
  • in conjunction with refers to administration of one treatment modality in addition to another treatment modality.
  • in conjunction with refers to administration of one treatment modality before, during or after administration of the other treatment modality to the individual.
  • package insert is used to refer to instructions customarily included in commercial packages of therapeutic products, that contain information about the indications, usage, dosage, administration, combination therapy, contraindications and/or warnings concerning the use of such therapeutic products.
  • sample refers to a composition that is obtained or derived from a subject having cancer that may contain a cellular and/or other molecular entity that is to be characterized and/or identified, for example based on physical, biochemical, chemical and/or physiological characteristics.
  • sample containing cancer cells and variations thereof refers to any sample obtained from a subject having cancer that may contain the cellular and/or molecular entity that is to be characterized.
  • a "reference value” or a “reference expression level” can be an absolute value; a relative value; a value that has an upper and/or lower limit; a range of values; an average value; a median value; a mean value; or a value as compared to a particular control or baseline value.
  • array refers to an ordered arrangement of hybridizable array elements, such as polynucleotide probes (e.g., oligonucleotides) and antibodies, on a substrate.
  • the substrate can be a solid substrate, such as a glass slide, or a semi-solid substrate, such as nitrocellulose membrane.
  • the nucleotide sequences can be DNA, RNA, or any permutations thereof.
  • Amplification generally refers to the process of producing multiple copies of a desired sequence.
  • Multiple copies means at least 2 copies.
  • a “copy” does not necessarily mean perfect sequence complementarity or identity to the template sequence.
  • copies can include nucleotide analogs such as deoxyinosine, intentional sequence alterations (such as sequence alterations introduced through a primer comprising a sequence that is hybridizable, but not complementary, to the template), and/or sequence errors that occur during amplification.
  • Polynucleotide or “nucleic acid,” as used interchangeably herein, refer to polymers of nucleotides of any length, and include DNA and RNA.
  • the nucleotides can be deoxyribonucleotides, ribonucleotides, modified nucleotides or bases, and/or their analogs, or any substrate that can be incorporated into a polymer by DNA or RNA polymerase.
  • a polynucleotide may comprise modified nucleotides, such as methylated nucleotides and their analogs. If present, modification to the nucleotide structure may be imparted before or after assembly of the polymer.
  • the sequence of nucleotides may be interrupted by non-nucleotide components.
  • a polynucleotide may be further modified after polymerization, such as by conjugation with a labeling component.
  • Other types of modifications include, for example, "caps", substitution of one or more of the naturally occurring nucleotides with an analog, internucleotide modifications such as, for example, those with uncharged linkages (e.g., methyl phosphonates, phosphotriesters, phosphoamidates, cabamates, etc.) and with charged linkages (e.g., phosphorothioates, phosphorodithioates, etc.), those containing pendant moieties, such as, for example, proteins (e.g., nucleases, toxins, antibodies, signal peptides, ply-L-lysine, etc.
  • proteins e.g., nucleases, toxins, antibodies, signal peptides, ply-L-lysine, etc.
  • any of the hydroxyl groups ordinarily present in the sugars may be replaced, for example, by phosphonate groups, phosphate groups, protected by standard protecting groups, or activated to prepare additional linkages to additional nucleotides, or may be conjugated to solid supports.
  • the 5' and 3' terminal OH can be phosphorylated or substituted with amines or organic capping groups moieties of from 1 to 20 carbon atoms. Other hydroxyls may also be derivatized to standard protecting groups.
  • Polynucleotides can also contain analogous forms of ribose or deoxyribose sugars that are generally known in the art, including, for example, 2'-0-methyl-2'-0- allyl, 2'-fluoro- or 2'- azido-ribose, carbocyclic sugar analogs, a- anomeric sugars, epimeric sugars such as arabinose, xyloses or lyxoses, pyranose sugars, furanose sugars, sedoheptuloses, acyclic analogs and abasic nucleoside analogs such as methyl riboside.
  • One or more phosphodiester linkages may be replaced by alternative linking groups. These alternative linking groups include, but are not limited to, embodiments where
  • each R or R' is independently H or substituted or unsubstituted alkyl (1-20 C) optionally containing an ether (—0—) linkage, aryl, alkenyl, cycloalkyl, cycloalkenyl or araldyl. Not all linkages in a polynucleotide need be identical. The preceding description applies to all polynucleotides referred to herein, including RNA and DNA.
  • Oligonucleotide generally refers to short, generally single stranded, generally synthetic polynucleotides that are generally, but not necessarily, less than about 200 nucleotides in length.
  • oligonucleotide and “polynucleotide” are not mutually exclusive. The description above for polynucleotides is equally and fully applicable to oligonucleotides.
  • a "primer” is generally a short single stranded polynucleotide, generally with a free 3'-OH group, that binds to a target potentially present in a sample of interest by hybridizing with a target sequence, and thereafter promotes polymerization of a
  • a "pair of primers” refer to a 5' primer and a 3' primer that can be used to amplify a portion of a specific target gene.
  • Detection includes any means of detecting, including direct and indirect detection.
  • the term "prediction" is used herein to refer to the likelihood that a subject will respond either favorably or unfavorably to a drug, therapeutic agent, or set of drugs or therapeutic agents. In one embodiment, the prediction relates to the extent of those responses. In one embodiment, the prediction relates to whether and/or the probability that a subject will survive or improve following treatment, for example treatment with a particular therapeutic agent, and for a certain period of time without cancer recurrence.
  • the predictive methods of the present disclosure can be used clinically to make treatment decisions by choosing the most appropriate treatment modalities for any particular subject. The predictive methods of the present disclosure can be used to select a subject for treatment, including selecting the subject for inclusion in a clinical trial.
  • the predictive methods of the present disclosure are valuable tools in predicting if a subject is likely to respond favorably to a treatment regimen, such as a given therapeutic regimen, including for example, administration of a given therapeutic agent, such as a BET inhibitor, or combination, surgical intervention, steroid treatment, etc., or whether long-term survival of the subject, following a therapeutic regimen is likely.
  • Responsiveness of a subject or “response of a subject” can be assessed using any endpoint indicating a benefit to the subject, including, without limitation, (1) inhibition, to some extent, of cancer progression, including slowing down and complete arrest; (2) reduction in the number of cancer episodes and/or symptoms; (3) reduction in lesional size; (4) inhibition (i.e., reduction, slowing down or complete stopping) of cancer cell infiltration into adjacent peripheral organs and/or tissues; (5) inhibition (i.e. reduction, slowing down or complete stopping) of cancer spread; (6) relief, to some extent, of one or more symptoms associated with the cancer; (7) increase in the length of cancer-free presentation following treatment; and/or (8) decreased mortality at a given point of time following treatment.
  • Reference to "about” a value or parameter herein includes (and describes) embodiments that are directed to that value or parameter per se. For example, description referring to "about X” includes description of "X.”
  • Biomarkers generally refers to biological molecules, and quantitative and qualitative measurements of the same, that are indicative of a disease state. Predictive biomarkers indicate whether a subject is likely to respond positively to a particular therapy. For example, HER2 profiling is commonly used in breast cancer patients to determine if those patients are likely to respond to Herceptin® (trastuzumab, Genentech). Pharmacodynamic biomarkers provide a measure of the response to a therapy and so provide an indication of whether a therapy is working. For example, decreasing levels of prostate specific antigen (PSA) generally indicate that anti-cancer therapy for a prostate cancer patient is working.
  • PSA prostate specific antigen
  • the present disclosure provides methods of treating or delaying progression of cancer in a subject having cancer with a BET inhibitor including the steps of performing a nucleic acid-based detection assay to detect the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from the subject; determining whether the cells in the sample from the subject express the eRNA at a level greater than a reference expression level of the eRNA; and administering an effective amount of the BET inhibitor to the subject if it is determined that the cells in the sample from the subject express the eRNA at a level greater than the reference expression level of the eRNA.
  • the methods include the steps of performing a nucleic acid-based detection assay to detect the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from the subject; determining that the cells in the sample from the subject express the eRNA at a level greater than a reference expression level of the eRNA; and administering an effective amount of the BET inhibitor to the subject having cancer cells that express the eRNA at a level greater than the reference expression level of the eRNA.
  • the present disclosure provides methods of treating a subject having colon cancer with a BET inhibitor, including the steps of performing a nucleic acid-based detection assay to detect the expression level of an eRNA comprising a sequence having at least 80% identity to SEQ ID NO: 1, SEQ ID NO: 2, or SEQ ID NO: 3 in a sample containing colon cancer cells from the subject; determining whether the cells in the sample from the subject express the eRNA at a level greater than a reference expression level of the eRNA; and administering an effective amount of the BET inhibitor to the subject if it is determined that the cells in the sample from the subject express the eRNA at a level greater than the reference expression level of the eRNA.
  • the present disclosure provides methods of selecting a subject for treatment with a BET inhibitor, including the steps of performing a nucleic acid-based detection assay to detect the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from the subject; determining whether the cancer cells from the subject express the eRNA at a level greater than a reference expression level of the eRNA; and selecting the subject for treatment with a BET inhibitor if the cells in the sample from the subject express the eRNA at a level greater than the reference expression level of the eRNA.
  • selecting the subject for treatment involves selecting the subject for treatment in a clinical trial.
  • the method involves selecting a specific BET inhibitor to administer to the subject.
  • the present disclosure provides methods of modulating the treatment of a subject undergoing BET inhibitor treatment for cancer, including the steps of performing a nucleic acid-based detection assay to detect the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from the subject; determining the expression level of the eRNA in the cancer cells; comparing the expression level of the eRNA in the cancer cells to a reference expression level of the eRNA; and modulating the amount of BET inhibitor administered to the subject based on the difference between the expression level of the eRNA in the cancer cells and the eRNA reference expression level.
  • the present disclosure provides methods of monitoring the treatment of a subject undergoing BET inhibitor treatment, including the steps of performing a nucleic acid-based detection assay to detect the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from the subject; determining the expression level of the eRNA in the cancer cells; and comparing the expression level of the eRNA in the cancer cells to a reference expression level of the eRNA.
  • the steps are repeated at multiple time points while the subject is undergoing BET inhibitor treatment.
  • the methods of the present disclosure may be performed by physicians, treatment providers, healthcare workers, hospitals, laboratories, patients, subjects, companies, and other institutions. All of the steps of a method of the present disclosure may be performed by one person, e.g. a physician, or the steps may be performed by multiple people in one institution. The steps may be performed by multiple people or multiple institutions at the direction of one person or one institution. Electronic means may be used to communicate information or data resulting from the step of determining whether cancer cells contained in a sample from a subject express an eRNA transcribed from a myc-associated enhancer element at a level greater than a reference expression level of the eRNA from one person or institution to another person or institution.
  • the present disclosure provides methods of predicting responsiveness of a subject having cancer to a BET inhibitor, including the steps of performing a nucleic acid-based detection assay to detect the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from a subject; determining whether the cells in the sample from the subject express the eRNA at a level greater than a reference expression level of the eRNA; and predicting that the subject will be responsive to a BET inhibitor if it is determined that the cells in the sample from the subject express the eRNA at a level greater than the reference expression level of the eRNA.
  • the prediction is communicated to a treatment provider.
  • methods of communicating the likelihood of response of a subject having cancer to a BET inhibitor include the steps of performing a nucleic acid-based detection assay to detect the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from a subject; determining whether the cells in the sample from the subject express the eRNA at a level greater than a reference expression level of the eRNA; and communicating to a treatment provider that the cells in the sample from the subject express the eRNA at a level greater than the reference expression level of the eRNA, wherein the treatment provider administers an effective amount of a BET inhibitor to the subject or selects the subject for treatment with a BET inhibitor based on the communication.
  • the steps are performed by a diagnostics company, a diagnostician, a diagnostics professional, or a technician. In other embodiments, the steps are performed by a health care provider.
  • Communication of a prediction or of the likelihood of response of the subject to a treatment provider typically involves communication by electronic means such as, for example, e-mail, text message, entering information into an online database, or updating the subject's electronic medical records.
  • the communication may also occur by in person interaction or telephonic interaction.
  • methods of treating or delaying progression of cancer in a subject having cancer with a BET inhibitor including the step of administering to the subject an effective amount of the BET inhibitor where cancer cells contained in a sample from the subject were determined to express an eRNA transcribed from a myc-associated enhancer element at a level greater than a reference expression level of the eRNA are provided.
  • the present disclosure provides methods of treating or delaying progression of cancer in a subject having cancer with a BET inhibitor, including the step of administering to the subject an effective amount of the BET inhibitor where the subject was selected for treatment based on a determination that cancer cells contained in a sample from the subject express an eRNA transcribed from a myc-associated enhancer element at a level greater than a reference expression level of the eRNA.
  • the present disclosure provides methods of treating or delaying progression of cancer in a subject including the step of administering to the subject an effective amount of a BET inhibitor where treatment is based upon the subject having cancer containing a cancer cell that expresses an eRNA transcribed from a myc-associated enhancer element at a level greater than a reference expression level of the eRNA.
  • the present disclosure provides methods of treating a cancer cell, where the cancer cell expresses an eRNA transcribed from a myc-associated enhancer element at a level greater than a reference expression level of the eRNA, the method including a step of providing an effective amount of a BET inhibitor to the cell.
  • the present disclosure provides methods of treating cancer or delaying progression of cancer in a subject provided that the subject has been found to have cancer containing a cancer cell that expresses an eRNA transcribed from a myc-associated enhancer element at a level greater than a reference expression level of the eRNA, the method including a step of administering to the subject an effective amount of a BET inhibitor.
  • the step or steps of the methods are performed by a treatment provider or health care provider such as a physician or nurse.
  • the subject is a human.
  • the methods of the present disclosure may be used to treat or select subjects having cancer of any type.
  • the cancer is colon cancer, lung cancer, pancreatic cancer, bladder cancer, kidney cancer, endometrial cancer, leukemia, prostate cancer, breast cancer, gastric cancer, lung cancer, or ovarian cancer.
  • the cancer is colon cancer.
  • the cancer is leukemia, and in some embodiments, the cancer is prostate cancer.
  • Colorectal tumors can be divided into three main subtypes based on initiating molecular alterations: 1) chromosomal instability (CIN), 2) CpG island methylator phenotype (CIMP) and 3) microsatellite instability (MSI).
  • CIN chromosomal instability
  • CIMP CpG island methylator phenotype
  • MSI microsatellite instability
  • the colon cancer may be CpG island methylator phenotype (+) colon cancer (Toyota (1999)).
  • CIMP CpG island methylator phenotype
  • Widespread CpG island hypermethylation underscores a distinct pathway in epigenetically dysregulated CIMP (+) colon cancer pathogenesis.
  • Tumors arising through the CIMP pathway comprise 20% of colorectal cancers and are characterized by poor patient outcome.
  • the methods of the present disclosure involve performing a nucleic acid-based detection assay to detect the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from the subject.
  • sample refers to a composition that is obtained or derived from a subject having cancer that may contain a cellular and/or other molecular entity that is to be characterized and/or identified, for example based on physical, biochemical, chemical and/or physiological characteristics.
  • sample containing cancer cells refers to any sample obtained from a subject having cancer that may contain the cellular and/or molecular entity that is to be characterized, such as an eRNA transcribed from a myc-associated enhancer element.
  • the sample, or a "tissue or cell sample” contains a collection of cells obtained from a tissue of a subject.
  • the source of the tissue or cell sample may be solid tissue as from a fresh, frozen and/or preserved organ or tissue sample or biopsy or aspirate; blood or any blood constituents; bodily fluids such as cerebral spinal fluid, amniotic fluid, peritoneal fluid, or interstitial fluid; cells from any time in gestation or development of the subject.
  • the tissue sample may also be primary or cultured cells or cell lines.
  • the sample is obtained from a diseased tissue or organ.
  • the sample may be obtained from tissue or an organ where cancer cells are present.
  • the sample contains both cancer cells and non-cancer cells.
  • the sample contains only cancer cells.
  • the sample may contain compounds which are not naturally intermixed with the tissue in nature such as preservatives, anticoagulants, buffers, fixatives, nutrients, antibiotics, or the like.
  • a "section" of a sample is meant a single part or piece of a tissue sample, e.g. a thin slice of tissue or cells cut from a tissue sample. It is understood that multiple sections of tissue samples may be taken and subjected to analysis according to the present disclosure.
  • the cancer cells in the sample are from colon cancer, colorectal cancer, rectal cancer, lung cancer, pancreatic cancer, bladder cancer, kidney cancer, endometrial cancer, leukemia, prostate cancer, breast cancer, gastric cancer, lung cancer, or ovarian cancer.
  • the cancer cells in the sample are from colon cancer.
  • the cancer cells in the sample are from CpG island methylator phenotype (CIMP) (+) colon cancer.
  • the cancer cells in the sample are from leukemia.
  • the cancer cells in the sample are from prostate cancer.
  • the present disclosure provides methods of treating a subject having cancer with a BET inhibitor, methods of selecting a subject for treatment with a BET inhibitor, and methods of modulating the treatment of a subject undergoing BET inhibitor treatment for cancer.
  • BET inhibitors are typically small molecules that inhibit the activity of the BET family of proteins.
  • the BET family of bromodomain-containing proteins comprises 4 proteins (BRD2, BRD3, BRD4 and BRD-t) which contain tandem bromodomains capable of binding to two acetylated lysine residues in close proximity, increasing the specificity of the interaction.
  • BRD2 and BRD3 were reported to associate with histones along actively transcribed genes and may be involved in facilitating transcriptional elongation (Leroy et al, Mol. Cell.
  • BET inhibitors Four main classes of BET inhibitors have been described: (1) thienodiazepines and benzodiazepines; (2) quinolone and quinazoline derivatives; (3) triazolopyridazines; and (4) N-methyl pyridinone and N-methylpyridazinone. Inhibitors from any of these groups may be used in the methods of the present disclosure.
  • Exemplary thienodiazepines and benzodiazepines include, without limitation, the compounds JQ1, 1-BET762 (GSK525762), CPI-203, MS417, and OTX-015.
  • Exemplary thienodiazepines and benzodiazepines are disclosed in WO2009084693, WO1998011111, WO2006129623, WO2011143669,
  • quinolone and quinazoline derivatives include, without limitation, I-BET151 (GSK1210151A), PFi-1, and RVX-208. Exemplary quinolone and quinazoline derivatives are disclosed in
  • WO2013027168 WO2011054848, WO2011054846, WO2011054843, WO2013024104, WO2008092231, WO2009158404, and WO2010123975.
  • Exemplary triazolopyridazines are disclosed in WO2012174487.
  • Exemplary N-methyl pyridinone and N-methylpyridazinones are disclosed in WO2013097601.
  • Bromodomain ligand dimers of JQ1 which bind to both bromodomains of the BET protein, have also been described as bromodomain inhibitors, as disclosed in WO2013033268.
  • the BET inhibitor is JQ1, i-BET 151 (GSK1210151A), i-BET 762 (GSK525762), OTX-015, TEN-010, CPI-203, or CPI-0610.
  • Additional BET inhibitors from alternative chemotypes to those described above may also be used in the methods of the present disclosure, which include, without limitation, 3,5-dimethylisoxazoles (Hewings et al. (2013) J Med Chem 56:3217-27), sulfonamide (Bamborough et al (2012) J Med Chem 55:587-96), and thiazolidione compounds (Zhao et al. (2013) J Med Chem 56:3833-51).
  • Enhancer RNA eRNA
  • Methods of the present disclosure involve detecting the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from a subject.
  • eRNA refers to any non-coding RNA that is transcribed off of an enhancer regulatory element.
  • IncRNAs long non-coding RNAs
  • lincRNAs large intergenic non-coding RNAs
  • IncRNAs are marked by trimethylation of lysine 4 of histone H3 (H3K4me3) at their promoter and trimethylation of lysine 36 of histone H3 (H3K36me3) along the transcribed region.
  • eRNAs enhancer RNAs
  • a "myc-associated enhancer element” is an enhancer that, when bound with certain protein activators, activates the transcription of the c-myc gene.
  • the myc-associated enhancer element is a myc-associated super enhancer element.
  • a "myc-associated super enhancer element” as used herein refers to a cluster of enhancer elements that may activate transcription of the c-myc gene more strongly than a myc-associated enhancer element.
  • super-enhancers differ from enhancers in size, transcription factor binding density and content, ability to activate transcription, and sensitivity to perturbation (Whyte, W.A., et al. Cell 153, 307-319 (2013))
  • Super-enhancers can ramp up the expression of oncogenic factors in a tumor-type specific and lineage dependent manner (Whyte (2013); Dowen, J.M., et al. Cell 159, 374-387 (2014); Mansour, M.R., et al. Science 346, 1373-1377 (2014)).
  • the myc proto-oncogene is a member of the basic helix-loop-helix leucine zipper family of transcription factors (reviewed in (Luscher, B., (2001). Gene 277, 1-14). Being submitted to bind promoters in as many as 15% of the genes in the human genome (Patel, J.H., Loboda, A.P., Showe, M.K., Showe, L.C. and McMahon, S.B., (2004). Nat Rev Cancer 4, 562-568), myc plays a role in a diverse array of processes of cancer development, including
  • cMYC upregulation in cancer can occur via numerous
  • Colon Cancer Associated Transcript 1 (CCATl ; also known as LOC 100507056) is a distinct long noncoding RNA (IncRNA) transcribed off the colon cancer cMYC super- enhancer element.
  • the CCATl transcript is located within a demarcated super-enhancer, 500 kb upstream of the cMYC promoter.
  • the CCATl sequence has been annotated in the Ensembl Genome Browser (SEQ ID NO: 1), the NCBI Reference Sequence Database (SEQ ID NO: 2), and by Xiang et al. (SEQ ID NO: 3).
  • the eRNA comprises a sequence having at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% identity to SEQ ID NO: 1, SEQ ID NO: 2, or SEQ ID NO:3.
  • the cancer may be colon cancer, lung cancer, pancreatic cancer, bladder cancer, kidney cancer, or endometrial cancer.
  • the cancer is CpG island methylator phenotype (CIMP) (+) colon cancer.
  • SEQ ID NO: 1 is the CCAT sequence as annotated by the Ensembl Genome Browser (record number: ENST00000500112). The sequence for SEQ ID NO: 1 is listed below. tcatcattaccagctgccgtgttaagcattgcgaaaacgctcacgattcacagaaaaatccatgctgttcttttgaaggcattcaagccttaa tagctagctggatgaatgttttaacttctaggccaggcactactctgtcccaacaataagccctgtgggaaaggtgccgagacatg aactttggtctctctgcaatccatctggagcattcactgacaacatcgacttttgaagttgcactgacctggccagccctgccacttacca ggttggctttacca
  • SEQ ID NO: 2 is the CCAT1 sequence as annotated by the NCBI Reference Sequence Database (record number: NR_108049.1). The sequence for SEQ ID NO: 2 is listed below. tttaaatcataccaattgaaccgagccttgtagaaacactatcacctacgcatacctctgcttcttttcattaacctgctatcctcttttacaaat gggattcttcacccactcccttcttctagattagcaatgccctgttaagtaaacgaacacgaaattcaaagggaaacaggagcaatcatc attaccagctgccgtgttaagcattgcgaaaacgctcacgattcacagaaaaatccatgctgttttttgaaaacgctcacgattca
  • SEQ ID NO: 3 contains the long isoform of CCAT1 based on 3' RACE (Xiang et al Cell Research (2014) 24:513-531 PMID: 24662484). The SEQ ID NO: 3 sequence is listed below.
  • LOC728724 is also a distinct long noncoding RNA (IncRNA) transcribed off the cMYC super-enhancer element. According to RNA-seq data from The Cancer Genome Atlas, expression of LOC728724 is restricted to leukemia.
  • SEQ ID NO: 4 is the LOC728724 sequence as annotated by the NCBI Reference Sequence Database (record number:
  • the eRNA comprises a sequence having at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% identity to SEQ ID NO: 4.
  • the cancer is leukemia.
  • PCAT1 is also a distinct long noncoding RNA (IncRNA) transcribed off the cMYC super-enhancer element. According to RNA-seq data from The Cancer Genome Atlas, PCAT1 shows preferential expression in prostatic carcinoma.
  • SEQ ID NO: 5 is the PCAT1 sequence as annotated by the NCBI Reference Sequence Database (record number: NR_045262.1).
  • the eRNA comprises a sequence having at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% identity to SEQ ID NO: 5.
  • the cancer is prostate cancer, bladder cancer, kidney cancer, endometrial cancer, breast cancer, gastric cancer, lung cancer, or ovarian cancer.
  • nucleic acid-based detection assays are used to detect the expression level of an eRNA transcribed from a myc-associated enhancer element.
  • the nucleic acid-based detection assay may be any assay deemed appropriate by one of skill in the art.
  • the nucleic acid-based detection assay may involve RNAseq, microarray analysis, direct RNA sequencing, in situ hybridization, and quantitative real-time PCR.
  • Nucleic acid-based detection assays are well known and include, for example, hybridization assays using complementary DNA probes (such as in situ hybridization using labeled riboprobes, Northern blot and related techniques) and various nucleic acid
  • amplification assays such as RT-PCR using complementary primers specific for eRNA and other amplification-type detection methods, such as, for example, branched DNA, SISBA, TMA and the like).
  • the nucleic acid-based detection assay uses PCR analysis.
  • RT-PCR assays such as quantitative PCR assays are well known in the art.
  • the nucleic acid-based detection assay involves producing cDNA from the sample by reverse transcription using at least one primer; amplifying the cDNA so produced using an eRNA polynucleotide as sense and antisense primers to amplify eRNA cDNAs therein; and detecting the presence of the amplified cDNA.
  • such assays can include one or more steps that allow one to determine the levels of eRNA in a biological sample (e.g. by simultaneously examining the levels of a comparative control mRNA sequence of a "housekeeping" gene such as an actin family member).
  • the sequence of the amplified eRNA cDNA can be determined.
  • the nucleic acid-based detection assay involves in situ hybridization (ISH).
  • In situ hybridization is a type of hybridization that uses a labeled complementary DNA or RNA strand as a probe to detect a specific DNA or RNA sequence in a portion or section of tissue (in situ), or, if the tissue is small enough, the entire tissue (whole mount ISH).
  • DNA ISH can be used to determine the structure of chromosomes.
  • RNA ISH is used to measure and localize mRNAs and other RNA transcripts within tissue sections or whole mounts. Sample cells and tissues are usually treated to fix the target transcripts in place and to increase access of the probe.
  • ISH can also use two or more probes, labeled with radioactivity or the other non-radioactive labels, to simultaneously detect two or more transcripts.
  • the probe used is a gene-specific probe for detection of human CCAT1 RNA (Affymetrix; VA1-17802) target region 2-2696 in Genbank accessions NR_108049.1.
  • Nucleic acid-based detection assays may involve the use of eRNA primers and primer pairs, which allow the specific amplification of the eRNAs of interest or of any specific parts thereof, and probes that selectively or specifically hybridize to the eRNAs of interest or to any part thereof.
  • Probes may be labeled with a detectable marker, such as, for example, a radioisotope, fluorescent compound, bioluminescent compound, a
  • Such probes and primers can be used to detect the presence of eRNA in a sample and as a means for detecting a cell expressing eRNA.
  • a great many different primers and probes may be prepared based on the sequences provided in herein and used effectively to amplify, clone and/or determine the presence and/or levels of eRNAs.
  • the nucleic acid-based detection assay involves direct RNA sequencing or RNAseq.
  • Illustrative non-limiting examples of nucleic acid sequencing techniques include, but are not limited to, chain terminator (Sanger) sequencing and dye terminator sequencing. Those of ordinary skill in the art will recognize that because RNA is less stable in the cell and more prone to nuclease attack RNA is usually reverse transcribed to DNA before sequencing.
  • Chain terminator sequencing uses sequence- specific termination of a DNA synthesis reaction using modified nucleotide substrates. Extension is initiated at a specific site on the template DNA by using a short radioactive, or other labeled, oligonucleotide primer complementary to the template at that region.
  • the oligonucleotide primer is extended using a DNA polymerase, standard four deoxynucleotide bases, and a low concentration of one chain terminating nucleotide, most commonly a di-deoxynucleotide. This reaction is repeated in four separate tubes with each of the bases taking turns as the di-deoxynucleotide.
  • the DNA polymerase Limited incorporation of the chain terminating nucleotide by the DNA polymerase results in a series of related DNA fragments that are terminated only at positions where that particular di- deoxynucleotide is used.
  • the fragments are size- separated by electrophoresis in a slab polyacrylamide gel or a capillary tube filled with a viscous polymer. The sequence is determined by reading which lane produces a visualized mark from the labeled primer as one scans from the top of the gel to the bottom.
  • Dye terminator sequencing alternatively labels the terminators. Complete sequencing can be performed in a single reaction by labeling each of the di-deoxynucleotide chain- terminators with a separate fluorescent dye, which fluoresces at a different
  • nucleic acid sequencing methods are contemplated for use in the methods of the present disclosure including, for example, chain terminator (Sanger) sequencing, dye terminator sequencing, and high-throughput sequencing methods. Many of these sequencing methods are well known in the art. See, e.g., Sanger et al, Proc. Natl. Acad. Sci. USA 74:5463-5467 (1997); Maxam et al, Proc. Natl. Acad. Sci. USA 74:560-564 (1977); Drmanac, et al, Nat. Biotechnol. 16:54-58 (1998); Kato, Int. J. Clin. Exp. Med.
  • NGS Next- generation sequencing
  • Amplification-requiring methods include pyrosequencing commercialized by Roche as the 454 technology platforms (e.g., GS 20 and GS FLX), the Solexa platform commercialized by Illumina, and the Supported Oligonucleotide Ligation and Detection (SOLiD) platform commercialized by Applied Biosystems.
  • Non-amplification approaches also known as single-molecule sequencing, are exemplified by the HeliScope platform commercialized by Helicos Biosciences, and emerging platforms commercialized by VisiGen, Oxford Nanopore Technologies Ltd., Life Technologies/Ion Torrent, and Pacific Biosciences, respectively.
  • RNAseq is a technique based on enumeration of RNA transcripts using next- generation sequencing methodologies. RNAseq is a relatively new technology that has been employed for mass sequencing of whole transcriptomes and that offers significant advantages over other methods employed for transcriptome sequencing, such as microarrays, including low levels of background noise, the ability to detect low levels of expression, the ability to detect novel mutations and transcripts, and the ability to use relatively small amounts of RNA (for a review of RNA-seq, see Wang end., Nat. Rev. Genet. (2009) 10:57-63).
  • the nucleic acid-based detection assay involves microarray technologies. Using nucleic acid microarrays, RNA in samples containing cancer cells from the subject and samples containing non-cancer cells or other control cells is reverse transcribed and labeled to generate cDNA probes. The probes are then hybridized to an array of nucleic acids immobilized on a solid support. The array is configured such that the sequence and position of each member of the array is known. For example, a selection of genes or non-coding RNAs that have potential to be expressed in certain disease states may be arrayed on a solid support.
  • Hybridization of a labeled probe with a particular array member indicates that the sample from which the probe was derived expresses that gene or non-coding RNA.
  • Differential expression analysis of disease tissue can provide valuable information.
  • Microarray technology utilizes nucleic acid hybridization techniques and computing technology to evaluate the RNA expression profile of thousands of genes or non- coding regions within a single experiment, (see, e.g., WO 01/75166, U.S. Patent 5,700,637, U.S. Patent 5,445,934, and U.S. Patent 5,807,522; Lockart, Nature Biotechnology, 14: 1675- 1680 (1996); Cheung, V.G.
  • DNA microarrays are miniature arrays containing gene fragments that are either synthesized directly onto or spotted onto glass or other substrates. Thousands of genes or genomic regions are usually represented in a single array.
  • a typical microarray experiment involves the following steps: 1) preparation of fluorescently labeled target from RNA isolated from the sample, 2) hybridization of the labeled target to the microarray, 3) washing, staining, and scanning of the array, 4) analysis of the scanned image and 5) generation of expression profiles.
  • oligonucleotide usually 25 to 70 mers
  • gene expression arrays containing PCR products prepared from cDNAs can be either prefabricated and spotted to the surface or directly synthesized on to the surface (in situ).
  • the Affymetrix GeneChip® system is a commerically available microarray system which comprises arrays fabricated by direct synthesis of oligonucleotides on a glass surface. Oligonucleotides, usually 25-mers, are directly synthesized onto a glass wafer by a combination of semiconductor-based photolithography and solid phase chemical synthesis technologies. Each array contains up to 400,000 different oligos and each oligo is present in millions of copies. Since oligonucleotide probes are synthesized in known locations on the array, the hybridization patterns and signal intensities can be interpreted in terms of genomic region identity and relative expression levels by the Affymetrix Microarray Suite software.
  • Each genomic region is represented on the array by a series of different oligonucleotide probes.
  • Each probe pair consists of a perfect match oligonucleotide and a mismatch oligonucleotide.
  • the perfect match probe has a sequence exactly complimentary to the particular gene or genomic region and thus measures the expression of the gene or genomic region.
  • the mismatch probe differs from the perfect match probe by a single base
  • the Microarray Suite software subtracts the hybridization intensities of the mismatch probes from those of the perfect match probes to determine the absolute or specific intensity value for each probe set. Probes are chosen based on current information from Genbank and other nucleotide repositories. The sequences are believed to recognize unique regions of the 3' end of the gene.
  • a GeneChip Hybridization Oven (“rotisserie” oven) is used to carry out the hybridization of up to 64 arrays at one time. The fluidics station performs washing and staining of the probe arrays.
  • the scanner is a confocal laser fluorescence scanner which measures fluorescence intensity emitted by the labeled eRNA bound to the probe arrays.
  • the computer workstation with Microarray Suite software controls the fluidics station and the scanner.
  • Microarray Suite software can control up to eight fluidics stations using preprogrammed hybridization, wash, and stain protocols for the probe array.
  • the software also acquires and converts hybridization intensity data into a presence/absence call for each gene using appropriate algorithms.
  • the software detects changes in gene expression between experiments by comparison analysis and formats the output into .txt files, which can be used with other software programs for further data analysis.
  • Methods of the present disclosure involve determining whether the cells in a sample from a subject express an eRNA at a level greater than a reference expression level of the eRNA or comparing the expression level of the eRNA in the cells in a sample to a reference expression level of the eRNA.
  • the methods involve determining whether the cancer cells in the sample from the subject express the eRNA at a level greater than a reference expression level of the eRNA or comparing the expression level of the eRNA in the cancer cells in a sample to a reference expression level of the eRNA.
  • the methods involve determining whether the cancer cells and the non- cancer cells in the sample from the subject express the eRNA at a level greater than a reference expression level of the eRNA or comparing the expression level of the eRNA in the cancer cells and the non-cancer cells in a sample to a reference expression level of the eRNA.
  • the reference expression level is based on the expression level of the eRNA in non-cancer cells.
  • the non-cancer cells are from the same tissue type as the cancer cells. For example, if the cancer cells are from colon cancer then the non-cancer cells are from healthy colon tissue.
  • the reference expression level is an average of expression levels of the eRNA from an earlier timepoint or timepoints.
  • the reference expression level of the eRNA is measured in a person or persons other than the subject with cancer.
  • the reference expression level of the eRNA is measured in a person or persons with similar characteristics to the subject with cancer.
  • the reference expression level of the eRNA is a combination of multiple expression levels of the eRNA from different sources.
  • the reference expression level can be measured in a sample, cell or tissue obtained from a source known, or believed, not to be afflicted with cancer. In some embodiments, the reference expression level is measured in a sample, cell or tissue obtained from a healthy part of the body of the same subject with cancer that is being treated or selected for treatment with methods of the present disclosure. In some embodiments, the reference expression level is measured in a sample, cell or tissue obtained from a healthy part of the body of an individual who is not the subject with cancer that is being treated or selected for treatment with methods of the present disclosure.
  • the present disclosure provides methods of modulating the treatment of a subject undergoing BET inhibitor treatment for cancer including the steps of performing a nucleic acid-based detection assay to detect the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample containing cancer cells from the subject; determining the expression level of the eRNA in the cancer cells; comparing the expression level of the eRNA in the cancer cells to a reference expression level of the eRNA; and modulating the amount of BET inhibitor administered to the subject based on the difference between the expression level of the eRNA in the cancer cells and the eRNA reference expression level.
  • the reference expression level is based on the expression level of the eRNA in the subject at an earlier timepoint during BET inhibitor treatment.
  • the earlier timepoint may be any timepoint during a course of BET inhibitor treatment, including a baseline timepoint such as the timepoint just before or at the same time that the first dose of BET inhibitor is given to the subject.
  • the method involves determining that the expression level of the eRNA in the cancer cells is less than the reference expression level of the eRNA and modulating the amount of BET inhibitor administered to the subject involves maintaining the same level or decreasing the level of BET inhibitor administered to the subject.
  • the method involves determining that the expression level of the eRNA in the cancer cells is the same or more than the reference expression level of the eRNA and modulating the amount of BET inhibitor administered to the subject involves increasing the level of BET inhibitor administered to the subject.
  • Expression of eRNA is at a level "greater than" the reference expression level if the expression level is at least about 1.5X, 1.75X, 2X, 3X, 4X, 5X, 6X, 7X, 8X, 9X or 10X or more of the reference expression level.
  • Expression of eRNA is at a level "less than” the reference expression level if the expression level is at least about 1.5X, 1.75X, 2X, 3X, 4X, 5X, 6X, 7X, 8X, 9X or 10X less than the reference expression level.
  • the reference expression level may be determined based on any assay known in the art, including but not limited to RNAseq, microarray analysis, direct RNA sequencing, in situ hybridization, and quantitative real-time PCR. Typically, the reference expression level will be determined using the same assay that was used to detect the expression level of the eRNA in the sample containing cancer cells. The reference expression level may be determined qualitatively and/or quantitatively.
  • Methods of the present disclosure involve administering an effective amount of a BET inhibitor to a subject or modulating the amount of BET inhibitor administered to the subject.
  • An effective amount refers to an amount effective, at dosages and for periods of time necessary, to achieve the desired therapeutic or prophylactic result.
  • An effective amount of a BET inhibitor may vary according to factors such as the cancer state, age, sex, and weight of the subject, and the ability of the BET inhibitor to elicit a desired response in the subject.
  • An effective amount is also one in which any toxic or detrimental effects of the BET inhibitor are outweighed by the therapeutically beneficial effects.
  • a BET inhibitor used in a method of the present disclosure can be administered in an amount of about 0.005 to about 500 milligrams per dose, about 0.05 to about 250 milligrams per dose, or about 0.5 to about 100 milligrams per dose.
  • a BET inhibitor can be administered, per dose, in an amount of about 0.005, 0.05, 0.5, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200, 250, 300, 350, 400, 450, or 500 milligrams, including all doses between 0.005 and 500 milligrams.
  • the dosage of a composition containing a BET inhibitor, or a composition containing the same can be from about 1 ng/kg to about 200 mg/kg, about 1 ⁇ g/kg to about 100 mg/kg, or about 1 mg/kg to about 50 mg/kg.
  • the dosage of a composition can be at any dosage including, but not limited to, about 1 ⁇ g/kg.
  • the dosage of a composition may be at any dosage including, but not limited to, about 1 ⁇ g/kg, 10 ⁇ g/kg, 25 ⁇ g/kg, 50 ⁇ g/kg, 75 ⁇ g/kg, 100 ⁇ g/kg, 125 ⁇ g/kg, 150 ⁇ g/kg, 175 ⁇ g/kg, 200 ⁇ g/kg, 225 ⁇ g/kg, 250 ⁇ g/kg, 275 ⁇ g/kg, 300 ⁇ g/kg, 325 ⁇ g/kg, 350 ⁇ g/kg, 375 ⁇ g/kg, 400 ⁇ g/kg, 425 ⁇ g/kg, 450 ⁇ g/kg, 475 ⁇ g/kg, 500 ⁇ g/kg, 525 ⁇ g/kg, 550 ⁇ ⁇ ⁇ ⁇ , 575 ⁇ ⁇ ⁇ ⁇ , 600 ⁇ ⁇ ⁇ ⁇ , 625 ⁇ ⁇ ⁇ ⁇ , 650 ⁇ ⁇ ⁇ ⁇ , 675 ⁇ ,
  • the above dosages are exemplary of the average case, but there can be individual instances in which higher or lower dosages are merited, and such are within the scope of this disclosure.
  • the physician determines the actual dosing regimen that is most suitable for an individual subject, which can vary with the age, weight, and response of the particular subject.
  • Such doses may be administered daily or intermittently, e.g., every week or every three weeks (e.g., such that the subject receives from about two to about twenty, or e.g., about six doses of the antibody).
  • An initial higher loading dose, followed by one or more lower doses may be administered.
  • other dosage regimens may be useful. The progress of the dosage regime is easily monitored by conventional techniques and assays.
  • a therapeutically effective amount of a BET inhibitor required for use in therapy varies with the nature of the condition being treated, the length of time that activity is desired, and the age and the condition of the subject, and ultimately is determined by the attendant physician. Dosage amounts and intervals can be adjusted individually to provide plasma levels of the BET inhibitor that are sufficient to maintain the desired therapeutic effects.
  • the desired dose conveniently can be administered in a single dose, or as multiple doses administered at appropriate intervals, for example as one, two, three, four or more subdoses per day. Multiple doses often are desired, or required.
  • a BET inhibitor can be administered at a frequency of: four doses delivered as one dose per day at four-day intervals (q4dx4); four doses delivered as one dose per day at three-day intervals (q3dx4); one dose delivered per day at five-day intervals (qdx5); one dose per week for three weeks (qwk3); five daily doses, with two days rest, and another five daily doses (5/2/5); or, any dose regimen determined to be appropriate for the circumstance.
  • Effective amounts of a BET inhibitor can be administered by any suitable route, for example by oral, buccal, inhalation, sublingual, rectal, vaginal, intracisternal or intrathecal through lumbar puncture, transurethral, nasal, percutaneous, i.e., transdermal, or parenteral (including intravenous, intramuscular, subcutaneous, intracoronary, intradermal, intramammary, intraperitoneal, intraarticular, intrathecal, retrobulbar, intrapulmonary injection and/or surgical implantation at a particular site) administration.
  • Parenteral administration can be accomplished using a needle and syringe or using a high pressure technique.
  • Various dosing schedules including but not limited to single or multiple administrations over various time-points, bolus administration, and pulse infusion are contemplated herein.
  • compositions containing BET inhibitors can be manufactured, for example, by conventional mixing, dissolving, granulating, dragee-making, emulsifying, encapsulating, entrapping, or lyophilizing processes. Proper formulation is dependent upon the route of administration chosen.
  • a therapeutically effective amount of a BET inhibitor is administered orally, the composition typically is in the form of a tablet, capsule, powder, solution, or elixir.
  • the composition additionally can contain a solid carrier, such as a gelatin or an adjuvant.
  • a liquid carrier such as water, petroleum, or oils of animal or plant origin, can be added.
  • the liquid form of the composition can further contain physiological saline solution, dextrose or other saccharide solutions, or glycols.
  • composition When a therapeutically effective amount of a BET inhibitor is administered by intravenous, cutaneous, or subcutaneous injection, the composition is in the form of a pyrogen-free, parenterally acceptable aqueous solution.
  • parenterally acceptable aqueous solution having due regard to pH, isotonicity, stability, and the like, is within the skill in the art.
  • a preferred composition for intravenous, cutaneous, or subcutaneous injection typically contains an isotonic vehicle.
  • BET inhibitors can be readily combined with pharmaceutically acceptable carriers well-known in the art. Such carriers enable the active agents to be formulated as tablets, pills, dragees, capsules, liquids, gels, syrups, slurries, suspensions and the like, for oral ingestion by a subject to be treated.
  • Pharmaceutical preparations for oral use can be obtained by adding the BET inhibitor to a solid excipient, optionally grinding the resulting mixture, and processing the mixture of granules, after adding suitable auxiliaries, if desired, to obtain tablets or dragee cores. Suitable excipients include, for example, fillers and cellulose preparations. If desired, disintegrating agents can be added.
  • a BET inhibitor can be formulated for parenteral administration by injection, e.g., by bolus injection or continuous infusion.
  • Formulations for injection can be presented in unit dosage form, e.g., in ampules or in multidose containers, with an added preservative.
  • the compositions can take such forms as suspensions, solutions, or emulsions in oily or aqueous vehicles, and can contain formulatory agents such as suspending, stabilizing, and/or dispersing agents.
  • compositions for parenteral administration include aqueous solutions of the active agent in water-soluble form.
  • suspensions of a compound can be prepared as appropriate oily injection suspensions.
  • Suitable lipophilic solvents or vehicles include fatty oils or synthetic fatty acid esters.
  • Aqueous injection suspensions can contain substances which increase the viscosity of the suspension.
  • the suspension also can contain suitable stabilizers or agents that increase the solubility of the compounds and allow for the preparation of highly concentrated solutions.
  • a BET inhibitor can be in powder form for constitution with a suitable vehicle, e.g., sterile pyrogen-free water, before use.
  • an article of manufacture or kit including reagents for detecting the expression level of an eRNA transcribed from a myc-associated enhancer element in a sample is provided.
  • the kit contains reagents for performing RNAseq, microarray analysis, direct RNA sequencing, in situ hybridization, or quantitative real-time PCR.
  • the kit contains instructions for using the reagents.
  • the kit contains instructions for performing any of the methods of the present disclosure.
  • the article of manufacture or kit typically includes a container and a label or package insert on or associated with the container.
  • kits may comprise a carrier means being compartmentalized to receive in close confinement one or more container means such as vials, tubes, and the like.
  • the containers may be formed from a variety of materials such as glass or plastic.
  • the container holds a composition which is by itself or combined with another composition effective for performing a nucleic-acid based detection assay.
  • the label or package insert indicates that the composition is used for performing a nucleic-acid based detection assay.
  • Each of the container means comprises one of the separate elements to be used in the method.
  • one of the container means may comprise a probe that is or can be detectably labeled.
  • Such probe may be a polynucleotide specific for an eRNA.
  • the kit may also have containers containing nucleotide(s) for amplification of the target nucleic acid sequence and/or a container comprising a reporter-means, such as a biotin-binding protein, such as avidin or streptavidin, bound to a reporter molecule, such as an enzymatic, florescent, or radioisotope label.
  • a reporter-means such as a biotin-binding protein, such as avidin or streptavidin
  • kits of the present disclosure will typically comprise the container described above and one or more other containers comprising materials desirable from a commercial and user standpoint, including buffers, diluents, filters, needles, syringes, and package inserts with instructions for use.
  • kits of the present disclosure have a number of embodiments.
  • a typical embodiment is a kit comprising a container, a label on said container, and a composition contained within said container; wherein the composition includes reagents for in situ hybridization, RNAseq, microarray, direct RNA sequencing, or quantitative real-time PCR, the label on said container indicates that the composition can be used to evaluate the presence of eRNA in at least one type of cancer cell, and instructions for using the reagents for evaluating the presence of eRNA in at least one type of cancer cell.
  • the kit can further comprise a set of instructions and materials for preparing a tissue sample and applying reagents to the same section of a tissue sample.
  • the kit includes a BET inhibitor.
  • Other optional components in the kit include one or more buffers (e.g. , block buffer, wash buffer, substrate buffer, etc), other reagents such as substrate (e.g. , chromogen) which is chemically altered by an enzymatic label, epitope retrieval solution, control samples (positive and/or negative controls), control slide(s) etc.
  • CCAT1 is a cMYC super-enhancer template RNA that predicts BET sensitivity in colorectal cancer
  • CIMP(+) colon cancers were found to be extremely dependent on BET activity for cMYC transcription.
  • An integrated transcriptomic and chromatin immunoprecipitation sequencing (ChlP-seq) analysis identified Colon Cancer Associated Transcript 1 (CCAT1; also known as LOC100507056) as a distinct long noncoding RNA (IncRNA) transcribed off the colon cancer cMYC super- enhancer element. Strikingly, CCAT1 expression predicted JQ1 sensitivity and BET- mediated cMYC regulation.
  • gRNA target sequences were designed using a previously developed algorithm. This algorithm software identifies gRNAs that have the highest probability of disrupting the targeted gene, while minimizing potential off-target effects.
  • Refseq RNAs were grouped by Entrez gene id to identify isoforms for each gene in the target set (Pruitt, K.D., et al. Nucleic Acids Res 42, D756-763 (2014)).
  • Gmap was used to align Refseq RNAs to the human genome (hgl9) to identify exons (Wu, T.D. & Watanabe, C.K. Bioinformatics 21, 1859-1875 (2005); Karolchik, D., et al.
  • the gRNA candidate set consisted of 20-mers on either strand flanked at the 3' end by the required PAM (-NGG) entirely contained in an exon in the gene of interest. A 5' G was not required because the 5'-most base would be replaced by G in the final gRNA.
  • the isoform coverage of each candidate gRNA and its proximity to the most distant CDS start in the isoform set was determined. Candidates not in the first 25% of the coding region (CDS) or within 20 bases of the CDS start were eliminated.
  • off-targets for a candidate gRNA were defined as 20-mers flanked by 3' NGG having zero or one mismatch in the 11 3'-most bases, and 4 or fewer mismatches in the 9 5'- most bases. Each off-target was classified as "exonic,” i.e., located anywhere in an exon of another gene, or "genomic.” A gRNA candidate was eliminated if it had more than 15 genomic off-target hits, or had any off-target site within 500 kb on the same chromosome. Each potential off-target was scored according to the location and number of mismatches. The more distal the first mismatch from the 3' end (PAM), the greater the penalty; the fewer the mismatches, the greater the penalty.
  • gRNA candidates were ranked by smallest total off-target penalty first (best off-target profile). The top 20 gRNA candidates were displayed, along with detailed off-target information, isoform coverage, and location relative to the CDS start.
  • gRNAs were cloned into the pLK02 (Sigma; SHC201) lentiviral plasmid as oligonucleotides or by site directed mutagenesis mediated insertion of 19-mer sequences (Genscript). Each gRNA clone was sequenced verified.
  • a human codon optimized Cas9 was cloned into pENTR3C dual selection vector (Invitrogen) and Gateway recombined into the lentiviral mammalian expression vector pLenti7.3 (Invitrogen). Lentiviral transduction of RKO cells was conducted at an MOI>l. Stably expressing Cas9 cells were collected 1 week after infection by FACS analysis using the GFP selectable marker.
  • Lentivirus production and infection was carried out as previously described (Adler, A.S., et al. Cancer Res 72, 2129-2139 (2012)).
  • lentivirus was generated in 96-well plates. 293T cells were seeded at 55,000 cells/well 18 hours prior to transfection. Cells were subsequently transfected with the pLK02-gRNA constructs along with pCMV-VSVG and pCMV-8.9 using Lipofectime 2000 (Invitrogen). Six hours after transfection, the media was changed to 200 ⁇ 1 of fresh growth media. Viral supernatant was harvested 48 hours after transfection. CRISPR high throughput arrayed cell viability screen
  • RKO-Cas9 cells were seeded (750 cells/well) 18 hours prior to infection in 96 well plates in media containing 8 g/ml polybrene. Virus particles were added to cells at an average MOI of 3-5 and spin infected at room temperature (1800 rpm, 30 minutes). Stable integration of gRNAs was selected with 2 g/ml puromycin starting 48 hours after infection. This was accomplished by a media change. To control for lentiviral infection, the primary screen was performed in duplicate for cells receiving puromycin and in singlet for cells not receiving puromycin. Infection and media changes were carried out using robotics (Oasis CB 650; Dynamic Devices).
  • Cell proliferation was measured 7 days after infection using CellTiter-Glo (CTG; Promega). Negative controls (Firefly Luciferase gRNAs) and positive controls (PLK1 gRNAs) were present on each plate in columns 1 and 7.
  • HDAC1 Cell Signaling; 5356S
  • CHD1 Cell Signaling; 4351S
  • PYG02 Epidermal
  • BRD4 Epidermal Deformation: 5716-1; Bethyl: A301-985A100; Cell Signaling: 12183
  • BRD3 Bethyl: A302-368A
  • BRD2 A302-583A
  • KAT8 Bethyl; A300- 992A
  • AURORA B BD Biosciences; 611082
  • KDM3B Sigma; HPA016610-100ul
  • B- Catenin Cell Signaling; 8480S
  • NSD2 Bethyl; A303-093A
  • EZH2 Cell Signaling; 5246
  • cMYC Epidermal
  • ACTIN MP Biomedicals; 691002
  • TUBULIN Sigma; T6074
  • BRD4 gRNAs targeting the 5 prime end of BRD4 targeting the 5 prime end of BRD4 (target sequences:
  • TTGGTACCGTGGAAACGCC and AAGATCATTAAAACGCCTA were cloned into pLK02 (Sigma; SHC201) based on published strategy (Mali (2013)).
  • BRD4 knockout cells were generated by transiently co-transfecting pTKneo-Cas9 and the gRNAs using
  • Lipofectamine LTX (Invitrogen). Untransfected cells were eliminated with a 24 hour Puromycin treatment (2 ⁇ g/ml) two days after transfection. Clonal populations were isolated by FACS in 96 well format and screened by immunofluorescence (using Epitomics: 5716-1 antibody) to identify BRD4 knockout cells. Knockout cells were confirmed by immunoblot analysis. Similarly, for BRD4 long isoform specific deletion a target gRNA (target sequence: AAAGAAGGGGCACCCCGGG) was cloned and transfected into cells as above. Clonal knockout cells were screened by immunofluorescence (using Bethyl: A301-985A100 antibody) and confirmed by immunoblot analysis.
  • target gRNA target sequence: AAAGAAGGGGCACCCCGGG
  • Xenograft tumor studies were carried out essentially as described (Adler, A.S., et al. Cancer Res 72, 2129-2139 (2012)). Briefly, HT-29 and HCT-116 cells were infected with doxycycline inducible pHUSH-shRNAs targeting BRD4 or NTC control and selected with 2 ⁇ g/ml puromycin for stable integration. Target sequences shBRD4-l (aggaagaggacaagtgcaa) and shBRD4-2 (agaagggagtgaagaggaa) were used. For each cell line, 5 x 106 cells were injected subcutaneously into the backs of female NCr nude mice (Taconic) to initiate tumor growth.
  • mice Once tumors reached 200 mm in size, hairpin expression was induced with 0.5 mg/ml doxycycline (or sucrose as control). A subset of mice was sacrificed after 7 days of doxycycline treatment to monitor shRNA efficiency. Tumor volume and body weight were measured on remaining mice every 3-4 days until the end of the study.
  • cell lines were defined as sensitive or resistant based on a 30%- and 70%-quantile cutoff, respectively.
  • genomic feature profiles for the classified sensitive (ATRFLOX, HT-29, RKO, CW-2, HCT15, SW48) and resistant (LS 180, SW480, LS-174t, GP5d, SW948, Colo-741) cell lines total copy number (26,347 features), expression (26,225 features) and mutation (314 features) data were retrieved (Klijn, C, et al. Nat Biotechnol 33, 306-312 (2015)).
  • RNAseq R package was applied to estimate size factors and obtain dispersion estimates for the associated RNAseq data (Anders, S. & Huber, W. Genome Biol 11, R106 (2010)). Gene expression was quantified with variance- stabilized counts. DNA methylation data yielded an additional 35,788 features per cell line. For both expression and methylation data, the classification approach was restricted to the 2000 most variable instances. Furthermore, 14 different measures for CIMP classification including established gene expression signatures (Ogino (2007)) were employed. EMT and MSI status, doubling time, seeding density and alteration status of canonical pathways formed eight additional features.
  • RNA-seq Transcriptome sequencing
  • RNA-seq reads were then mapped to the human genome (NCBI Build 37) by using GSNAP (Wu and Nacu 2010), allowing a maximum of three mismatches per 75 bp sequencing end, where 65-83% of reads were uniquely mapped to the human reference genome.
  • the differential gene expression was performed with DESeq both of which are based on a negative binomial distribution model. For analysis of differentially expressed genes, the following cutoffs were used: 2 fold change, median RPKM >0.1, and adjusted p value ⁇ 0.01. Clustering was performed with Cluster 3.085 and heatmap representation of differentially expressed genes was generated using Java Tree View
  • GSEA Gene set enrichment analysis
  • GSEA87 was performed using JQ1/DMSO log2 fold change for each cell line.
  • An FDR cutoff of 5% was used.
  • Sonicated DNA was immunoprecipitated with 2 ⁇ g of rabbit anti-H3K27ac antibody
  • DNA samples were used directly to prepare the indexed Illumina library.
  • ChIP DNA (3 - lOng) or the Input DNA (250-300 ng) was subjected to the standard Illumina library preparation. The process starts from end repair to convert the overhangs into blunt ends. A single "A" nucleotide was then added to the 3 'ends of the blunt fragment followed by ligating the standard Illumina adapter to the DNA fragments. The adapter-ligated DNA fragments were then enriched with PCR amplification. Standard Illumina barcode was also added to each library during the library preparation process. The completed libraries were then checked and quantified with Qubit, Bioanalyzer and qPCR. Twenty libraries were then clustered onto the flow cell with 10 libraries in one lane. The libraries were then sequenced with HiSeq2500 using 75 bp, single end read.
  • Bioinformatics analysis includes de-multiplexing and filtering followed by alignment to the human genome (hgl9) using the BWA algorithm (default settings). Duplicate reads were removed and uniquely mapped reads were normalized for total read number per sample.
  • the spike-in normalization was performed by equalizing the Drosophila tag counts across all samples so that the final tag counts were based off of the sample containing the lowest number of Drosophila tags. Then the human tags counts for all samples were proportionally scaled based on the ratios used to adjust the drosophila tag counts. Scaling to the target tag number was performed by randomly removing excess tags. [0163] Alignments were extended in silico at their 3 '-ends to a length of 200 bp, which is the average genomic fragment length in the size-selected library, and assigned to 32-nt bins along the genome. The resulting histograms (genomic "signal maps”) were stored in bigWig files.
  • MACS peak locations and BAM files were used as input into the ROSE software to identify super-enhancers (Whyte (2013); Loven, J., et al. Cell 153, 320-334 (2013)).
  • the default stitching distance of 12.5 kb was used and promoters were not excluded.
  • Super- enhancers were annotated to genes if they fell within 50 kb upstream or downstream of the gene.
  • Heatmap representation of drosophila chromatin normalized BRD4 binding at super- enhancer regions was generated using seqplots (Github). Overlapping super-enhancer regions were grouped into active regions defined by the most upstream start position and the most downstream end position (the union of overlapping intervals).
  • BRD4 tags for each sample were normalized using drosophila chromatin input method while H3K27ac tags and input tags were normalized to a specific tag number using random downsampling. Coverage was calculated across 10 bp bins using BEDTools
  • Sonication was performed in sonication buffer (0.1% SDS, 1 mM EDTA, 10 mM Tris-HCl, pH 8.0) on a Covaris E220 platform (duty: 20%, peak incident power: 175 W, cycles per burst: 200, time: 30 min).
  • An aliquot of chromatin was quantified and 60 ug of sonicated DNA was immunoprecipitated with 10 ⁇ g of rabbit anti-Brd4 antibody (Bethyl Laboratories, A301-895, Lot. A301-985A100-4) and 100 ⁇ of protein A beads. Complexes were washed and eluted from beads with SDS buffer.
  • ChIP DNA and input DNA were subjected to RNase and proteinase K treatment and crosslinks were reversed by incubation at 65°C.
  • DNA was purified using QIAquick PCR purification kit (Qiagen). qPCR was performed with TaqMan Universal PCR Master Mix (Applied Biosystems) with custom designed primers and probe for CCAT1 (forward: 5'- CAAAGGTCCCAATTTCACACT; reverse: 5'- AC AACTGTGCTCCTGAATGC ; probe: 5'-
  • TCCAGTTGGGTTCTCTTTCCTTTGCT and a negative control locus on chromosome 4 (forward: 5'- G ATGGCCC AGTGTAAGC ATT ; reverse: 5'- TGACTCTGACGATAGCTCTCAAA; probe: 5'- AATGTCCTAGTTTCATAAATTACGGTCACTCTATCTGG).
  • TMAs were constructed as above with one core of normal mucosa and three cores of adenocarcinoma per patient. Approval for the use of this tissue was provided by the local research ethics committee.
  • ISH Non-isotopic in situ hybridization
  • Gene-specific probe for detection of human CCAT1 RNA Affymetrix; VA1- 17802
  • target region 2-2696 in Genbank accessions NR_108049.1 was used on tissue samples.
  • a probe set to Bacillus subtilis dihydropicolinate reductase (dapB) VFl-11712
  • target region 1363-2044 in Genbank accession L38424 was used as a negative control.
  • HRP Horseradish peroxidase
  • TSA Plus DIG stock solution digoxigenin
  • Amplification Diluent and applied to sections and incubated for 10 minutes at room temperature. This was followed by incubation with anti-DIG-AP (Roche 11093274910) diluted 1:500 in TNB blocking buffer with 4% lamb serum (Gibco, 16070-096) for 30 minutes at room temperature.
  • Vulcan Fast Red substrate (Biocare, FR805S) was used for chromogenic detection.
  • genomic DNA was isolated with the DNeasy blood & tissue kit (Qiagen). Quantitative PCR for cMYC copy number was performed with the TaqMan genotyping master mix using Taqman copy number probes (Applied Biosystems). For colon cell lines and tumors, samples were normalized to copy number at the TERT locus, which is rarely amplified or deleted in colon cancer
  • An arrayed CRISPR loss-of-function screen identified BRD4 as a critical regulator of colon cancer growth.
  • FIG. 1A Introduction of the Cas9 nuclease and guide RNAs (gRNA) was carried out in a two-step process (FIG. 1A). Lentivirus was utilized to generate RKO cells that stably express Cas9, and cells were subsequently transduced with relevant gRNAs. To examine the specificity and validate this CRISPR system, RKO (wild-type) and RKO-Cas9 cells were infected with gRNAs targeting the firefly lucif erase gene and the mitotic kinase PLKl. Overall, five independent gRNAs targeting PLKl consistently reduced cell viability in the Cas9 expressing cells, but did not hinder the growth of cells lacking Cas9 (FIG. IB). Three non-targeting luciferase gRNAs did not impact cell proliferation.
  • a gRNA library targeting the 5' exons of over 200 genes involved in epigenetic regulation ('Epi200 library') was designed with a median coverage of 5 gRNAs per gene.
  • High throughput cloning and viral production was employed to construct an arrayed lentiviral library containing over 1000 gRNAs.
  • the library was subsequently transduced into RKO-Cas9 cells, infected cells were selected with puromycin 48 hours after infection, and cell viability was measured 7 days after transduction (FIGS. 1C&D).
  • phenotypic effects were correlated with genotypic activity for each set of gRNAs.
  • Robust gRNA-mediated protein depletion was detected for BRD4, KAT8, CHDl, HDACl, and AURKB by both immunoblot and immunofluorescence microscopy and positively correlated with the observed cell growth effects (FIGS. 1E& F and FIGS. 2A-D). More than half of all gRNAs tested by
  • the long isoform of BRD4 is critical for colon cancer cell proliferation.
  • BRD4 was chosen for further analysis.
  • BRD4 small molecule inhibitors have entered clinical trials in several hematological malignancies (Shi, J. & Vakoc, C.R. Mol Cell 54, 728- 736 (2014)).
  • As investigations of BRD4 in colon tumors have been limited (Rodriguez, R.M., et al. J Mol Med (Bed) 90, 587-595 (2012); Hu, Y., et al. Int JMol Sci 16, 1928-1948 (2015)), BRD4 activity in colon cancer was evaluated.
  • BRD4 transcript variants Two alternatively spliced BRD4 transcript variants have been described, a long (BRD4-LF) and short isoform (BRD4-SF) (Floyd, S.R., et al. Nature 498, 246-250 (2013); Wang, R., Li, Q., Heifer, CM., Jiao, J. & You, J. J Biol Chem 287, 10738-10752 (2012)).
  • BRD4 expression was characterized by
  • BRD4-LF was consistently expressed in colonic cancer cell lines compared to BRD4-SF (FIG. 3C). While both BRD4 isoforms encode bromodomains, the BRD4-LF has been more strongly implicated in transcriptional regulation due to its C-terminal p-TEFb binding motif (Yang, Z., et al. Mol Cell 19, 535-545 (2005); Jang, M.K., et al. Mol Cell 19, 523-534 (2005)).
  • isoform specific BRD4 expression was reconstituted by delivery of BRD4-LF or BRD4-SF splice variants to BRD4-null colon cancer cells. While BRD4-SF was unable to restore growth, expression of BRD4-LF rescued the growth defect of BRD4 knockout cells to wild-type levels (FIGS. 3H& I and FIG. 4A). BRD4 constructs containing bromodomain inactivating mutations failed to rescue the growth defect.
  • CTM pTEFb binding C-terminal motif
  • CRISPR was used to ablate the BRD4-LF isoform in colon cancer cells. Analysis of four independent BRD4-LF specific nullizygous HCT-116 cell lines showed reduced cell proliferation (FIG. 3J&K). These data indicate an important role for the BRD4-LF in colon cancer cell proliferation.
  • BRD4 loss reduced colon tumor growth and induced cellular differentiation in vivo.
  • BRD4 and in particular the BRD4-LF variant, have been implicated in maintaining embryonic pluripotency.
  • BRD4 inhibition has been shown to induce differentiation effects in hematological malignancies (Alsarraj, J., et al. Cancer Res 71, 3121-3131 (2011); Zuber, J., et al. Nature 478, 524-528 (2011)).
  • a doxycycline inducible shRNA system was used to deplete BRD4 in implanted tumors (Gray, D.C., et al. BMC Biotechnol 7, 61 (2007)).
  • BET inhibitors preferentially impaired CIMP(+) colon cancer growth.
  • GSEA Gene set enrichment analysis
  • cMYC plays a critical role in colon cancer initiation and progression (Fearon, E.R. & Dang, C.V. Curr Biol 9, R62-65 (1999); Sansom, O.J., et al. Nature 446, 676-679 (2007)), cMYC protein levels were examined by immunoblot analysis after BET inhibition in colon cancer cell lines. cMYC protein was dramatically reduced in CIMP(+) cell lines 24 hours after JQ1 treatment compared to CIMP(-) colon cancers (FIGS. 6H& I).
  • CCAT1 is a BET transcriptional target gene and a marker of BET activity near the cMYC locus.
  • RNA-seq transcriptomic
  • ChlP-seq genomic genomic
  • the CCAT1 transcript was one of the most highly down-regulated genes in CIMP(+) cells and its genomic locus ranked as one of the densest BRD4 enriched enhancers (i.e. 'super-enhancer') in CIMP(+) colon cancer (FIG. 11B).
  • the CCAT1 transcript is located within a demarcated super-enhancer, 500 kb upstream of the cMYC promoter. Both BRD4 binding and H3K27ac levels were enriched at the CCAT1 associated super-enhancer in the CIMP(+) colon cancer cell lines, indicating that its activation may be context specific (FIG. l lC and FIG. 12A-E).
  • CCAT1 is a long noncoding RNA (IncRNA) that is expressed in colon, gastric and gallbladder cancer (Ma, M.Z., et al. Cell Death Disease 6, el583 (2015); Mizrahi, I., et al. J Cancer 6, 105-110 (2015); Xiang, J.F., et al. Cell Res 24, 513-531 (2014)). While CCAT1 has been reported to regulate cMYC expression (Xiang (2014)), its relationship to BET activity has not been previously reported.
  • CCAT1 RNA levels were higher in the CIMP(+) cell lines used in the RNA-seq analysis and correlated with the amount of BRD4 binding and H3K27ac at the CCAT1 -associated super-enhancer (FIGS. 11C& D).
  • CCAT1 expression was sensitive to JQ1, indicating that it was a direct transcriptional target of BRD4 (FIG. 1 IE).
  • JQ1 treatment preferentially reduced cMYC expression in CCAT1 expressing CIMP(+) cells (FIG. 11F).
  • CCAT1, PC AT, LOC728724 are BRD4 transcriptional targets and markers for sensitivity to BET inhibitors.
  • RNA polymerase II RNA polymerase II
  • BRD4 has been shown to regulate eRNA expression in murine cells (Kanno, T., et al. Nat Struct Mol Biolll, 1047-1057 (2014)).
  • H3K27ac was associated with the presence of two distinct eRNAs, PCAT1 (Prostate Cancer Associated Transcript 1) and LOC728724 in prostate and T-ALL, respectively (FIG. 13A) (Mansour, M.R., et al. Science 346, 1373-1377 (2014); Asangani, I.A., et al. Nature 510, 278-282 (2014)). Both leukemia and prostate cells have been reported to be sensitive to BET inhibition. To determine whether the expression of these eRNAs was restricted to cancer type and super-enhancer activation, the expression of CCATl, PCATl and LOC728724 was examined across different cancer indications using RNA-seq data from The Cancer Genome Atlas (TCGA).
  • TCGA Cancer Genome Atlas
  • eRNAs showed distinct tumor specificity, with LOC728724 expression restricted to leukemia and PCATl showing preferential expression in prostatic carcinoma. While CCATl expression has been previously linked to colon cancer, it was also highly expressed in a subset of lung, pancreatic and gastric tumors (FIG. 13B).
  • cMYC RNA levels were measured in CCATl -high and
  • CCATl -low cell lines following a 24 hour JQ1 treatment. 14 of 16 CCATl high cell lines (CCATl RPKM threshold>1.0) showed 50% or greater reduction in cMYC levels.
  • CCATl predicted cell line sensitivity to JQ1.
  • Colon, lung, gastric and pancreatic cell lines were treated for 3 days with JQ1 and relative EC50 values were calculated.
  • JQ1 and relative EC50 values were calculated.
  • all other tumor types pancreatic, lung and colon cells
  • exhibited a significant correlation between CCAT1 expression and JQ1 sensitivity FIG. 13D, FIG. 15B-E.
  • PCAT1 FIG. 15F-H
  • LOC728724 FIG. 15I& J
  • CCAT1 and other eRNAs serve as predictive biomarkers to identify tumors that utilize BET-mediated cMYC transcription for tumor growth.
  • cMYC upregulation in colon cancer can occur via numerous mechanisms, including locus amplification, mutation, super-enhancers, and post-translation modifications.
  • the ability of CCAT1 expression to identify tumors that rely on a super-enhancer to drive cMYC expression was evaluated.
  • a CCAT1 in situ hybridization assay was developed (FIG. 16A and FIG. 17A&B).
  • CCAT1 expression was examined directly in colon tumors (FIG. 16B).
  • the array-based CRISPR library yielded robust and reproducible target depletion and phenotypic response. While advantages exist to both arrayed and pooled screening platforms (Boettcher, M. & Hoheisel, J.D. Curr Genomics 11, 162-167 (2010)), the screen described herein represents an important step in characterizing the CRISPR technology in an arrayed platform.
  • BRD4 was pursued, as BRD4 inhibitors have entered clinical trials in several hematological malignancies (Shi, J. & Vakoc, C.R. (2014)). Consistent with the oncogenic effects of BRD4 in other malignancies, genetic or pharmacological inhibition of BRD4 reduced cancer proliferation and abrogated tumor growth in colon cancer xenograft models. BRD4 loss led to tumor differentiation in vivo with crypt-like structures formed in the HT-29 xenografted model. Colon cancer has long been postulated to be a stem-cell driven disease.
  • Colon tumors characterized by a high degree of CpG island methylation are both biologically and clinically distinct (Lao, V.V. & Grady, W.M. (2011); Suzuki, H., Yamamoto, E., Maruyama, R., Niinuma, T. & Kai, M. Biochem Bioph Res Co 455, 35-42 (2014)).
  • CIMP-ness has been correlated with a poor patient outcome and resistance to chemotherapy (Phipps, A. I., et al. Gastroenterology 148, 77-87 e72 (2015)).
  • a significant correlation between JQ1 sensitivity and CIMP positivity was observed in colon cancer cells.
  • JQ1 JQ1-induced cMYC expression specifically in CIMP(+) cells.
  • CIMP(+) tumors have a low level of CIN and hence disomy at the cMYC locus (Cheng, Y.W., et al. Clin Cancer Res 14, 6005-6013 (2008)).
  • the preferential effect of JQ1 on cMYC in this context indicates that cancers with cMYC disomy may be more dependent on super-enhancers and other epigenetic mechanisms to drive cMYC expression.
  • the array-based CRISPR screen described herein identified the BRD4 oncogene as a critical driver of proliferation and the dedifferentiated state in colon cancer.
  • CCATl a super-enhancer RNA, predicted growth sensitivity to BET inhibitors and marked cancer cells utilizing BRD4 to drive MYC expression.

Abstract

L'invention concerne des méthodes de traitement d'un sujet souffrant d'un cancer à l'aide d'un inhibiteur BET (bromodomaine et domaine terminal), des procédés de sélection d'un sujet pour un traitement à l'aide d'un inhibiteur BET, des procédés permettant de prédire la réponse d'un sujet souffrant d'un cancer à un inhibiteur BET, des procédés permettant de communiquer la probabilité de réponse d'un sujet souffrant d'un cancer à un inhibiteur BET, et des procédés permettant de moduler le traitement d'un sujet subissant un traitement par inhibiteur BET contre le cancer. Les procédés décrits comprennent les étapes consistant à effectuer un essai de détection à base d'acide nucléique pour détecter le niveau d'expression d'un ARNa (activateur) transcrit à partir d'un élément activateur associé à un myc dans un échantillon contenant des cellules cancéreuses du sujet et à déterminer le niveau d'expression de l'ARNa dans les cellules de l'échantillon.
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WO2019113260A1 (fr) * 2017-12-05 2019-06-13 The Regents Of The University Of Colorado A Body Corporate Cibles génomiques d'inhibiteurs de l'histone désacétylase (hdaci) et leurs méthodes d'utilisation
WO2020227213A1 (fr) * 2019-05-03 2020-11-12 Icahn School Of Medicine At Mount Sinai Procédés de régulation et d'amélioration de la santé cérébrale
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