Sellers, Thomas A.

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 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.

Abstract Background: Common genetic variants identified by genome-wide association studies and follow-up genotyping initiatives only explain a small proportion of the heritability of epithelial ovarian cancer (EOC). We hypothesized that some of the missing heritability may be explained by rare (minor allele frequency (MAF) <0.5%) and low-frequency (MAF 0.5-5%) protein-coding variants that are not well captured by genotyping arrays that focus on common variants. Methods: To examine the association between uncommon variants and EOC susceptibility, we genotyped 7,060 EOC cases and 6,712 controls from the Ovarian Cancer Association Consortium using the Affymetrix Axiom Exome Genotyping Array. This platform contains 300,785 putative functional coding variants selected from exome sequences of 12,000+ individuals representing multiple ethnicities and complex traits. After performing quality control (QC), we used unconditional logistic regression treating the number of minor alleles carried as an ordinal variable (log-additive model) to evaluate SNP-EOC risk associations. Genotype cluster plots were visually inspected for top-ranking variants to determine assay success, and allele frequencies of samples from the 1000 Genomes Project and other cohorts were evaluated for QC purposes. Results: A total of 13,318 samples (97%) passed QC, and 12,779 eligible samples (6,293 invasive serous and endometrioid cases and 6,486 controls) were included in the analyses. 280,737 (93%) of the 300,785 attempted markers were successfully genotyped and had call rates >90%. After removing 31,436 monomorphic markers, the 249,301 remaining markers were included in association analyses. We confirmed variants at previously reported EOC susceptibility loci (9p22, 3q25, 17cen-q21.3, and 8q24), with p-values between 10-5 and 10-11. Several correlated low-frequency non-synonymous variants (MAF=5%) residing in a novel EOC susceptibility gene at 3q25.31 were risk-associated. The most significant variant at 3q25.31 had an OR=1.36 and p = 5.58x10-8. Also noteworthy is a rare variant at 15q15.1-q21.1 (MAF=0.5%) that introduces a stop codon in a gene belonging to the tyrosine kinase family (OR=0.39, CI=0.26-0.58, p = 4.52x10-6). We also identified a more common synonymous coding variant in a phosphatase at 6q21.3 that was associated with increased risk (OR=1.22, CI=1.13-1.33, p = 1.84x10-6, MAF=9.6%). Population stratification and gene-based analyses are underway to further examine the impact of the newly-identified variants on EOC risk. A meta-analysis to include data from an additional 2104 EOC cases and 2516 controls genotyped with Illumina's HumanExome Beadchip rare variant array is also underway. Functional analysis of the most promising variants will follow. Conclusions: Preliminary data from this large-scale study reveals novel rare and low-frequency variants that may influence susceptibility to epithelial ovarian cancer. Citation Format: Jennifer Permuth-Wey, Y. Ann Chen, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Simon Gayther, Ellen L. Goode, Edwin Iversen, Alvaro N.A. Monteiro, Leigh Pearce, Paul D.P. Pharoah, Catherine M. Phelan, Ailith Pirie, Susan Ramus, Mary Ann Rossing, Joellen M. Schildkraut, Thomas A. Sellers, on behalf of the Ovarian Cancer Association Consortium. Exome genotyping array identifies rare and low-frequency variants that may be associated with ovarian cancer risk. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 946. doi:10.1158/1538-7445.AM2014-946

Abstract Purpose: Mammographic breast density is an established and strong risk factor for breast cancer. Recently, a number of common genetic susceptibility loci have been identified as risk factors for breast cancer. We present the first report on the relative contribution of 76 validated breast cancer susceptibility loci, in the context of a polygenic risk score (PRS), to the breast density and breast cancer association. We also examine whether the PRS improves prediction of the Breast Cancer Surveillance Consortium (BCSC) 5-year risk model above and beyond breast density and clinical factors included in the model. Methods: The study population included 1643 cases and 2397 controls from three independent epidemiologic studies: the Mayo Mammography Health Study (MMHS), the Mayo Clinic Breast Cancer Study (MCBCS), and the Bavarian Breast Cancer Cases and Control Study (BBCC). Data collected on patients in each of the studies included clinical risk factor, BI-RADS breast density [a) almost entirely fat; b) scattered fibroglandular densities; c) heterogeneously dense; and d) extremely dense] and genotypes for the 76 breast cancer susceptibility loci known at the time of the study. We formed a PRS from the reported per-SNP odds ratios (OR) for 76 known breast cancer susceptibility loci, and evaluated whether BI-RADS density and the PRS were independent risk factors for breast cancer, when adjusted for age, 1/BMI and study. We also incorporated the PRS (OR) into the BCSC 5-year risk model and estimated 5-year risk for the MMHS nested case-control study of 339 invasive cases, 765 controls. Results: BI-RADS density (p<0.0001) and PRS (p<0.0001) were independent risk factors for breast cancer that together showed greater discrimination of risk (AUC=0.69) than density (AUC=0.66; ΔAUC=0.029) or PRS score alone (AUC=0.68; ΔAUC=0.013; p<0.001). Relative to those with scattered fibroglandular densities and average (2nd quartile) PRS, women with extremely dense breasts and in the highest PRS quartile, had a 2.7 fold (95%CI: 1.7-4.1) increased risk of breast cancer, while those with fatty breasts and in the lowest PRS quartile had a reduced risk (OR=0.30, 95%CI: 0.18-0.51). Incorporation of the PRS into the BCSC risk model improved discrimination (ΔAUC=0.031, p=0.001), for a net reclassification improvement of 20% (95%CI: 11%-28%), split equally among cases (9%) and controls (11%). Conclusion: BI-RADS density and the PRS are both important risk factors for breast cancer that can be included in breast cancer risk models to improve prediction of this disease. Using these models to identify high and low-risk risk groups will facilitate improved tailored screening and primary prevention interventions. Citation Format: Celine M. Vachon, V. Shane Pankratz, Christopher G. Scott, Lothar Haeberle, Elad Ziv, Matthew R. Jensen, Kathleen R. Brandt, Dana H. Whaley, Janet E. Olson, Katharina Heusinger, Carolin C. Hack, Sebastian M. Jud, Matthias W. Beckmann, Jeffrey A. Tice, Kristen S. Purrington, Thomas A. Sellers, Karla Kerlikowske, Peter A. Fasching, Fergus J. Couch. The contribution of common breast cancer susceptibility loci to the breast density and breast cancer association and the Breast Cancer Surveillance Consortium (BCSC) risk model. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 940. doi:10.1158/1538-7445.AM2014-940

Abstract Both genetic and epigenetic factors influence the development and progression of epithelial ovarian cancer (EOC). However, there is an incomplete understanding of the interrelationship between these factors and whether they interact to impact disease risk. Given that the development of ovarian cancer is complex, we aimed to identify DNA methylation marks that are candidates for mediating ovarian cancer genetic risk. We used 214 cases and 214 age-matched controls from the Mayo Clinic Ovarian Cancer Study. Pretreatment, blood-derived DNA was profiled for genome-wide methylation (Illumina Infinium HumanMethylation27 BeadArray) and single nucleotide polymorphisms (SNPs, Illumina Infinium HD Human610-Quad BeadArray). We employed a three-step filtering procedure, followed by the Causal Inference Test (CIT), to distinguish CpG sites that mediate genetic risk, from those that are consequential or independently acted on by genotype. Controlling for the estimated distribution of immune cells and other key covariates, we identified 1,993 out of 25,926 (7.7%) CpGs that were significantly differentially methylated between cases and controls (FDR, q < 0.05). The relationship between methylation and case-control status among these 1,993 CpGs was found to be highly consistent with the results of an independent study. Implementation of the CIT test revealed 13 CpG/SNP pairs, comprising 13 unique CpGs and 17 unique SNPs, which represent potential methylation-mediated relationships between genotype and EOC risk. These findings provide additional insight into EOC etiology and may serve as novel biomarkers for EOC susceptibility. Citation Format: Devin C. Koestler, Prabhakar Chalise, Mine S. Cicek, Julie M. Cunningham, Sebastian Armasu, Melissa C. Larson, Jeremy Chien, Matthew Block, Kimberly R. Kalli, Thomas A. Sellers, Ellen L. Goode, Brooke L. Fridley. Integrative genomic analysis identifies epigenetic marks that mediate genetic risk for epithelial ovarian cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 260. doi:10.1158/1538-7445.AM2014-260

Abstract An ovarian cancer Genome Wide Association Study (GWAS) identified 9p22.2 as a novel susceptibility locus with the most statistically significant single nucleotide polymorphisms (SNPs) located in an intergenic region near the Basonuclin 2 (BNC2) gene, which codes for a putative transcription regulator containing three pairs of zinc finger (ZF) domains. The minor alleles are protective in terms of ovarian cancer susceptibility. However, the molecular mechanisms by which these SNPs modify susceptibility remain largely unknown. The significant SNPs in the 9p22.2 locus lie in non-coding regions and therefore are hypothesized to affect the activity of regulatory elements and modify the expression of a target gene(s). In order to test this hypothesis we conducted fine mapping for the locus which delimited a ∼74kb region containing SNPs with a p-value less than 10-8. FAIRE-Seq and ChIP-Seq experiments for histone markers conducted in immortalized ovarian surface epithelial cells (IOSE) and fallopian tube epithelial cells (IFTE) were used to prioritize functional SNP candidates which overlap with regulatory elements. Luciferase assays tested the ability of these regulatory elements to activate transcription. Chromosome conformation capture (3C) experiments demonstrate a physical interaction between the BNC2 promoter and candidate regulatory elements containing risk-associated SNPs. Methylation Quantification at Trait Loci (mQTL) revealed an association between decreased methylation at the BNC2 promoter and the protective minor alleles. Expression analysis shows decreased expression of BNC2 in cancer versus normal tissue implicating tumor suppressor function of BNC2. Therefore the protective minor allele likely increases expression of BNC2 which in turn contains tumor suppressing properties that decrease ovarian cancer risk. BNC2 protein is in complex with transcriptional regulatory proteins, in particular the NURD complex components. Moreover, BNC2 acts as a transcriptional repressor in in vitro transfection assays indicating that it functions in transcriptional repression. We then used protein binding microarrays and CHIP-Seq experiments to identify its putative DNA binding motifs and its downstream target genes. Analysis of this data suggests that BNC2 functions in a regulatory transcription network that impacts on genes implicated in ovarian cancer with enrichment for genes in the TGF-beta response pathway. Citation Format: Melissa A. Buckley, Howard C. Shen, Gustavo A. Mendoza-Fandino, Nicholas T. Woods, Anxhela Gjyshi, Juliet French, Kate Lawrenson, Honglin Song, Jonathan Tyrer, Renato S. Carvalho, Alexandra Valle, Ann Chen, Sean Yoder, Gregory Bloom, Ya-Yu Tsai, Ally Yang, Timothy R. Hughes, Xiaotao Qu, Mine Cicek, Melissa Larson, Ellen Goode, Brooke Fridley, Susan Ramus, Georgia Chenevix-Trench, Paul Pharoah, Thomas A. Sellers, Simon Gayther, Alvaro N.A. Monteiro, Ovarian Cancer Association Consortium. Functional analysis of the 9p22 locus implicates the transcriptional regulation of BNC2 as a mechanism in ovarian cancer predisposition. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3285. doi:10.1158/1538-7445.AM2014-3285

Abstract Background Genome-wide association studies (GWAS) previously identified 8 new risk loci for all subtypes of epithelial ovarian carcinoma (EOC) and one specific to invasive serous EOC. One locus, at 2q31, was also associated with invasive mucinous EOC (mEOC) at P=7.3 x 10-7 (Nat Genet 2010:874). Here, we report new risk loci for mEOC, which is thought to develop from a borderline mucinous tumor. These loci may provide clues to the molecular basis of the disease. Methods We used genotype data from 4 GWAS of EOC and from multiple case-control studies in the Ovarian Cancer Association Consortium that had been genotyped using the iCOGS custom SNP panel (210k SNPs) developed for the Collaborative Oncological Gene-environment Study. We imputed genotypes of common variation across the genome using the 1000 Genomes Project reference panel and tested for association using log-additive unconditional regression models. Results Genotypes were available for 1,643 combined invasive and borderline mEOC and for 1,002 invasive-only mEOC of European ancestry. Three loci in new regions, and one locus in a previously published region, with minor allele frequency (MAF) > 1% and P ≤ 10-7 were found. The imputed SNP rs72831838 (imputation r2=0.67, MAF=0.15) is located at 2q13 in an intron of the PAX8 (paired box 8) gene (all mEOC OR=1.35, P=4.2 x 10-8 and invasive-only OR=1.43, P=9.6 x 10-8). PAX8 is a transcription factor and may be a Müllerian lineage marker that distinguishes carcinomas of gynecologic origin from other sites. The imputed variant at chr19:39745695 (imputation r2=0.61, MAF=0.32) is an insertion/deletion polymorphism located at 19q13.2 and falls within the MSRB1P1 (methionine sulfoxide reductase B1 pseudogene 1). This locus was associated with decreased risk (all mEOC OR=0.74, P = 2.1 x 10-9 and invasive-only OR=0.79, P = 8.1 x 10-5) and is enriched with the H3K27Ac histone mark that identifies active enhancers of gene expression. The imputed SNP rs6425050 (imputation r2=0.45, MAF=0.19) is located at 1q25 (all mEOC OR=1.38, P=4.7 x 10-8 and invasive-only OR=1.41, P=1.6x10-6). This SNP is intronic to PLA2G4A (phospholipase A2, group IVA), which encodes an enzyme that hydrolyzes membrane phospholipids for eicosanoid metabolism and signaling. None of these loci were associated with other EOC histological subtypes at P ≤ 10-7. The genotyped SNP, rs711830 (MAF=0.32), is located at 2q31.1 in the 3′ region of the HOXD3 homeobox gene (all mEOC OR=1.30, P=7.5 x 10-12 and invasive-only OR=1.26, P=7.8 x 10-7). This SNP is highly correlated (r2=0.99) with rs2072590, which is located 5.3kb upstream and previously reported by us to be associated with mEOC and invasive serous EOC (Nat Genet 2010:874). The HOXD3 locus is highly conserved and may also be a marker of Müllerian cell type origin. Conclusions The 3 new loci for mEOC require confirmation by genotyping. Fine mapping and functional analysis of all loci is needed in order to determine their likely target genes. Citation Format: Linda E. Kelemen, Jonathan Tyrer, Catherine M. Phelan, Susan J. Ramus, Andrew Berchuck, Simon A. Gayther, Ellen L. Goode, Celeste L. Pearce, Joellen M. Schildkraut, Georiga Chenevix-Trench, Alvaro N. Monteiro, Marc T. Goodman, Thomas A. Sellers, Paul PD Pharoah. GWAS identifies risk variants for mucinous ovarian carcinoma. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3283. doi:10.1158/1538-7445.AM2014-3283