ABSTRACTEpithelial‐mesenchymal transition (EMT) is a process whereby epithelial cells assume mesenchymal characteristics to facilitate cancer metastasis. However, EMT also contributes to the initiation and development of primary tumors. Prior studies that explored the hypothesis that EMT gene variants contribute to epithelial ovarian carcinoma (EOC) risk have been based on small sample sizes and none have sought replication in an independent population. We screened 15,816 single‐nucleotide polymorphisms (SNPs) in 296 genes in a discovery phase using data from a genome‐wide association study of EOC among women of European ancestry (1,947 cases and 2,009 controls) and identified 793 variants in 278 EMT‐related genes that were nominally (P < 0.05) associated with invasive EOC. These SNPs were then genotyped in a larger study of 14,525 invasive‐cancer patients and 23,447 controls. A P‐value <0.05 and a false discovery rate (FDR) <0.2 were considered statistically significant. In the larger dataset, GPC6/GPC5 rs17702471 was associated with the endometrioid subtype among Caucasians (odds ratio (OR) = 1.16, 95% CI = 1.07–1.25, P = 0.0003, FDR = 0.19), whereas F8 rs7053448 (OR = 1.69, 95% CI = 1.27–2.24, P = 0.0003, FDR = 0.12), F8 rs7058826 (OR = 1.69, 95% CI = 1.27–2.24, P = 0.0003, FDR = 0.12), and CAPN13 rs1983383 (OR = 0.79, 95% CI = 0.69–0.90, P = 0.0005, FDR = 0.12) were associated with combined invasive EOC among Asians. In silico functional analyses revealed that GPC6/GPC5 rs17702471 coincided with DNA regulatory elements. These results suggest that EMT gene variants do not appear to play a significant role in the susceptibility to EOC.
Abstract 4634: Variants within super-enhancer regulatory elements associate with epithelial ovarian cancer risk
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 4633: Evidence that long non-coding RNA variants associate with epithelial ovarian cancer risk
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
Network-Based Integration of GWAS and Gene Expression Identifies a
HOX
-Centric Network Associated with Serous Ovarian Cancer Risk
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
Cell-type-specific enrichment of risk-associated regulatory elements at ovarian cancer susceptibility loci
ScopeWe reevaluated previously reported associations between variants in pathways of one‐carbon (1‐C) (folate) transfer genes and ovarian carcinoma (OC) risk, and in related pathways of purine and pyrimidine metabolism, and assessed interactions with folate intake.Methods and resultsOdds ratios (OR) for 446 genetic variants were estimated among 13 410 OC cases and 22 635 controls, and among 2281 cases and 3444 controls with folate information. Following multiple testing correction, the most significant main effect associations were for dihydropyrimidine dehydrogenase (DPYD) variants rs11587873 (OR = 0.92; p = 6 × 10−5) and rs828054 (OR = 1.06; p = 1 × 10−4). Thirteen variants in the pyrimidine metabolism genes, DPYD, DPYS, PPAT, and TYMS, also interacted significantly with folate in a multivariant analysis (corrected p = 9.9 × 10−6) but collectively explained only 0.2% of OC risk. Although no other associations were significant after multiple testing correction, variants in SHMT1 in 1‐C transfer, previously reported with OC, suggested lower risk at higher folate (pinteraction = 0.03–0.006).ConclusionVariation in pyrimidine metabolism genes, particularly DPYD, which was previously reported to be associated with OC, may influence risk; however, stratification by folate intake is unlikely to modify disease risk appreciably in these women. SHMT1 SNP‐by‐folate interactions are plausible but require further validation. Polymorphisms in selected genes in purine metabolism were not associated with OC.
Variation in NF-κB Signaling Pathways and Survival in Invasive Epithelial Ovarian Cancer