Goode, Ellen L.

Abstract Purpose: It is well known that the immune system impacts the clinical course of ovarian cancer suggesting that immune-based approaches may effective in treating the disease. This has led to several clinical trials of novel treatments such as antibody, vaccine, and adoptive T cell therapy. PD-1:PD-L1 axis is a major immune regulatory pathway that blunts immune effectors in the tumor microenvironment. It is well known that high surface expression of PD-1 on tumor infiltrating T cells is a sign of their exhaustion. However, the complete mechanism behind the PD-1 regulation of T cell exhaustion is yet to be explored. Recently we identified that PD-1 is also expressed on ovarian tumor-infiltrating myeloid dendritic cells (DCs) that exhibit an immunosuppressive phenotype. Our goal in this study was to understand the mechanism by which PD-1 mediates the paralysis of ovarian cancer infiltrating DCs. Experimental procedures: PD-1+ DCs obtained from ID8 mouse model of ovarian cancer were used in this study. Data from this preclinical model was confirmed by using myeloid DCs obtained from ovarian cancer patient’s samples. Using standard flow cytometry, immunoassays (ELISA, multiplexed cytokine assay), PCR array, western blot and confocal microscopy, PD-1 mediated paralysis of ovarian cancer DCs was determined. Results: Our data shows that blockade of surface PD-1 on ovarian cancer infiltrating DCs results in their activation by, enhancing their surface co-stimulatory molecules expression, increasing their motility, enhancing their antigen presentation capacity, and increasing their production of immunostimulatory cytokines. Also, our results suggest that PD-1 expressed on tumor DCs mediates the suppression of NFkB which occurs through SHP-2 and IKK dependent mechanisms. Conclusion: Our study reveals that blockade of PD-1 on ovarian cancer infiltrating DCs results in the reversal of their paralysis to such an extent that it overrides their B7-H1 mediated suppression of T cells and this occurs through the reversal of PD-1 mediated tonic suppression of NFkB. Citation Format: Lavakumar Karyampudi James Krempski, Purushottam Lamichhane, Kimberly R. Kalli, Marshall D. Behrens, Doris M. Vargas, Lynn C Hartmann, Karen E Hedin, Ellen L. Goode, Keith L. Knutson. PD-1 mediated paralysis of ovarian cancer infiltrating dendritic cells [abstract]. In: Proceedings of the 10th Biennial Ovarian Cancer Research Symposium; Sep 8-9, 2014; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(16 Suppl):Abstract nr POSTER-THER-1418.

Abstract The known genetic variance for epithelial ovarian cancer (EOC) accounts for less than half the familial risks of the disease. BRCA1 and BRCA2 are the major high-penetrance EOC susceptibility genes. More recently genes that interact with BRCA1 and BRCA2 in the same biological pathways, but conferring more moderate penetrance (e.g. RAD51C, RAD51D) have also been identified. Mutations in these genes result in defects in homologous recombination and double strand break repair (HR/DSB). We hypothesized that other genes operating in these and other DNA repair pathways may also confer EOC susceptibility. Whole exome sequencing data, available from more than 400 high-grade serous ovarian cancers, were used to identify 24 candidate genes harboring germline truncating mutations in at least 2 cases, followed by replication analysis using targeted resequencing in ~3,000 cases and 3,000 controls. Subjects were also sequenced for the known susceptibility genes listed above. The data confirmed the previously reported contributions of BRCA1, BRCA2, RAD51C and RAD51D to EOC. In addition, we identified BRIP1, and FANCM as candidate EOC susceptibility genes. Surprisingly, for several genes we found truncating mutations were equally prevalent in cases as they were in controls. These mutations may still represent rare low-penetrance susceptibility alleles for EOC, which we are too limited in sample size and power to confirm; or more likely, it indicates that cells can tolerate heterozygous loss-of-function mutations in apparently critical DNA repair genes without any impact on neoplastic development. These findings may have implications for risk prediction and prevention strategies for EOC and possibly for the identification of novel therapeutic targets. Citation Format: Susan J. Ramus, Honglin Song, Ed Dicks, Maria Intermaggio, Jane Hayward, Jonathan P. Tyrer, Jacek Gronwald, Susanne Krüger Kjær, Alice Wittemore, Beth Karlan, Kunle Odunsi, Usha Menon, David D. Bowtell, Ellen L. Goode, Paul D.P. Pharoah, Simon A. Gayther. Whole exome and targeted resequencing, of population based ovarian cancer cases and controls, identifies susceptibility genes for ovarian cancer [abstract]. In: Proceedings of the 10th Biennial Ovarian Cancer Research Symposium; Sep 8-9, 2014; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(16 Suppl):Abstract nr POSTER-CTRL-1213.

Abstract Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer death among women in the United States (5% of cancer deaths). The standard treatment for patients with advanced EOC is initial debulking surgery followed by carboplatin-paclitaxel combination chemotherapy. Unfortunately, even with modern chemotherapy, most patients relapse and die with the five-year overall survival around 45%. In addition, those patients that initially respond to taxane-platinum therapy eventually develop platinum-resistant tumors and relapse. Thus, finding novel therapeutics for treating EOC is essential. One approach that has been used widely in cancer drug discovery is Connectivity Mapping (CMAP) using gene expression data and drug phenotype data assessed on cancer cell lines (CCL) (i.e. “sensitive” or “resistant” based on dose-response drug data). However, recent publications have highlighted some issues with the use of these standard CCL sets that are often used in these drug screening studies. Therefore, instead of CMAP analysis based on gene expression signatures developed on drug response data collected on a small set of EOC cell lines, we took a novel CMAP approach based on information collected on EOC patients and clinical endpoints. That is, we determined the gene expression signature (e.g., set of genes) that were associated with time to recurrence in data collected on EOC patients within TCGA (n = 518) and a Mayo Clinic study (n = 474). The set of genes associated with time to recurrence (with and without adjustment for additional clinical covariates) was completed separately for TCGA and Mayo Clinic studies, restricting all analyses to EOC tumor of high-grade serous histology. Each of these 4 sets of genes, where genes with hazard ratios (HR) > 1 coded as “positively” associated and genes with HR < 1 coded as “negatively” associated with the phenotype, were inputted into CMAP software (Broad Institute) to determine a set of drugs for which our signature “matches” the “reference” signature. The drugs that overlapped between the CMAP analyses on the two studies were carried forward for validation studies involving drug screens on a set of 10 EOC cell lines. Of the 11 drugs carried forward, we a priori hypothesized that 5 of these drugs would kill EOC cells (mitoxantrone, podophyllotoxin, wortmannin, doxorubicin, and 17-AAG), for which all 5 showed an ability to kill EOC cells in vitro (cell lines were treated using serial dilutions of the drugs (20-0 μM) for 72 h followed by measuring cell viability using the CellTiter-Blue assay). Further research is on-going to understand the functional mechanism by which these candidate drugs might treat EOC and to apply this bioinformatics approach to other cancer drug screening studies. Note: This abstract was not presented at the meeting. Citation Format: Brooke L. Fridley, Rama Raghavan, Gottfried E. Konecny, Chen Wang, Ellen L. Goode, Harsh B. Pathak, Stephen Hyter. A bioinformatics approach to drug discovery: patient based connectivity mapping. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4853. doi:10.1158/1538-7445.AM2015-4853

Abstract Background: We investigated the role of multifactor interactions and epithelial ovarian cancer (EOC) risk using data collected within the Collaborative Oncological Gene-environment Study and the Ovarian Cancer Association Consortium containing 18,000 EOC cases and 26,000 controls. To date, researchers have identified 18 EOC susceptibility loci. However, it has been estimated that many more common variant loci exist; we hypothesized that some of the unexplained variation is due to gene-environment interactions. Similar to breast and endometrial cancers, many EOC risk factors relate to estrogen exposure, and increased levels of estrogen has been associated with obesity in post-menopausal women. Therefore, we hypothesized that gene-environment interactions dealing with hormone-related risk factors could differ between obese and non-obese women. Methods: We considered multifactor interactions between single nucleotide polymorphisms (SNPs) and six hormone-related factors: oral contraceptive use; parity; endometriosis; tubal ligation; hormone replacement therapy (HRT); and estrogen use; and assessed whether these GE interactions differed between obese and non-obese women. The SNPs included in this analysis included the top associated markers within the 18 confirmed risk loci, as well as, 36,811 SNPs that lie within 84 candidate gene regions related to hormone biosynthesis & metabolism and insulin-like growth factors. For the candidate SNP analyses, we assessed multifactor interactions across environmental factors using logistic regression models including age, study site, and population substructure. For the candidate gene analyses, a two-stage screening and testing procedure was utilized. All analyses were completed including: (1) all histologies; and (2) only serous histology. Results: For the 18 known EOC risk loci, no hormone-related risk factors showed statistically significant interaction at a threshold of 10-4. In contrast, the two-stage analysis of the candidate genes found several significant gene-environment-environment effects, after adjusting for multiple testing. For analysis of all cases, the SNPs in the following candidate genes showed a multifactor interaction with a hormone-related risk factor and obesity: IGFBP5 (HRT, rs729597, p = 1.3×10-13), CGA (HRT, rs58124219, p = 1.0×10-5), and SSTR1 (parity, rs77266093, p = 1.1×10-5). Similarly, the serous histology analyses detected a multifactor interaction with HRT, obesity and IGFBP5 (rs729597, p = 8.8×10-5). Additionally, serous only analyses also detected an interaction involving ESR1 (tubal ligation, Chr6:152246911(indel), p = 8.0×10-6). Conclusions: In a very large case-control collection, assessment of multifactor gene-environment interaction is feasible, and, here, suggest that the relationship between SNPs in candidate genes and hormone-related risk factors in EOC susceptibility may vary. Citation Format: Joseph Usset, Brooke Fridley, Ellen Goode, Joellen Schildkraut, Paul Pharoah. Assessment of multifactor gene-environment interactions and ovarian cancer risk: SNPs, obesity, and hormone-related risk factors. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4684. doi:10.1158/1538-7445.AM2015-4684

Abstract Background: Recent bioinformatic analyses and high-throughput sequencing efforts have revealed that RNA editing is a widespread post-transcriptional modification that affects non-coding repetitive elements throughout the genome. This modification, which involves the conversion of adenosine into inosine, is mediated by the action of the adenosine deaminases acting on RNA (ADAR) family of enzymes. Based on reports of dysfunctional ADAR expression in epithelial ovarian cancers (EOC), we hypothesized that single nucleotide polymorphisms (SNPs) in five ADAR genes (ADAD1, ADAR1, ADAR2, ADAR3, SND1) may contribute to EOC susceptibility, potentially by altering the expression of corresponding genes in ovarian tissues. Methods: Using directly genotyped and imputed data from 10,891 invasive EOC cases and 21,693 healthy controls of European ancestry represented in the international Collaborative Oncological Gene-environment Study, we evaluated the frequency of 7,133 SNPs in 5 RNA editing genes. Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) between genotypes and case status under a log-additive genetic model, with adjustment for the first five principal components representing European ancestry. Subgroup analysis was conducted for the four main histologic sub-types of EOC. We also aggregated SNP-level data and conducted gene-level analyses using the Admixture Maximum Likelihood (AML) test and the Sequence-Kernel Association test for the combined effect of common and rare variants (SKAT-CR). Results: Association analysis revealed a top risk-associated SNP (OR (95% CI) = 1.39 (1.17-1.64)) in ADAR3 with P = 1.3 x10−4, 17 additional SNPs in ADAR1, ADAR3, or SND1 with P = 10−4, and 51 SNPs with P = 10−3; this observed number of statistically-significant SNPs was greater than expected. When restricting to the 6,500 invasive serous adenocarcinomas, the magnitude of association strengthened for numerous SNPs. Exploratory analysis for the less common histologic subtypes (endometrioid (n = 1,439), mucinous (n = 696), and clear cell (n = 660)) revealed SNP-level associations (P<10−3) unique to each sub-type. Gene-level analyses based on AML and SKAT-CR revealed that ADAR1 was globally associated (P<0.10) with susceptibility to invasive EOC, with P = 0.024 and P = 0.023, respectively. Expression quantitative trait locus analysis is underway to evaluate associations between genotype and gene expression in EOC and precursor tissues using data from The Cancer Genome Atlas Project and other sources. Conclusions: Preliminary data from this large-scale collaboration suggest that germline variation involving RNA editing genes may influence susceptibility to EOC. This novel finding warrants further investigation, as inherited and acquired alterations affecting RNA editing may serve as important biological mechanisms that promote the development of EOC and possibly other malignancies. Citation Format: Jennifer Permuth-Wey, Brett M. Reid, Y. Ann Chen, Hui-Yi Lin, Alvaro Monteiro, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Simon Gayther, Ellen Goode, Edwin Iversen, Leigh Pearce, Paul D. P. Pharoah, Catherine Phelan, Susan Ramus, Mary Anne Rossing, Joellen Schildkraut, Thomas Sellers, on behalf of the Ovarian Cancer Association Consortium. Inherited variants affecting RNA editing may contribute to ovarian cancer susceptibility. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4635. doi:10.1158/1538-7445.AM2015-4635

Abstract Background: Cell-type-specific super enhancers, or large clusters of mediator-rich enhancers, are highly transcribed regions of the genome with key functions in the maintenance of cell identity and control. These regulatory elements are easily perturbed and enriched for disease-associated sequence variation. Identification of disease-associated super-enhancers and investigation of their sequence variants may help identify important, biologically relevant associations previously overlooked by genome-wide studies. Thus, we sought to identify variants within ovarian tissue specific super-enhancers and investigate their association with epithelial ovarian cancer (EOC) susceptibility. Methods: We utilized genotype data from a European population of ∼11,000 invasive EOC cases and 22,000 healthy controls from the Ovarian Cancer Association Consortium. A public catalog of 478 super-enhancers, identified by peak histone H3K27ac ChIP-seq signal in ovarian tissue, was used to identify 72,116 variants located within 344 super-enhancer regions. Unconditional logistic regression (log-additive model) was used to assess individual SNP-EOC risk associations. Additionally, we reviewed associations within 500 kb of super-enhancer regions to identify proximal associated variants. When LD structure indicated, we employed conditional analysis to determine independence of the super-enhancer signal. Gene-EOC risk associations were assessed with the Admixture Maximum Likelihood (AML) test and Sequence-Kernel Association Test (SKAT) for the combined effect of common and rare (MAF<0.01) variants. Models were adjusted for population stratification using the first five principal components. To adjust for multiple comparisons, a false discovery rate of 10% was used. Results: The most significant SNP observed was rs147487657 (p = 7.7×10−6) on locus 2q37.3 in the HDAC4 gene and there were an additional 12 SNPs with p<1.0×10−4, although not significant at 10% FDR. Gene-level analyses identified two super-enhancers significantly associated with EOC risk. An enhancer at the previously reported 2q31 locus, containing HOXD8 and HOXD-AS2, associated (SKAT p = 4.3×10−5; AML p<0.001) with the top SNP located within the 5′UTR of HOXD8 transcription factor (rs847163 (T>C); p<2.08×10−5). Conditional analysis did not identify an independent association within the super-enhancer region. The second EOC-associated super-enhancer identified was at locus 1q32 (SKAT p = 0.00052, AML p = 0.001) containing the CSRP1 gene. There were 6 SNPs with p<0.001 and 16 SNPs with p<0.01, all were inversely associated with risk and consistent with the top hit at rs927901 T>C (OR = 0.94; 95% CI: 0.90-0.97; p = 2.1×10−4). Associations varied by histologic subtype, possibly due to variance in disease relevant super-enhancer cell-type.Conclusion: These findings suggest germline variation within super-enhancer regions may contribute to EOC susceptibility Citation Format: Brett M. Reid, Jennifer Permuth-Wey, Y. Ann Chen, Hui-Yi Lin, Alvaro Monteiro, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Simon Gayther, Ellen L. Goode, Edwin Iversen, Leigh Pearce, Paul Pharoah, Catherine Phelan, Susan Ramus, Mary Anne Rossing, Joellen Schildkraut, Thomas Sellers, on behalf of the Ovarian Cancer Association Consortium. Variants within super-enhancer regulatory elements associate with epithelial ovarian cancer risk. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4634. doi:10.1158/1538-7445.AM2015-4634

Abstract Background: Genome wide association studies (GWAS) have identified 20 loci associated with epithelial ovarian cancer (EOC) risk. Additional EOC risk loci await identification, and biological approaches may represent a useful strategy for overcoming sample size limitations. The ENCODE project recently concluded that only ∼1.2% of the genome encodes proteins, but at least 20% exhibits biological function and over 80% exhibits biochemical indices of function. Post-GWAS follow-up studies have firmly established that some associations are due to inter-individual differences in non-coding RNAs (ncRNAs). To estimate the magnitude of impact of variants in long non-coding RNAs (lncRNAs), we assessed enrichment of EOC-associated SNPs in lncRNA regions by comparing the density of EOC-associated loci between lncRNA regions, non-lncRNA regions, and the whole genome. Methods: The study population included ∼18,000 invasive EOC cases and 34,000 healthy controls of European ancestry from the Ovarian Cancer Association Consortium with GWAS data imputed to 1000 Genomes Project (1KGP) density. Density was compared with two measures: average chromosome length required for one EOC-associated SNP (kb/locus) and average number of tested SNPs containing one EOC-associated SNP (SNPs/locus). Coordinates and annotation for 13,870 lncRNA genes were downloaded from the publicly available GENCODE (v19) database and were used to annotate SNPs from the 1KGP imputed GWAS data, yielding 13,192 lncRNA genes with biallelic variants imputed at rsquare ≥0.25. A SNP was considered EOC-associated if it reached a significance level of P<10−5. Results: Genome-wide, 11.6% of the 15,123,646 tested SNPs fell within lncRNA regions. Of 5,294 EOC-associated SNPs that were identified, 27.7% were located within lncRNAs, a higher frequency than expected (<v:shape style = “WIDTH: 16.5pt; HEIGHT: 18pt” id = _x0000_i1026 equationxml = ‘14pχ2′ type = “#_x0000_t75”> = 9.35×10−22). Additionally, EOC-associated SNPs were located on average every 237.6 kb (or 1204 tested SNPs) in lncRNA regions versus every 657.7 kb (or 3489 SNPS) in non-lncRNA regions and every 541.5 kb (or 2857 SNPs) in the whole genome, clearly demonstrating an enrichment of EOC-associated loci in lncRNA regions. A total of 1,464 lncRNA SNPs from 53 unique lncRNAs associated with EOC risk (P<10−5); 70 of the identified lncRNA SNPs had P-values between 10−20 and 10−32, and 221 had P-values between 10−10 and 10−15, representing 21 unique regions > 500kb apart. Conclusions: These results justify efforts to integrate functional and population level genetic data on lncRNA regions to explore a new paradigm that addresses the problem of the missing heritability for cancer where restrictions in sample size and statistical power limit the ability to discover additional risk loci. Citation Format: Thomas A. Sellers, Brett M. Reid, Y. Ann Chen, Hui-Yi Lin, Edward Richards, Jamie Teer, Alvaro Monteiro, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Ellen Goode, Edwin Iverson, Leigh Pearce, Paul Pharoah, Catherine Phelan, Susan Ramus, Mary Anne Rossing, Joellen Schildkraut, Jin Cheng, Simon Gayther, Jennifer Permuth-Wey, on behalf of the Ovarian Cancer Association Consortium. Evidence that long non-coding RNA variants associate with epithelial ovarian cancer risk. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4633. doi:10.1158/1538-7445.AM2015-4633

Abstract Introduction Epigenetic changes are reversible features of the genome that regulate gene transcription and protein expression on several levels including DNA methylation, histone modification or miRNA expression. We investigated the association between inherited variation in genes of key epigenetic processes and risk of multiple cancers within the GAME-ON consortium. Methods We performed a pathway based meta-analysis using genotypes from more than 50,000 cases of breast, lung, prostate, ovarian and colorectal cancer cases and more than 60,000 controls from various genome wide association studies participating in the GAME-ON consortium to estimate associations with cancer risk. Using the 1000GenomeProject database, we selected 505,702 genotyped and imputed single nucleotide polymorphisms in 551 genes (flanking region +/- 250kb) related to DNA methylation, histone modification or chromatin remodeling based on GO and GeneCard databases. In order to allow variants to be associated with only a subset of traits we used subset based meta-analysis. False-discovery rate (FDR) corrected p-values (q-values) lower than 0.05 were considered significant. Results and Discussion 582 SNPs were significantly associated with risk of at least one cancer. We identified nine major regions that showed significant associations with more than one cancer type. Among the most interesting regions was the region around PHC3 (3q36), which showed associations with prostate and colorectal cancer and clear cell ovarian carcinomas. PHC3 is involved in chromatin remodeling and plays a role in epithelial neoplasms. Significant Odds ratios (ORs) ranged from 0.80 to 1.31. The number of risk and protective alleles in this region was similarly distributed (19 and 18, respectively). One of the strongest associations was observed for rs76925190 (intronic in PRKC1), which increased the risk of colorectal and prostate cancer (q-value 4.28*10-10). Variants in this region were previously associated with prostate cancer. Polymorphisms in the region (19q13) around BABAM1 (RISC and BRCA1 A complex member 1), were associated with lung, breast, ovarian and prostate cancer. BABAM1 is associated with the BRCA1-complex. Its function in histone modification and DNA repair emphasizes its importance in carcinogenesis. Significant ORs ranged from 0.88 to 1.14 with similar distribution of risk and protective alleles in this region (19 and 17, respectively). The strongest association was observed for rs4808076 (intronic in ANKLE1), which increased the risk of squamous lung, serous ovarian and ER- -breast cancer (q-value 2.40*10-6). Variants in this region were previously associated with risk of breast and ovarian cancer. Conclusions This study emphasizes the importance of variants in genes of epigenetic processes on cancer risk and further provides insights into novel, pleiotropic epigenetic mechanisms of cancer development. Citation Format: Dominique Scherer, Reka Toth, Linda Kelemen, Angela Risch, Aditi Hazra, Jean Pierre Issa, Victor Moreno, Rosalind A. Eeles, John Quackenbush, Ellen L. Goode, Shuji Ogino, Rayjean Hung, Cornelia M. Ulrich. Genetic variants in epigenetic pathways and risk of multiple cancer types in the GAME-ON consortium. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4612. doi:10.1158/1538-7445.AM2015-4612

Abstract Many germline genetic variants have been found to be associated with susceptibility to epithelial ovarian cancer (EOC), but currently few associations have been identified for EOC outcomes such as overall survival. In the absence of evidence for common germline markers, it is possible that rare variants not captured in GWAS arrays may be associated with overall survival. We hypothesize that rare variants, either individually or combined across a gene, may be associated with overall survival in EOC. We utilized data from two genotyping projects of the Ovarian Cancer Association Consortium (OCAC) that used commercial exome-based arrays. The primary sample, genotyped on the Affymetrix Axiom Exome Array at 227,892 standard and custom variants, consisted of 14 independent EOC studies (4293 cases; 2257 deaths). The secondary sample, genotyped on the Illumina Infinium HumanExome BeadChip at 114,620 variants, consisted of six additional EOC studies (1744 cases; 1027 deaths). Both sets were analyzed using Cox proportional hazards regression to determine the association of each variant with overall survival time. Meta-analysis was conducted across samples at 73,203 overlapping variants. Gene-level tests of over 18,000 genes were also conducted using burden tests and Sequencing Kernel Association Tests (SKAT) adapted for Cox proportional hazards models. Gene-level tests were conducted separately for the primary and secondary cases and then were meta-analyzed. Models were adjusted for age, site, and three principle components. Six individual variants had meta-analysis p-values < 1.0E-4, five of which were rare (MAF < 0.003). Common variant rs8170 (MAF = 0.2) in BABAM1 encoding BRISC and BRCA1 A complex member 1 - previously reported to be associated with EOC risk_showed evidence of association with overall survival (Pmeta = 1.5E-5) and consistent estimates of effect size across both samples (HR1 = 1.18, HR2 = 1.19). In imputed genotype data from over 18,000 subjects from OCAC genotyped on the COGS array, this association reaches genome-wide significance (HR = 1.15, P = 4.7E-9). Five genes had gene-level meta-analysis p-values < 1.0E-4, including top ranked ATG2B (p = 1.1E-6), an autophagy gene important for apoptosis; zinc finger protein PEG3 (p = 1.8E-5), playing a role in autophagy and down-regulated in EOC; helicase-like transcription factor HLTF (p = 1.9E-5), involved in post-replication DNA repair; mitochondrial fission regulator 1-like gene FAM54B (p = 3.1E-5); and T-cell surface glycoprotein CD1E (p = 8.8E-5). With over 6000 EOC cases in the primary and secondary samples, this is the largest genome-wide assessment of rare variant genetic associations with EOC overall survival. Variant rs8170 in BABAM1, a necessary component of the BRCA1 complex, is associated with overall survival. Single variant and gene-level analyses provide complementary approaches, suggesting additional candidates that warrant follow-up study. Citation Format: Stacey J. Winham, Brooke L. Fridley, Melissa C. Larson, Zachary Fogarty, Andrew Berchuck, Yian Ann Chen, Hui-Yi Lin, Georgia Chenevix-Trench, Jenny Permuth-Wey, Thomas A. Sellers, Ailith Pirie, Ellen L. Goode, Ovarian Cancer Association Consortium. Investigation of exome variants associated with overall survival in ovarian cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4636. doi:10.1158/1538-7445.AM2015-4636

Abstract Background: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. Methods: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. Cancer Epidemiol Biomarkers Prev; 24(10); 1574–84. ©2015 AACR.