Rewiring of master transcription factor cistromes during high-grade serous ovarian cancer development

The transcription factors MECOM, PAX8, SOX17 and WT1 are candidate master regulators of high-grade serous 'ovarian' cancer (HGSC), yet their cooperative role in the hypothesized tissue of origin, the fallopian tube secretory epithelium (FTSEC) is unknown. We generated 26 epigenome (CUT&TAG, CUT&RUN, ATAC-seq and HiC) data sets and 24 profiles of RNA-seq transcription factor knock-down followed by RNA sequencing in FTSEC and HGSC models to define binding sites and gene sets regulated by these factors in cis and trans. This revealed that MECOM, PAX8, SOX17 and WT1 are lineage-enriched, super-enhancer associated master regulators whose cooperative DNA-binding patterns and target genes are re-wired during tumor development. All four TFs were indispensable for HGSC clonogenicity and survival but only depletion of PAX8 and WT1 impaired FTSEC cell survival. These four TFs were pharmacologically inhibited by transcriptional inhibitors only in HGSCs but not in FTSECs. Collectively, our data highlights that tumor-specific epigenetic remodeling is tightly related to MECOM, PAX8, SOX17 and WT1 activity and these transcription factors are targetable in a tumor-specific manner through transcriptional inhibitors.

Epigenomic charting and functional annotation of risk loci in renal cell carcinoma

While the mutational and transcriptional landscapes of renal cell carcinoma (RCC) are well-known, the epigenome is poorly understood. We characterize the epigenome of clear cell (ccRCC), papillary (pRCC), and chromophobe RCC (chRCC) by using ChIP-seq, ATAC-Seq, RNA-seq, and SNP arrays. We integrate 153 individual data sets from 42 patients and nominate 50 histology-specific master transcription factors (MTF) to define RCC histologic subtypes, including EPAS1 and ETS-1 in ccRCC, HNF1B in pRCC, and FOXI1 in chRCC. We confirm histology-specific MTFs via immunohistochemistry including a ccRCC-specific TF, BHLHE41. FOXI1 overexpression with knock-down of EPAS1 in the 786-O ccRCC cell line induces transcriptional upregulation of chRCC-specific genes, TFCP2L1, ATP6V0D2, KIT, and INSRR, implicating FOXI1 as a MTF for chRCC. Integrating RCC GWAS risk SNPs with H3K27ac ChIP-seq and ATAC-seq data reveals that risk-variants are significantly enriched in allelically-imbalanced peaks. This epigenomic atlas in primary human samples provides a resource for future investigation.

chromMAGMA: regulatory element-centric interrogation of risk variants

Candidate causal risk variants from genome-wide association studies reside almost exclusively in noncoding regions of the genome and innovative approaches are necessary to understand their biological function. Multi-marker analysis of genomic annotation (MAGMA) is a widely used program that nominates candidate risk genes by mapping single-nucleotide polymorphism summary statistics from genome-wide association studies to gene bodies. We augmented MAGMA to create chromatin-MAGMA (chromMAGMA), a method to nominate candidate risk genes based on the presence of risk variants within noncoding regulatory elements (REs). We applied chromMAGMA to a genetic susceptibility dataset for epithelial ovarian cancer (EOC), a rare gynecologic malignancy characterized by high mortality. This identified 155 unique candidate EOC risk genes across five EOC histotypes; 83% (105/127) of high-grade serous ovarian cancer risk genes had not previously been implicated in this EOC histotype. Risk genes nominated by chromMAGMA converged on mRNA splicing and transcriptional dysregulation pathways. chromMAGMA is a pipeline that nominates candidate risk genes through a gene regulation-focused approach and helps interpret the biological mechanism of noncoding risk variants for complex diseases.

The transcription factor PAX8 promotes angiogenesis in ovarian cancer through interaction with SOX17

PAX8 is a master transcription factor that is essential during embryogenesis and promotes neoplastic growth. It is expressed by the secretory cells lining the female reproductive tract, and its deletion during development results in atresia of reproductive tract organs. Nearly all ovarian carcinomas express PAX8, and its knockdown results in apoptosis of ovarian cancer cells. To explore the role of PAX8 in these tissues, we purified the PAX8 protein complex from nonmalignant fallopian tube cells and high-grade serous ovarian carcinoma cell lines. We found that PAX8 was a member of a large chromatin remodeling complex and preferentially interacted with SOX17, another developmental transcription factor. Depleting either PAX8 or SOX17 from cancer cells altered the expression of factors involved in angiogenesis and functionally disrupted tubule and capillary formation in cell culture and mouse models. PAX8 and SOX17 in ovarian cancer cells promoted the secretion of angiogenic factors by suppressing the expression of SERPINE1, which encodes a proteinase inhibitor with antiangiogenic effects. The findings reveal a non-cell-autonomous function of these transcription factors in regulating angiogenesis in ovarian cancer.

A multi-level investigation of the genetic relationship between endometriosis and ovarian cancer histotypes

Endometriosis is associated with increased risk of epithelial ovarian cancers (EOCs). Using data from large endometriosis and EOC genome-wide association meta-analyses, we estimate the genetic correlation and evaluate the causal relationship between genetic liability to endometriosis and EOC histotypes, and identify shared susceptibility loci. We estimate a significant genetic correlation (r_g) between endometriosis and clear cell (r_g = 0.71), endometrioid (r_g = 0.48), and high-grade serous (r_g = 0.19) ovarian cancer, associations supported by Mendelian randomization analyses. Bivariate meta-analysis identified 28 loci associated with both endometriosis and EOC, including 19 with evidence for a shared underlying association signal. Differences in the shared risk suggest different underlying pathways may contribute to the relationship between endometriosis and the different histotypes. Functional annotation using transcriptomic and epigenomic profiles of relevant tissues/cells highlights several target genes. This comprehensive analysis reveals profound genetic overlap between endometriosis and EOC histotypes with valuable genomic targets for understanding the biological mechanisms linking the diseases.

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Endometriosis is genetically correlated with CCOC, ENOC, and HGSOC

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Genetic liability to endometriosis confers risk of these EOC histotypes

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Profound colocalization of genetic associations at endometriosis and EOC risk loci

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Functional annotation highlights shared target genes elucidating the genetic link

In vivo discovery of RNA proximal proteins via proximity-dependent biotinylation

RNA molecules function as messenger RNAs (mRNAs) that encode proteins and noncoding transcripts that serve as adaptor molecules, structural components, and regulators of genome organization and gene expression. Their function and regulation are largely mediated by RNA binding proteins (RBPs). Here we present RNA proximity labelling (RPL), an RNA-centric method comprising the endonuclease-deficient Type VI CRISPR-Cas protein dCas13b fused to engineered ascorbate peroxidase APEX2. RPL discovers target RNA proximal proteins in vivo via proximity-based biotinylation. RPL applied to U1 identified proteins involved in both U1 canonical and noncanonical functions. Profiling of poly(A) tail proximal proteins uncovered expected categories of RBPs and provided additional evidence for 5'-3' proximity and unexplored subcellular localizations of poly(A)+ RNA. Our results suggest that RPL allows rapid identification of target RNA binding proteins in native cellular contexts, and is expected to pave the way for discovery of novel RNA-protein interactions important for health and disease.

Predicting master transcription factors from pan-cancer expression data

Critical developmental “master transcription factors” (MTFs) can be subverted during tumorigenesis to control oncogenic transcriptional programs. Current approaches to identifying MTFs rely on ChIP-seq data, which is unavailable for many cancers. We developed the CaCTS (Cancer Core Transcription factor Specificity) algorithm to prioritize candidate MTFs using pan-cancer RNA sequencing data. CaCTS identified candidate MTFs across 34 tumor types and 140 subtypes including predictions for cancer types/subtypes for which MTFs are unknown, including e.g. PAX8, SOX17, and MECOM as candidates in ovarian cancer (OvCa). In OvCa cells, consistent with known MTF properties, these factors are required for viability, lie proximal to superenhancers, co-occupy regulatory elements globally, co-bind loci encoding OvCa biomarkers, and are sensitive to pharmacologic inhibition of transcription. Our predictions of MTFs, especially for tumor types with limited understanding of transcriptional drivers, pave the way to therapeutic targeting of MTFs in a broad spectrum of cancers.

A clinically applicable integrative molecular classification of meningiomas

Meningiomas are the most common primary intracranial tumour in adults1. Patients with symptoms are generally treated with surgery as there are no effective medical therapies. The World Health Organization histopathological grade of the tumour and the extent of resection at surgery (Simpson grade) are associated with the recurrence of disease; however, they do not accurately reflect the clinical behaviour of all meningiomas2. Molecular classifications of meningioma that reliably reflect tumour behaviour and inform on therapies are required. Here we introduce four consensus molecular groups of meningioma by combining DNA somatic copy-number aberrations, DNA somatic point mutations, DNA methylation and messenger RNA abundance in a unified analysis. These molecular groups more accurately predicted clinical outcomes compared with existing classification schemes. Each molecular group showed distinctive and prototypical biology (immunogenic, benign NF2 wild-type, hypermetabolic and proliferative) that informed therapeutic options. Proteogenomic characterization reinforced the robustness of the newly defined molecular groups and uncovered highly abundant and group-specific protein targets that we validated using immunohistochemistry. Single-cell RNA sequencing revealed inter-individual variations in meningioma as well as variations in intrinsic expression programs in neoplastic cells that mirrored the biology of the molecular groups identified.

Single-cell transcriptomics identifies gene expression networks driving differentiation and tumorigenesis in the human fallopian tube

The human fallopian tube harbors the cell of origin for the majority of high-grade serous "ovarian" cancers (HGSCs), but its cellular composition, particularly the epithelial component, is poorly characterized. We perform single-cell transcriptomic profiling of around 53,000 individual cells from 12 primary fallopian specimens to map their major cell types. We identify 10 epithelial subpopulations with diverse transcriptional programs. Based on transcriptional signatures, we reconstruct a trajectory whereby secretory cells differentiate into ciliated cells via a RUNX3^high intermediate. Computational deconvolution of advanced HGSCs identifies the "early secretory" population as a likely precursor state for the majority of HGSCs. Its signature comprises both epithelial and mesenchymal features and is enriched in mesenchymal-type HGSCs (p = 6.7 × 10^-27), a group known to have particularly poor prognoses. This cellular and molecular compendium of the human fallopian tube in cancer-free women is expected to advance our understanding of the earliest stages of fallopian epithelial neoplasia.

Reprogramming of the FOXA1 cistrome in treatment-emergent neuroendocrine prostate cancer

Lineage plasticity, the ability of a cell to alter its identity, is an increasingly common mechanism of adaptive resistance to targeted therapy in cancer. An archetypal example is the development of neuroendocrine prostate cancer (NEPC) after treatment of prostate adenocarcinoma (PRAD) with inhibitors of androgen signaling. NEPC is an aggressive variant of prostate cancer that aberrantly expresses genes characteristic of neuroendocrine (NE) tissues and no longer depends on androgens. Here, we investigate the epigenomic basis of this resistance mechanism by profiling histone modifications in NEPC and PRAD patient-derived xenografts (PDXs) using chromatin immunoprecipitation and sequencing (ChIP-seq). We identify a vast network of cis-regulatory elements (N~15,000) that are recurrently activated in NEPC. The FOXA1 transcription factor (TF), which pioneers androgen receptor (AR) chromatin binding in the prostate epithelium, is reprogrammed to NE-specific regulatory elements in NEPC. Despite loss of dependence upon AR, NEPC maintains FOXA1 expression and requires FOXA1 for proliferation and expression of NE lineage-defining genes. Ectopic expression of the NE lineage TFs ASCL1 and NKX2-1 in PRAD cells reprograms FOXA1 to bind to NE regulatory elements and induces enhancer activity as evidenced by histone modifications at these sites. Our data establish the importance of FOXA1 in NEPC and provide a principled approach to identifying cancer dependencies through epigenomic profiling.

Transcription factors in epithelial ovarian cancer: histotype-specific drivers and novel therapeutic targets

Transcription factors (TFs) are major contributors to cancer risk and somatic development. In preclinical and clinical studies, direct or indirect inhibition of TF-mediated oncogenic gene expression profiles have proven to be effective in many tumor types, highlighting this group of proteins as valuable therapeutic targets. In spite of this, our understanding of TFs in epithelial ovarian cancer (EOC) is relatively limited. EOC is a heterogeneous disease composed of five major histologic subtypes; high-grade serous, low-grade serous, endometrioid, clear cell and mucinous. Each histology is associated with unique clinical etiologies, sensitivity to therapies, and molecular signatures - including diverse transcriptional regulatory programs. While some TFs are shared across EOC subtypes, a set of TFs are expressed in a histotype-specific manner and likely explain part of the histologic diversity of EOC subtypes. Targeting TFs present with unique opportunities for development of novel precision medicine strategies for ovarian cancer. This article reviews the critical TFs in EOC subtypes and highlights the potential of exploiting TFs as biomarkers and therapeutic targets.

Ovarian Cancer Risk Variants Are Enriched in Histotype-Specific Enhancers and Disrupt Transcription Factor Binding Sites

Quantifying the functional effects of complex disease risk variants can provide insights into mechanisms underlying disease biology. Genome-wide association studies have identified 39 regions associated with risk of epithelial ovarian cancer (EOC). The vast majority of these variants lie in the non-coding genome, where they likely function through interaction with gene regulatory elements. In this study we first estimated the heritability explained by known common low penetrance risk alleles for EOC. The narrow sense heritability (hg2) of EOC overall and high-grade serous ovarian cancer (HGSOCs) were estimated to be 5%-6%. Partitioned SNP heritability across broad functional categories indicated a significant contribution of regulatory elements to EOC heritability. We collated epigenomic profiling data for 77 cell and tissue types from Roadmap Epigenomics and ENCODE, and from H3K27Ac ChIP-seq data generated in 26 ovarian cancer and precursor-related cell and tissue types. We identified significant enrichment of risk single-nucleotide polymorphisms (SNPs) in active regulatory elements marked by H3K27Ac in HGSOCs. To further investigate how risk SNPs in active regulatory elements influence predisposition to ovarian cancer, we used motifbreakR to predict the disruption of transcription factor binding sites. We identified 469 candidate causal risk variants in H3K27Ac peaks that are predicted to significantly break transcription factor (TF) motifs. The most frequently broken motif was REST (p value = 0.0028), which has been reported as both a tumor suppressor and an oncogene. Overall, these systematic functional annotations with epigenomic data improve interpretation of EOC risk variants and shed light on likely cells of origin.

Abstract A30: Super-enhancer-associated long noncoding RNA UCA1 interacts directly with AMOT to inhibit Hippo signaling pathway in epithelial ovarian cancer

Long noncoding RNAs (lncRNAs) have emerged as critical regulators of tumorigenesis and yet their mechanistic role remains challenging to characterize. Here, we present LncRNA Interpreter, a strategy integrating functional proteomics with interacting proteins to characterize lncRNAs. Its robustness is exemplified by lncRNA Urothelial Cancer Associated 1 (UCA1), a driver of ovarian cancer development. Reverse phase protein array (RPPA) analysis indicates that UCA1 inhibits Hippo signaling pathway and in vivo RNA antisense purification (iRAP) of UCA1 interacting proteins identified angiomotin (AMOT), a known YAP regulator, as direct binding partner. Loss-of-function experiments show that AMOT mediates Hippo signaling pathway inhibition by UCA1. UCA1 enhances the AMOT-YAP interaction to prevent YAP phosphorylation and facilitate its nuclear translocation. Together, our LncRNA Interpreter pipeline identified UCA1 as an lncRNA regulator of the Hippo signaling pathway and highlighted the UCA1-AMOT-YAP signaling axis in ovarian cancer development. LncRNA Interpreter can readily be applied to other lncRNAs implicated in complex diseases.

Citation Format: Xianzhi Lin, Tassja J. Spindler, Marcos A de Souza Fonseca, Rosario I. Corona, Ji-Heui Seo, Felipe S Dezem, Lewyn Li, Janet M. Lee, Henry W. Long, Thomas A. Sellers, Beth Y. Karlan, Houtan Noushmehr, Matthew L. Freedman, Simon A. Gayther, Kate Lawrenson. Super-enhancer-associated long noncoding RNA UCA1 interacts directly with AMOT to inhibit Hippo signaling pathway in epithelial ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on the Hippo Pathway: Signaling, Cancer, and Beyond; 2019 May 8-11; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(8_Suppl):Abstract nr A30.

Non-coding somatic mutations converge on the PAX8 pathway in ovarian cancer

The functional consequences of somatic non-coding mutations in ovarian cancer (OC) are unknown. To identify regulatory elements (RE) and genes perturbed by acquired non-coding variants, here we establish epigenomic and transcriptomic landscapes of primary OCs using H3K27ac ChIP-seq and RNA-seq, and then integrate these with whole genome sequencing data from 232 OCs. We identify 25 frequently mutated regulatory elements, including an enhancer at 6p22.1 which associates with differential expression of ZSCAN16 (P = 6.6 × 10-4) and ZSCAN12 (P = 0.02). CRISPR/Cas9 knockout of this enhancer induces downregulation of both genes. Globally, there is an enrichment of single nucleotide variants in active binding sites for TEAD4 (P = 6 × 10-11) and its binding partner PAX8 (P = 2×10-10), a known lineage-specific transcription factor in OC. In addition, the collection of cis REs associated with PAX8 comprise the most frequently mutated set of enhancers in OC (P = 0.003). These data indicate that non-coding somatic mutations disrupt the PAX8 transcriptional network during OC development.

Abstract AP11: IDENTIFYING FUNCTIONAL NONCODING SOMATIC MUTATIONS IN OVARIAN CANCER

Epithelial ovarian cancer (OC) is a heterogeneous disease that stratifies into different histologic subtypes including high-grade serous (HGSOC), clear cell (CCOC), endometrioid (EnOC) and mucinous (MOC) ovarian cancer. HGSOC is the most common, and each histotype is characterized by largely distinct germline genetics, somatic alterations and clinical biomarkers. Recently, whole genome sequencing (WGS) studies have catalogued genome-wide somatic variation for most OC histotypes. These data demonstrate that OC histotypes harbor thousands of noncoding somatic mutations and our next major challenge is to distinguish the few important noncoding somatic drivers from the thousands of passenger mutations.

We hypothesized that driver noncoding somatic mutations impact disease development and progression through altering the sequence of regulatory elements (REs), such as enhancers and promoters, resulting in perturbed expression of genes involved in neoplastic development of OC. To systematically address this hypothesis, we established genome-wide H3K27ac epigenomic profiles, annotating active REs for the different ovarian cancer histotypes using chromatin immunoprecipitation sequencing (ChIP-seq) in 20 fresh frozen primary OC tissue samples—five tumors for each major histotype. In parallel, we performed transcriptional profiling using RNA sequencing (RNA-seq). Together, these two datasets enabled us to evaluate epigenetic alterations and the transcriptome.

We identified histotype-specific active REs, and common active REs across all histotypes. First, we used the RNA-seq data to assess the effect of the histotype-specific REs in gene expression, and to find target genes of cis-REs and novel histotype-specific biomarkers. Next, we integrated these unique profiles with WGS data from 232 OCs (169 HGSOCs, 35 CCOCs and 28 EnOCs). The number of somatic single nucleotide variants per sample range from 481 to 40,764 (mean=7199, sd = 5751). Of these, 9.4% were noncoding and overlapped active REs in OC. Using a Poisson binomial distribution, we tested the significance of the observed number of mutated samples for any given active RE. We identified several frequently mutated REs in HGSOC, CCOC and EnOC, including promoters (POLR3E and CHCHD6 for HGSOC, CA5BP1 and C16orf87 for EnOC, DKC1 and SLIT3 for CCOC+EnOC), enhancers and super enhancers (KLF6 for HGSOC). We developed a novel approach to identifying target genes associated with a collection of frequently mutated enhancers by correlating enhancer activity (H3K27ac ChIP-Seq signal) vs. gene expression (RNA-seq signal), identifying HOXD cluster genes and C19orf44 as targets of mutated REs in OC.

In conclusion, we have used a multi-omics method to identify functional, driver noncoding somatic mutations for ovarian cancer based on their interaction with disease-specific regulatory elements. This represents a powerful way to distinguish important noncoding somatic drivers from a much larger number of passenger mutations that accumulate during tumor development.

Citation Format: Rosario I. Corona, Ji-Heui Seo, Dennis J. Hazelett, Xianzhi Lin, Paulette Y. Mhawech-Fauceglia, Jenny Lester, Sohrab P. Shah, David G. Huntsman, Beth Y. Karlan, Alexander Gusev, Benjamin P. Berman, Matthew L. Freedman, Simon A. Gayther, Kate Lawrenson. IDENTIFYING FUNCTIONAL NONCODING SOMATIC MUTATIONS IN OVARIAN CANCER [abstract]. In: Proceedings of the 12th Biennial Ovarian Cancer Research Symposium; Sep 13-15, 2018; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2019;25(22 Suppl):Abstract nr AP11.

Abstract GMM-042: PAN-CANCER TRANSCRIPTION FACTOR ANALYSES IDENTIFY ZNF217 AS A NOVEL DRIVER IN HGSOC

Ovarian cancer is a rare but highly lethal gynecologic malignancy, causing around 14,000 deaths annually in the US. The current standard of care for ovarian cancer includes a combination of surgical cytoreduction and platinum-based chemotherapy. Despite these aggressive treatments, most patients suffer from fatal relapses that indicate an urgent need for novel targeted therapies. Master Transcription Factors (MTFs) are transcriptional regulators responsible for cellular identity, and are associated with cell type specific regions of active chromatin termed super-enhancers (SEs). In cancer, MTFs are drivers of tumor development across a variety of organs, and MTF interfering therapies are one of the most successful therapies available today. To further identify tumor-specific MTFs, we have developed the ‘Cancer Core Transcription factor Specificity (CaCTS)' algorithm and prioritized MTFs from a pan-cancer cohort of 10,000 tumors profiled by RNA-sequencing. Results demonstrated that many tumor MTFs derived from CaCTS were specific to its normal tissue-type, validating the algorithm's ability to identify factors involved in cellular identity. On the other hand, a set of highly expressed TFs were frequently observed in multiple cancer types, indicating two distinct classes of MTFs: lineage-specific MTFs and pan-cancer MTFs.

In High-Grade Serous Ovarian Cancer (HGSOC), CaCTS prioritized 21 TFs with lineage specific MTF traits. All 21 candidate MTFs were highly expressed in primary HGSOC specimens and aligned with HGSOC SEs identified via H3K27ac chromatin immunoprecipitation sequencing (ChIP-seq). As expected, WT1 and PAX8 were identified, transcription factors previously implicated to be essential in HGSOC lineage specificity. Our algorithm also identified ZNF217, a novel candidate MTF in HGSOC. ZNF217 plays a key role in breast cancer, a tumor type that shares many epidemiological, hormonal and genetic risk factors with HGSOC. Mining of a publicly available gene knockout experiment in 13 HGSOC cell lines revealed ZNF217 to have similar levels of gene essentiality as PAX8. We are currently examining the role of ZNF217 as a MTF in HGSOC by determining its target genes, binding partners, and cellular consequences of siRNA-mediated knockdown. We expect ZNF217 to occupy SEs that drive expression of genes critical for cell identity, co-occupy SEs with other candidate MTFs, and depletion of ZNF217 to result in loss of cell state. Understanding the mechanisms of transcriptional control in HGSOC will ultimately help to identify clinically relevant drivers which can serve as novel therapeutic targets for this devastating disease.

Citation Format: Robbin Nameki, Marcos A. S. Fonseca, Jessica Reddy, Kevin C. Vavra, Felipe Segato, Rosario I. Corona, Ji-Heui Seo, Annie Liu, Forough Abbasi, Xianzhi Lin, Beth Y. Karlan, Matthew L. Freedman, Simon A. Gayther, Houtan Noushmehr, Kate Lawrenson. PAN-CANCER TRANSCRIPTION FACTOR ANALYSES IDENTIFY ZNF217 AS A NOVEL DRIVER IN HGSOC [abstract]. In: Proceedings of the 12th Biennial Ovarian Cancer Research Symposium; Sep 13-15, 2018; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2019;25(22 Suppl):Abstract nr GMM-042.

Substrates' and products' inhibition in fructanase production by a new Kluyveromyces marxianus CF15 from Agave tequilana fructan in a batch reactor

This study focuses on fructanase production in a batch reactor by a new strain isolated from agave juice (K. marxianus var. drosophilarum) employing different Agave tequilana fructan (ATF) concentrations as substrate. The experimental data suggest that the fructanase production may be inhibited or repressed by high substrate (50 g/L) and ethanol (20.7 g/L) concentrations present in culture medium. To further analyze these phenomena an unstructured kinetic mathematical model taking into account substrate and products inhibition was proposed and fitted. The mathematical model considers six reaction kinetics and the ethanol evaporation, and predicts satisfactorily the biomass, fructan, glucose, fructose, ethanol, and fructanase behavior for different raw material initial concentrations. The proposed model is the first to satisfactorily describe the production of fructanase from branched ATF with a new strain of K. marxianus.

Abstract 2615: Systematic approaches to predict oncogenic transcriptional regulatory circuitries identify important nodes in high-grade serous ovarian cancer

Previous work indicates that identifying core transcription regulatory circuitries (CRCs) predicts tumor-specific genetic dependencies, in the form of transcription factors responsible for establishing this circuitry (Durbin, Zimmerman, Dharia, et al., 2018), which suggest targetable, onco-requisite factors. However, a systematic effort to identify CRCs across tumors has been challenging, since current approaches rely on data difficult to acquire in heterogeneous or low cell number samples. Here, we combine -omics approaches, including a newly developed algorithm to predict super-enhancer—driven CRCs in a range of tumor types. Our work leverages two characteristics CRC members: association with super-enhancers, defined using ChIP-Seq data, and highly cell type-specific expression, analyzed using the Cancer Cell-Type-Specificity (CaCTS) algorithm. CRC members uncovered with the CaCTS algorithm recover known drivers of specific tumor types and known misregulated pathways. We deeply characterized the CRC of high-grade serous ovarian cancer (HGSOC), a tumor type with poor overall prognosis for which few known driver mutations or targetable oncogenes are known. Our CRC models contain onco-requisite transcription factors that dominate the HGSOC gene expression program, including ESR1, MECOM (EVI1), and NOTCH2, each of which play important roles in other malignancies. Many of these CRC members represent HGSOC-selective dependencies in CRISPR/Cas9 screens. Profiling CRCs in HGSOC cells and presumed cells-of-origin (fallopian tube and ovarian tissue) highlights a set of CRC genes whose expression appears to have been evolved by HGSOC cells, including an isoform of the estrogen receptor. The dependence of HGSOC cells on transcription factors suggests a state of “transcriptional addiction,” which has been targeted with molecules against transcription apparatus. HGSOC lines are correspondingly susceptible to treatment with small molecules against transcriptional CDKs (CDK7 and CDK12). Also, some HGSOC-specific SEs are associated with genes druggable with existing small molecules. Thus, identifying the CRC governing HGSOC predicts dominant factors and suggests therapeutic avenues in this underserved disease. Similar predictions of CRCs in other poorly-studied tumors may also enhance understanding of those tumor cell identities and targetable nodes.

Citation Format: Brian J. Abraham, Jessica Reddy, Marcos A. Fonseca, Isaac A. Klein, Lena K. Afeyan, Rosario I. Corona, Paloma Cejas, Felipe Segato, Beth Y. Karlan, Simon A. Gayther, Matthew L. Freedman, Houtan Noushmehr, Myles Brown, Ursula A. Matulonis, Kate Lawrenson, Richard A. Young. Systematic approaches to predict oncogenic transcriptional regulatory circuitries identify important nodes in high-grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2615.

Genome-wide association studies identify susceptibility loci for epithelial ovarian cancer in east Asian women

OBJECTIVE

Genome-wide association studies (GWASs) for epithelial ovarian cancer (EOC) have focused largely on populations of European ancestry. We aimed to identify common germline variants associated with EOC risk in Asian women.

METHODS

Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations.

RESULTS

At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10-9) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10-9). SNP rs6902488 at 6p25.2 (r2 = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP <10%). At chromosome 20q11.22, rs74272064 was associated with HGSOC risk (OR = 1.27, P = 9.0 × 10-8). Overall EOC risk was associated with rs10260419 at chromosome 7p21.3 (OR = 1.33, P = 1.2 × 10-7) and rs74917072 at chromosome 2q37.3 (OR = 1.25, P = 4.7 × 10-7). At 2q37.3, expression quantitative trait locus analysis in 404 HGSOC tissues identified ESPNL as a putative candidate susceptibility gene (P = 1.2 × 10-7).

CONCLUSION

While some risk loci were shared between East Asian and European populations, others were population-specific, indicating that the landscape of EOC risk in Asian women has both shared and unique features compared to women of European ancestry.

An SVM-based method for assessment of transcription factor-DNA complex models

Background

Atomic details of protein-DNA complexes can provide insightful information for better understanding of the function and binding specificity of DNA binding proteins. In addition to experimental methods for solving protein-DNA complex structures, protein-DNA docking can be used to predict native or near-native complex models. A docking program typically generates a large number of complex conformations and predicts the complex model(s) based on interaction energies between protein and DNA. However, the prediction accuracy is hampered by current approaches to model assessment, especially when docking simulations fail to produce any near-native models.

Results

We present here a Support Vector Machine (SVM)-based approach for quality assessment of the predicted transcription factor (TF)-DNA complex models. Besides a knowledge-based protein-DNA interaction potential DDNA3, we applied several structural features that have been shown to play important roles in binding specificity between transcription factors and DNA molecules to quality assessment of complex models. To address the issue of unbalanced positive and negative cases in the training dataset, we applied hard-negative mining, an iterative training process that selects an initial training dataset by combining all of the positive cases and a random sample from the negative cases. Results show that the SVM model greatly improves prediction accuracy (84.2%) over two knowledge-based protein-DNA interaction potentials, orientation potential (60.8%) and DDNA3 (68.4%). The improvement is achieved through reducing the number of false positive predictions, especially for the hard docking cases, in which a docking algorithm fails to produce any near-native complex models.

Conclusions

A learning-based SVM scoring model with structural features for specific protein-DNA binding and an atomic-level protein-DNA interaction potential DDNA3 significantly improves prediction accuracy of complex models by successfully identifying cases without near-native structural models.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2538-y) contains supplementary material, which is available to authorized users.

Protein side-chain packing problem: is there still room for improvement?

The protein side-chain packing problem (PSCPP) is an important subproblem of both protein structure prediction and protein design. During the past two decades, a large number of methods have been proposed to tackle this problem. These methods consist of three main components: a rotamer library, a scoring function and a search strategy. The average overall accuracy level obtained by these methods is approximately 87%. Whether a better accuracy level could be achieved remains to be answered. To address this question, we calculated the maximum accuracy level attainable using a simple rotamer library, independently of the energy function or the search method. Using 2883 different structures from the Protein Data Bank, we compared this accuracy level with the accuracy level of five state-of-the-art methods. These comparisons indicated that, for buried residues in the protein, we are already close to the best possible accuracy results. In addition, for exposed residues, we found that a significant gap exists between the possible improvement and the maximum accuracy level achievable with current methods. After determining that an improvement is possible, the next step is to understand what limitations are preventing us from obtaining such an improvement. Previous works on protein structure prediction and protein design have shown that scoring function inaccuracies may represent the main obstacle to achieving better results for these problems. To show that the same is true for the PSCPP, we evaluated the quality of two scoring functions used by some state-of-the-art algorithms. Our results indicate that neither of these scoring functions can guide the search method correctly, thereby reinforcing the idea that efforts to solve the PSCPP must also focus on developing better scoring functions.

Abstract 395: Identifying the functional drivers of noncoding somatic mutations in ovarian cancer

Epithelial ovarian cancer (OC) is a heterogeneous disease that has been stratified into different histologic subtypes: high-grade serous (HGSOC), clear cell (CCOC), endometrioid (EnOC) and mucinous (MOC). HGSOC is the most common, but every histotype is characterized by largely distinct germline genetics, somatic alterations and clinical biomarkers. Recently, whole-genome sequencing (WGS) studies have catalogued genome-wide somatic variation for most OC histotypes. These data demonstrate that OC histotypes harbor thousands of noncoding somatic mutations and our next major challenge is to distinguish the few important noncoding somatic drivers from the thousands of passenger mutations. We hypothesized that driver noncoding somatic mutations impact disease development and progression through altering the sequence of regulatory elements (REs), such as enhancers and promoters, eventually resulting in perturbation of the expression of target genes. To systematically address this hypothesis, we established genome-wide H3K27ac epigenomic profiles, annotating active REs for the different ovarian cancer histotypes using chromatin immunoprecipitation sequencing (ChIP-seq) in 20 fresh frozen primary OC tissue samples—five tumors for each major histotype. In parallel, we performed transcriptional profiling using RNA sequencing (RNA-seq). Together, these two datasets enabled us to evaluate epigenetic alterations and the transcriptome. We identified histotype-specific active REs, and common active REs across all histotypes. We used the RNA-seq data to assess the effect of the histotype-specific REs in gene expression, and to find target genes of cis-REs and novel histotype-specific biomarkers. Next, we integrated these unique profiles with WGS data from 232 OCs (169 HGSOCs, 35 CCOCs and 28 EnOCs). The number of somatic single-nucleotide variants per sample range from 481 to 40,764 (mean=7199, sd = 5751). Of these, 9.4% were noncoding and overlapped active REs in OC. Using a Poisson binomial distribution, we tested the significance of the observed number of mutated samples for any given active RE. Importantly, the method adjusted for interpatient mutation rate heterogeneity. Using the Benjamini-Hochberg procedure for p-value correction, we identified several significantly mutated active REs, including the promoters of POLR3E and WDR74. In conclusion, we have used an integrative method to identify functional, driver noncoding somatic mutations for ovarian cancer based on their interaction with disease-specific regulatory elements, and their putative target genes. This represents a powerful way to distinguish important noncoding somatic drivers from a much larger number of passenger mutations that accumulate during tumor development. The approach can be applied to other cancer types if sufficient depth and quality of genetic, transcriptomic and epigenomic datasets are available.

Citation Format: Rosario I. Corona, Ji-Heui Seo, Dennis J. Hazelett, Xianzhi Lin, Paulette Y. Mhawech-Fauceglia, Jenny Lester, Sohrab Shah, David G. Huntsman, Beth Y. Karlan, Benjamin P. Berman, Matthew L. Freedman, Simon A. Gayther, Kate Lawrenson. Identifying the functional drivers of noncoding somatic mutations in ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 395.

Abstract 1494: SOX18: A novel master regulator of high-grade serous ovarian tumorigenesis

High-grade serous ovarian cancer (HGSOC) is the most common and lethal subtype of ovarian cancer. Recent data indicate that fallopian tube secretory epithelial cells (FTSECs) represent the cell of origin for HGSOC. While many studies have characterized molecular features associated with HGSOC biology, the master transcription factors (TFs) that drive disease development are not known. To identify master TFs for HGSOC, we first performed an integrative analysis of gene expression profiles from 73 FTSEC samples and 394 HGSOCs from The Cancer Genome Atlas (TCGA) project. We then integrated these data with chromatin immunoprecipitation sequencing (ChIP-seq) analyses performed on primary HGSOC samples to select active chromatin regions marked by H3k27ac and to identify super-enhancer (SE) regions. These analyses identified overexpressed TFs that coincide with tumor-specific SEs, a hallmark of master TFs. We identified multiple putative master TFs including SOX18, which was highly overexpressed in HGSOCs relative to normal FTSECs (log2 fold change in expression = 3.5, p = 2.5x10-19). SOX18 is a TF that regulates development of blood and lymphatic vessels, but its association with HGSOC development has not been reported before. We examined the expression of SOX18 in ~8,000 tumors representing 17 tumor types from TCGA. SOX18 expression was significantly elevated in HGSOC relative to any other tumor types, suggesting it is highly specific to this cancer. We found that SOX18 is highly expressed in the HGSOC cell lines UWB1.289, Kuramochi, and EFO21, and we then performed lentiviral-mediated shRNA knockdown of SOX18 in these cell lines to establish the effects of SOX18 depletion on neoplastic phenotypes. In ongoing experiments, we are performing gene expression profiling and H3k27ac ChIP-seq analysis after SOX18 knockdown to identify SOX18 target genes and characterize the landscape of SOX18 binding sites in HGSOC. These studies will likely identify novel molecular biomarkers that may represent much-needed therapeutic targets for HGSOC.

Citation Format: Annie Y. Liu, Kevin C. Vavra, Rosario I. Corona, Forough Abassi, Marcos Fonseca, Felipe Segato, Matthew L. Freedman, Simon A. Gayther, Houtan Noushmehr, Kate Lawrenson. SOX18: A novel master regulator of high-grade serous ovarian tumorigenesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1494.

Abstract 1498: The role of tissues specific super-enhancers in mediating the genetic risk of ovarian cancer

Super-enhancers demarcate regions of master regulators involved in cellular differentiation and tumorigenesis. While many trait-associated variants discovered through genome wide association studies are enriched in regulatory elements, the role of super-enhancers in disease susceptibility is less well understood. We evaluated the role of super-enhancers, defined by H3K27ac chromatin immunoprecipitation sequencing (ChIP-seq) analysis of epithelial ovarian cancers (EOC) and precursor cells, in mediating the genetic risk of EOC. We characterized super-enhancer-risk SNP intersections to identify a series of risk-associated loci where multiple candidate causal alleles overlap with ovarian super-enhancers (approximately 33% of candidate causal loci). In particular, a risk locus at 3q25 marked by SNP rs7651446, (odds ratio = 1.59, p = 1.5x10-34), is tagged by 79 candidate causal risk SNPs, more than half of which coincide with super-enhancers detected in EOC precursor cells (ovarian and fallopian tube epithelia) but not in ovarian cancer cell lines or primary tumors suggesting that loss of activity of this super-enhancer is associated with EOC development.

We hypothesized that SNPs at the 3q25 locus modulate activity of super-enhancers that regulate in cis the expression of genes involved in the identity of normal tissue precursors, and that these genes are downregulated during tumorigenesis. We tested the effect of decreasing the binding affinity of BRD4, a protein that binds super-enhancer regions, using a small molecule inhibitor (JQ1). We measured the expression of genes at this locus following JQ1 treatment in EOC precursor cells, identifying three candidate genes, LEKR1, SSR3, and TiPARP, that show decreased expression due to BRD4 binding inhibition. For SSR3 and TIPARP, these expression level changes mirrored the differential expression observed between normal precursor cells and primary high grade serous ovarian cancer. We then established stable shRNA-mediated knockdown models for SSR3 and TIPARP in normal EOC precursor cell lines to establish a role for these genes in ovarian cancer development. In summary, we have identified a potential role for super-enhancers at a subset of EOC risk loci, and present a functional pipeline for identification of the target gene/genes and evaluation of their role in neoplastic transformation.

Citation Format: Kevin C. Vavra, Rosario I. Corona, Ji-Heui Seo, Simon G. Coetzee, Janet M. Lee, Matthew L. Freedman, Paul D. Pharoah, Dennis J. Hazelett, Simon A. Gayther, Kate Lawrenson. The role of tissues specific super-enhancers in mediating the genetic risk of ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1498.

Abstract 5435: Role of the WT1 transcription factor in high-grade serous ovarian cancer

The Wilms Tumor protein 1 (WT1) transcription factor (TF) is a ubiquitous biomarker of high-grade serous ovarian carcinoma (HGSOC), which is the most common and aggressive subtype of epithelial ovarian cancer (EOC). This TF interacts with a host of cellular factors including the tumor suppressor P53, which is mutated in virtually all HGSOC cases. Studies have suggested a role for WT1 in HGSOC development, but little is known about the underlying mechanism. We have generated unique catalogues of epigenomic landscapes (specifically H3K27ac) in primary HGSOC using chromatin immunoprecipitation sequencing (ChIP-seq). Using Bayesian analyses of H3K27ac profiling in HGSOCs, we identified significant tissue specific enrichment of active chromatin at the WT1 locus in HGSOC when compared to all other EOC tumor histotypes. Furthermore, this locus contains a superenhancer in HGSOCs and in normal fallopian tube secretory epithelial cells (FTSECs). This locus features a bidirectional promoter that is shared by WT1-AS lncRNA and that contains a WT1 binding site. LncRNAs are essential in many cellular processes, and have been shown to play pivotal roles in tumorigenicity. The WT1-AS lncRNA is implicated in other diseases but little is known of its function in EOC. We have investigated the mechanisms of interaction between WT1 and WT1-AS. We observed that both protein and transcript expression for WT1 and WT1-AS are positively correlated in HGSOC cell lines. Analysis of data for &gt;400 primary HGSOCs from TCGA further supported this correlation. We hypothesized that WT1 is a critical TF in the development of HGSOC, and that WT1-AS plays a key role in its regulatory pathway. We evaluated the regulatory role of WT1 first by analyzing cellular phenotypes and target gene expression changes in HGSOC cell lines after shRNA mediated knockdown (KD) of WT1. HGSOC cells with stable WT1 knockdown had impaired proliferation and concomitant reduction of WT1-AS expression. We also identified a decrease in expression of SHMT1 in WT1 KD cells, which is a known WT1 target gene. Integrated genome-wide analysis of the WT1 transcriptome by RNA-seq and the WT1 cistrome by ChIP-seq, in parallel with ChIP-MS, is being used to establish the architecture of the WT1 regulome, specifically to establish the regulatory mechanisms and relationships between WT1 and WT1-AS. Ultimately, these studies aim to establish the mechanisms of action for the WT1 TF in neoplastic transformation of HGSOC.

Citation Format: Norma I. Rodriguez-Malave, Justyna E. Kanska, Kevin C. Vavra, Dennis Hazelett, Rosario I. Corona, Ji-Heui Seo, Matthew Freedman, Simon R. Knott, Sandra Orsulic, Beth Y. Karlan, Kate Lawrenson, Simon A. Gayther. Role of the WT1 transcription factor in high-grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5435.

Abstract 725: Feasibility and evaluation of exosomal RNAs as novel diagnostic biomarkers for high grade serous epithelial ovarian cancer

Introduction: High-grade serous ovarian cancer (HGSOC) survival has been essentially unchanged over the last ten years despite new therapeutic strategies. In order to make a large-scale impact on overall survival, early detection strategies are imperative. Exosomes are cell-derived vesicles derived from multivesicular bodies or the plasma membrane that carry a variety of biomolecules, including protein, DNA, and RNA. Exosomal contents represent a novel and underexplored source of tumor biomarkers, in particular for HGSOC. This study aimed to first evaluate approaches to exosomal RNA purification and to then compare the exosomal RNA profiles from serum of patients with benign ovarian disease and HGSOC to determine if unique profiles exist, and to identify biomarkers useful for early detection.

Methods: Cell free serum was obtained from patients in each of the following categories: HGSOC with early (n=24) or late stage (n=24) disease, benign ovarian masses (n=24) and healthy age-matched controls (n=24). We compared ultracentrifugation and a commercial precipitation solution to enrich and isolate exosomes. Exosomal enrichment was confirmed by both transmission electron microscopy (TEM) and western blot using anti-CD63 antibodies. RNA was extracted for each and deep sequencing analysis was performed for 12 candidates within each group. A second cohort of 48 samples will be used for validation of the best performing candidate biomarkers from the discovery cohort via RT-qPCR.

Results: Enrichment of exosomes was confirmed via qualitative assessment using TEM and Western blot analysis. RNA quality was superior when RNA isolations were performed using the QIAgen RNeasy kit compared to the AllPrep kit. Mean RNA yield for each group ranged from 10.3-28.6ng/µl and RNA yield and quality was independent of sample age. RNAseq analyses are ongoing to identify biomarkers specific to HGSOC that can be detected at the earliest stages. The top differentially RNAs for the ovarian cancer groups will be validated in an independent cohort of specimens. A panel will then be generated in combination with CA125 to determine the clinical utility of an integrated -omics approach in early stage detection of HGSOC.

Conclusions: Efficient isolation of exosomes and RNA can be achieved from archived specimens &gt;10 years old. Evaluation of exosomal RNA in HGSOC provides a novel method for biomarker discovery.

Citation Format: Emily N. Prendergast, Xianzhi Lin, Rosario I. Corona, Dennis J. Hazelett, Beth Y. Karlan, Kate Lawrenson. Feasibility and evaluation of exosomal RNAs as novel diagnostic biomarkers for high grade serous epithelial ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 725. doi:10.1158/1538-7445.AM2017-725

Statistical analysis of structural determinants for protein-DNA-binding specificity

DNA-binding proteins play critical roles in biological processes including gene expression, DNA packaging and DNA repair. They bind to DNA target sequences with different degrees of binding specificity, ranging from highly specific (HS) to nonspecific (NS). Alterations of DNA-binding specificity, due to either genetic variation or somatic mutations, can lead to various diseases. In this study, a comparative analysis of protein-DNA complex structures was carried out to investigate the structural features that contribute to binding specificity. Protein-DNA complexes were grouped into three general classes based on degrees of binding specificity: HS, multispecific (MS), and NS. Our results show a clear trend of structural features among the three classes, including amino acid binding propensities, simple and complex hydrogen bonds, major/minor groove and base contacts, and DNA shape. We found that aspartate is enriched in HS DNA binding proteins and predominately binds to a cytosine through a single hydrogen bond or two consecutive cytosines through bidentate hydrogen bonds. Aromatic residues, histidine and tyrosine, are highly enriched in the HS and MS groups and may contribute to specific binding through different mechanisms. To further investigate the role of protein flexibility in specific protein-DNA recognition, we analyzed the conformational changes between the bound and unbound states of DNA-binding proteins and structural variations. The results indicate that HS and MS DNA-binding domains have larger conformational changes upon DNA-binding and larger degree of flexibility in both bound and unbound states. Proteins 2016; 84:1147-1161. © 2016 Wiley Periodicals, Inc.