WO2019113260A1

WO2019113260A1 - Genomic targets of histone deacetylase inhibitors (hdaci) and methods of use thereof

Info

Publication number: WO2019113260A1
Application number: PCT/US2018/064142
Authority: WO
Inventors: Xuedong Liu; Gilson J. SANCHEZ
Original assignee: The Regents Of The University Of Colorado A Body Corporate
Priority date: 2017-12-05
Filing date: 2018-12-05
Publication date: 2019-06-13

Abstract

The present invention relates in some aspects to HDAC inhibitor dose-responsive transcripts, enhancers, super-enhancers and noncoding RNAs and related compositions, methods and agents that are useful for targeting genes that are responsible for cancer cell proliferation, differentiation and death for cancer therapeutics.

Description

GENOMIC TARGETS OF HISTONE DEACETYLASE INHIBITORS (HD AC I) AND METHODS OF USE THEREOF

This application claims the benefit of and priority to U.S. Provisional Application No. 62/594,952 filed December 5, 2018. The entire specification and figures of the above-mentioned application is hereby incorporated, in its entirety by reference.

GOVERNMENT INTEREST

This invention was made with US government support under grant numbers CA107098 and AR068254 awarded by the National Cancer Institute and National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health respectively. The government has certain rights in the invention. This invention was also made with Colorado state government support under grant number 14BGF-28 awarded by the Bioscience Discovery Evaluation Grant Program.

TECHNICAL FIELD

The present invention relates novel methods for treatment of diseases modulated by super-enhancers and compositions for the same. In certain embodiments, the invention specifically relates to novel therapeutic aspects of HD AC inhibitors. In other embodiments, such therapeutics effects may include dose combinations, dose-responsive transcripts, enhancers, super-enhancers and non-coding RNAs, and related compositions, methods and agents that are useful for targeting genes that are responsible for cancer cell proliferation, differentiation, and death for cancer therapeutics.

BACKGROUND

Super-enhancers are large clusters of transcriptionally active regions of DNA that drive the expression of genes that control cell identity. Super-enhancers become dysregulated in multiple disease states, including but not limited to, cancer. Super-enhancers recruit transcription factors, cofactors, chromatin regulators, signaling enzymes (e.g., kinases), and the transcriptional machinery (e.g., RNA polymerase II) that form a large complex that regulates the expression of multiple genes simultaneously that are not necessarily in close proximity in regard to the linear form of DNA. Super-enhancers allow cells to have efficiencies in regulating groups of genes that work in concert to determine or maintain cell identity. It has been demonstrated that cancer cells reprogram super-enhancer complexes to change the transcriptional activity of a cancer cell leading to oncogenesis, metastasis, and progression of the disease. In fact, it has been postulated that many diseases, even outside of cancer, are ultimately a result of malfunctioning super enhancer complexes.

Known components of the super-enhancer complex include cyclin-dependent kinases (e.g., Cdk9), bromo and extra terminal (BET) domain proteins (e.g., Brd4), histone deacetylases (HDACs), histone acetyltransferases (e.g., p300), histone demethylases (e.g., Lsdl), histone methyltransferase (e.g., DotlL), and others. These components are generally involved in typical transcriptional regulation. However, inhibiting components of super-enhancers function has been shown to have a more profound effect on super-enhancer controlled genes as compared to genes controlled by typical enhancer elements. One of the possible reasons for this observation is the enrichment of transcriptional and chromatin modifying proteins at super-enhancers as compared with typical enhancers. For instance, the Mediator complex (which includes Cdk8) and Brd4 are present at both super-enhancers and typical enhancers. However, the amount of Mediator at a super-enhancer compared with a typical enhancer has been found to be in excess of 25-fold. Similarly, the level of Brd4 at super-enhancers has been shown to be approximately 20-fold higher than at typical enhancers.

Genes expressed from super-enhancers have been shown to mediate disease progression in some cancers. For instance, multiple myeloma (MM) tumor cells often have a translocation that places a super-enhancer element adjacent to the MYC gene. Similar alterations have been found in patients with acute lymphoblastic leukemia (T-ALL), lung cancer, pancreatic cancer, colorectal cancer, breast cancer, chronic myelogenous leukemia (CML), glioblastoma, lymphoblastoid, cervical cancer, and prostate cancer.

As noted above, secondary modifications of histone proteins play an important role in the regulation of expression of super-enhances. For example, reversible lysine acetylation is important for homeostatic regulation of many cellular processes. The lysine residues in the N- terminal tail of histones are tightly regulated by acetylation and deacetylation modifications catalyzed by enzymes known as histone acetyltransferases (HATs) and histone deacetylases (HDACs) respectively. It has been long recognized that HDACs are predominantly involved in transcriptional repression as loss of histone lysine acetylation, a hallmark of transcriptionally active chromatin, decreases chromatin accessibility. HDACs often exist as the catalytic module of chromatin remodeling machineries, including CoREST, NuRD, Sin3, and N-CoR. These molecular complexes target specific genomic regions through sequence specific interactions mediated by non-histone proteins such as transcription factors, methyl binding proteins (MBDs), or other epigenetic modifier enzymes such as DNA and histone methyltransferases (DNMTs or HMTs).

Deregulation of histone post-translational modifications have been observed in human tumors. Indeed, transcription of tumor suppressor genes is frequently silenced in tumor cells due the hyper or aberrant activity of HDACs. Accordingly, HDACIs are used clinically for the treatment of a subset of hematologic tumors. There are 18 HD AC enzymes in the human genome, belonging to four distinct classes . Class I, II, and IV enzymes contain a zinc (Zn2+) ion in their catalytic site and are inhibited by pan-HDACIs such as Vorinostat, Belinostat, or Panobinostat. Class III comprises the mechanistically distinct NAD+-dependent sirtuins. Aberrant recruitment of HDACs, as seen in cells with chromosomal translocations or mutations in certain transcription factors, contribute to development of tumors. Hence, HDACIs are used to de-repress silenced genes in cancer treatment. The therapeutic benefits of HD AC inhibition are thought to be associated with their chromatin remodeling activities and the resulting transcriptional reprogramming changes. However, exactly what type of chromatin remodeling activities or resulting chromatin mark changes are responsible for HDACI-regulated gene expression are still not fully understood. As expected, previous transcriptome analysis in the presence of HDACIs revealed the drastic up-regulation of a large number of genes.

Surprisingly, transcription of many genes is also repressed by HDACI exposure. The opposing functions of HDACIs on transcription are difficult to reconcile. Genome-wide HD AC localization analyses indicate that HDACs are associated strongly with actively transcribed genes in human cells. Divergent activities of HDACIs on transcription could be a result of deacetylation activity towards different classes of targets. For example, non-histone substrates, including certain transcription factors, are activated when deacetylated. A recent study suggests that HDACIs target the transcription elongation complex and cause redistribution of other elongation factors across the genome.

Despite the clinical efficacy of HD AC inhibition for certain tumors, it has been generally challenging to understand the disparate activities of HDAC inhibitors in vitro and in vivo. As numerous biological activities of HDAC inhibitors are dose-dependent, it is imperative to characterize dose-dependent changes at molecular and genome-wide levels. The importance of HDACIs as anticancer therapies warrants more in-depth understanding of their dose-dependent activities in transcriptional regulation.

Largazole, a marine natural product discovered in cyanobacteria, is a highly potent Class I, Class lib, and Class IV selective HDACI and displays selective killing of tumor cells. Largazole offers a unique tool to address the mechanism of HD AC inhibition in cancer biology due to its selectivity, superb potency, and minimal off-target activities. Parsing out various mechanisms underlying largazole-induced transcription activation and repression could offer fundamental insights critical for developing superior HDACIs with better clinical efficacy and low toxicity. To this end, the present inventors conducted comprehensive analysis of the specificity and molecular mechanisms of action for HDACIs, such as largazole, in both transformed and non-transformed cell lines.

BET-bromodomain inhibitor JQ1 is a small-molecule inhibitor of BRD4 that can displace BRD4 from histones by competitively binding to its acetylated lysine recognition pocket. The action of JQ1 presents another opportunity to elucidate the mechanism of HD AC inhibition in cancer biology, and in particular the role of BRD4’s interaction with super-enhancer regions of the genome. Another aspect of investigation may include the combinatorial action for HDACIs, such as largazole and JQ1 and their role in BRD4’s role in generation of mRNA transcripts from super-enhancer regions.

DISCLOSURE OF INVENTION(S)

Histone deacetylase inhibitors (HDACIs) are known to alter gene expression by both up- and down-regulation of protein-coding genes in normal and cancer cells. However, the exact regulatory mechanisms of action remain uncharacterized. The present inventors investigated genome wide dose-dependent epigenetic and transcriptome changes in response to HDACI largazole and/or BET-bromodomain inhibitor JQ1 in a transformed and non-transformed cell lines. Exposure to low nanomolar largazole concentrations (<GLo) predominantly resulted in upregulation of gene transcripts whereas higher largazole doses (>GLo) triggered a general decrease in mRNA accumulation. Largazole induces elevation of histone H3 acetylation at Lys-9 and Lys-27 along many gene bodies but does not correlate with up- or down-regulation of the associated transcripts. A higher dose of largazole results in more RNA polymerase II pausing at the promoters of actively transcribed genes and cell death. The most prevalent changes associated with transcriptional regulation occur at distal enhancer elements. Largazole promotes H3K27 acetylation at a subset of poised enhancers and unexpectedly, the present inventors also found active enhancers that become decommissioned in a dose and cell type-dependent manner. In particular, largazole decreases RNA polymerase II accumulation at super-enhancers (SEs) and preferentially suppresses SE-driven transcripts that are associated with oncogenic activities in transformed cells.

The present inventors have shown that largazole selectively inhibits class I and class lib HD AC enzymes at a sub-nanomolar range and causes cytostatic responses in a variety of tumor cell lines. The present inventors performed genome wide studies to identify histone marks and gene signatures whose dose-responsive changes, upon exposure to increasing concentrations of largazole, closely match the GI50 curve of the cytostatic response.

The present inventors have further shown that HDAC inhibitors, such as largazole, induces profound dose-dependent changes in H3K9ac, H3K27ac, H3K4mel, H3K4me2, and perturbs the association of RNAPII with enhancers, promoters, and gene bodies. Low doses of largazole exposure resulted mostly in the up-regulation of gene transcripts whereas mid to high doses lead to more pronounced transcriptional suppression. The present inventors observe a correlation between the effect of largazole on cellular proliferation and transcriptional suppression with its effects on enhancer elements. Thus, the present inventor’s results reveal that largazole causes remodeling of numerous enhancer elements by modulating H3K27ac and retooling the enhancer atlas in a dose dependent manner, and may uncover the cohesin complex as targets of HDAC inhibitors.

Another aspect of the current invention may include the novel therapeutic application of HDACIs, such as largazole, to suppress cohesin proteins/complex as well as CTCF, which in turn modulates expression of SEs and SE-driven gene expression. The present inventors have shown that HDACIs, such as largazole, modulate the expression of lncRNA / LINC. The present inventive technology further relates to the novel use of HDACIs to modulate the expression of long non-coding RNA (lncRNA), as well as their use as effective biomarkers for sensitivity to, and effectiveness of HDACIs.

The present invention further includes the novel use of histone deacetylases inhibitors (HDACIs) to treat a disease state. Specifically, the present disclosure relates to novel systems, compositions, methods, and agents that are useful for modulating expression of super-enhancers (SEs), SE-driven transcripts, and other genes and/or genome targets that may be required for maintenance of a disease state, such as cancer. In particular, the invention relates to the novel use of HDACIs to modulate the expression of enhancer and super-enhancers as a therapeutic treatment for cancer and other disease states. Modulating expression of SEs may be mediated by suppression of cohesin proteins as well as transcriptional repressors, such as, CTCF by HDACIs.

The present inventive technology further relates to the novel use of HDACIs to modulate the expression of long non-coding RNA (lncRNA). The present inventive technology further relates to predictive biomarkers that may be indicative of more effective application of HDACIs and/or HDACI sensitivity in a patient with a disease state such as cancer. In particular, up and down regulation of select biomarkers or biomarker groups may be used as biomarkers for predicting HDACI sensitivity in cell line and patient samples.

The present inventors have further shown that super-enhancer associated transcriptional coactivator BRD4 is an important mediator in the regulation of super-enhancer regions. Another aspect of the present invention includes novel methods, systems, and compositions for the inhibition of BRD4. More specifically, one aspect of the present invention includes the inhibition of BRD4 through combinatorial administration of one or more HDAC inhibitors with BET- bromodomain protein inhibitor JQ1. This inhibition of BRD4 results in the downregulation of various oncogenic genes and transcription factors.

Another aspect of the present invention includes novel methods, systems and compositions for the use of BRD4 as a pharmacodynamic (PD) biomarker. Specifically, in one preferred embodiment, a BRD4 may act as a PD biomarker to evaluate a diseased cell, and preferably, a cancer cell susceptibility to therapeutic treatment by: one or more HDAC inhibitors; one or more HDAC inhibitors provided in combination with one or more BRD4 inhibitors, such as JQ1; or BRD4 inhibitors, such as JQ1.

Another aspect of the current invention may further include the novel methods, systems, and compositions for the use of one or more HDAC inhibitors alone or in combination with one or more BRD4 inhibitors, such as JQ1 to induce alternative splicing through RNA transcription pulsing, which may be caused by RNAPII pausing during transcription of BRD4-respnsive gene transcripts. Such alternative splicing may be detrimental to, for example, cancer cell growth, and may further generate a variety of novel, non-naturally occurring alternatively-spliced (AS) peptides. These AS peptides may further be processed and presented by a treated diseased cell, such as a cancer cell. Such AS peptides may provide novel antigenic epitopes that may allow a host’s immune system to more efficiently, recognize, bind, and destroy a cancer cell.

Another aspect of the current invention may include the use of novel HDACI compounds identified in co-owned US Patent No. US8754050. Specifically, in this preferred embodiment, one or more which described novel largazole analog compounds, having histone deacetylase (HDAC) inhibition properties that may induce one or more of the therapeutic or other cellular effects described herein. Each compounds identified in the ‘050 Patent is specifically incorporated herein by reference.

While the invention has been particularly shown and described with reference to a number of embodiments, it would be understood by those skilled in the art that changes in the form and details may be made to the various embodiments disclosed herein without departing from the spirit and scope of the invention and that the various embodiments disclosed herein are not intended to act as limitations on the scope of the claims. All references cited herein are incorporated in their entirety by reference.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1. Dose-dependent cellular and histone acetylation responses to largazole treatment in HCT116 cells. (A) Quantitative analysis of the cell cycle progression by propidium iodide staining using flow cytometry in HCT116 cells treated with the indicted largazole concentration for 25 h. (B) Histogram showing the percentages of cells in Gl (red), S (blue), and G2 (yellow) phases of the cell cycle as well as subGl fraction (green). (C) Dose-dependent global changes in indicated histone marks upon largazole exposure for 16 h as determined by immunoblotting with antibodies against each histone mark. Total histone H3 was used as a loading control. (D) and (E) Changes in H3K9ac and H3K27ac induced by largazole according to genomic territories. Pie charts illustrate the distribution of H3K9ac and H3K27ac signals (as determined by FStitch) from ChIP-seq experiments in vehicle (DMSO) treated HCT116 cells. Genomic territories are divided by gene bodies (purple), enhancer regions (green), TSS (blue), intergenic locations (orange) and 3’ ends (red). (F) and (G) The log2 fold change ratio for increasing H3K9ac and H3K27ac in each genomic territory with various doses of largazole (nM) exposure.

Figure 2 Distinct H3K9 and H3K27 hyperacetylation responsive patterns upon largazole treatment. (A) A representative genomic snapshot of H3K27ac peaks illustrating different responses of gene bodies to newly acetylated histones. The signal initiates from the TSS (red dotted rectangle) of the FAT1 gene (orange panel) and spreads into the coding region or as in the case of CYP4V2 (purple panel), the preexisting acetylated TSS remains unmodified throughout all largazole dose treatments. Genes that do not show H3K9 or -K27 acetylation at the TSS (green panel) under basal conditions do not associate with the two histone marks as a result of largazole treatment. (B) Number of gene regions associated with the three response categories for H3K27ac (left) and H3K9ac (right). (C) Venn diagram showing the number of genes that exhibit new association with H3K27ac (green), H3K9ac (purple), and those that display both acetylation marks.

Figure 3 Increasing dose of largazole causes more gene suppression than activation and hyperacetylation of gene body territories does not predict higher mRNA accumulation. (A) Total number of genes differentially expressed at each largazole dose treatment showing newly differentially expressed in grey and transcripts that were inherited from a lower dose in black. (B) Differentially expressed transcripts unique to each largazole dose treatment based on DESeq analysis with an adjusted p-v alue cutoff of less than 0.1. Transcripts are shown as a fraction of total elements per dose where those that are upregulated (red) are plotted above the zero line and below those that are downregulated (green). DREM version 2.0 software was used to visualize dynamic transcript changes as a function of largazole dose with a minimal absolute expression fold change of 2. Differentially expressed mRNAs from genes with only (C) H3K27 hyperacetylation, (D) H3K9 hyperacetylation, or (E) those displaying an increase association with both histone marks. (F) Effects of largazole on RNAPII pausing index. Histograms depicting the calculated PI distribution of a group of genes treated with DMSO (blue), 75 nM largazole (green), and 300 nM largazole (red). (G) Contour plots showing Pearson correlation analysis between the calculated pausing indexes under two different largazole treatments. (H) Screen shot of the TFDP1 loci showing total RNAPII ChIP-seq signal from HCT116 cells treated with vehicle (blue), largazole at 75 nM (green) and largazole at 300 nM (red) showing the calculated pausing index. (I) Correlation between pausing index and relative transcript levels (FPKMs). Pearson correlation method was implemented using the ln(PI) and ln(FPKM) values from -2200 transcribable gene regions (grey). The input gene list was generated from gene bodies with a minimum length of 3 kb and that were bound by total RNAPII at the transcription start site, as determined from MACS2 narrow peak calling signal. Overlapping gene regions and genes containing intergenic enhancers were excluded from the analysis. Three categories of transcriptionally regulated genes are shown as representative elements of the data; downregulated (green), upregulated (red), and not changing gene transcripts (orange).

Figure 4 Correlation between histone acetylation signal spread sensitivity along gene bodies and pausing index. (A) Snap shots from UCSC Genome Browser showing H3K27ac ChIP-seq signal over three different gene regions illustrate different dose-dependent acetylation of H3K27; low dose (red), mid dose (green), and high dose responders (blue). (B) EC50 values calculated by dose response plots of the normalized H3K27ac gene body coverage (FStitch signal) for the three genes in (A). (C) Histograms showing the distribution of EC50 values, for both H3K27ac (green) and -K9ac (orange), associated with a set of selected gene regions. (D) Student’s unpaired t-test analysis between the calculated RNAPII pausing indexes from genes with the lowest (20%) and highest (20%) EC50 values determined from the histogram shown in (C). Individual genes with associated PI are plotted and the mean and standard deviation are shown with black horizontal lines.

Figure 5 Dose dependent largazole effects on the epigenetic features of distal enhancer elements. (A) and (B) Screen shots from Genome Browser (ETC SC) showing ChIP-seq and associated signal determined by FStitch (black rectangles) from HCT116 cells targeting H3K27ac (orange) starting with untreated cells (DMSO) at the bottom and followed by eight increasing largazole dose treatments on top (4.7 nM to 300 nM). ChIP-seq signal accumulation for p300 (purple) (23), total RNAPII (green), H3K4mel (yellow), and H3K4me2 (pink) is shown for untreated HCT116 cells and for those treated with either 75 nM or 300 nM largazole concentrations (insets to the right). GRO-seq data from unstimulated HCT116 cells illustrate the presence of nascent transcripts resulting from the plus (red) and negative strand (blue) (24). (C) and (D) Schematic diagram shown illustrates the features used to identify isolated enhancers (IE) for genomic regions displaying both H3K27ac and H3K4mel signal (determined by FStitch and MACS2 respectively). Only enhancers elements (green) located with a minimal distance of +/- 10 kb from neighboring H3K27ac/H3K4mel locations from canonical (n = 8,667) and poised (n = 3,505) enhancers were used for further cluster analyses. (E) and (F) Largazole induces both the decommission and activation of transcriptional enhancers in a dose dependent manner. Shown are the fraction of IE regions with H3K27ac (left) and H3K9ac (right) signal (FStitch calls) along a +/- 10 kb distance centered on overlapping peak regions. Peak center locations are indicated by black triangles. Nine ChIP-seq experiments are illustrated with vehicle (DMSO) at the bottom and followed by increasing doses of largazole treatments to a maximum of 300 nM at the top. The fraction of IE elements with significant signal (FStitch) for each histone acetylation marks is illustrated by the heat-color scale: all regions (red); half of regions (green); no regions with signal detected (dark blue).

Figure 6 Dose dependent largazole-induced depletion of RNAPII occupancy at most individual elements within super-enhancer regions. (A) Graph illustrates the Log2 fold change in mRNA accumulation from HCT116 cells treated for 16 h in the absence (DMSO) or presence of increasing concentrations of largazole (4.7 nM - 300 nM). Each grey line depicts the trend of an individual gene transcript, with upregulated mRNAs (Log2 > 1) shown above the black horizontal line and below those downregulated (Log2 < -1). Distribution of total number of SE- associated transcripts differentially expressed under largazole. (B) Screenshot of Genome Browser (ETCSC) along the MYC super enhancer (SE #34241) (30) showing normalized ChIP- seq data in untreated (DMSO) or increasing largazole dose treatment of HCT116 cells targeting H3K4mel, H3K27ac and RNAPII. GRO-seq signal (red and blue) from (24) and the associated DNAse I hypersensitivity peak clusters from ENCODE under basal conditions (www.encodeproject.org). (C) Delineation of super-enhancers based on RNAPII occupancy in untreated and largazole exposed HCT116 cells using the ROSE algorithm (31, 40).

Figure 7 Dose-dependent largazole effects on epigenetic features in RPE cells. (A) Distribution of H3K27 acetylation by type of genomic region. Pie chart illustrates the distribution of H3K27ac signals (as determined by SICER) from ChIP-seq experiments using RPE cells exposed to vehicle (DMSO) for 16 h. (B) Histogram showing H3K27ac ChIP-seq signal coverage in million base pair windows along the indicated genomic territory in RPE cells untreated (DMSO) or treated with 35.7 nM, 75 nM, or 300 nM largazole. Genomic territories are divided by gene bodies (purple), enhancer regions (green), TSS (blue), intergenic locations (orange) and 3’ ends (red). (C) Snapshot from UCSC Genome Browser showing H3K27ac ChIP- seq signal spread (red rectangle) into the coding region of the LRRC47 gene. (D) and (E) Largazole stimulates the decommission and activation of canonical enhancers in RPE cells. Shown are the fraction of enhancer regions with H3K27ac (left) and H3K4mel (right) signal (SICER and MACS2 calls, respectively) along a +/- 10 kb distance centered on overlapping peak regions. Four ChIP-seq experiments are illustrated with vehicle (DMSO) at the bottom and followed by 37.5 nM, 75 nM, and 300 nM at the top. (F, G, H) Largazole promotes RNAPII pausing at proximal promoters of genes in RPE cells. Histogram and cumulative index plot depicting the calculated PI distribution of a group of genes treated with DMSO (blue), 75 nM largazole (green), and 300 nM largazole (red). Screen shot of the MYL6 loci showing total RNAPII ChIP-seq signal from RPE cells treated with vehicle (blue), largazole at 75 nM (green) and largazole at 300 nM (red) showing the calculated pausing index.

Figure 8 Largazole spares most super-enhancers in RPE cells. (A) Delineation of superenhancersin RPE cells based on RNAPII occupancy in untreated and largazole exposed HCT116 cells using the ROSE algorithm. Screenshot of Genome Browser (UCSC) encompassing three super-enhancers near the locus of the (a) NEAT1, (b) MALAT1 lncRNAs, and the (c) FOSL1 gene in (B) RPE and (C) HCT116 cells. (D) Real time quantitative PCR analysis of mRNA levels in HCT116 and RPE cells exposed for 16 h to 75 nM largazole. Data are represented as mean +/- s.e.m. (n = 2).

Figure 9 Dose-dependent suppression of the expression and function of the cohesin complex by largazole. (A) The expression levels of cohesin subunits and CTCF in the presence of increasing concentrations of largazole as determined by RNA-seq analysis. (B) and (C) Real time quantitative PCR analysis of mRNA levels in HCT116, RPE, SW620, LS180 and Caco-2 cells exposed to 75 nM largazole. (D) chromosome alignment analysis of HCT116 cells in the presence of increasing concentrations of largazole. Representative images showing metaphase chromosome alignment in control or 250 nM largazole treated cells. Cells with mis-aligned chromosomes are indicated by dashed circles. Three types of chromosome mis-alignments are typically seen in largazole treated cells. Mitotic catastrophe (a), lagging chromosomes (b) and failure of chromosome congression (c). (E) The percentage of cells in prometaphase, metaphase or missed-metaphase in largazole treated cells is quantified.

Figure 10. Dose-dependent modulation of non-coding RNA (lncRNA) / LINC expression. The HDAC inhibitor largazole induces accumulation of lncRNAs in the human HCT116 colon cancer cells. (A) Heat map diagram of expression levels of a subset of largazole- dependent lncRNAs. Differentially expressed lncRNAs were identified using DESeq version 1.30.0 and illustrated as logl0(FPKM +1) values. Color scale indicates relative lncRNA accumulation levels from low (blue) to high (red) in HCT116 cells treated with vehicle (DMSO) or with increasing largazole concentrations. (B) lncRNA expression patterns of three significantly clustered profiles determined on degree of transcript accumulation (low, medium, and high). Solid purple lines illustrate the mean and grey shaded area represent +/- standard deviation for each cluster. (C) Snap shot from UCSC Genome Browser with nascent (bottom) and polyadenylated RNA (nine tracks on top) normalized signal over the LINC01647 lncRNA loci illustrates different dose-dependent RNA accumulation levels.

Figure 11. Systematic identification of genome wide acetylated histone marks with F Stitch. (A) comparison of two ChIP-seq signal calling algorithms (FStitch and MACS2). A screen shot from Genome Browser (UCSC) showing H3K27ac ChIP-seq data in HCT116 cells untreated (bottom) or treated with 300 nM largazole (top). The 125 kb genomic window illustrates the statistical significant regions called by FStitch (grey) and MACS2.0.10 broad calls (orange) using their default signal thresholds. (B) Overlap between total genomic distances called by each algorithm. Venn diagram shows -78% of the peaks called by FStitch (grey) using DMSO data were not detected by MACS2 (orange) and -96.3% when a similar comparison was made usingthe 300 nM ChIP-seq data. (C) The log2 fold change ratio for H3K9ac and H3K27ac enrichment in the 3’ ends and intergenic territories with increasing doses of largazole (nM). (D) Number of mapped reads from individual ChIP-seq experiment targeting H3K9ac and H3K27ac.

Figure 12 Inactivation of the HNRUNPU associated transcriptional enhancer. (A) Screenshot of Genome Browser (UCSC) along the HNRNPU locus showing H3K27ac ChIP-seq (light green) and the associated signal determined by FStitch (light green rectangles) from HCT116 cells starting with untreated cells (DMSO) at the bottom and followed by eight increasing largazole dose treatments on top (4.7 nM to 300 nM). ChIP-seq signal accumulation for total RNAPII (blue), H3K4mel (dark purple), and H3K4me2 (light purple) are shown for untreated (DMSO) HCT116 cells and for those treated with either 75 nM or 300 nM largazole concentrations. ChIP-seq signal for p300 (orange) and MLL4 (dark green) were gathered from unstimulated HCT116 cells (Hu et ah, 20l3b). The transcriptional start site of HNRNPU gene and the associated upstream enhancer are denoted with red dotted rectangles. (B) Concentration inhibition profile of largazole towards the HNRNPU coding mRNA as determined by RNA-seq.

Figure 13 Meta-analysis of histone modification changes. RNAPII occupancy and motif enrichment for remodeled enhancers. (A, B, C, D) Average normalized densities of ChIP-seq reads for RNAPII, H3K4mel, and H3K4me2 along a +/- 1 kb distance centered on isolated enhancer (IE) regions presented in Figure 5C. Data from three ChIP-seq experiments are shown; DMSO (blue), largazole 75 nM (green), and largazole 300 nM (red). Sequence motif associated with the corresponding cluster of isolated poised (A,B) or isolated canonical (C,D) enhancers. Shown are the determined E-values from the MEME de novo motif finding algorithmand from TOMTOM describing the certainty of the match between the identified motif and the transcription factor database position weight matrices. Pie charts illustrate the percentage of enhancer elements positive for the corresponding identified consensus motif. (E) Largazole stimulated transcriptional activation of genes coding for protein members of the AP-l complex. mRNA accumulation levels from HCT116 cells treated for 16 h with the indicated largazole concentration. (F) Four clusters of isolated enhancers based on their largazole-induced functional state and dose-response: largazole-deactivated enhancers at low-dose (n = 416), mid-dose (n = 381), and largazole-activated enhancers at high-dose (n = 914) and mid-dose (n = 688). Top panel, shown are the fraction of enhancer regions with H3K27ac signal as described in Figure 5. Bottom panel, average normalized density of ChIP-seq reads from unstimulated HCT116 cells for p300 (orange) (Hu et al., 20l3b) and H3K27ac (solid blue from domestic and dotted blue from (Frietze et al., 2012)) along a +/- 1 kb distance centered on enhancer regions shown on top.

Figure 14 Depletion of active enhancer associated marks along super-enhancers. (A) Screenshot of Genome Browser (ETCSC) along the MYC super enhancer (SE #34241) (Khan and Zhang, 2016) showing normalized ChIP-seq data in untreated (DMSO) or the indicated largazole dose treatment of HCT116 cells targeting H3K4me2, H3K4mel, H3K27ac, RNAPII, GRO-seq (red and blue) from (Allen et al., 2014), p300 and MLL4 from and the associated DNAse I hypersensitivity peak clusters from ENCODE (www.encodeproject.org). (B) A total of 1534 individual enhancers clustered by largazole-induced RNAPII read density changes. Shown are the average normalized density of ChIP-seq reads for RNAPII, H3K4mel and H3K4me2 along a +/- 1 kb distance centered on overlapping peak regions. Data from three ChIP-seq experiments are shown: DMSO (blue), 75 nM (green), and 300 nM (red). Accumulation of H3K27ac signal (FStitch calls) along the corresponding +/- 1 kb enhancer locations from nine ChIP-seq experiments starting with vehicle (DMSO) at the left and followed by increasing largazole dose treatments to the right (4.7 nM - 300 nM). Each line illustrates the accumulation of H3K27ac signal (FStitch) along an individual enhancer with centroids (means) indicated by black solid lines. Figure 15. Dose-dependent cell cycle H3K27 acetylation and transcript level changes in largazole treated RPE cells. (A) Global changes in H3K27ac induced in RPE cells by increasing concentrations of largazole exposure for 16 h as determined by immunoblotting. (B) Analysis of cell cycle state distribution by propidium iodide staining using flow cytometry in RPE cells treated with the indicated largazole concentration for 25 h. (C) Comparison of the total number of enhancers identified in RPE and HCT116 cells. (D) Expression profiles of a set of histone remodeling genes in HCT116 cells treated for 16 h with increasing concentrations of largazole.

Figure 16 Improvement of cancer growth inhibition by combinatorial inactivation of BRD4 with JQ1 and largazole (HDACi). (A) 3D scatter plot illustrating cell viability after treatment with dual compound inhibition. Results represent the percentage of growth inhibition compared to untreated HCT116 cells; they are mean values of three independent experiments (six duplicates/experiment). Cells were treated with increasing doses of largazole (HDACi) combined with increasing doses of JQ1 (BETi). (C) Representative snapshot of BRD4 ChIPseq peaks along two responsive genes: NEAT1 and MALAT1. (D) Radial barcharts illustrating quantitative BRD4 chromatin occupancy levels, as determined by ChIPseq, across four cell treatments. Distribution of BRD4 is shown as bar plots in megabase pairs (Mbp) and colored according to five genomic categories. Grey shaded regions denote BRD4 signal in control conditions.

Figure 17 BRD4 displacement from transcription start sites correlates with RNAPII pausing. (A and D) ChIPseq density profiles centered across all peaks detected for each epitope in untreated HCT116 cells; BRD4, H3K27ac, and H3K4mel (left, middle, and right). (B and E) Density difference of BRD4 ChIPSeq signal (RPKMs) at enhancers (B) and transcription start sites (E) in HCT116 cells following 16 hr treatment with DMSO or 75 nM largazole. Genomic regions are ranked in order of increasing signal under largazole treatment. (C and F) ChIPseq meta-profiles for BRD4 and RNAPII representing the average read densities (RPM) flanking 250 enhancers (-3 kb to +3 kb) and 250 transcription start sites (-2 kb to +4 kb). Data from two ChIPseq experiments are shown; DMSO (blue) and 75 nM largazole (green).

Figure 18 JQ1 plus largazole disrupt BRD4 occupancy at super enhancers and drive greater expression changes of SE-associated genes. (A) Snapshot of BRD4 ChIPseq peaks (top panel) showing responses to inhibitors as a single compound or in combination. Bottom panel illustrates ChIPseq peaks from H3K27ac, H3K4mel, and RNAPII experiments and nascent RNA transcription. HCT116 cells were treated for 16 hr with either DMSO (blue), largazole 75 nM (green), or the indicated inhibitor(s). Shaded regions mark the boundaries of two super-enhancers from the db SUPER database. (B) Pearson correlation plot on 368 super-enhancer regions (dbSUPER) showing BRD4 occupancy levels. (C) Heat map showing mRNA accumulation changes from super-enhancers associated genes. Each row illustrates a drug treatment and the associated change in FPKM value. (D) Delineation of super-enhancers using ROSE algorithm based on BRD4 signal in untreated and three treated HCT116 cells.

Figure 19 JQ1 plus largazole generate widespread defects on mRNA processing. (A) Upset plot showing the intersection of transcription start sites (TSS) bound by BRD4 in cells treated with either DMSO, JQ1, largazole, or JQ1 + largazole. (B) Gene set enrichment analysis output from 497 TSS sites that display eviction of BRD4 only under JQl+largazole cell treatment. Inset illustrates the distribution of RNA accumulation changes from 43 genes associated with mRNA metabolic processes. Three cell treatments; JQ1 (red), largazole (green), or JQ1 + largazole (blue). (C) Number of significantly differentially spliced AS events reported in five categories. (D) An example of multiple skipped exon events along the gene UQCRH. (E) Validation of alternative transcript processing by quantitative PCR.

Figure 20 HDAC inhibition alone is sufficient to disrupt mRNA processing. Number of significantly differentially spliced AS events reported in five categories for distinct human and mouse cells.

Tables and any sequence listings also are provided herein, or incorporated specifically by reference and are part of the specification.

DETAILED DESCRIPTION OF THE INVENTION

The present invention embodies systems and methods for genome-wide dose-dependent inhibition of histone deacetylasas which may result in enhancer remodeling and suppression of oncogenic enhancer, super-enhancers, the cohesin complex and modulation of lncRNAs expression. The inventive technology further embodies novel systems, methods and compositions for the inhibition of BRD4. Further embodiment may include the use of BDR4 as a PD biomarker to determine HDACI of a cancer call to HDACI therapy. The inventive technology further includes combinational therapeutic applications of HDACIs, such as largazole, and bromodomain protein inhibitors, such as JQ1. Finally, certain embodiments may include the disruption of mRNA processing resulting in alternative splicing of mRNA transcripts, and in particular transcripts from BRD4-associated super enhancer regions.

HD AC inhibitors, or HDACI, (the terms being generally interchangeable) are known to induce extensive transcriptome changes in tumor and normal cells and gene regulation is thought to contribute at least in part to their effects on cell proliferation and death. Therapeutically effective HDAC inhibitors target multiple HDAC enzymes. Using largazole as a prototypical HDACI, the present inventors demonstrate that largazole induces dose-dependent changes in transcriptome, histone marks, and cell death. Low dose largazole induces mostly transcriptional activation while high dose causes mostly transcriptional repression. The present inventor’s results reveal that largazole differentially regulates acetylation of H3K9 and - K27 in a dose- dependent manner. The most notable effect of largazole is in the enhancer regions where largazole treatment promotes poised enhancers to become fully active with increased H3K27ac.

Notably, at higher doses of largazole, the present inventors observe the loss of H3K27ac at enhancers, a subset of which are super-enhancers. This loss leads to preferential suppression of super-enhancer associated transcripts, which is associated with cell death response. While largazole has similar effects on hyperacetylation of histones and transcription pausing in both transformed and non-transformed cell lines, it has more profound and polarizing effects on enhancers and super-enhancers in transformed cell lines. In addition, the demonstration that largazole suppresses expression of a subset of cohesin proteins, may contribute to its preferential effect on super-enhancers. Collectively, these results demonstrated by the present inventors, uncover novel mechanisms of action for largazole and other HDAC inhibitors in their mechanisms of gene expression and tumor suppression.

The prevailing notion about HDACI transcriptional regulation is that hyperacetylation of histones positively regulate gene expression. For example, in Drosophila cells, HDAC inhibition by both TSA and SAHA contribute to histone H3 acetylation at promoters and downstream regions. This event stimulates both transcription initiation and elongation. More recent studies from human cells suggest that TSA or SAHA induce a decrease of transcription along gene bodies without affecting nascent transcript production at the corresponding promoters. This effect has been attributed to failure of NELF eviction at promoters and loss of eRNA synthesis at some enhancers. The present inventor’s dose-dependent analysis of the effect of largazole on transcription may provide a new insight into transcriptional activation and repression by a HDAC inhibitor. Low doses of largazole (9.4 nM and 18.8 nM) mostly induce transcriptional activation but as the dose of largazole treatment increases the fraction of up-regulated transcripts decreases (Figure 3B). At 300 nM, more genes are repressed than activated. Therefore, transcriptional reprogramming by HDAC inhibition is dose-dependent. In agreement with the previous observations, the present inventors saw an increase in RNAPII pausing which may be responsible for elevated transcriptional repression. Increase in RNAPII pausing could be the result of a defect in the formation of the preinitiation complex or perturbations of the transcription elongation process. The present inventors further unexpectedly discovered that a subset of active enhancers lose H3K27ac upon largazole exposure in a dose-dependent manner. Since H3K9ac and H3K27ac elevation and spreading in the gene bodies do not correlate well with observed transcription changes (activation or repression) but H3K27ac loss at enhancers does correlate with target gene repression, the present inventors propose that deactivation of enhancers is likely to be part of the underlying mechanism of largazole induced transcriptional repression. As to the function of HDACs in gene bodies, the inventor’s data is more in line with previous findings that histones are deacetylated co-transcriptionally to suppress histone eviction and spurious intragenic transcription rather than to regulate the rate of transcription.

As noted, loss of H3K27 acetylation at enhancer elements with higher doses of largazole is rather counterintuitive. One possibility is that H3K27ac histones were replaced by non- modified histones or through wholesale nucleosome replacement or loss. This event may be less likely since the H3K9ac mark was retained in many cases despite the loss of H3K27ac. Another factor that may contribute to loss of H3K27ac is suppression of the enzymes that make H3K27ac. CBP and p300 are known writers for H3K27ac.

While there is little change in p300 RNA levels across the inventor’s experiments, CBP expression shows dose-dependent reduction up to -40% at the highest dose of largazole treatment (Figure 15D). For H3K9ac writers, the level of KAT2A (GCN5) mRNA is reduced by -75% while no significant expression of KAT2B (PCAF) is seen in HCT116 cells. Thus, despite the general increase in histone acetylation particularly along gene bodies upon largazole treatment, loss of H3K27ac at certain enhancers could be the result of decreased CBP levels or recruitment when it becomes limiting.

Finally, loss of H3K27ac at enhancers could also be a result of aberrant recruitment of another class of lysine deacetylases to the enhancer regions. It has been shown previously that sirtuins also possess histone deacetylase activity. For instance, in rat cardiomyocytes, Sirt6 interacts with a c-Jun homodimer, is recruited to proximal promoters, and inhibits the transcription activation of insulin-like growth factor (IGF) signaling related genes by deacetylating histone H3 at lysine 9. Redundant activity of HDACs and sirtuins could lead to the disappearance of H3K27ac at the enhancers.

The present inventor’s global analysis of cv.v- regulatory elements highlights the differences in the number of active enhancers and super-enhancers in HCT116 from RPE cells. This is not very surprising as tumor cells are dedifferentiated and generally more transcriptionally active. Previous studies suggest super-enhancers are bound by terminal transcription factors of signaling pathways and super-enhancer alterations are frequently found in tumor cells in response to oncogenic signaling. As demonstrated below, targeting super-enhancer associated factors such as BRD4 and CDK7 has emerged as a promising cancer treatment strategy. This genome-wide analysis points to super-enhancers from tumor cells as distinctly sensitive to perturbation by largazole, and other bromodomain protein inhibitors as discussed below. Of particular interest is the fact that SE-driven genes are predominantly down-regulated by largazole. Genes that have been shown to be critical for oncogenic signaling such as c-Myc and FOSL1 are particularly sensitive to such down-regulation. This result suggests that largazole may suppress oncogenic signaling through down-regulation of SE-driven genes, which may explain why HD AC inhibition has anti-tumor activity.

Additionally, RNA-seq and qPCR analysis revealed that largazole suppresses cohesin and CTCF expression in a dose-dependent manner. It has been demonstrated previously that the function of cohesin in regulating chromatin structure and transcription is highly sensitive to their expression levels. For example, Smc3 haploinsufficiency results in disruption of cis-regulatory elements and downregulation of gene expression. Thus the present inventors propose that reduction of expression of several cohesin subunits seen in largazole treated cells could result in loss of connections between enhancers and promoters and consequently transcriptional suppression. Additionally, largazole potentially inhibits HDAC8, a class I HD AC enzyme which is known to control acetylation of cohesin. In this manner, cohesin suppression by HDACIs constitutes a biomarker to predict patient response to HD AC therapies.

Accumulating evidence now supports the notion that there are active, poised, and latent enhancers in the genome which are defined by distinct histone marks. Poised enhancers bear the features of H3K4mel or H3K4me2 histone marks, absent or low acetylation of H3K27 and minimal association with RNAPII. Largazole-induced increase in H3K27ac at poised enhancers suggests that these enhancers are normally maintained by a steady-state active deacetylation and acetylation cycle. This interpretation is in agreement with a model in which both HATs and HDACs occupy the poised enhancer region but overall maintain a repressed state. Establishment of this repressed or poised state could be a result of association of these enhancers with sequence-specific transcriptional repressors, which are known to recruit HDACs or the HDAC containing Nucleosome Remodeling and Deacetylation (NuRD) complex. Once HDACs are inhibited by largazole, the balance shifts toward acetylation of H3K9/27, critical for subsequent enhancer activation. Several lines of evidence support this hypothesis. In macrophages, the NCoRl/HDAC3 complex is recruited to promoter regions bearing AP-l binding sites where it modulates transcription factor accessibility likely by mediating deacetylation of histone tails required for transcription activity. These observations imply that HDAC complexes could be recruited to particular enhancer elements for active histone deacetylation and repression of specific gene transcripts. Indeed, in CD4+ T cells, class I HDACs (HDAC2, and 3) and several HATs (p300, CBP, PCAF, MOF, and Tip60) can be found bound to the same intergenic regions at high frequency, suggesting dynamic histone acetylation remodeling at these locations. Interestingly, under basal cellular conditions the present inventors found high levels of p300 ChIP-seq signal at intergenic regions that become activated enhancers under largazole stimulation. However, these genomic locations display minimal H3K27ac signal. Given largazole has superb potency against class I HDAC enzymes, it may be speculated that this class of HDACs is involved in maintaining poised enhancers in the repressive state.

Dose-dependent transcriptome changes correlate with the biological responses of cancer cells. It has been shown previously that a low dose of largazole induces cell growth arrest at the Gl phase of the cell cycle while a high dose of largazole causes G2/M arrest and apoptosis. Based on these results, it is tempting to speculate that transcriptional activation at low largazole doses may contribute to cell cycle arrest at Gl and that the profound transcriptional repression observed upon treatment with a high largazole dose is linked to G2 arrest and apoptosis. Since most therapeutic drugs are administered just below the maximum dose tolerance or maximum tolerable dose (MTD), HDACI-induced transcriptional repression is probably both relevant to their therapeutic benefits and their undesirable toxicity. Recent clinical success in treatment of ER positive breast cancer with Cdk4/6 inhibitor Palbociclib (Pfizer) sparks renewed interest in developing inhibitors that block Gl to S transition and promote cell differentiation. One implication of this study is that low doses of HDACI could also be an effective yet unexplored treatment strategy, especially in developing combination therapies in conjunction with chemotherapeutic agents.

The present genome-wide dose-response analysis of transcriptome and histone signatures revealed new target specificity of largazole in transcriptional reprogramming. The present inventors provide a more mechanistic explanation of the effect of HDACI on gene expression. Future studies focusing on dynamic changes of histone signatures and more comprehensive profiling of histone marks should provide more insights into remodeling of enhancer landscapes and their link to therapeutic responses in vivo and ultimately uncover additional predictive biomarkers.

In one embodiment of the present invention, the present inventors have shown that HDACIs, such as largazole, suppresses cohesin proteins/complex as well as CTCF, which in turn modulates expression of SEs and SE-driven gene expression. The present inventors have shown that HDACIs, such as largazole, modulate the expression of lncRNA / LINC. The present inventive technology further relates to the novel use of HDACIs to modulate the expression of long non-coding RNA (lncRNA), as well as their use as effective biomarkers for sensitivity to, and effectiveness of HDACIs. The present inventors have further shown that HDACIs, such as largazole, in combination with bromodomain protein inhibitors such as JQ1, inhibit the activity of BRD4. This inhibition of BRD4’s activity caused differential regulation of SE-associated genes, as well as disrupted mRNA processing resulting in BRD4-associated super-enhancer transcripts that are alternatively spliced generating novel peptide formations and combinations.

The present invention further includes the novel use of histone deacetylases inhibitors (HDACIs) to treat a disease state. Specifically, the present disclosure relates to novel systems, compositions, methods, and agents that are useful for modulating expression of super-enhancers (SEs), SE-driven transcripts, and other genes and/or genome targets that may be required for maintenance of a disease state, such as cancer. In particular, the invention relates to the novel use of HDACIs to modulate the expression of enhancer and super-enhancers as a therapeutic treatment for cancer and other disease states. Modulating expression of SEs may be mediated by suppression of cohesin proteins as well as CTCF by HDACIs. The present inventive technology further relates to the novel use of HDACIs to modulate the expression of long non-coding RNA (lncRNA). The present inventive technology further relates to predictive biomarkers that may be indicative of more effective application of HDACIs and/or HDACI sensitivity in a patient with a disease state such as cancer. In particular, up and downregulation of select biomarkers or biomarker groups may be used as biomarkers for predicting HDACI sensitivity in cell line and patient samples. One embodiment of the present invention relates to a method to treat a patient with cancer or other HDAC -related disease state. The method includes the step of administering to the patient one or more histone deacetylase inhibitors or HDACIs. Other methods include the step of administering to the patient one or more HDACI and at least one other therapeutic agents, such as anti-cancer agents.

The present invention relates in some aspects to HDAC inhibitor dose-responsive transcripts, enhancers, super-enhancers and noncoding RNAs, and related compositions, methods, and agents that are useful for targeting genes that are responsible for cancer cell proliferation, differentiation and death for cancer therapeutics. In yet another embodiment of the invention, a method of treating a patient with cancer is provided comprising, in addition to one or more HDACI compounds described herein, at least one pharmaceutically-acceptable carrier. The composition can take any suitable form for the desired route of administration. Where the composition is to be administered orally, any suitable orally deliverable dosage form can be used, including without limitation tablets, capsules (solid or liquid filled), powders, granules, syrups and other liquids, elixirs, inhalants, troches, lozenges, and solutions. Injectable compositions or i.v. infusions are also provided in the form of solutions, suspensions, and emulsions.

In yet another embodiment, a pharmaceutical composition including at least one HDACI according to the present invention may contain one or more additional therapeutic agents, for example, to increase the efficacy or decrease side effects. In some embodiments, accordingly, a HDACI pharmaceutical composition further contains one or more additional therapeutic agents selected from active ingredients useful to treat or inhibit diseases mediated directly or indirectly by HDAC. Examples of such active ingredients are, without limitation, agents to treat or inhibit cancer, Huntington's disease, cystic fibrosis, liver fibrosis, renal fibrosis, pulmonary fibrosis, skin fibrosis, rheumatoid arthritis, diabetes, or heart failure. In yet another embodiment, an additional HDACI therapeutic agent to be included is an anti-cancer agent. Examples of an anti-cancer agent include, but are not limited to, alkylating agents such as cyclophosphamide, dacarbazine, and cisplatin; anti-metabolites such as methotrexate, mercaptopurine, thioguanine, fluorouracil, and cytarabine; plant alkaloids such as vinblastine and paclitaxel; antitumor antibiotics such as doxorubicin, bleomycin, and mitomycin; hormones/antihormones such as prednisone, tamoxifen, and flutamide; other types of anticancer agents such as asparaginase, rituximab, trastuzumab, imatinib, retinoic acid and derivatives, colony stimulating factors, amifostine, camptothecin, topotecan, thalidomide analogs such as lenalidomide, CDK inhibitors, proteasome inhibitors such as Velcade and other HDAC inhibitors, for example those identified in US Patent Application No. US8754050.

In yet another embodiment, the present invention provides a method of inhibiting or treating diseases arising from abnormal cell proliferation and/or differentiation in a subject in need thereof, comprising administering to said subject a therapeutically effective amount of one or more HDACI compounds according to the present invention. In one embodiment, the method of inhibiting or treating disease comprises administering to a subject in need thereof, a composition comprising an effective amount of one or more HDACI compounds of the invention and a pharmaceutically acceptable carrier. The HDACI composition to be administered may further contain a therapeutic agent such as an anti-cancer agent, or bromodomain protein inhibitor.

One aim of the present inventive technology is to include novel therapeutic uses of HDACIs. In such embodiments, one or more HDACIs may be used to modulate the expression of transcripts, enhancers, super-enhancers and noncoding RNAs. Another aim of the present inventive technology is to include novel dose-dependent therapeutic uses of HDACIs. In such embodiments, one or more HDACIs may be used to modulate the expression of transcripts, enhancers, super-enhancers, and lncRNAs in a dose dependent manner.

Another aspect of the present inventive technology includes the identification of select HDACI regulated biomarkers or biomarker groups that may be used for predicting HDACI sensitivity in cell line and patient samples. One aim of this embodiment may include the method comprising the step of evaluating a cancer or disease condition to predict resistance or sensitivity to a HDAC inhibitor prior to administration of the therapeutic composition. For example, the step of evaluating the cancer can include: (a) detecting in a sample of tumor cells from a patient a level of a biomarker; (b) comparing the level of the biomarker in the tumor cell sample to a control level of the biomarker selected from: (i) a control level of the biomarker that has been correlated with sensitivity to the HDACI; and (ii) a control level of the biomarker that has been correlated with resistance to the HDACI; and (c) selecting the patient as being predicted to not benefit from therapeutic administration of the HDACI, or being predicted to benefit from the combination of HDACI and another therapeutic compound, if the level of the biomarker in the patient's tumor cells is statistically less than the control level of the biomarker that has been correlated with sensitivity to the HDACI, or if the level of the biomarker in the patient's tumor cells is statistically similar to or less than the level of the biomarker that has been correlated with resistance to the HDACI.

In another aspect of this embodiment, one method of the current invention may additionally comprise the steps of: (a) detecting a level of expression of biomarker in the tumor cell sample; (b) comparing the level of a biomarker protein expression in the tumor cell sample to a control level of biomarker protein expression selected from: (i) a control level that has been correlated with sensitivity to the HDACI; and (ii) a control level that has been correlated with resistance to the HDACI; and (c) selecting the patient as being predicted to not benefit from therapeutic administration of the HDACI, or being predicted to benefit from the combination of HDACI and another therapeutic compound, if the level of biomarker protein expression in the patient's tumor cells is statistically less than the control level of biomarker protein expression that has been correlated with sensitivity to the HD AC inhibitor, or if the level of biomarker protein expression in the patient's tumor cells is statistically similar to or less than the level of biomarker expression that has been correlated with resistance to the HDACI.

In another aspect of this embodiment, one method of the current invention may additionally comprise the steps of: (a) detecting a level of expression of enhancer and/or super enhancer biomarkers in the tumor cell sample; (b) comparing the level of a enhancer and/or super-enhancer biomarker protein expression in the tumor cell sample to a control level of enhancer and/or super-enhancer biomarker protein expression selected from: (i) a control level that has been correlated with sensitivity to the HDACI; and (ii) a control level that has been correlated with resistance to the HDACI; and (c) selecting the patient as being predicted to not benefit from therapeutic administration of the HDACI, or being predicted to benefit from the combination of HDACI and another therapeutic compound, if the level of enhancer and/or super- enhancer biomarker protein expression in the patient's tumor cells is statistically less than the control level of enhancer and/or super-enhancer biomarker protein expression that has been correlated with sensitivity to the HDAC inhibitor, or if the level of enhancer and/or super enhancer biomarker protein expression in the patient's tumor cells is statistically similar to or less than the level of enhancer and/or super-enhancer biomarker expression that has been correlated with resistance to the HD ACI.

In another aspect of this embodiment, one method of the current invention may additionally comprise the steps of: (a) detecting a level of expression of noncoding RNA biomarkers, or lncRNAs, in the tumor cell sample; (b) comparing the level of one or more noncoding RNA biomarker expression in the tumor cell sample to a control level of noncoding RNA biomarker expression selected from: (i) a control level that has been correlated with sensitivity to the HD ACI; and (ii) a control level that has been correlated with resistance to the HDACI; and (c) selecting the patient as being predicted to not benefit from therapeutic administration of the HDACI, or being predicted to benefit from the combination of HDACI and another therapeutic compound, if the level of noncoding RNA biomarker expression in the patient's tumor cells is statistically less than the control level of biomarker expression that has been correlated with sensitivity to the HDAC inhibitor, or if the level of noncoding RNA biomarker expression in the patient's tumor cells is statistically similar to or less than the level of noncoding RNA biomarker expression that has been correlated with resistance to the HDACI.

In another aspect of this embodiment, one method of the current invention may additionally comprise the steps of: (a) detecting a level of expression of transcript biomarkers, in the tumor cell sample; (b) comparing the level of one or more transcript biomarkers expression in the tumor cell sample to a control level of transcript biomarker expression selected from: (i) a control level that has been correlated with sensitivity to the HDACI; and (ii) a control level that has been correlated with resistance to the HDACI; and (c) selecting the patient as being predicted to not benefit from therapeutic administration of the HDACI, or being predicted to benefit from the combination of HDACI and another therapeutic compound, if the level of transcript biomarker expression in the patient's tumor cells is statistically less than the control level of biomarker expression that has been correlated with sensitivity to the HDAC inhibitor, or if the level of transcript biomarker expression in the patient's tumor cells is statistically similar to or less than the level of transcript biomarker expression that has been correlated with resistance to the HD ACL

In another aspect of this embodiment, one method of the current invention may additionally comprise the steps of: (a) detecting a level of expression and formation of a cohesion complex as a biomarker in the tumor cell sample; (b) comparing the level of one or more cohesion complex biomarkers in the tumor cell sample to a control level of cohesion complex biomarker expression selected from: (i) a control level that has been correlated with sensitivity to the HDACI; and (ii) a control level that has been correlated with resistance to the HDACI; and (c) selecting the patient as being predicted to not benefit from therapeutic administration of the HDACI, or being predicted to benefit from the combination of HDACI and another therapeutic compound, if the level of cohesion complex biomarker expression in the patient's tumor cells is statistically less than the control level of cohesion complex biomarker expression that has been correlated with sensitivity to the HDAC inhibitor, or if the level of cohesion complex biomarker in the patient's tumor cells is statistically similar to or less than the level of cohesion complex biomarkers that has been correlated with resistance to the HDACI.

In another aspect of this embodiment, one method of the current invention may additionally comprise the steps of: (a) detecting a level of chemical modification of a biomarker, such as epigenetic modifications, or more particularly, acetylation or deacetylation of certain amino acids of a histone protein biomarker in the tumor cell sample; (b) comparing the level of a biomarker acetylation or deacetylation in the tumor cell sample to a control level of biomarker acetylation or deacetylation selected from: (i) a control level that has been correlated with sensitivity to the HDACI; and (ii) a control level that has been correlated with resistance to the HDACI; and (c) selecting the patient as being predicted to not benefit from therapeutic administration of the HDACI, or being predicted to benefit from the combination of HDACI and another therapeutic compound, if the level of biomarker acetylation or deacetylation in the patient's tumor cells is statistically less than the control level of biomarker acetylation or deacetylation that has been correlated with sensitivity to the HDAC inhibitor, or if the level of biomarker acetylation or deacetylation in the patient's tumor cells is statistically similar to or less than the level of biomarker acetylation or deacetylation that has been correlated with resistance to the HDACI. In another aspect of this embodiment, one method of the current invention may additionally comprise the steps of: (a) detecting a level of expression chemical modification, such as acetylation or deacetylation of certain amino acids of a histone protein biomarker in the tumor cell sample; (b) comparing the level of biomarker acetylation or deacetylation in the tumor cell sample to a control level of biomarker acetylation or deacetylation selected from: (i) a control level that has been correlated with sensitivity to the HDACI; and (ii) a control level that has been correlated with resistance to the HDACI; and (c) selecting the patient as being predicted to not benefit from therapeutic administration of the HDACI, or being predicted to benefit from the combination of HDACI and another therapeutic compound, if the level of biomarkers acetylation or deacetylation in the patient's tumor cells is statistically less than the control level of biomarkers acetylation or deacetylation that has been correlated with sensitivity to the HD AC inhibitor, or if the level of biomarker protein expression in the patient's tumor cells is statistically similar to or less than the level of biomarker acetylation or deacetylation that has been correlated with resistance to the HDACI.

The present invention further includes the novel use of HDACIs and bromodomain protein inhibitors to treat a disease state. Specifically, the present disclosure relates to novel systems, compositions, methods, and agents that are useful for modulating expression of super enhancers (SEs), SE-driven transcripts, and other genes and/or genome targets that may be required for maintenance of a disease state, such as cancer. In particular, the invention relates to the novel use of HDACIs and bromodomain protein inhibitors, which may preferably be largazole and JQ1 respectively, to modulate the expression of enhancer and super-enhancers as a therapeutic treatment for cancer and other disease states. Modulating expression of SEs may be mediated by suppression of BRD4 activity by the therapeutic combinatorial application HDACIs and bromodomain protein inhibitors.

In one preferred embodiment, the invention may include systems, methods and compositions for the inhibition of one or more histone deacetylase (HDAC) proteins. Such compositions may include one or more therapeutic agents that inhibit a HDAC protein. HDAC proteins may be grouped into classes based on homology to yeast HDAC proteins with Class I made up of HDAC1, HDAC2, HDAC3 and HDAC 8; Class Ila made up of HDAC4, HDAC5, HDAC7 and HDAC 9; Class lib made up of HDAC6 and HDAC 10; and Class IV made up of HDAC11. In some of these embodiments, the HDAC protein inhibitor therapeutic agent may be trichostatin A, vorinostat, givinostat, belinostat, panobinostat, resminostat, quisinostat, entinostat, mocetinostat or valproic acid.

In one preferred embodiment, at least one of the HDACI therapeutic agents may inhibit bromodomain proteins such as BRD2, BRD3, BRDT, and more preferably BRIM. In some of these embodiments, the therapeutic agent may be a HDACI, such as largazole of an analog thereof, or other HDACI identified herein. In another preferred embodiment, a HDACI, such as largazole and another therapeutic agent that may inhibit bromodomain proteins, such as JQ1, may be utilized in combination to inhibit the activity of one or more bromodomain proteins such as BRD2, BRD3, BRDT, and more preferably BRD4. Additional bromodomain protein compounds that may be coupled with one or more HDACIs may include, but not be limited to: B 12536, TG101209, OTX015, IBET762, PFI-l, or CPI-0610.

A preferred embodiment of the current invention include methods for treating a super- enhancer-mediated disease, the method comprising administering an effective amount of at least one HDACI and a bromodomain protein inhibitor. In certain embodiments, at least one HDACI therapeutic agent and at least one bromodomain protein inhibitor may disrupt the function of one or more genomic SE regions. In this embodiment, a HDACI therapeutic agent may be largazole or an analog thereof, and a bromodomain protein inhibitor may be JQ1, which may synergistically disturb the function of BRD4. This synergistic inhibition of BRD4 may cause differential expression of SE-associated genes. In this preferred embodiment, the synergistic inhibition of BRD4 through the administration of a therapeutically effective amount of largazole and JQ1, may be used as a method for preventing, treating, or ameliorating a symptom associated with a disease, disorder, or pathological condition involving SE function, such as cancer among others.

In another embodiment, the inventive technology may include the synergistic inhibition of BRD4 through the administration of a therapeutically effective amount of largazole, or an analog thereof, and JQ1, to a subject in need thereof to downregulate expression of SE- associated oncogenic genes, such as oncogenic transcription factors that may result in cancer. Such synergistic or combinatorial inhibition of BRD4 through the administration of a therapeutically effective amount of largazole and JQ1, may inhibit the growth of cancer cells through the differential expression of SE-associated genes among other processes described herein. In another embodiment, the inventive technology may include the synergistic inhibition of a SE-associated transcription factor through the administration of a therapeutically effective amount of a HDACI and a bromodomain protein inhibitor to a subject in need thereof to downregulate expression of SE-associated gene through disruption of the formation and/or function of the of RNAPII. In this embodiment, the synergistic or combinatorial inhibition of a SE-associated transcription factor through the administration of a therapeutically effective amount of a HDACI and a bromodomain protein inhibitor may modulate the activity and/or accumulation of RNAPII at super-enhancers. Specifically, in this embodiment, synergistic or combinatorial inhibition of a SE-associated transcription factor through the administration of a therapeutically effective amount of a HDACI and a bromodomain protein inhibitor may cause displacement of one or more SE-associated transcription factors from Transcription Start Site (TSS) of certain SE regions. This displacement of one or more SE-associated transcription factors from may further cause RNAPII pausing or sputtering during transcription of one or more SE-associated gene transcripts.

In another embodiment, the inventive technology may include the synergistic inhibition of BRD4 through the administration of a therapeutically effective amount of largazole, or an analog thereof, and JQ1, to a subject in need thereof to modulate expression of SE-associated genes through disruption of the formation and/or function of the of RNAPII. In this embodiment, the synergistic or combinatorial inhibition of BRD4 through the administration of a therapeutically effective amount of largazole and JQ1 may modulate the activity and/or accumulation of RNAPII at super-enhancers. Specifically, in this embodiment, synergistic or combinatorial inhibition of BRD4 through the administration of a therapeutically effective amount of largazole and JQ1 may cause displacement of BRD4 from Transcription Start Site (TSS) of certain SE regions. This displacement of BRD4 from may further cause RNAPII pausing or sputtering during transcription of BRD4-respnsive SE-gene transcripts.

In another embodiment, the inventive technology may include the inhibition of BRD4 through the administration of a therapeutically effective amount of HDACI, such as largazole, or an analog thereof, to a subject in need thereof to downregulate expression of SE-associated gene through disruption of the formation and/or function of RNAPII. In one preferred embodiment, a therapeutically effective amount of largazole may modulate the activity and/or accumulation of RNAPII at super-enhancers regions. Specifically, in this embodiment, the inhibition of BRD4 through the administration of a therapeutically effective amount of largazole, or an analog thereof, may cause displacement of BRD4 from Transcription Start Site (TSS) of certain SE regions. This displacement of BRD4 from may further cause RNAPII pausing or sputtering during transcription of BRD4-respnsive SE-gene transcripts.

In another embodiment, the inventive technology may include the inhibition of BRD4 through the administration of a therapeutically effective amount of bromodomain protein inhibitor, such as JQ1, or an analog thereof, to a subject in need thereof to downregulate expression of SE-associated gene through disruption of the formation and/or function of the RNAPII. In one preferred embodiment, a therapeutically effective amount of JQ1 may modulate the activity and/or accumulation of RNAPII at super-enhancers regions. Specifically, in this embodiment, the inhibition of BRD4 through the administration of a therapeutically effective amount of JQ1, or an analog thereof, may cause displacement of BRD4 from Transcription Start Site (TSS) of certain SE regions. This displacement of BRD4 from may further cause RNAPII pausing or sputtering during transcription of BRD4-respnsive SE-gene transcripts.

In another embodiment, the inventive technology may include the synergistic inhibition of super-enhancer associated transcription factors through the administration of a therapeutically effective amount of a HDACI, and a bromodomain protein inhibitor, to a subject in need thereof to cause defects in mRNA expression of SE-associated genes, such as oncogenic transcription factors that may result in cancer. Such synergistic or combinatorial inhibition of super-enhancer associated transcription factors through the administration of a therapeutically effective amount of a HDACI, and a bromodomain protein inhibitor, may generate systemic alternative splicing (AS) events resulting in the production of differentially spliced and distinct proteins associated with SE-genes. Such differentially processed and transcribed mRNAs may give rise to non- naturally occurring peptides and/or peptide fragments having novel antigenic epitopes that may be processed and presented by a cell and, in turn, recognized by a host’s immune system. In this manner, a host’s immune system, for example through antibody or T-cell recognition of such novel antigenic epitopes may more easily recognize, bind and destroy diseased cells. In one preferred embodiment, such novel antigenic presentation may be on a cancer cell. Such AS mRNA transcripts, and novel peptides and peptide fragments as well as antigen presentation may act as a pharmacodynamic biomarker of BRD4 activity as generally described below. In another embodiment, the inventive technology may include the synergistic inhibition of BRD4 through the administration of a therapeutically effective amount of largazole, or an analog thereof, and JQ1, to a subject in need thereof to cause defects in mRNA expression of SE- associated genes, such as oncogenic transcription factors that may result in cancer. Such synergistic or combinatorial inhibition of BRD4 through the administration of a therapeutically effective amount of largazole and JQ1, may generate systemic alternative splicing (AS) events resulting in the production of differentially spliced and distinct proteins associated with SE- genes. Such differentially processed and transcribed mRNAs may give rise to non-naturally occurring peptides having novel antigenic epitopes that may be processed and presented by a cell and, in turn, recognized by a host’s immune system. In this manner, a host’s immune system, for example through antibody or T-cell recognition of such novel antigenic epitopes may more easily recognize, bind and destroy diseased cells. In one preferred embodiment, such novel antigenic presentation may be on a cancer cell.

In another embodiment, the synergistic inhibition of BRD4 through the administration of a therapeutically effective amount of largazole, or an analog thereof, to a subject in need thereof to cause defects in mRNA expression of SE-associated genes, such as oncogenic transcription factors that may result in cancer. Such inhibition of BRD4 through the administration of a therapeutically effective amount of largazole, or an analog thereof, may generate systemic alternative splicing (AS) events resulting in the production of differentially spliced and distinct proteins associated with SE-genes. Such differentially processed and transcribed mRNAs may give rise to non-naturally occurring peptides having novel antigenic epitopes that may be processed and presented by a cell and, in turn, recognized by a host’s immune system. In this manner, a host’s immune system, for example through antibody or T-cell recognition of such novel antigenic epitopes may more easily recognize, bind and destroy diseased cells. In one preferred embodiment, such novel antigenic presentation may be on a cancer cell.

In another embodiment, the synergistic inhibition of BRD4 through the administration of a therapeutically effective amount of JQ1, or an analog thereof, to a subject in need thereof to cause defects in mRNA expression of SE-associated genes, such as oncogenic transcription factors that may result in cancer. Such inhibition of BRD4 through the administration of a therapeutically effective amount of JQ1, or an analog thereof, may generate systemic alternative splicing (AS) events resulting in the production of differentially spliced and distinct proteins associated with SE-genes. Such differentially processed and transcribed mRNAs may give rise to non-naturally occurring peptides having novel antigenic epitopes that may be processed and presented by a cell and, in turn, recognized by a host’s immune system. In this manner, a host’s immune system, for example through antibody or T-cell recognition of such novel antigenic epitopes may more easily recognize, bind and destroy diseased cells. In one preferred embodiment, such novel antigenic presentation may be on a cancer cell.

In yet another embodiment, the inventive technology may include one or more pharmacodynamic biomarkers that may be used for diagnostic purposes, as well as for therapeutic, drug screening, treatment efficacy, and susceptibility purposes as well as other purposes described herein. In certain embodiments, these pharmacodynamic markers may include markers for predicting HDACI and/or BRD4 sensitivity/resistance in a patient, cell, tissue, tumor and the like. Pharmacodynamic biomarkers may include, but not be limited to BRD4 and its activity in the presence of one or more HDACI and/or other inhibitors such as JQ1, and BRD4-expression products as generally described herein.

The present invention includes all compositions and methods relying on correlations between the reported pharmacodynamic biomarkers and the HDACI sensitivity or resistance of cancer or other diseased cells. Such methods include methods for determining whether a cancer patient or tumor is predicted to respond to administration of HDACI therapy, as well as methods for assessing the efficacy of HDACI therapy. Additional preferred embodiments may further include methods for determining whether a cancer patient or tumor is predicted to respond to administration of BRD4 inhibition therapy, as well as methods for assessing the efficacy of a BRD4 inhibition therapy. Additional methods may include determining whether a cancer patient or tumor is predicted to respond to administration of HDACI therapy coupled with BRD4 inhibition therapy. Such diagnostic information may be used to more effectively treat or kill, for example, cancerous cells. This diagnostic activity may be done in vivo , in vitro , or ex vivo.

Further included are methods for improving the efficacy of HDACI therapy by administering to a subject a therapeutically effective amount of an agent that alters the activity of a pharmacodynamic biomarker, such as BRD4. In this context, the term“effective” is to be understood broadly to include reducing or alleviating the signs or symptoms of a BRD4- associated disease condition, improving the clinical course of a BRD4-associated disease condition, enhancing killing of a BRD4-associated cancerous cells, or reducing any other objective or subjective indicia of a BRD4-associated disease condition, and/or inducing an observable change in the activity of BRIM. Different drugs, doses and delivery routes can be evaluated by performing the method using different drug administration conditions. The markers may also be used as pharmaceutical compositions or in kits. The pharmacodynamic biomarkers may also be used to screen candidate compounds that modulate their activity.

Another specific embodiment of the present inventive technology includes the identification of biomarkers or biomarker groups that may be used for predicting BRD4-specific HDACI sensitivity in cell line and patient samples. One aim of this embodiment may include the method comprising the step of evaluating a cancer or disease condition to predict resistance or sensitivity to a HDAC inhibitor, such as largazole or an analog thereof. In this embodiment, one method of the current invention may additionally comprise the steps of: (a) detecting a level of activity of a BRD4 biomarker in the tumor cell sample; (b) comparing the level of a BRD4 biomarker protein activity in the tumor cell sample to a control level of biomarker protein activity selected from: (i) a control level that has been correlated with sensitivity to the BRD4- specific HDACI; and (ii) a control level that has been correlated with resistance to the BRD4- specific HDACI; and (c) selecting the patient as being predicted to not benefit from therapeutic administration of the BRD4-specific HDACI, or being predicted to benefit from the combination of BRD4-specific HDACI and another therapeutic compound, such as a bromodomain protein inhibitor, such as the BRD4-specific compound JQ1, if the level of BRD4 biomarker protein activity in the patient's tumor cells is statistically less than the control level of BRD4 biomarker protein activity that has been correlated with sensitivity to the BRD4-specific HDAC inhibitor, or if the level of biomarker protein activity in the patient's tumor cells is statistically similar to or less than the level of biomarker activity that has been correlated with resistance to the BRD4- specific HDACI.

Another embodiment of the present inventive technology includes the identification of pharmacodynamic biomarkers or pharmacodynamic biomarker groups that may be used for predicting BRD4-specific HDACI sensitivity in cell line and patient samples. One aim of this embodiment may include the method comprising the step of evaluating a cancer or disease condition to predict resistance or sensitivity to a HDAC inhibitor, such as largazole or an analog thereof. In this embodiment, one method of the current invention may additionally comprise the steps of: (a) detecting a level of activity of a BRD4 biomarker in the cell sample; (b) administering a therapeutically effective dose of one or more BRD4-specific HDACI to a cancer subject; (c) detecting a level of activity of a BRD4 biomarker in a second cell sample; (d) comparing the level of a BRD4 biomarker protein activity in the cell samples to a control level of biomarker protein activity selected from: (i) a control level that has been correlated with sensitivity to the BRD4-specific HDACI; and (ii) a control level that has been correlated with resistance to the BRD4-specific HDACI; and (e) selecting the patient as being predicted to not benefit from therapeutic administration of the BRD4-specific HDACI, or being predicted to benefit from the combination of BRD4-specific HDACI and another therapeutic compound, such as a bromodomain protein inhibitor, such as the BRD4-specific compound JQ1, if the level of BRD4 biomarker protein activity in the patient's tumor cells is statistically less than the control level of BRD4 biomarker protein activity that has been correlated with sensitivity to the BRD4- specific HD AC inhibitor, or if the level of biomarker protein activity in the patient's tumor cells is statistically similar to or less than the level of biomarker activity that has been correlated with resistance to the BRD4-specific HDACI.

Another aspect of the present inventive technology includes the identification of select HDACI regulated pharmacodynamic biomarkers or pharmacodynamic biomarker groups that may be used for predicting HDACI sensitivity in cell line and patient samples. One aim of this embodiment may include the method comprising the step of evaluating a cancer or disease condition to predict resistance or sensitivity to a HD AC inhibitor, preferably at least one HDACi and at least one bromodomain inhibitor. For example, the step of evaluating the cancer can include: (a) detecting in a sample of tumor cells from a patient a level of a pharmacodynamic biomarker, preferably BRD4; (b) comparing the level of the pharmacodynamic biomarker in the tumor cell sample to a control level of the pharmacodynamic biomarker, (i) a control level of the pharmacodynamic biomarker that has been correlated with sensitivity to at least one HDACi and at least one bromodomain inhibitor; and (ii) a control level of the biomarker that has been correlated with resistance to at least one HDACI and at least one bromodomain inhibitor; and (c) selecting the patient as being predicted to not benefit from therapeutic administration of at least one HDACI and at least one bromodomain inhibitor, or being predicted to benefit from the combination of at least one HDACI and at least one bromodomain inhibitor and another therapeutic compound, if the level of the biomarker in the patient's tumor cells is statistically less than the control level of the biomarker that has been correlated with sensitivity to at least one HDACI and at least one bromodomain inhibitor, or if the level of the biomarker in the patient's tumor cells is statistically similar to or less than the level of the biomarker that has been correlated with resistance to at least one HDACI and at least one bromodomain inhibitor.

In an alternative embodiment of the invention, a method is provided for assessing the efficacy or effectiveness of HDACI sensitivity and/or treatment being administered to a patient, preferably a cancer patient. The method is performed by obtaining a first sample, such as serum or tissue, from the subject at a certain time (to); measuring the activity level of at least one of the target pharmacodynamic biomarkers in the biological sample after administration of a therapeutically effective amount of a HDACI has been administered to a patient; and comparing the measured level with the level measured with respect to a sample obtained from the subject at a later time (tl). Depending upon the difference between the measured levels, it can be seen whether the target pharmacodynamic biomarkers activity level has increased, decreased, or remained constant over the interval (trto). Subsequent sample acquisitions and measurements can be performed as many times as desired over a range of times t2 to in. If a target pharmacodynamic biomarker’s activity maintains a consistent level or level of activity, or only raises or lowers to within a pre-determined threshold that has been shown to be indicative of a therapeutic effect, it would indicate that the HDACI therapy has resulted in a therapeutic effect and/or may be maintained, increased, decreased or modified. Such modifications may include administration of additional therapeutic compounds.

In an alternative embodiment of the invention, a method is provided for assessing the efficacy or effectiveness of HDACI sensitivity and/or treatment being administered to a patient, preferably a cancer patient. The method is performed by obtaining a first sample, such as serum or tissue, from the subject at a certain time (to) and measuring the activity level of BRD4 in the biological sample, after which a therapeutically effective amount of one or more BRD4 -targeted HDACIs has been administered to said patient; and comparing the measured level with the level measured with respect to a sample obtained from the subject at a later time (tl). Depending upon the difference between the measured levels, it can be seen whether the BRD4 activity level has increased, decreased, or remained constant over the interval (trto). Subsequent sample acquisitions and measurements can be performed as many times as desired over a range of times t2 to in. If BRD4’s activity maintains a consistent level of activity, or only raises or lowers to within a pre-determined threshold that has been shown to be indicative of a therapeutic effect, it would indicate that the HDACI therapy has resulted in a therapeutic effect and/or may be maintained, increased, decreased or modified. Such modifications may include the administration of one or more additional therapeutic compounds.

In yet another alternative embodiment of the invention, a method is provided for assessing the efficacy or effectiveness of a BRD4-directed combinatorial treatment being administered to a patient, preferably a cancer patient. The method is performed by obtaining a first sample, such as serum or tissue, from the subject at a certain time (to) and measuring the activity level of BRD4 in the biological sample, after which a therapeutically effective amount of one or more HDACIs and a bromodomain protein inhibitor may be administered to said patient; and comparing the measured level with the level measured with respect to a sample obtained from the subject at a later time (tl). Depending upon the difference between the measured levels, it can be seen whether the BRD4 activity level has increased, decreased, or remained constant over the interval (trto). Subsequent sample acquisitions and measurements can be performed as many times as desired over a range of times t2 to in. If BRD4’s activity maintains a consistent level of activity, or only raises or lowers to within a pre-determined threshold that has been shown to be indicative of a therapeutic effect, it would indicate that the combination HDACI and bromodomain protein inhibitor therapy has resulted in a therapeutic effect and/or may be maintained, increased, decreased or modified. Such modifications may include the administration of one or more additional therapeutic compounds. It should be noted that the activity of BRD4 in this embodiment, may include one or more of the activities of BRD4 described herein, whether in a wild-type state, or in response to inhibiting compounds, such as a HDACI and/or bromodomain protein inhibitor, preferably largazole and its analogs, and JQ1 respectively.

In another preferred aspect, one or more of the following diagnostic embodiments may be included in a kit, including all necessary equipment and reagents to perform the diagnostic procedure. Each of the above embodiments may further be used as a method to select a cancer patient who is predicted to benefit from therapeutic administration of a combination of, or at least one HDAC inhibitor, and/or at least one bromodomain protein inhibitor. Preferred embodiments may include the HDAC inhibitor largazole and its analogs, while a preferred bromodomain protein inhibitor may include the compound JQ1. In yet another aspect, the present invention provides pharmaceutical compositions of compounds or pharmaceutically acceptable salts of one or more HDACI and/or bromodomain protein inhibitor compounds described herein and a pharmaceutically acceptable carrier. In yet another aspect, the present invention provides methods of treating diseases mediated by HD AC enzymes, comprising administering to a subject in need thereof a therapeutically effective amount of one or more HDACI compounds described herein. Other methods involve co- therapies by administering one or more HDACI and/or bromodomain protein inhibitor compounds of the present invention with other anti-cancer agents. Another aspect of the invention involves administering to a subject in need thereof a therapeutically effective low-dose amount of one or more HDACI and/or bromodomain protein inhibitor compounds described herein. Other methods involve co-therapies by administering a low-dose of one or more HDACI compounds of the present invention with other bromodomain protein inhibitor compounds as well as other anti-cancer agents.

The terminology used herein is for describing particular embodiments and is not intended to be limiting. As used herein, the singular forms“a,”“and” and“the” include plural referents unless the content and context clearly dictate otherwise. Thus, for example, a reference to“a” or “the” marker may include a combination of two or more such markers. Unless defined otherwise, all scientific and technical terms are to be understood as having the same meaning as commonly used in the art to which they pertain. For the purposes of the present invention, the following terms are defined below.

The biomarkers of the invention are set forth in Table 4. As used herein, a biological marker (“biomarker” or“marker” or“pharmacodynamic biomarker”) is a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacological responses to therapeutic interventions, consistent with NIH Biomarker Definitions Working Group (1998). Markers can be individual genes, or genome wide markers, or individual residues of a protein, such as a histone residue that may be chemically modified, such as through acetylation and deacetylation. Markers can also include patterns or ensembles of characteristics indicative of particular biological processes. Markers can also include patterns or ensembles of characteristics indicative of dose-dependent biological processes. The biomarker measurement can increase or decrease (“modulate”) to indicate a particular biological event or process. In addition, if the biomarker measurement typically changes in the absence of a particular biological process, a constant measurement can indicate occurrence of that process.

The markers of this invention may be used for diagnostic and prognostic purposes, as well as for therapeutic, drug screening and patient stratification purposes (e.g., to group patients into a number of“subsets for evaluation”), as well as other purposes described herein. Further included is information related to the function of the gene and the biological process that it is involved in. The polynucleotide sequences of these genes, as well as the sequences of the polypeptides encoded by them, expression levels, chemical modifications, and epigenetic modifications, are publicly available and known to one having average skill in the art. All information associated with the publicly-available identifiers and accession numbers, including the nucleic acid sequences of the associated genes and the amino acid sequences of the encoded proteins is incorporated herein by reference in its entirety.

The present invention includes all compositions and methods relying on correlations between the reported biomarkers and HDACI and/or BRD4 inhibition sensitivity (sensitivity and/or resistance) and/or bromodomain protein inhibitors of the cancer cells. Such methods include methods for determining whether a cancer patient is predicted to respond to administration of a certain single, or combination of therapies, as well as methods for assessing the efficacy of such therapy.

Further included are methods for improving the efficacy of a cancer therapy by administering to a subject a therapeutically effective amount of one or more HDACIs, such as largazole, and/or one or more bromodomain protein inhibitor, such as JQ1. In this context, the term“effective” or“effective amount” or“therapeutically effective amount” is to be understood broadly to include reducing or alleviating the signs or symptoms of cancer, improving the clinical course of the disease, or reducing any other objective or subjective indicia of the disease, or inducing an observable effect, such a modulations in transcription of mRNA processing and the like. Different drugs, doses and delivery routes can be evaluated by performing the method using different drug administration conditions. Toxicity and therapeutic efficacy of such compositions can be determined by standard pharmaceutical procedures in cell cultures or experimental animals, e.g., for determining the LD₅₀ (the dose lethal to 50% of the population) and the ED₅₀ (the dose therapeutically effective in 50% of the population). The dose ratio between toxic and therapeutic effects is the therapeutic index, and it can be expressed as the ratio LD50/ED50. Compounds that exhibit large therapeutic indices are preferred. The data obtained from these cell culture assays and additional animal studies can be used in formulating a range of dosage for human use. The dosage of such compounds lies preferably within a range of circulating concentrations that include the ED50 with little or no toxicity. The dosage varies within this range depending upon the dosage form employed, sensitivity of the patient, and the route of administration.

Further included are methods for improving the efficacy of a cancer therapy by administering to a subject a therapeutically effective amount of one or more HDACI. In this context, the term“low dose,” or“low effective dose,” or“low therapeutically effective dose” is to be understood broadly to mean a HDACI dose sufficient to result in the upregulation of gene transcripts in a target cell low as generally described herein. In other embodiments, it can mean a nanomolar HDACI concentrations (<GEo) that predominantly results in upregulation of gene transcripts in a target cell as generally described herein. In other embodiments, it can mean a nanomolar HDACI dose ranging from 9.4 nM and 18.8 nM, 1 nM and 299nM. In other embodiments, it can mean a dose sufficient to modulate SEs expression.

Further included are methods for improving the efficacy of a cancer therapy by administering to a subject a therapeutically effective amount of one or more HDACI. In this context, the term“high dose,” or“high effective dose,” or“high therapeutically effective dose” is to be understood broadly to mean a HDACI dose sufficient to result in the repression of transcription in a target cell low as generally described herein. In other embodiments, it can mean a nanomolar HDACI concentrations (>GEo) that predominantly results in suppression of gene transcripts and mRNA accumulation in a target cell as generally described herein. In other embodiments, it can mean a nanomolar HDACI dose ranging from 300 nM and 1000 nM,. In other embodiments, it can mean a dose sufficient to modulate SEs expression. In other embodiments, it can mean a dose sufficient to demonstrate the loss/reduction of H3K27 acetylation, and/or a loss/reduction of H3K27 acetylation at enhancers and/or SEs, and/or a reduction in the expression of CBP, and/or RNAP II pausing, RNAP II accumulation at SEs, and/or RNAP II activity or expression, and/or poised SEs.

In any of the embodiments of the present invention, the HD AC inhibitor can include, but is not limited to, any compound or its analog that inhibits the function or activity of a histone deacetylases. HD AC inhibitors can include, hydroxamic acid, a carboxylic acid, a benzamide, an epoxide, a short- chain fatty acid, a cyclic tetrapeptide containing a 2-amino-8-oxo-9, 10-epoxy - decanoyl moiety, and a cyclic peptide without the 2-amino-8-oxo-9, lO-epoxy-decanoyl moiety. A hydroxamic acid can include, but is not limited to, suberoylanilidine hydroxamic acid, TSA, and SAHA. A carboxylic acid can include, but is not limited to, butanoic acid, valproic acid, and 4-phenylbutanoic acid. A benzamide can include, but is not limited to, N- acetyldinaline and MS-275. An epoxide can include, but is not limited to, trapoxin, depeudecin, and depsipeptide FK 228.

In a preferred embodiment, the HDAC inhibitor is largazole. In another preferred embodiment, HDAC inhibitor comprises the macrocyclic compounds described in US Pat. App. No.13/700,373, entitled “Macrocyclic Compounds Useful As Inhibitors of Histone Deacetylases.” (Each compound disclosed in that application, in particular all macrocyclic compounds disclosed in figures 1-7, paragraphs 14-73 and claims 20-33. In addition, each compound disclosed in claims 1-11 of US Pat. No. 8754050, and claims 1-15 of US Pat. No. 9422340, all of which are specifically incorporated herein by reference and may generally be referred to as ONK101 or paragazole.) In a preferred embodiment, the HDAC inhibitor is one or more of the following: Vorinostat, Romidepsin (Isodax), SAHA (Vironostat), PDX101 (Belinostat), Panobinostat, Eintinostat, TSA (Trichostatin), ONK101 (Paragazole), Largazole, and chidamide (CS055).

In certain embodiments, the methods are useful for disrupting super-enhancer function and/or for preventing, treating, or ameliorating of a symptom associated with a disease, disorder, or pathological condition involving super-enhancer function. A preferred embodiment of the current invention include methods for treating a super-enhancer-mediated disease, the method comprising administering an effective amount of at least one HDACI and/or at lease one bromodomain protein inhibitor. A preferred embodiment of the current invention includes methods for treating a super-enhancer-mediated disease, the method comprising administering an effective amount of at least one HDACI and/or at lease one bromodomain protein inhibitor that may inhibit BRD4.

The term“enhancer” and/or“super-enhancer” as used herein, generally refers to large clusters of transcriptionally active regions of DNA that drive the expression of genes that control cell identity. Super-enhancers become dysregulated in multiple disease states, including but not limited to, cancer. Super-enhancers recruit transcription factors, cofactors, chromatin regulators, signaling enzymes (e.g., kinases) and the transcriptional machinery (e.g., RNA polymerase II) that form a large complex that regulates the expression of multiple genes simultaneously that are not necessarily in close proximity in regard to the linear form of DNA (Smith and Shilatifard, 2014, Nature Structural and Molecular Biology 21(3):210-219). Super-enhancers allow cells to have efficiencies in regulating groups of genes that work in concert to determine or maintain cell identity. It has been demonstrated that cancer cells reprogram super-enhancer complexes to change the transcriptional activity of a cancer cell leading to oncogenesis, metastasis, and progression of the disease. In fact, it has been postulated that many diseases, even outside of cancer, are ultimately a result of malfunctioning super-enhancer complexes (Cell 2013, Nov 7;l55(4):934-47). As used herein, the definition of a“super-enhancer” is also at least consistent with the definition provided in paragraphs 0005-0024 of US Patent Application No. 2014/0287932, being incorporated in their entirety by reference. A“super-enhancer” also includes all genes under its direct or indirect control. As used herein, a“super-enhancer” also includes all super-enhancers described in in any of Tables 1-90 in US Patent Application No. 2014/0287932. (Such Tables being incorporated herein by reference as being specifically included in Table S5 below)

As used herein, the phrase“expression,”“gene expression” or“protein expression,” such as the level of includes any information pertaining to the amount of gene transcript or protein present in a sample, in a cell, in a patient, secreted in a sample, and secreted from a cell as well as information about the rate at which genes or proteins are produced or are accumulating or being degraded (e.g., reporter gene data, data from nuclear run-off experiments, pulse-chase data etc.). Certain kinds of data might be viewed as relating to both gene and protein expression. For example, protein levels in a cell are reflective of the level of protein as well as the level of transcription, and such data is intended to be included by the phrase“gene or protein expression information.” Such information may be given in the form of amounts per cell, amounts relative to a control gene or protein, in unitless measures, etc. The term“expression levels” refers to a quantity reflected in or derivable from the gene or protein expression data, whether the data is directed to gene transcript accumulation or protein accumulation or protein synthesis rates, etc.

The term“modulate” when in reference to the expression may mean up-regulation as well as down-regulation of expression as compared to a baseline, as well as in some cases no expression, as well as alternative expression and modifications, such as alternative splicing of mRNAs. The term “modulate” when in reference to chemical modification, epigenetic modifications, or acetylation of deacetylation may mean increases in, as well as decreases of, expression from a base-line as well as in some cases no chemical modification or maximal chemical modification, such as hyperacetylation.

The terms “reduce,” “inhibit,” “diminish,” “suppress,” “decrease,” “prevent” and grammatical equivalents (including“lower,”“smaller,” etc.) when in reference to the expression of any symptom in an untreated subject relative to a treated subject, mean that the quantity and/or magnitude of the symptoms in the treated subject is lower than in the untreated subject by any amount that is recognized as clinically relevant by any medically trained personnel. In one embodiment, the quantity and/or magnitude of the symptoms in the treated subject is at least 10% lower than, at least 25% lower than, at least 50% lower than, at least 75% lower than, and/or at least 90% lower than the quantity and/or magnitude of the symptoms in the untreated subject.

The term“drug” or“compound” as used herein, refers to any pharmacologically active substance capable of being administered which achieves a desired effect. Drugs or compounds can be synthetic or naturally occurring, non-peptide, proteins or peptides, oligonucleotides or nucleotides, polysaccharides or sugars. The term“administered” or“administering,” as used herein, refers to any method of providing a composition to a patient such that the composition has its intended effect on the patient. An exemplary method of administering is by a direct mechanism such as, local tissue administration (i.e., for example, extravascular placement), oral ingestion, transdermal patch, topical, inhalation, suppository etc.

The term“patient,” as used herein, is a human or animal and need not be hospitalized. For example, out-patients or persons in nursing homes are“patients.” A patient may comprise any age of a human or non-human animal and therefore includes both adult and juveniles (i.e., children). It is not intended that the term“patient” connote a need for medical treatment, therefore, a patient may voluntarily or involuntarily be part of experimentation whether clinical or in support of basic science studies. The term“cell” as used herein, may include a cell or cells in an in vivo system, such as a subject or patient, or an in vitro system, such as a cell-line or cell- based assay. The term“subject” as used herein refers to a vertebrate, preferably a mammal, more preferably a primate, still more preferably a human. Mammals include, without limitation, humans, primates, wild animals, feral animals, farm animals, sports animals, and pets. The term “protein” as used herein, refers to any of numerous naturally occurring extremely complex substances (as an enzyme or antibody) that consist of amino acid residues joined by peptide bonds, contain the elements carbon, hydrogen, nitrogen, oxygen, usually sulfur. In general, a protein comprises amino acids having an order of magnitude within the hundreds. The term“peptide” as used herein, refers to any of various amides that are derived from two or more amino acids by combination of the amino group of one acid with the carboxyl group of another and are usually obtained by partial hydrolysis of proteins. In general, a peptide comprises amino acids having an order of magnitude with the tens.

The term“pharmaceutically” or“pharmacologically acceptable,” as used herein, refer to molecular entities and compositions that do not produce adverse, allergic, or other untoward reactions when administered to an animal or a human. The term,“pharmaceutically acceptable carrier,” as used herein, includes any and all solvents, or a dispersion medium including, but not limited to, water, ethanol, polyol (for example, glycerol, propylene glycol, and liquid polyethylene glycol, and the like), suitable mixtures thereof, and vegetable oils, coatings, isotonic and absorption delaying agents, liposome, commercially available cleansers, and the like. Supplementary bioactive ingredients also can be incorporated into such carriers. The term “salts,” as used herein, refers to any salt that complexes with identified compounds contained herein. Examples of such salts include, but are not limited to, acid addition salts formed with inorganic acids (e.g. hydrochloric acid, hydrobromic acid, sulfuric acid, phosphoric acid, nitric acid, and the like), and salts formed with organic acids such as, but not limited to, acetic acid, oxalic acid, tartaric acid, succinic acid, malic acid, fumaric acid, maleic acid, ascorbic acid, benzoic acid, tannic acid, pamoic acid, alginic acid, polyglutamic, acid, naphthalene sulfonic acid, naphthalene disulfonic acid, and polygalacturonic acid. Salt compounds can also be administered as pharmaceutically acceptable quaternary salts known by a person skilled in the art, which specifically include the quaternary ammonium salts of the formula— NR,R',R"+Z— , wherein R, R', R" is independently hydrogen, alkyl, or benzyl, and Z is a counter ion, including, but not limited to, chloride, bromide, iodide, alkoxide, toluenesulfonate, methyl sulfonate, sulfonate, phosphate, or carboxylate (such as benzoate, succinate, acetate, glycolate, maleate, malate, fumarate, citrate, tartrate, ascorbate, cinnamoate, mandeloate, and diphenylacetate). Salt compounds can also be administered as pharmaceutically acceptable pyridine cation salts having a substituted or unsubstituted partial formula: wherein Z is a counter ion, including, but not limited to, chloride, bromide, iodide, alkoxide, toluenesulfonate, methyl sulfonate, sulfonate, phosphate, or carboxylate (such as benzoate, succinate, acetate, glycolate, maleate, malate, fumarate, citrate, tartrate, ascorbate, cinnamoate, mandeloate, and diphenylacetate).

“Cancer” is a term used for diseases in which abnormal cells divide without control and are able to invade other tissues. There are more than 100 different types of cancer. Most cancers are named for the organ or type of cell in which they start— for example, cancer that begins in the colon is called colon cancer; cancer that begins in basal cells of the skin is called basal cell carcinoma. The main categories of cancer include carcinomas, sarcomas, leukemias, lymphomas and myelomas, and central nervous system cancers. Some common cancer types include, but are not limited to, bladder cancer, breast cancer, colon and rectal cancer, endometrial cancer, kidney (renal cell) cancer, leukemia, lung cancer, melanoma, non-Hodgkin's lymphoma, pancreatic cancer, prostate cancer, skin cancer (non-melanoma), and thyroid cancer. In one embodiment, the cancers contemplated for treatment herein include colon and breast cancers and the like.

The terms“comprises”,“comprising”, are intended to have the broad meaning ascribed to them in U.S. Patent Law and can mean“includes”,“including” and the like.

EXAMPLES

Example 1 : This example illustrates a dose-dependent cytostatic activity of largazole

As a HD AC inhibitor, the natural product largazole selectively inhibits class I, class lib, and to a lesser extent class IV HDACs but spares class Ila HDACs (Supplementary Table Sl). Largazole has a broad spectrum tumor inhibitory activity towards most of the NCI 60 cell lines, with an average GI50 of approximately 10 nM (Supplementary Table S2 - incorporated specifically by reference from priority document U.S. Provisional Application No. 62/594,952). The present inventors found that colorectal cell lines are particularly sensitive to largazole and because HCT116 cells have been consistently investigated by genome-wide sequencing analyses, the present inventors chose this cell line for all follow-up studies. Cell cycle analysis of HCT116 cells by flow cytometry revealed that largazole stimulation for 25 h alters cell cycle progression and leads to significant cell death (Figure 1A and B). Specifically, exposure of HCT116 cells to low concentrations of largazole induces cell cycle arrest at Gl (~2 nM) and G2/M (~37 nM) phases; however, these effects systematically dissipate at higher largazole concentrations. Significantly, largazole caused a dramatic increase of sub-Gl phase (apoptotic) cells in a dose- dependent manner that becomes apparent at -18 nM and plateaus at -300 nM. These results confirm that largazole inhibits proliferation and induces significant cell death of HCT116 cells at low nanomolar concentrations (GI50 = ~34 nM) and further demonstrate that its effect on cell cycle profile is dose dependent.

Example 2: This example illustrates that histone marks undergo dose-dependent changes in response to largazole treatment

Histone H3 acetylation has been used as a reliable pharmacodynamic mark for HDACI on-target activity. To determine largazole’ s effects on acetylation of specific lysine residues, the present inventors analyzed dose-dependent accumulation of acetylated lysine 9 and 27 on histone H3 (H3K9/27ac). It is important to note that largazole-induced cell death occurs after 17 h exposure based on time and dose dependent GI50 measurement. At the 16 h time point, there is no significant cell death (data not shown). For most of the genome-wide studies in this report, the present inventors collected cells at 16 h post treatment. As expected, both H3K9ac and H3K27ac signals elevated significantly over the range of largazole doses used but the EC50 of the two marks appear to be different (Figure 1C). Moreover, three H3 lysine methylation marks were also analyzed. While there was a noticeable increase in global H3K4mel, no significant changes in H3K4me2 or H3K4me3 were observed (Figure 1C). Because hyperacetylation of histones is linked to gene activation, the present inventors hypothesized that genomic location-specific changes in histone acetylation may account for the altered regulation of the largazole responsive genes. To test this hypothesis, the present inventors employed chromatin immunoprecipitation coupled with massive parallel sequencing (ChIP-seq) using antibodies targeting H3K9ac and H3K27ac in HCT116 cells treated with increasing concentrations of largazole.

Because largazole confers an extensive degree of acetylation over genomic regions that can extend for several kilobases (Figure 11 A), the present inventors used Fast Read Stitcher (F Stitch) under default signal threshold, to identify broad regions of enrichment over a wide range of signal strength (26). FStitch exhibited a detection range superior to MACS2 (32) for low-profile acetylation signal found in cells treated with high largazole concentrations. Over 96% of the genomic space identified by FStitch in H3K27ac ChIP-seq data from cells treated with 300nM largazole was not detected by MACS2 (Figure 11B). To gain a better understanding of the signal distribution of H3K9/27ac, the present inventors divided the human genome into five territories based on the RefSeq hgl8 gene alignment from the UCSC Genome Browser (25): proximal promoter (+/- 2kb from the TSS), gene region (-2kb from TSS to end of annotated gene), 3’ end (end of annotated gene to 2kb downstream), enhancer elements (+/- 2kb from the determined center), and intergenic regions. In unstimulated cells, ~5% of the genome was associated with H3K9ac and -K27ac ChIP-seq signal, with both marks heavily enriched at enhancer elements (54.0% for H3K27ac and 42.4% for H3K9ac) and transcription start sites (23.6% for H3K27ac and 26.1% for H3K9ac) (Figure 1D and E).

Increasing doses of largazole (nM) exposure shows a general trend of gradual H3K9ac enrichment for all genomic territories analyzed, with the gene body regions displaying the highest elevation (expanding purple region of the log2 ratio of largazole/vehicle) (Figure 1F and Figure 11C). In contrast, H3K27ac enrichment is mostly restricted to gene body regions (Figure 1G and Figure 11C). Unexpectedly, a notable reduction in H3K27ac signal was seen in the enhancer elements as largazole concentration increased (Figure 1G, green). Collectively, the data indicates that H3K9ac and H3K27ac undergo similar dose-dependent changes along gene body regions but opposite trends at enhancer locations in response to largazole.

Example 3: This example illustrates dose-dependent spreading of H3K9ac and K27ac at specific regions of the genome upon largazole exposure

Since H3K9ac and -K27ac are functionally associated with proximal promoters and the most drastic acetylation changes occurred at protein-coding regions, the present inventors further examined genes that were occupied by H3K9ac and -K27ac under basal conditions. A total of 10,356 unique genes with a minimal length of 3 kb exhibited H3K9ac at their transcription start site (TSS) and 10,272 genes were positive for H3K27ac signal. As shown in Figure 2A, the present inventors found distinct gene patterns associated with H3K9 and -K27 acetylation changes. One class of genes displays a TSS highly occupied by acetylated H3K27 or -K9 at basal state, and the signal spreads in a dose-dependent manner into the transcribed region upon largazole treatment (Figure 2A, orange region; box on the right). The second class of genes displays a moderate amount of histone acetylation at the TSS with DMSO treatment and the signal remains anchored to the promoter throughout all largazole doses (Figure 2A, blue region; box on the left). Lastly, the present inventors found over 7,600 genes that are not associated with H3K9/27ac and remain acetylation free under any dose of largazole stimulation (Figure 2A, green region; dash box in the middle). Using a cutoff of a two-fold spread in histone acetylation signal from untreated (DMSO) versus 300 nM largazole, the present inventors found 4,154 unique genes exhibiting H3K27 hyperacetylation and 5,969 genes with higher levels of acetylated H3K9 (Figure 2B and C). The relative number of genes without significant acetylation (acetylation“deserted” genes) is very similar for both histone marks. Thus, largazole-induced dose-dependent changes in histone acetylation are both acetylation mark specific and restricted to defined genomic regions.

Example 4: This example illustrates that largazole induces dose-dependent changes in RNA transcript levels irrespective of spreading of histone acetylation marks

Since a subset of genes exhibited dose-dependent H3K9ac and H3K27ac signal spreading, the present inventors wondered if these patterns are predictive of changes in gene expression. The present inventors harvested poly(A) RNA from HCT116 cells treated for 16 h with increasing concentrations of largazole and performed RNA-seq analysis. Only transcripts that exhibit dose-dependent up- or down-regulation based on DESeq analysis with an adjusted p- value cutoff of less than 0.1 were selected for further analysis (18). Dose-dependent transcripts were identified through this approach. A striking pattern emerged when differentially expressed transcripts were plotted against largazole dose. Whereas a higher dose of largazole resulted in more significantly deregulated genes (Figure 3 A), increasing dosage led more genes to be down- regulated than up-regulated (Figure 3B). This event is unlikely due to the cell loss associated with nonspecific toxic effects of largazole as a more polarized gene expression pattern is observed with no significant decrease in cell numbers at this endpoint. Thus, low dose largazole exposure triggers selective gene activation and higher dose of largazole is associated with wide spread transcriptional suppression.

To examine the effect of hyperacetylation of gene bodies on transcription, the present inventors plotted mRNA levels from all nine treatments for the set of genes that showed significant acetylation spread. Surprisingly, hyperacetylated genes with H3K9ac or -K27ac showed no consistent behavior in expression changes, as the present inventors found both up- and down-regulated transcripts (based on an arbitrary 2-fold change cutoff) as well as a relatively large set of genes with no significant changes in mRNA levels (Figure 3C and D). It is worth noting that the change in transcript levels associated with H3K9ac occurs at a lower largazole dose than the observed changes in H3K27ac spread (Figure 3D).

To explore a possible synergy between H3K9ac and -K27ac with respect to transcriptional effects, the present inventors also looked at the mRNA expression levels of 3,115 genes that developed enrichment for both histone marks (Figure 2C). Similar to mRNA expression patterns from genes hyperacetylated at H3K9 or -K27, mRNAs from genes whose coding regions exhibited spread of both acetylation marks showed both events of up- and down- regulation (Figure 3E). Taken together, these findings show that the spectacular elevation and spreading of H3K9ac or H3K27ac upon largazole exposure appears to be insufficient to predict the direction of change (i.e. up or down) in transcript levels with largazole exposure.

Example 5: This example illustrates that largazole induces RNAPII pausing at a subset of genes.

Because previous reports suggest HDACI target the transcription elongation complex (12), the present inventors sought to examine the genome wide effects of largazole-induced hyperacetylation on RNAPII occupancy along gene bodies. To this end, the present inventors conducted ChIP-seq experiments targeting total RNAPII in HCT116 cells treated with DMSO and those treated with either 75 nM and 300 nM largazole. The present inventors used the ‘pausing index’ (PI) (28) as the measurement to determine the extent of RNAPII pausing in a representative set of genes (refer to methods and materials for selection criteria). Pausing index was calculated by dividing the RNAPII ChIP-seq unique read density in the proximal promoter region by that in the gene body. The present inventors observed that RNAPII Pis increased systematically upon largazole treatment for most of the -2300 genes analyzed. As shown in Figure 3F, most genes exhibit an increased PI when comparing 75nM largazole treated to DMSO treated cells. Treatment with 300nM largazole further increased Pis relative to 75nM treatment, but this increase was not as pronounced as that between DMSO and 75nM largazole-treated cells. Correlation comparisons of pausing indices from the three cellular conditions further illustrate that Pis increase with largazole dosage (refer to slopes in Figure 3G). In addition, examination of specific gene loci suggests that the relative distribution of RNAPII along genes is different across largazole-dose treatments. For example, the PI for the region coding of transcription factor DP1 (TFDP1) in DMSO treated cells is 0.43 and the index increased to 3.70 in cells treated with 75 nM largazole (Figure 3H, blue and green). In this case, depletion of RNAPII signal throughout the gene body is the main contributing factor to the increase of PI at the TFDP1 locus. However, at higher largazole dose treatment (300 nM), the TFDP1 gene region displays a PI of 16.36 that mainly reflects the vast accumulation of RNAPII restricted to the proximal promoter (Figure 3H, red). The present inventors then examined the influence of RNAPII pausing on the relative accumulation of transcripts associated with affected genes. In untreated cells, the present inventors found a modest but strongly supported (p = 2.2e-l6) negative correlation (r = -0.333) between RNAPII pausing indices and relative accumulation of mRNAs (FPKM values in RNA- seq) (Figure 31, left). The present inventors observed that highly expressed genes, such as TFDP1 and MYC (FPKMs > 80), are associated with relatively low Pis (0.46 and 2.74, respectively), whereas silent genes or those with low levels of expression (FPKMs < 1) such as BEST3 illustrate Pis greater than 20 (Figure 31, left). Analyses of data from cells treated with either 75 nM and 300 nM concentrations of largazole showed a marginal decrease in the correlation between Pis and FPKM values, however a general unidirectional trend of some genes became evident when looking at the changes in both Pis and FPKM values from downregulated genes (Figure 3, middle and right). Increase in pausing indices is clearly the most dominant pattern observed among the analyzed gene regions; however, the present inventors also see a small number of genes with unchanged Pis and relatively constant FPKM values (GAPDH and RPS11) as well as genes that became less paused and more transcriptionally active (SAT1 and SIRT4). Thus for most genes analyzed, largazole specifically interrupts RNAPII occupancy downstream of proximal promoters and this event most likely affects the transition from initiation to elongation or the elongation steps of RNA synthesis and plausibly contributes to down-regulation of gene expression at higher dose of largazole.

Example 6: This example illustrates that genes with promoter-paused RNAPII are more resistant to H3K27 hyperacetylation by largazole

Class I HDACs preferentially occupy promoters of active genes and positively correlate with transcription levels (8). Accordingly, it is expected that highly expressed (low paused) genes should be more sensitive to largazole. This should be reflected in the data by the accumulation of newly acetylated H3K9 and -K27 signal along highly expressed genes in cells treated with relatively low concentrations of largazole. Among the genes displaying hyperacetylation of histone H3K9 and -K27, the present inventors noticed clear differences in dose-specific signal spread. For instance, the transcribed region of the protocadherin gene FAT1, displays a substantial association with H3K27ac in cells treated with 18.75 nM largazole and the signal reaches complete gene body coverage in cells stimulated with 75 nM (Figure 4A, top). The present inventors also found gene regions, such as the HNRNPM locus that do not associate with significant H3K27ac levels until ~30 nM largazole treatments (Figure 4A, middle). Finally, there is a group of genes that are more resistant to hyperacetylation changes. For example, in the EMC1 gene region newly acetylated histones are only detected in cells treated with largazole concentrations at or above 75 nM (Figure 4A, bottom).

To elucidate the sensitivity of each gene to largazole-induced acetylation changes the present inventors determined the largazole concentration necessary to induce a half-maximal acetylation response (EC50) in genes displaying 50% or greater H3K9ac or -K27ac signal coverage over the annotated gene lengths. ETsing FStitch calls, the present inventors calculated the total acetylation signal for both H3K9ac and -K27ac along the gene bodies for each of the nine corresponding ChIP-seq experiments and used the Sigmoidal Dose Response Search algorithm (SDRS) with a p = 0.05 cutoff (33). This approach allowed us to effectively assign each gene a largazole dosage sensitivity for both H3K9ac and -K27ac changes (Figure 4B). Distribution analysis of EC50 values from the two histone marks revealed a similar overall range of largazole dose sensitivity (~8 nM to -210 nM) (Figure 4C). However, within the population of gene regions associated with H3K27ac, the present inventors observed a higher number of genes responsive to low concentrations of largazole as compared to H3K9ac.

To explore a possible correlation between the basal pause state of genes and sensitivity to largazole-induced acetylation changes, the present inventors compared the Pis from the 20% of genes most sensitive to largazole (lowest EC50) to that of the 20% of genes exhibiting the most resistance to acetylation changes (highest EC50) (Figure 4D). The present inventors found that gene bodies with low H3K27ac EC50 scores (more sensitive) are significantly less paused under basal conditions, when compared to the pausing indices of genes most resistant to H3K27ac association (least sensitive) (Figure 4D, left). In contrast, a similar analysis revealed that the pausing state of RNAPII from genes in untreated cells has no statistically significant influence on the dose-dependent changes of H3K9ac (Figure 4D, right). Overall, the data shows that dose- dependent changes in H3K9ac and H3K27ac by largazole have distinct dose-response behaviors. Genes that are highly expressed with low RNAPII pausing prior to treatment are more sensitive to low dose H3K27 hyperacetylation whereas H3K9 acetylation dose-dependent changes do not seem to be influenced by pausing state.

Example 7: This example illustrates that largazole induces major changes in the landscapes of histone marks in distal regulatory elements Although H3K9ac and H3K27ac undergo a broad dose-dependent increase in the gene body region, the present inventors observed dramatic differences between the two marks at enhancer regions. Specifically, the present inventors observed the loss of H3K27ac but not H3K9ac with higher doses of largazole (Figure 1F and G). The present inventors wondered whether the increase in RNAPII pausing observed with higher concentrations of largazole may be the result of remodeling of enhancer elements. To this end, the present inventors measured enhancer associated histone acetylation (H3K4mel and H3K4me2 (34, 35)) and RNAPII binding as a function of largazole dose in treated cells. The present inventors performed H3K4mel and H3K4me2 ChIP-seq of crosslinked nuclear extracts obtained following either vehicle (DMSO), 75 nM, or 300 nM largazole treatments of HCT116 cells. To help identify active enhancer regions, the present inventors used published GRO-seq (24) as well as ChIP-seq data for MLL4 and p300 (23) in untreated HCT116 cells. The present inventors then searched for genomic regions containing overlapping H3K27ac and H3K4mel peaks (as determined by FStitch and MACS2, respectively) that were not superimposed over annotated transcription start sites. The present inventors identified 41,017 inter- and intragenic enhancer locations co-occupied by both H3K27ac and H3K4mel prior to largazole treatment (Figure 5 A). The present inventors refer to these enhancers as“canonical enhancers”. When postlargazole treatment data was examined, another class of enhancer elements the present inventors refer to as“poised enhancers” became apparent. These enhancers are characterized by the dramatic dose-dependent increase of H3K27ac, H3K4me2, and RNAPII occupancy and are marked by H3K4mel prior to largazole stimulation (Figure 5B). These regions are frequently occupied by MLL4, display unusually high levels of p300, and produce low amounts of eRNA in the basal cellular state. The present inventors identified 18,240 poised enhancer elements in HCT116.

Many enhancer elements span large regions likely containing multiple nucleosomes, which makes it difficult to analyze dose responsive changes in H3K27ac. To minimize the number of false-positive deactivated and activated enhancers, the present inventors focused on a subset of isolated enhancer regions marked with a single, centered H3K27ac peak in a 20 kb genomic window for further analysis (Figure 5C). From the originally identified -41,000 putative enhancers in untreated cells, the present inventor’s selected 8,667 isolated active enhancers that met the above criteria (Figure 5D, left). Similarly, the present inventors selected 3,505 isolated enhancers from an initial 18,240 identified poised elements (Figure 5D, right). To examine epigenetic modifications of enhancer elements as a function of dose, the present inventors quantified H3K27ac signal coverage (FStitch) over +/- 1.5 kb of the enhancer regions in data from each largazole treatment X-means clustering of the 8,667 isolated active enhancers and subsequent filtering for decreased RNAPII accumulation, revealed the presence of 797 largazole-inactivated regulatory elements. An example of largazole-deactivated enhancer is seen in the hnRNPU locus (Figure 12 A), a gene that is required for the association of Xist RNA with the Xi and accumulation of H3K27me3 to ensure X chromosome inactivation (36). While the gene body of hnRNPU undergoes largazole-dependent H3K27ac increase and expansion, the upstream enhancer region (identified by p300, RNAPII, MLL4, H3K4mel, and H3K4me2 marks) exhibits dose-dependent decline in H3K27ac, H3K4mel, and H3K4me2 signal. Moreover, the hnRNPU mRNA levels show dose-dependent inhibition, which correlates with the loss of H3K27ac at its enhancer (Figure 12B).

The present inventors further segregated the deactivated enhancers into low-dose (416 elements) and middose (381 elements) affected subsets (Figure 5D, left). The low dose deactivated enhancer cluster displays a high H3K27ac and low H3K9ac signature at the basal state (Figure 5E, top). Low dose largazole treatments erase H3K27ac while the H3K9ac signal retains a low profile. Interestingly, the H3K9ac boundaries associated with these genomic regions undergo a significant expansion with increasing largazole dosage. Consistent with deactivation of these enhancers, dose-dependent reduction of H3K4mel and RNAPII association were observed and loss of H3K4me2 only occurred at high dose exposure (Figure 13D). The middose deactivated cluster exhibits gradual loss of H3K27ac and a bell-shaped response in H3K9ac changes with increasing largazole exposure (Figure 5E, bottom). In this cluster of enhancers, H3K4mel association shows a dose-dependent decline while H3K4me2 is unchanged (Figure 13C). Hence, largazole treatment causes a significant_number of enhancers to be deactivated with the characteristic loss of H3K27ac.

A similar analysis on the selected poised enhancers yielded mid-dose (688 elements) and high-dose (914 elements) activated subsets. The high dose cluster exhibited a largazole dose- dependent enrichment of H3K27ac and to a lesser degree it also accrued H3K9ac signal (Figure 5F, top). There is a significant RNAPII association and only a slight increase in H3K4mel in this group. In contrast, H3K4me2 signal was barely detectable with DMSO and 75 nM largazole but elevated drastically upon treatment with 300 nM largazole which correlates with the dose- dependent rise of H3K27ac (Figure 13B). The mid-dose induced cluster showed a gradual increase in H3K27ac and RNAPII but a fluctuating H3K9ac level as largazole dose was increased (Figure 5F, bottom and Figure 13A). H3K4me2 was unchanged and H3K4mel displayed a slight decrease at 300 nM largazole. A striking feature associated with the activation of the poised enhancers is that under basal conditions they tend to display high p300 occupancy yet minimal or absent H3K27ac signal (Figure 13F). The presence of H3K4mel and absence of H3K27ac in untreated HCT116 cells suggest that this subset of enhancers is in a poised state but likely primed for prompt activation. It is interesting to note that certain sequence motifs such as the binding site for transcription factor AP-l (activator protein- 1) are enriched in these epigenetically remodeled enhancer regions (Figure 13A-C). Furthermore, the expression of AP-l is upregulated by largazole (Figure 13E), suggesting that AP-l may play a role in enhancer remodeling with HDACs. These results suggest that HDACs are probably actively involved in maintaining the poised state and largazole inhibition of histone deacetylases tip the balance in favor of H3K27 acetylation. Taken together, these findings show that largazole acts through inhibition of HD AC targets both in the deactivation and activation of distinct classes of enhancer elements that can be discerned by their dose sensitivity.

Example 8: This example illustrates that largazole perturbs super-enhancers and

preferentially suppresses SE-associated transcripts

Initially identified as large clusters of transcription factor binding sites (37, 38), superenhancers have been shown to be involved in driving expression of genes that play prominent roles in cell proliferation and differentiation (39). Perturbations of super-enhancer function are frequently associated with human diseases including tumorigenesis. Since it was showed that largazole suppresses expression of some genes in a dose dependent manner, the present inventors wondered whether largazole targets transcripts known to be regulated by super enhancers. The present inventors analyzed RNA-seq data from HCT116 cells exposed to increasing doses of largazole. Among 387 superenhancer associated genes previously identified in HCT116 cells (30), only 285 of these have significant expression (FPKM values > 5) and were selected for further analysis. The present inventors found that in this subset of genes, 132 transcripts are down-regulated (> 2-fold), in a dose-dependent manner (Figure 6A). In contrast, only 27 are up-regulated under the same parameters. No significant changes were observed in the levels of the remaining 126 transcripts. The present inventors noted that among the super enhancer associated genes, the c-Myc oncogene, which is frequently up regulated in tumor cells, is suppressed by high dose largazole treatment (Figure 6A). Furthermore, inspection of the corresponding c-Myc super-enhancer region revealed a reduction of RNAPII and H3K4mel ChIP-seq signals upon largazole treatment (Figure 6B). These observations suggest that largazole perturbs super-enhancer function and preferentially suppresses super enhancer-associated transcripts.

Super-enhancers consist of a collection of many individual enhancers. To determine the effect of largazole on the super-enhancers previously delineated in HCT116 cells (30), the present inventors characterized the largazole response of the individual enhancer regions that make up SEs. Reduction of RNAPII signal was the most dramatic perturbation observed on the c-Myc SE. Therefore, the present inventors utilized RNAPII occupancy trends resulting from largazole treatments and identified distinct responsive patterns (Figure 14A). In cells treated with largazole, 65.7% (1008 out of 1534) of individual RNAPII peak-regions showed decreased densities of RNAPII signal when compared to untreated cells (patterns a, b, and c). The present inventors found 18% of individual enhancers with no change in RNAPII occupancy (pattern d) and only ~9% displayed a gained in RNAPII occupancy (patterns e, f, and g). The remaining 7% of single peaks did not cluster. All individual enhancers analyzed displayed a general loss of H3K4mel in response to largazole (Figure 14A). To further evaluate the largazole-dependent depletion of RNAPII on super-enhancers in an unbiased approach, the present inventors determined the number of SEs in vehicle (DMSO) and largazole treated cells using RNAPII ChIP-seq peak-enrichment ranking method (31, 40) to separate super-enhancers from conventional enhancers. Under basal cellular conditions the present inventors identified 538 super-enhancers characterized with high levels of RNAPII signal and this number is reduced by half to 271 elements in cells under high largazole treatment (Figure 6C). Unlike conventional enhancers that become inactivated by largazole, the present inventors detected no discemable change in the boundaries of H3K27 acetylation along super-enhancers under largazole treatment (Figure 14B, black centroids). Taking together, largazole promotes a dose dependent depletion of RNAPII and H3K4mel levels at most individual peaks within super-enhancer regions but spares histone H3K27 acetylation marks. Example 9: This example illustrates largazole-induced genome response in transformed and non-transformed cell lines

Largazole is known to have differential growth inhibitory activity between transformed and non-transformed cells (13, 41). The present inventors sought to investigate the divergent and convergent genome wide responses to largazole between HCT116 and RPE cells, a nontumorigenic retinal pigmented epithelial cell line immortalized by telomerase overexpression. As seen with HCT116, largazole treatment leads similar dose-dependent increases in H3 acetylation measured by immunoblotting in RPE cells (Figure 15 A). Cell cycle analysis with RPE shows that higher doses of largazole result in more G2/M cells and a reduction in Gl and S phase cells, suggesting G2/M arrest in response to largazole treatment (Figure 15B). However, the frequency of sub Gl cells is lower in largazole treated RPE cells than in HCT116. Consistent with less cell death, RPE cells are less sensitive to largazole in the growth inhibition assay (GI50 = 86 nM). Next, the present inventors performed ChIP-seq studies in RPE cells exposed to 0, 37.5 nM, 75 nM and 300 nM largazole for 16 hr with antibodies against H3K27ac and H3K4mel and 0, 75 nM and 300 nM targeting RNAPII. Vehicle treated RPE cells have higher H3K27ac signal enrichment along gene body regions (~65 Mbp vs. ~20 Mbp) in comparison to HCT116 (Figure 7A vs. Figure 1E). Similar H3K27ac signal was detected at enhancer elements (~90 Mbp) and TSS defined regions (~40 Mbp) for both cell lines. With increasing doses of largazole, there is an increase in H3K27ac signal along gene bodies and decrease at enhancer locations in RPE cells resembling the effect on HCT116 (Figure 7B vs. Figure 1G). Examples of H3K27ac signal spreading are shown in Figure 7C and Figure 4. One notable difference between RPE and HCT116 cells, however, is the number of enhancers defined by the histone marks H3K27ac and H3K4mel, and occupied by RNAPII. RPE cells have fewer enhancer elements in comparison to HCT116 (1,332 vs 8,045) (Figure 15C). Nevertheless, dose dependent deactivation and activation of enhancers seen in HCT116 also occurs in RPE with increasing exposure to largazole (Figure 7D and E). Finally, the present inventors investigated the extent of RNAPII promoter pausing in a representative set of genes in RPE cells (n = 1,644). As seen with HCT116, higher doses of largazole exposure led to more RNAPII pausing, ascertained by the pausing indices of the genes analyzed (Figure 7F, G and H). Therefore, largazole treatment induces shared global genome-responses in transformed and non-transformed cells through spreading of H3K27ac signal, loss of H3K27ac at enhancer elements, and increase promoter pausing of RNAPII.

Example 10: This example illustrates that differential super-enhancer responses to largazole in transformed and non-transformed cell lines

HCT116 and RPE cells differ widely in the number of active super-enhancers. In vehicle treated RPE cells, only 162 elements possess the hallmarks of SEs compared to 538 in HCT116 cells (Figure 15C). In contrast to SEs in HCT116, fewer SEs exhibit significant changes in RNAPII occupancy in response to increasing doses of largazole in RPE cells (Figure 8A vs. Figure 6C). Two super-enhancers associated with the non-coding RNAs NEAT1 and MALAT1 appear to be more active with largazole exposure (Figure 8B). Conversely, the SE encompassing the FOSL1 locus shows dose-dependent decrease in activity based on RNAPII occupancy (Figure 8B). FOSL1 is a member of the Fos gene family that can dimerize with components of the JUN family of proteins to form AP-l transcription factor complexes. Unlike other Jun/Fos genes which are up-regulated by largazole (Figure 13E), expression of FOSL1 is suppressed in both HCT116 and RPE cells. Previously, FOSL1 was identified as a gene involved in controlling Gl/S phase transition by upregulating CCND1 (42). Depletion and gene expression studies have revealed that FOSL1 is an oncogene and its elevated expression is essential for KRAS-driven lung and pancreatic cancer by regulating cell motility and invasion as well as mitotic progression (43-45). Interestingly, the FOSLl-associated SE is deactivated in both RPE and HCT116 cells (Figure 8B and C). To independently validate changes in gene expression of SE associated transcripts in HCT116 and RPE cells in response to largazole treatment, quantitative real-time RT-PCR analysis was performed with selected SE-driven transcripts (Figure 8D). In agreement with RNA-seq and ChIP-seq results, FOSL1, CCND1, CDC20 are down-regulated by largazole in both cell lines while c-Myc is suppressed in HCT116 but not RPE cells. Collectively, these results indicate that largazole preferentially targets super-enhancers in transformed cells and suppresses oncogenes that fuel cellular transformation.

Example 11 : Largazole suppresses expression of cohesin complex and perturbs chromosome alignment during mitosis

It has been shown recently that super-enhancer-driven genes generally occur within chromosome structures that are formed by the looping of two interacting CTCF sites co-occupied by cohesin or by cohesin independent of CTCF (62, 63). In Drosophila , cohesion selectively binds genes with paused RNA polymerase 35. The formation of specific chromatin architecture through cohesin-mediated looping promotes the recruitment and activity of RNA polymerase II, facilitating transcriptional activation 36. Given the activity of largazole on RNAPII pausing and SEs, the present inventors investigated whether largazole affects the expression of cohesin and CTCF along with SE-associated factor BRD4 and Mediator subunits. As shown in Fig. 7a, expression of both CTCF and cohesin subunits (RAD21, STAG1/2, SMC1A/3) show dose- dependent suppression based on the RNA-seq data, while cohesin loading protein WAPAL and NIPBL have no or modest decrease. No changes were seen with BRD4 or Mediator subunits. Suppression of the observed RNA-seq gene expression was independently confirmed by quantitative real time PCR analysis (Fig. 9b). Down regulation of these genes by largazole is also seen in several other cell lines suggesting that perturbation of cohesin and CTCF expression occurs in multiple cell lines (Fig. 9c).

Since cohesin is known to be involved in chromosome alignment during mitosis, downregulation of cohesin is expected to cause defects in chromosome alignment in prometaphase. To test this hypothesis, HCT116 cells were synchronized by double thymidine block and released into nocodazole to establish mitotic arrest. Cells arrested were released from G2/M by removal of nocodazole and the addition of largazole at indicated concentrations along with MG132 which blocks metaphase to anaphase transition. Chromosome alignment is measured by scoring cells with chromosome configurations. Representative images from control and largazole treated cells are shown in Fig. 9d. Quantitation of the effect of largazole on chromosome alignment reveals that increase largazole exposure resulted in significant defects in chromosome alignment (defective chromosome alignment is seen in up to 50% cells with 500 nM largazole). Higher concentrations of largazole results in mitotic failure and increased rate of mitotic catastrophe (Fig. 9e). Since chromosome alignment is very sensitive to cohesin expression, this result is consistent with suppression of cohesin by largazole. As cohesins are critical for long distance communication between enhancers and promoters, downregulation of cohesin and CTCF may be responsible for perturbations of enhancers and super-enhancers when cells are exposed to increasing concentrations of largazole.

Example 12: Dose-dependent modulation of non-coding RNA (IncRNA) / LINC expression. The present inventors have demonstrated that largazole also regulates noncoding RNA/LINC expression. As shown in Figure 10, in this embodiment largazole modulates the expression of a plurality of lncRNAs. This indicates, and the present inventors have shown that largazole or HDACI regulates noncoding RNA expression such that one or more lncRNAs can be used for biomarkers for therapeutics and diagnostics. In a preferred embodiment, the up and down regulated individual or groups of lncRNAs can be used as signatures for predicting HDACi sensitivity in cell lines and patient samples.

Example 13: Improvement of cancer growth inhibition by combinatorial inactivation of BRD4 with JQ1 and largazole (HDACi).

The present inventors demonstrate that the co-administration of largazole (HDACi) and JQ1 (BETi) inhibits growth of cancer cells in vitro , through the inhibition of super-enhancer BRD4. Specifically, HCT116 cells were treated with largazole (HDACi) combined with increasing doses of JQ1 (BETi). As demonstrated in figure l6(a-b), the combinatorial administration of both largazole and JQ1 demonstrated a synergistic effect in inhibiting the grown and violability of cancer cell growth compared with untreated cells. Figure 16(A) shows a 3D scatter plot illustrating cell viability after treatment with dual compound inhibition. Results represent the percentage of growth inhibition compared to untreated HCT116 cells. The data presented was derived from the mean values of three independent experiments (six duplicates/experiment). The present inventors further investigated the combinatorial administration of both largazole and JQ1 on the activity of BRD4. ChIP-sequencing, also known as ChIPseq was used by the present inventors to determine the activity of BRD4 with respect to two known BRD4-repsonsive genes, namely NEAT1 and MALAT1. As demonstrated in Figure 1(C), representative snapshot of BRD4 ChIPseq peaks along the NEAT1 and TL477genes demonstrating decreases BRD4 interaction both NEAT1 and MTL477genes, indicating the downregulation of BRD4’s activity in response to the combination administration of largazole and JQ1. As further shown in figure 1(D), the present inventor’s generated radial barcharts illustrating quantitative BRD4 chromatin occupancy levels, as determined by ChIPseq, across four cell treatments. Distribution of BRD4 is shown as bar plots in megabase pairs (Mbp) and colored according to five genomic categories. Grey shaded regions denote BRD4 signal in control conditions. These data demonstrate the inhibition of BRD4’s ability to access genomic Transcription Start Sites (TSS), resulting in a corresponding downregulation of expression of BRD4-dependent gene as a result of the combinatorial administration of largazole and JQ1.

Example 14. BRD4 displacement from transcription start sites correlates with RNAPII pausing.

Based on the finding that combinatorial administration of largazole and JQ1 disturbs the ability of BRD4 to access TSS locations, the present inventors further demonstrated that this displacement correlated with RNAPII pausing as previously described. As shown in Figures 17 A-C, ChIPseq density profiles were generated and centered across all peaks detected for each epitope in untreated, namely BRIM, H3K27ac, and H3K4mel (left, middle, and right), in HCT116 cells. The present inventors demonstrated the expression density difference of BRIM ChIPSeq signal Reads Per Kilobase of transcript per Million mapped reads (RPKMs) at enhancers (B) and transcription start sites (E) in HCT116 cells following 16 hr treatment with DMSO or 75 nM largazole. Genomic regions were ranked in order of increasing signal under largazole treatment. As shown in figures 17 (C and F), ChIPseq meta-profiles for BRIM and RNAPII representing the average read densities (RPM) flanking 250 enhancers (-3 kb to +3 kb) and 250 transcription start sites (-2 kb to +4 kb) was also generated with data from two ChIPseq experiments are shown; DMSO (blue) and 75 nM largazole (green). These data demonstrated that largazole-dependent inhibition of BRD4 is correlated with RNAPII pausing resulting in the expression changes of BRD4-responsive genes.

Example 15 JQ1 plus largazole disrupt BRD4 occupancy at super-enhancers and drive greater expression changes of SE-associated genes.

The present inventors demonstrate that the action of largazole and JQ1 results in the combinatorial inhibition of SE regions, and in particular BRD4-responsive SE regions. Specifically, the present inventors investigated the interaction of various genomic DNA-protein interaction of BRD4. Specifically, the present inventors treated HCT116 cells for 16 hr with either DMSO (blue), largazole 75 nM (green), or JQ1. As shown in Figure 18(A), BRD4’s genomic binding is decreased in response to largazole and JQ1 inhibitors as a single compound or in combination. The bottom panel of Figure 18(A) illustrates ChIPseq peaks from H3K27ac, H3K4mel, and RNAPII experiments and nascent RNA transcription. Shaded regions mark the boundaries of two super-enhancers from the dbSUPER database. As shown in Figure 18(A-B), the present inventors further generated Pearson correlation plots on 368 super-enhancer regions (dbSUPER) showing BRD4 occupancy levels, as well as “heat map” showing mRNA accumulation changes from super-enhancers associated genes. With respect to this heat-map, each row illustrates a drug treatment and the associated change in Fragments Per Kilobase of transcript per Million mapped reads (FPKM) value. The present inventors further calculated the delineation of super-enhancers using ROSE algorithm based on BRD4 signal in untreated and three treated HCT116 cells. Such data demonstrate that the JQ1 plus largazole disrupt BRD4 interaction with SE regions resulting in differential expression of se-dependent genes.

Example 16 JQ1 plus largazole generate widespread defects on mRNA processing.

As noted above, largazole, and in particular largazole and JQ1 provided to a cell in combination may inhibit the interaction of BRD4 with certain SE regions. This disruption further interferes with the formation of a RNAPII holoenzyme resulting in transcriptional pausing or sputtering. As a result, the present inventors sought to evaluate the effect of BRD4 inhibition on transcription, and in particular mRNA length. As generally shown in Figure 19, administration of HDACIs, and in particular largazole and JQ1 results widespread defects in mRNA processing resulting in alternative splicing (AS) events resulting differentially transcribed mRNAs. Specifically, as shown in Figure 19(A), the present inventors generated an upset plot showing the intersection of TSS bound by BRD4 in cells treated with either DMSO, JQ1, largazole, or JQ1 + largazole. As further shown in Figure 19(B), from this data, the present inventors conducted gene set enrichment analysis output from the 497 TSS sites that display eviction of BRD4 only under JQl+largazole cell treatment. Inset illustrates the distribution of RNA accumulation changes from 43 genes associated with mRNA metabolic processes. Three cell treatments; JQ1 (red), largazole (green), or JQ1 + largazole (blue). The present inventors further demonstrated that the combination of largazole and JQ1 resulted in a significant increase in the number of alternative spliced mRNA’s. Specifically, as shown in Figure 19(C), the number of significantly differentially spliced AS events reported in five categories analyzed. As demonstrated, the combination of largazole and JQ1 resulted in a significant increase in alternative transcript processing resulting in the production of a number of differentially produced mRNA transcripts. For example, in one example highlighted in Figure 19(D), the present inventors demonstrated multiple skipped exon events along the gene UQCRH. Validation of alternative transcript processing was performed by quantitative PCR techniques known in the art. Example 17. HD AC inhibition alone is sufficient to disrupt mRNA processing. The present inventors further demonstrated that HDAC inhibitors significantly increase AS events. As shown in Figure 20, HDAC inhibitors, such largazole and JQ1 single, and in combination generated a number of significantly differentially spliced AS events reported in five categories for distinct human and mouse cells.

Example 18: This example identifies various methods and apparatus related to embodiments of the present invention:

Cell culture and largazole treatment

Cells were cultured in Dulbecco modified Eagle medium (DMEM) supplemented with 10% fetal bovine serum (Sigma), 1% penicillin streptomycin, and 1 % GlutaMAX (Invitrogen) and maintained at 37°C and 5% C02. Prior to treatment, HCT116 and RPE cells were grown in complete media and passaged for 3 consecutive days. Cells were treated with the indicated largazole concentration or equivalent amount of vehicle (DMSO) at 70% confluency and harvested after 16 hours for all ChIP-seq experiments as well as for immunoblotting assays. Synthesis of largazole has been described previously (15).

RNA extraction and library preparation

Total RNA was extracted from 16 hours treated HCT116 cells using TRIzol reagent (Life Technologies) according to the manufacturer’s protocol. The concentration of each sample was quantified using the QubitTM 3.0 Fluorometer (Thermo Fisher), and integrity was measured on an Agilent Bioanalyzer 2100 (Agilent Technologies). The Illumina TruSeq RNA Sample Prepartaion kit (Illumina) was used to generate the RNA sequencing libraries. Briefly, mRNA was purified from 2.5 ug total RNA from each sample, fragmented, and converted to doublestranded cDNA with the use of modified oligo(dT) primers. Sequencing barcodes were ligated to the cDNA fragments, and the resulting fragments were amplified using PCR. The final lengths of oligos from each library were validated on an Agilent Bioanalyzer 2100.

Sequencing

Libraries were quantified using the QubitTM 3.0 Fluorometer and sequenced at the Next- Generation Sequencing Facility at the University of Colorado BioFrontiers Institute and University of Colorado Anschutz Medical Campus. All sequencing libraries were multiplexed and sequenced on an Illumina HiSeq 2000 sequencing system (Illumina).

RNA mapping and normalization Reads were trimmed to a final length of 43bp and mapped to human genome 18 (RefSeq) using Bowtie version 2.02.0 and TopHat version 2.0.6 (16). After mapping, alignment files were processed using SAMtools version 0.1.18.0 (17). Using Cuffdiff version 2.1.1, the present inventors counted the total number of sequencing reads that aligned to each putative gene model in the human genome. To determine which genes were differentially expressed, the present inventors used the R package DESeq version 1.30.0 (18).

Immunoblotting, antibodies, and signal quantification

Western blots were carried out using standard protocols. Briefly, HCT116 and RPE cells were grown, treated, and harvested as previously mentioned. Nuclear protein lysates were separated by SDS-PAGE and transferred to GVS nitrocellulose 0.22 micron membranes. Blots were probed with primary antibodies, followed by peroxidase-conjugated secondary antibodies (GE Healthcare Life). Signal for all immunoblots was acquired using the ImageQuant LAS 4000 biomolecular imager (GE Healthcare LS) with an average exposure of 30 seconds. Antibodies used are as follows: H3K9ac (abeam, cat. # ab444l); H3K27ac (abeam, cat. # ab4729); H3K4mel (abeam, cat. # ab8895); H3K4me2 (abeam, cat. # ab7766); H3K4me3 (abeam, cat. # ab8580); total H3 (abeam, cat #1791).

Chromatin immunoprecipitation

HCT116 and RPE cells were treated with largazole or vehicle for 16 hours and cross- linked with 1% formaldehyde for 15 minutes at room temperature (25°C). Cells were washed two times with PBS and membranes ruptured in hypotonic buffer (50 mM NaCl, 1% NP-40 alternative, 2 mM EDTA, 10 mM Tris, 1 mM DTT, 2 mM EDTA, IX protease inhibitor cocktail (Roche # 04693124001). The cell nuclei were recovered by centrifugation and resuspended in lysate buffer (150 mM NaCl, 0.5% Triton X-100, 2 mM EDTA, 0.1% SDS, 20 mM Tris, 1 mM DTT, IX protease inhibitor cocktail). Resuspended samples were sonicated for 25 cycles (30s ‘on’ at high level and 30s‘off per cycle) using a Bioruptor (Diagenode; Denville, NJ, USA) and spun for 10 minutes at l6,000x g in a microcentrifuge. Samples were incubated for 5 hours at 4°C with 5 to 20 pg of antibodies and 20 pl of 50% slurry with protein A beads (Millipore; Billerica, MA, USA). The immunoprecipitated chromatin was then recovered and DNA purified using phenol chloroform extraction. Sequencing libraries were prepared using an Illumina ChlP- Seq DNA Sample Prep Kit (cat. # IP- 102- 1001), with a starting sample varying from 2 to 20 ng of DNA isolated from the immunoprecipitation step. Antibodies used are as follows: RNAPII (Santa Cruz sc-899 lot # K0111); H3K9ac (abeam, cat. # ab444l); H3K27ac (abeam, cat. # ab4729); H3K4mel (abeam, cat. # ab8895); H3K4me2 (abeam, cat. # ab7766).

ChIP-seq mapping and normalization

ChIP-seq datasets were aligned using Bowtie mapping software version 0.12.7 (19). To maintain the same read length across all experiments, 1 X 150 bp ChIP-seq raw datasets (fastq files) were trimmed to 50bp using FASTX-toolkit (version 0.0.13.2) or Trimmomatic (version 0.36) (20). All reads were mapped to the hgl8 reference human genome with a number of base pairs mismatch not greater than 2 (96% sequence match). The present inventors used SAMtools version 0.1.19 (21) to generate a sorted pileup format of the aligned reads. Reads were then extended from the 3’-end to a final length of l50bp. For each experiment, genome coverage bed graph files were generated using BEDTools2 version 2.25.0 (22) and then normalized by multiplying the read density times 100 and dividing by the total number of mapped reads. Normalized bed graph files were subsequently converted to bigwig files and uploaded to UCSC Genome Browser for visualization. The present inventors downloaded ChIP seq data for p300, MLL4, and the corresponding input from HCT116 cells previously published (23), from the GEO database accession number GSE1176. In addition, the present inventors also acquired published GRO-seq data for HCT116 cells from the GEO database accession number GSE53964 (24). Raw ChIP-seq data for p300, MLL4, as well as the GROseq data were processed in the same manner as mentioned above.

Identification of ChIP-seq signal

H3K4me 7, H3K4me2, RNA PI I, p300, and MLL4 With the exception of H3K9ac and - K27ac, signal analyses for all ChIP-seq datasets experiments were performed using MACS2 version 2.1.0.20150731 (25) under default settings and a p-v alue cutoff of le-05. The present inventors used—broad -g hs -keep-dup=auto -p le-5 -m 10 200 -bw 200 and selected broad peak calls.

H3K9ac and H3K27ac

The FStitch algorithm (26) was used to identify genomic regions enriched with H3K9ac and - K27ac signal from HCT116 ChIP-seq experiments. In order to acquire uniform FStitch signal calls across experiments targeting the same acetylated lysine, the present inventors determined the minimal number of unique reads found in datasets for H3K9ac as well as in those for H3K27ac (Figure 1D). Based on these numbers, the present inventors randomly subsample 12,844,004 unique reads from all H3K9ac ChIP-seq experiments and 9,122,018 unique reads from all nine H3K27ac ChIP-seq datasets. For H3K9ac ChIP-seq data analyses, the present inventors used 20 genomic regions from untreated HCT116 H3K9ac ChIP-seq data as FStitch- training genomic locations (Supplementary Table S3). In a similar manner, the present inventors used 19 genomic regions from H3K27ac under basal experimental conditions as FStitch training parameters (Supplementary Table S4). Segmentation analysis for all ChIP-seq experiments targeting the same lysine on histone H3 were conducted using the output parameters gathered from the training sessions. The same analysis was performed on the input experiment and any resulting signal was subtracted from all ChIP-seqs. Signal analysis for H3K27ac ChIP-seq experiments gathered from RPE cells was performed using SICER (version 1.1) (27) with flags “hgl8 1 200 150 0.74 600 0.01”.

Defining promoter proximal start sites and positive association with RNAPII

To select for genes bound by RNAPII at transcription start sites, the present inventors defined proximal gene promoter regions as lOObp +/- from annotated TSSs using the January 2016 UCSC RefSeq gene assembly (hgl8). RNAPII ChIP-seq signal was determined using MACS2 (version 2.1.0.20150731) narrow peak analysis based on default settings and a p value cutoff equal to le-05. Using merged peak-signals of fragments within a lkb range resulting from MACS2 analysis, the present inventors identified proximal gene promoter regions positively associated with RNAPII in untreated cells. Because many annotated genes contain multiple isoforms associated with a single TSS, the present inventors selected for the longest annotated gene versions and for genes which bodies did not overlap with other genes. From this list, the present inventors excluded genes which associated TSSs were within 2kb from neighboring genes, genes which annotated lengths are smaller than 3 kb, genes that contained intragenic enhancer elements (based on H3K27ac and H3K4mel cooccupancy), as well as genes that displayed multiple internal TSSs occupied by RNAPII. Using this method, the present inventors identified 2,352 genes in HCT116 and 1,644 in RPE cells that were bound by RNAPII at the corresponding TSS and deemed suitable for pausing index assessment.

Pausing index calculation

Calculations were performed as in (28). For the selected genes, the present inventors defined promoter regions from -30 to +300 relative to the TSS and the gene body extending from +300bp to the end of the gene annotation. RNAPII accumulation at promoters and gene bodies was determined using unique mapped reads from RNAPII ChIP-seq experiments of untreated, and largazole treated cells with 75 nM, and 300 nM concentrations. Read density for promoter and gene body windows were calculated by dividing the number of unique reads by the total base pairs associated with each specified window. Pausing index was assigned to each gene from the ratio between RNAPII density in the promoter region to that of the gene body.

De novo motif analysis

For de novo motif discovery, the present inventors used MEME (29). Analysis were performed with a search window of 800 and 500bp flanking the center enhancer elements associated with the defined cluster. The reported E-value is the output of the MEME de novo motif finding algorithm. To identify related transcription factors, each identified motif was input to TOMTOM version 4.11.1 (16) using motif database JASPAR DNA CORE (2016) or HUMAN DNA HOCOMOCO (vlO). The present inventors also report the E-value describing the certainty of the match between the identified de novo motif and the database position weight matrices. The images were prepared using Adobe Illustrator CS6 or Photoshop CS6.

Identification of conventional enhancer elements

The present inventors first determined H3K27ac ChIP-seq signal (FStitch or SICER), as mentioned above, resulting from unstimulated and largazole treated cells. The present inventors performed fragment intersect analyses to extract genomic regions with overlapping H3K27ac and H3K4mel accumulation for both cell lines. To further define the boundaries of enhancer regions in HCT116 cells, the present inventors trimmed the co-occupied regions using MACS2 broad peak calls gathered from H3K4me2, RNAPII, and MACS2 narrow peaks from p300 ChIP- seq data gathered from unstimulated HCT116 cells (23). The present inventors then eliminated all genomic regions which coordinates overlapped with annotated transcription start sites based on the January 2016 UCSC RefSeq gene assembly (hgl8). This led to identification of 41,017 and 28,299 putative enhancer elements in unstimulated HCT116 and RPE cells, respectively. Identification of super-enhancers

Genomic locations and associated genes for super-enhancers in HCT116 cells were extracted from the dbSUPER database (http://bioinfo.au.tsinghua.edu.cn/dbsuper) (30). The effects of largazole on RNAPII occupancy along SEs for both HCT116 and RPE cells were determined using ROSE (https://bitbucket.org/young_computation/rose) (31). The present inventors used an exclusion zone of 5 kb (“-t 2500”) flanking the transcription start site and the default stitching size of 12.5 kb. RNAPII peaks as determined by MACS2 were used as input constituent enhancers.

K-means clustering of H3K27ac signal along enhancer regions

K-means clustering was performed on the enhancer data set referred as “isolated enhancers” (n = 12,172) from HCT116 cells. These elements are characterized by a single H3K27ac peak, co-occupied by H3K4mel, centered along a 20kb genomic region, either under basal cellular conditions (n = 8,667) or resulting from stimulation with 300 nM largazole treatment (n = 3,505). To this end, the present inventors used H3K27ac FStitch calls from all nine ChIP-seq experiments along +/- lkb distance centered on overlapping peak regions (H3K27ac, H3K4mel (MACS2 BP), and H3K4me2 (MACS2 BP), RNAPII (MACS2 BP) or p300 (MACS2 NP) when present). Two filters were applied on the analyzed enhancer list. First, the K-means clusters were selected based on two general H3K27ac signal trends, decreasing or increasing under largazole treatments. Second, an additional filtered was applied on these clusters based on RNAPII normalized read density patterns; selecting enhancer regions with both decreasing H3K27ac ChIP-seq signal in concomitance with an overall decreasing in RNAPII occupancy (based on DMSO, 75 nM, and 300 nM data) or enhancer elements with increasing H3K27ac ChIP-seq signal accompanied by the systematic increase of RNAPII binding.

Cell viability assay

Cell viability for HCT116 cells, treated for 48 hours with the indicated largazole concentration or unstimulated (DMSO), was measured using the crystal violet staining method. In short, treated cells were gently washed once with phosphate buffer saline (PBS) and fixed for 20 mins at room temperature with 4% paraformaldehyde under constant rocking. After a single wash with PBS, fixed cells were stained with 0.5% crystal violet (Sigma) in 20% methanol at room temperature for 10 mins. Cells were then thoroughly washed with water and left overnight to dry. Last, 150 pl of developing solution (4: 1 : 1 mix of methanol, ethanol, and water) was added to each well and absorbance was measured at l = 560 nM.

Flow cytometry analysis

HCT116 and RPE cells (1x106) were treated with vehicle (DMSO) or the indicated dose of largazole for 25 hours. For each cell population analyzed, the present inventors washed with ice-cold PBS, treated with trypsin solution, and fixed in cold 70% ethanol overnight. Fixed cells were then washed with ice cold PBS, and incubated in 0.25 mg/ml or RNase (Sigma) for 1 hour at 37°C. Before analysis, cells were stained with 10 ug/ml of propidium iodide (PI) (Sigma) at 4°C for 1 hour. Analysis was performed using a FACSAccuri flow cytometer (Becton- Dickinson). Data obtained from the cell cycle distribution were analyzed using FlowJo version 10.1 (Tree Star). Gaussian distributions and S-phase polynomial were assigned to each cell population using the Watson pragmatic model. Starting from samples treated with 9.4 nM largazole dose and above, the present inventors specified the range of Gl and G2 peaks in order to gather percentage of cells in each cell cycle phase.

Genome Datasets

The genomic datasets from this study have been deposited by the present inventors in NCBFs Gene Expression Omnibus (GEO) database under accession number GSE101708.

Additional Materials and Methods

Additional materials and methods may also be encompassed within this specification. For example, data, tables, and figures were generated using materials and methods that would be understood and recognized by those of ordinary skill in the art without undue experimentation.

Those skilled in the art will appreciate, or be able to ascertain using no more than routine experimentation, further features and advantages of the invention based on the above-described embodiments. Accordingly, the invention is not to be limited by what has been particularly shown and examples described. All publications and references are herein expressly incorporated by reference in their entirety.

REFERENCES:

The following references are each incorporated herein by reference:

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Table SI. Largazole specificity for HDAC inhibition.

Table S3. GO categories based on the identity of differentially expressed mRNAs for each largazole drug treatment. Gene Ontology (GO) analysis for differentially expressed transcripts for each largazole drug treatment using the database for annotation, visualization and integrated discovery (DAVID) bioinformatics tools (Huang et al., 2009a, 2009b). The top GO biological processes based on their enrichment p-value are reported per dose treatment.

Table S4. List of biomarkers

Table S5. Identification of Super-Enhancer Coordinates

Claims

CLAIMS What is claimed is:

1. A method for assessing BRD4 sensitivity in a cancer subject, the method comprising:

obtaining a first sample, such as serum or tissue, from the subject at a certain time (to); measuring the activity level BRD4 in the biological sample;

administrating a therapeutically effective amount of at least one BRD4 inhibitor and at least one histone deacetylase inhibitor (HDACI) to the patient;

obtaining a second sample, such as serum or tissue, from the subject at a certain time (ti); comparing the measured level of activity of BRD4 from said first sample with the measured level of activity of BRD4 with respect to said second sample; and

- wherein the measured level of activity of BRD4 comprises an activity selected from the group consisting of: the modulation of expression of BRD4-associated super-enhancer genes; disrupted mRNA processing of BRD4-associated super-enhance genes generating a plurality of alternatively spliced mRNA transcripts; and novel peptide antigen formation from said alternatively spliced mRNA transcripts.

2. The method of claim 1, wherein said effective amount of at least one BRD4 inhibitor comprises an effective amount of JQ1.

3. The method of claim 2, wherein said effective amount of at least one HDACI comprises an effective amount of largazole or an analog of largazole.

4. The method of claim 3, wherein the at least one chemotherapeutic agent is also concurrently administered: prior to t_0. at ti, or some intermediate time prior to ti.

5. A method for determining if a cancer patient is predicted to respond to the administration of BRD4 inhibitor therapy, the method comprising:

detecting in a sample of tumor cells from a patient, a level of gene expression of BRD4, wherein the expression levels of the BRD4 are indicative of whether the patient will respond to the administration of BRD4 inhibitor therapy, wherein said BRD4 inhibitor therapy comprises administering effective amount of at least one histone deacetylase inhibitor (HDACI) and at least one BET-bromodomain inhibitor.

6. The method of claim 5, wherein said effective amount of at least one BRD4 inhibitor comprises an effective amount of JQ1.

7. The method of claim 6, wherein said effective amount of at least one HDACI comprises an effective amount of largazole or an analog of largazole.

8. A method of assessing the efficacy or effectiveness of a BRD4 inhibitor therapy treatment being administered to a cancer subject, the method comprising comparing:

measuring the activity level of a pharmacodynamic biomarker BRD4in a first sample obtained from the subject at a time to;

measuring the activity level of the pharmacodynamic biomarker BRD4 in a second sample obtained from the subject at time ti; and,

wherein a change in the activity level of the pharmacodynamic biomarker BRD4in the second sample relative to the first sample is an indication that the BRD4 inhibitor treatment is effective for treating cancer in the subject.

9. The method of claim 39, wherein the BRD4 inhibitor treatment comprises an effective amount of at least one histone deacetylase inhibitor (HDACI) and at least one BET-bromodomain inhibitor

10. The method of claim 9, wherein said HDACI is largazole and said BET-bromodomain inhibitor is JQ1.

11. The method of claim 39, wherein the time to is before the treatment has been administered to the cancer subject, and the time E is after the treatment has been administered to the subject.

12. The method of claim 11, wherein the activity level of the pharmacodynamic biomarker BRD4 is the modulation of expression of BRD4-associated super-enhance genes and/or disrupted mRNA processing BRD4-associated super-enhance genes generating a plurality of alternatively spliced mRNA transcripts and/or novel antigen formation from said alternatively spliced mRNA transcripts.

13. The method of claim 13, wherein the comparing is repeated over a range of times.

14. The method of claim 13, wherein the at least one chemotherapeutic agent is also concurrently administered: prior to to_, at ti, or some intermediate time prior to ti.

15. A method of modulating expression of a super-enhancer, or functional fragment or variant thereof in a cell or patient, the method comprising administering to the cell or patient an effective amount of at least one histone deacetylase (HDAC) inhibitor and at least one BET-bromodomain inhibitor.

16. The method of claim 15, wherein said HDAC inhibitor comprises an effective amount of largazole.

17. The method of claim 15, wherein said BET-bromodomain inhibitor comprises an effective amount of JQ1.

18. The method of claim 15, wherein said HDAC inhibitor comprises an effective amount of largazole and said BET-bromodomain inhibitor comprises an effective amount of JQ1.

19. The method of claim 18, wherein said effective amount of largazole and JQ1 inhibit the activity of BRD4.

20. The method of claim 19, wherein said inhibition of the activity of BRD4 comprises modulating expression of genes associated with the super-enhancer.

21. The method of claim 20, wherein said genes associated with the super-enhancer comprises downregulating at least one oncogene.

22. The method of claim 19, wherein said inhibition of the activity of BRD4 comprises disrupting mRNA processing associated with super-enhancer genes.

23. The method of claim 22, wherein said disrupting mRNA processing associated with super enhancer genes comprises generating a plurality of alternatively spliced mRNA transcripts from a BRD4-associated super-enhancer.

24. The method of claim 23, wherein said generating a plurality of alternatively spliced mRNA transcripts from a BRD4-associated super-enhancer comprises generating a plurality of novel antigenic peptides from said alternatively spliced mRNA transcripts.

25. The method of claim 19, wherein said inhibition of the activity of BRD4 comprises displacing BRD4 from super-enhancer associated Transcription Start Sites (TSS).

26. The method of claim25, said displacing BRD4 from super-enhancer associated TSS comprises RNA polymerase II pausing at the TSS of actively transcribed genes in a super enhancer region.

27. A method for treating a cancer in a patient in need thereof, the method comprising administering to the patient a therapeutically effective amount of an histone deacetylase (HD AC) inhibitor and at least one BET-bromodomain inhibitor that modulates the activity or expression of a super-enhancer.

28. The method of claim 27, wherein said HDAC inhibitor comprises an effective amount of largazole and said BET-bromodomain inhibitor comprises an effective amount of JQ1.

29. A method for treating a cancer in a patient in need thereof, the method comprising administering to the patient a low-dose therapeutic amount of an histone deacetylase (HDAC) inhibitor and at least one BET-bromodomain inhibitor that modulates the activity of BRD4.

30. The method of claim 29, wherein said HDAC inhibitor comprises an effective amount of largazole and said BET-bromodomain inhibitor comprises an effective amount of JQ1.

31. A method for treating a cancer in a patient in need thereof, the method comprising administering to the patient a high-dose therapeutic amount of an histone deacetylase (HDAC) inhibitor and at least one BET-bromodomain inhibitor that modulates the activity of BRD4.

32. The method of claim 31, wherein said HDAC inhibitor comprises an effective amount of largazole and said BET-bromodomain inhibitor comprises an effective amount of JQ1.

33. A dose-dependent method of modulating expression of a super-enhancer, or functional fragment or variant thereof in a cell or patient, the method comprising administering to the cell or patient an effective amount of at least one histone deacetylase (HD AC) inhibitor.

34. The method of claim 33, further comprising dose-dependent method of modulating expression of genes associated with the super-enhancer.

35. The method of claim 34, wherein said genes associated with the super-enhancer mediated disease.

36. The method of claim 34, wherein said super-enhancer mediated disease is cancer.

37. The method of claim 36, wherein said effective amount comprises a low-dose therapeutic amount.

38. The method of claim 36 wherein said effective amount comprises a high-dose therapeutic amount.

39. The method of claim 37, wherein said low-dose therapeutic amount result in upregulation of target genes transcripts.

40. The method of claim 38, wherein said high-dose therapeutic amount result in suppression of target genes transcripts, and/or H3 histone acetylation at Lys-9 (H3K9ac) and Lys-27 (H3K27ac), and/or RNA polymerase II pausing at the promoters of actively transcribed genes, and modulation of H3K4mel, H3K4me2.

41. The method of claim 40 wherein said histone deacetylase (HD AC) inhibitor is selected from the group consisting of: Vorinostat, Romidepsin (Isodax), SAHA (Vironostat), PDX101 (Belinostat), Panobinostat, Eintinostat, TSA (Trichostatin), ONKlOl(Paragazole), Largazole, and chidamide (CS055).

42. The method of claim 41, wherein said super-enhancer is selected from the group consisting of the super-enhancers coordinates listed in Table S5.

43. The method of claim 42, further comprising administering to the cell or patient an effective amount of at least one HD AC inhibitor and at least one chemotherapeutic agent.

44. The method of claim 43, wherein the combination said of at least one HDAC inhibitor and said at least one chemotherapeutic agent is administered sequentially.

45. The method of any one of the preceding claims, wherein the cancer is sensitive to HDAC inhibitors.

46. The method of any one of the preceding claims, wherein the cancer is sensitive to one or more chemotherapeutic agents.

47. A dose-dependent method for treating a cancer in a patient in need thereof, the method comprising administering to the patient a therapeutically effective amount of an histone deacetylase (HDAC) inhibitor that modulates the activity or expression of a super-enhancer.

48. A method for treating a cancer in a patient in need thereof, the method comprising administering to the patient a low-dose therapeutic amount of an histone deacetylase (HDAC) inhibitor that modulates the activity or expression of a super-enhancer.

49. A method for treating a cancer in a patient in need thereof, the method comprising administering to the patient a high-dose therapeutic amount of an histone deacetylase (HDAC) inhibitor that modulates the activity or expression of a super-enhancer.

50. A method for treating a cancer in a patient in need thereof, comprising the step of contacting the cell with an histone deacetylase (HDAC) inhibitor that selectively modulates the expression of at least one super-enhancer in a dose-dependent manner.

51. A method for treating a cancer in a patient in need thereof, comprising the step of contacting the cell with an histone deacetylase (HDAC) inhibitor that selectively modulates the expression of one or more genes associated with a super-enhancer in a dose-dependent manner.

52. A method for treating a cancer in a patient in need thereof, comprising the step of contacting the cell with an histone deacetylase (HDAC) inhibitor that selectively modulates the expression of one or more genes associated with a super-enhancer in a dose-dependent manner.

53. A method for treating a cancer in a patient in need thereof, comprising the step of contacting the cell with an histone deacetylase (HDAC) inhibitor that selectively modulates the acetylation of one or more histone proteins in a dose-dependent manner.

54. The method of claim 53, wherein said dose comprises high-dose histone deacetylase (HDAC) inhibitor therapeutic amount that results in the deacetylation of one or more histone proteins.

55. The method of claim 54, wherein said histone proteins comprise histone proteins associated with one or more super-enhancers.

56. The method of claim 56, wherein said histone protein residues deacetylation in response to a high-dose histone deacetylase (HDAC) inhibitor therapeutic amount comprise residues H3 histone acetylation sites at Lys-9 (H3K9ac) and/or Lys-27 (H3K27ac).

57. A method for treating a cancer in a patient in need thereof, comprising the step of contacting the cell with an histone deacetylase (HDAC) inhibitor that selectively modulates activity and/or accumulation of RNAP II at super-enhancers in a dose-dependent manner.

58. The method of claim 57, and further comprising the step of suppressing super-enhancer driven transcripts that are associated with oncogenic activities in a dose-dependent manner.

59. A method for treating a cancer in a patient in need thereof, comprising the step of contacting the cell with a histone deacetylase (HDAC) inhibitor that modulates the acetylation of H3K9ac in a dose-dependent manner.

60. A method for treating a cancer in a patient in need thereof, comprising the step of contacting the cell with a histone deacetylase (HDAC) inhibitor that modulates expression of the cohesin complex and/or its sub-parts in a dose-dependent manner.

61. A method for treating a cancer in a patient in need thereof, comprising the step of contacting the cell with a histone deacetylase (HD AC) inhibitor that modulates expression of long non coding RNAs (lncRNAs) in a dose-dependent manner.

62. The method of claim 61, wherein said modulates expression of long non-coding RNAs (lncRNAs) comprise the accumulation of long non-coding RNAs (lncRNAs) in said cell.

63. A method for treating a cancer in a patient in need thereof, comprising the step of contacting the cell with an histone deacetylase (HDAC) inhibitor that causes poised enhancers to become fully active in response to increased H3K27ac and/or H3K9ac in a dose-dependent manner.

64. A method for treating a cancer in a patient in need thereof, comprising the step of contacting the cell with a histone deacetylase (HDAC) inhibitor that modulates the expression of proteins that generate H3K27ac and/or H3K9ac in a dose-dependent manner.

65. The method of claim 64, wherein said proteins that generate H3K27ac and/or H3K9ac comprise proteins selected from the group consisting of: CBP, p300, and KAT2A.

66. The method of any one of the preceding claims, wherein the dose comprises a low-dose therapeutic amount.

67. The method of any one of the preceding claims, wherein the dose comprises a high-dose therapeutic amount.

68. A method for determining if a cancer patient is predicted to respond to the administration of histone deacetylase (HDAC) inhibitor therapy, the method comprising:

detecting in a sample of tumor cells from a patient, a level of gene expression of a biomarker plurality of biomarker selected from the group identified in Table S4, wherein the expression levels of the markers are indicative of whether the patient will respond to the administration of histone deacetylase (HDAC) inhibitor therapy.

69. The method of claim 68, wherein said method is histone deacetylase (HDAC) inhibitor dose dependent.

70. The method of claim 69, wherein said dose comprises a low-dose therapeutic amount, a mid- dose therapeutic amount, or a high-dose therapeutic amount.

71. A method of assessing the efficacy or effectiveness of a histone deacetylase (HD AC) inhibitor therapy treatment being administered to a cancer subject, the method comprising comparing:

- the expression level of a bio marker measured in a first sample obtained from the subject at a time t₀, wherein the marker is biomarker selected from the group identified in Table S4;

- the level of the biomarker in a second sample obtained from the subject at time ti; and,

- wherein a change in the level of the biomarker in the second sample relative to the first sample is an indication that the histone deacetylase (HDAC) inhibitor treatment is effective for treating cancer in the subject.

72. The method of claim 71, wherein the time to is before the treatment has been administered to the subject, and the time ti is after the treatment has been administered to the subject.

73. The method of claim 72, wherein the comparing is repeated over a range of times.

74. The method of claim 73, wherein the at least one chemotherapeutic agent is also concurrently administered: prior to to_. at t₀, or some intermediate time prior to ti.

75. The method of claim 74, wherein said method is histone deacetylase (HDAC) inhibitor dose dependent.

76. The method of claim 75, wherein said dose comprises a low-dose therapeutic amount, a mid- dose therapeutic amount, or a high-dose therapeutic amount.

77. An assay system for predicting patient response or outcome to histone deacetylase (HDAC) inhibitor therapy for cancer comprising a means to detect the biomarker or plurality of biomarker selected identified in Table S4, wherein said detection step may include detection of expression levels of said biomarker, and/or chemical changes such as acetylation levels of said biomarker.

78. A method for improving the response of a cancer patient to histone deacetylase (HDAC) inhibitor therapy comprising administering to the patient a therapeutically effective amount of an histone deacetylase (HDAC) inhibitor that suppresses the activity or expression of one or more super-enhancers.

79. The method of claim 78, wherein said method is histone deacetylase (HDAC) inhibitor dose dependent.

80. The method of claim 79, wherein said dose comprises a low-dose therapeutic amount, a mid- dose therapeutic amount, or a high-dose therapeutic amount.

81. A method for improving the response of a cancer patient to histone deacetylase (HDAC) inhibitor therapy comprising administering to the patient a therapeutically effective amount of an histone deacetylase (HDAC) sufficient to demonstrate the loss/reduction of H3K27 acetylation, and/or a loss/reduction of H3K27 acetylation associated with super-enhancers.

82. The method of claim 81, wherein said method is histone deacetylase (HDAC) inhibitor dose dependent.

83. The method of claim 82, wherein said dose comprises a low-dose therapeutic amount, a mid dose therapeutic amount, or a high-dose therapeutic amount.

84. The method of claim 83, wherein the histone deacetylase (HDAC) inhibitor therapy is administered along with the administration of a chemotherapeutic agent.

85. The method of any one of the preceding claims, wherein said histone deacetylase (HDAC) inhibitor is selected from the group consisting of: Vorinostat, Romidepsin (Isodax), SAHA (Vironostat), PDX101 (Belinostat), Panobinostat, Eintinostat, TSA (Trichostatin), ONKlOl(Paragazole), Largazole, and chidamide (CS055).

86. The method of any one of the preceding claims, wherein said super-enhancer is selected from the group consisting of the super-enhancers coordinates listed in Table S5.