Chen, Zhihua

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 Background: Variation in mitochondrial genes in cancer cells alters the mitochondrial bioenergetic and biosynthetic state, which mediates cross-talk between mitochondria and the nucleus to modulate many cellular processes. The objective of this study was to comprehensively evaluate mitochondria-nuclear cross-talk in terms of SNP-SNP interactions associated with invasive epithelial ovarian cancer (EOC) risk, which may play an important role in unveiling the underlying mechanism of this complex lethal disease. Methods: Our analyses were based on 1,938 invasive EOC cases and 2,009 controls with greater than 80% European ancestry from five case-control studies genotyped using the Illumina 610quad chip. We evaluated 2,488 SNPs in over 1,500 genes in eight mitochondria-related pathways (apoptosis, oxidation-reduction, epithelial-mesenchymal transition, immunomoduation, transmembrane transport, small GTPases, BRCA1-interactors and circadian rhythm). SNPs with strong linkage disequilibrium of r2 > 0.8 were excluded. We examined 2-way SNP-SNP interactions associated with invasive EOC risk using the two-stage Random Forests plus Multivariate Adaptive Regression Splines (TRM) approach. Bootstrapping was further performed to select important variables and reduce false positive findings. Based on the scree plot using 1,000 bootstrap samples, the factors with more than 4% of bootstrap frequency were defined as significant factors. We then included each identified factors separately in model adjusting for study site and first principal component representing European ancestry. Results: Five significant SNP-SNP interactions were observed: (rs2270799 in IQSEC3 (12p13.33) + rs933305 in CUX2 (12q24.3), (p= 6.3x10−5); rs6063251 in PREX1 (20q13.3) + rs9705 in SLC39A8 (4q22-q24), (p= 3.5x10−5); rs933305 in CUX2 (12q24.3) + rs1712957 in ARHGAP15 (2q22.2-q22.3), (p=4.2x10−7), rs2861828 in SLIT1 (10q23.3-q24) + rs6063251 in PREX1 (20q13.3), (p=2.5x10−7); rs10954593 in SEMA3C (7q21-q31) + rs933305 in CUX2 (12q24.3), (p=2.8x10−3). Four of the five interactions involved SNPs from genes in the small GTPases pathway (IQSEC3; PREX1 (twice) and ARHGAP15). In addition, three of the five interaction pairs involved the CUX2 gene. This gene encodes a protein which contains three CUT domains and a homeodomain, which are DNA-binding motifs. The main mitochondrial SNP-SNP interaction involved the nuclear mitochondria gene SLC39A8. Conclusions: Our results suggest that genetic variation in mitochondrial-related pathways may be associated with invasive EOC risk. These findings highlight important genes/pathways that may interact as a network to influence invasive EOC risk and may generate novel therapeutic targets. External validation will be done using other independent studies for future analyses. Citation Format: Hui-Yi Lin, Ya-Yu Tsai, Y. Ann Chen, Zhihua Chen, Xiaotao Qu, Ellen L. Goode, Joellen Schildkraut, Edwin Iversen, Steven A. Narod, Thomas A. Sellers, Catherine M. Phelan. SNP-SNP interactions in mitochondria-related pathways are associated with invasive Epithelial Ovarian Cancer (EOC) risk . [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4839. doi:10.1158/1538-7445.AM2013-4839

Abstract Since most GWAS hits fall in non-coding regions of the genome and long non-coding RNAs (lncRNAs) are emerging as drivers of carcinogenesis, we hypothesized that SNPs in lncRNAs influence epithelial ovarian cancer (EOC) risk. A comprehensive lncRNA database (lncRNA db) that contained 104 human lncRNAs when downloaded in November 2011 was used to identify 1,737 variants in 63 unique lncRNAs that were represented in three genome-wide association studies from North America, the United Kingdom, and Poland (3,995 EOC cases and 3,277 controls of European background). SNPs with MAF <5% were excluded, and missing genotypes were inferred with Mach using the HapMap CEU population. Unconditional logistic regression treating alternate alleles as an ordinal variable was used to evaluate individual SNP-EOC risk associations. Subgroup analysis was conducted for serous adenocarcinomas (N= 2,066), the main histologic subtype of EOC. Models were adjusted for study and European ancestry using the first two principal components (PCs). We reduced correlated signals (r2 ≥ 0.8) within each lncRNA and kept the most statistically significant variants based on Wald tests, resulting in 651 SNPs for further analyses. Fisher's product method was used to aggregate evidence of multiple variants within each lncRNA using 10,000 permutations. To adjust for multiple comparisons, a false discovery rate (FDR) of 10% was used. A replication phase was carried out for top-ranked SNPs from an additional 9,854 EOC cases (5,802 serous) and 17,633 controls genotyped through an international effort known as the Collaborative Oncological Gene-Environment study (COGS). Four lncRNAs, WT1-AS (p = 0.005, n = 2 SNPs), Hoxa11as (p = 0.013, n = 2), AK082072 (p = 0.016, n = 4) and H19 (p = 0.020, n = 2), were significantly associated with EOC risk among all histologies (FDR ≤ 10%). The SNP in WT1-AS most significantly associated with EOC risk was rs3809061 (T>C) (minor allele frequency= 36%, odds ratio (OR) = 0.91, CI: 0.84-0.97, p = 0.008). Among serous cases, rs3809061 was also protective (OR = 0.92, p = 0.04). These findings were replicated by a correlated SNP rs2301250 (r2 = 0.84) evaluated in COGS among serous cases (OR = 0.94, CI: 0.90-0.99, p = 0.009) and less significant among all histologies (OR = 0.96, CI: 0.93-1.00, p = 0.054). We further interrogated its functional role by performing an expression quantitative trait locus analysis on WTI-AS mRNA expression using the Cancer Genome Atlas (TCGA) data (N = 462 serous cases). WT1-AS expression was significantly higher among carriers of the variant allele (compared to TT homozygotes) using the Mann-Whitney U test (p = 0.001). WT1-AS is the antisense and possible regulator of WT1, a tumor suppressor gene reported to be prognostic in advanced EOC. These findings implicate germline lncRNA variants associated with EOC risk that merit further investigation. Citation Format: Yian Ann Chen, Zhihua Chen, Jennifer Permuth-Wey, Ya-Yu Tsai, Hui-Yi Lin, Xiaotao Qu, Kate Lawrenson, David Fenstermacher, Catherine M. Phelan, Alvaro Monteiro, Simon A. Gayther, Steven A. Narod, Rebecca Sutphen, Michael J. Birrer, Nicolas Wentzensen, Joellen M. Schildkraut, Ellen L. Goode, Paul Pharoah, Thomas Sellers. Variants in long non-coding RNAs are associated with epithelial ovarian cancer risk in a pooled analysis of three genome-wide association studies. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4579. doi:10.1158/1538-7445.AM2013-4579

Abstract Introduction The epithelial-mesenchymal transition (EMT) pathway contributes to epithelial ovarian cancer (EOC) progression. Previously we identified associations of single nucleotide polymorphisms (SNPs) in EMT-related genes and EOC risk (data not shown). To further investigate the role of EMT-related gene variants in EOC and to derive more reliable risk estimates, we evaluated associations for 795 SNPs from 278 EMT-related genes in a replication study of 43 studies within the Ovarian Cancer Association Consortium (OCAC). Methods The study population included 14,736 cases and 23,448 controls of European ancestry, 89 cases and 200 controls of African ancestry, and 249 cases and 1574 controls of Asian ancestry. The 795 SNPs were genotyped using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS). For women of European ancestry, both invasive cancers combined and the four main histological subtypes (serous [n=8,372], endometroid [n=2,068], clear cell [n=1,025] and mucinous [n=943] were analyzed, while for women of African and Asian ancestries only the serous subtype was analyzed. SNP analyses were conducted using unconditional logistic regression under a log-additive model separately for women of each ancestry. All analyses were adjusted for study site and population substructure within each ancestry. Results For women of European ancestry, the strongest evidence of an association for invasive cancers combined was observed for IGF1R rs10794486 (OR=1.05, 95%CI=1.02-1.09, P=0.002), which was also associated with serous (P=0.019), but not the other histological subtypes. In the histological subtype-specific analysis, the most significant association for serous was observed at NRP2 rs3771044 (OR=1.09, 95%CI=1.03-1.15, P=0.00014), for endometroid at rs1770247 (13q31.3, OR=1.16, 95%CI=1.07-1.25, P=0.00028), for clear cell at rs4848300 (2q13, OR=0.84, 95%CI=0.76-0.93, P=0.00099) and for mucinous at SEMA4B rs8030039 (OR=1.09, 95%CI=1.01-1.17, P=0.00019). For women of African ancestry, the strongest association for serous histological subtype was observed at F9 rs6048 (OR=1.71, 95%CI=1.17-2.50, P=0.006). This SNP was not significant in women of European or Asian ancestry. The strongest association for women of Asian ancestry was IGF1R rs10794486 (OR=1.68, 95%CI=1.16-2.45, P=0.007), which was also significant in women of European, but not African, ancestry. Conclusion Findings from this large study provide additional evidence that variants in EMT-related genes may be associated with ovarian cancer risk and that EMT susceptibility loci may differ by ovarian cancer histological subtypes. Furthermore, the findings suggest that susceptibility locus for the serous subtype may be different for women of African ancestry. Future studies are warranted to confirm these findings. Citation Format: Ernest K. Amankwah, Jonathan Tyrer, Hui-Yi Lin, Ya-Yu Tsai, Zhihua Chen, Gang Han, Xiaotao Qu, Ellen Goode, Julie Cunninghan, Edward Iverson, Susan Ramus, Andrew Berchuck, Joellen Schildkraut, Alvaro Monteiro, Simon Gayther, Steven Narod, Paul Pharoah, Thomas A. Sellers, Catherine Phelan. Epithelial-mesenchymal transition (EMT) gene variants influence epithelial ovarian cancer risk in women of European, African and Asian ancestry. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1352. doi:10.1158/1538-7445.AM2013-1352

Abstract Population stratification in case-control studies can result from differences in ancestral make-up between cases and controls due to sampling variation. Ancestry is therefore routinely estimated and controlled for in these studies. Although less common, it is also possible for ancestry to truly be associated to the disease of interest. Controlling for ancestry can then compromise the power to detect variants that underlie both ancestry and disease. Using data from a multi-center case-control study of epithelial ovarian cancer (OC) among women of European-American ethnicity in which case-control samples were drawn from four geographically distinct North-American sites, we developed a three-step method to investigate whether the stratification observed across the four sites is due to chance or to a non-spurious association between European ancestry and OC. First, we collapsed genome-wide data into two principal components (PCs) that represent the major axes of European ancestral variation, which correspond to north-south and to west-east geographical clines. Next, we determined the discriminant function based on these two PCs that best separates cases and controls for each individual study site and we used the largest angle between the four discriminant function vectors as a measure of similarity ranging from 0 degrees, where all four vectors are exactly the same, to 180 degrees where two of the vectors face exactly opposite directions. If stratification is due to sampling, it is unlikely that the four sites will present similar discriminant functions by chance alone. We then gauged significance of similarity by permuting the case control status across individuals within each site and recalculating the maximum angle between the discriminant function vectors, thus obtaining a null distribution for the statistic. We found that all four sites present the greatest separation between cases and controls on the west-east axis of ancestral variation, with a higher proportion of ovarian cancer cases presenting western ancestry. The largest angle between the four discriminant function vectors observed was of 36.5 degrees. Permutation testing showed this level of similarity between the functions to have a p-value < 0.01 and suggests that OC risk is somehow tied to European ancestry. It remains to be seen whether shared culture or other exposures such as parity or oral contraceptive use explain this connection or whether genetic variants underlie it and are potentially being missed due to routine ancestry control in association testing. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1678. doi:1538-7445.AM2012-1678

Abstract DNA copy number variations (CNVs) are a significant and ubiquitous source of human genetic variation. However, the influence of CNVs on cancer susceptibility remains poorly understood. Out of 83 genome-wide association studies (GWAS) on cancer to date, only a few studies found significant associations on germline CNVs and cancer. Here we analyzed data from our ongoing two-stage GWAS of four North American case-control studies to test the hypothesis that CNVs in germline DNA from peripheral blood lymphocytes may serve as risk factors for epithelial ovarian cancer (EOC). To reduce disease heterogeneity, we focused on the subset of cases with serous histology. The analysis was therefore based on 942 serous ovarian cancer patients and 1,682 healthy controls who were genotyped using the Illumina 610K quad array. Subjects with extreme noise and genomic waviness in log R ratio (LR) were excluded prior to segmentation; principal component analysis was performed to adjust for batch effects. CNV segmentation was performed on LR data from 22 autosomes using circular binary segmentation embedded in the Copy Number Analysis Module from Golden Helix SNP Variation Suite version 7. Copy number segment covariates were discretized based on the thresholds that signify a transition between copy number states (deletion/no deletion; duplication/no duplication) after the segmentation. Unconditional logistic regression on a log-additive model was used to evaluate the association between copy number states and serous EOC risk after adjusting for study sites. By comparing single marker copy number states at 388,958 SNPs on 22 autosomes, we observed a total of 134 SNPs significantly associated with risk of serous EOC with a p value below 10−6. Associations with deletion polymorphisms were observed on chromosomes 7, 8, 14, and 18 when controlling for false discovery rate at 1%; no duplication polymorphisms were significant. We observed a large deletion at chromosome 14 that occurred in 8.9% of cases but in only 3.9% of controls, with a p value of 5.59×10−8 (Odds Ratio (OR): 2.56, 95% confidence interval (CI): 1.82-3.60). Another common deletion on chromosome 7 occurred in 8.8% of cases and only 4.3% of controls (p=3.83×10−6; OR: 2.23, 95% CI: 1.60-3.10). Two additional regions on chromosomes 8 and 18 with deletion events less than 5% were also identified. Women who harbored the deletion on chromosome 8 were at lower risk of developing serous ovarian cancer (p=4.83×10−8; OR: 0.04, 95% CI: 0.01-0.30). Women who carried the deletion on chromosome 18 had an increased risk for serous EOC (p=9.04×10−7; OR: 7.26, 95% CI: 2.94-17.97). Further validation of these four regions using independent data sets is currently underway. In summary, this is the largest reported genome-wide study of CNVs and serous EOC risk. These preliminary results suggested that germline CNVs may play an important role in ovarian cancer susceptibility. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1649. doi:1538-7445.AM2012-1649

Abstract Epithelial ovarian cancer (EOC) is the 6th most commonly diagnosed cancer among women in the world, accounting for 4% of all female cancers. On a worldwide basis, an estimated 204,000 new cases are diagnosed and 125,000 women die of EOC annually, with 5-year survival rate at 45%. Metastasis and its complications are the usual cause of EOC-related deaths. Thus, factors related to tumor aggressiveness, response to therapy, and the underlying health state of the patient often predict survival. Candidate gene and genome-wide association studies (GWAS) for survival from EOC have discovered only a few the genetic variants, accounting for only a small proportion of the heritability. One explanation for the missing heritability is that the common analysis approach _ assessing the effect of each single nucleotide polymorphism (SNP) individually _ is not well suited to the detection of small effects of multiple SNPs. Gene set analysis (GSA) overcomes this limitation by assessing the overall evidence of association of a phenotype with all measured variation in a set of genes or pathway. Therefore, we conducted a GSA using data from an EOC GWAS, using the Illumina 610-quad SNP array, to determine novel gene sets (GSs) associated with overall survival (OS) from EOC (N cases = 1057, N deaths = 495). All subjects were non-Hispanic, non-Jewish Caucasians, with sample and SNP call rates >95%. Subjects with ambiguous gender, unresolved identical genotypes, and less than 80% European ancestry were also excluded. SNPs were mapped to genes within 20 kb, with genes then mapped to GSs defined by the following: KEGG, Gene Ontology (biological, cellular, molecular) and PharmGKB. GSA was completed in which the association of each gene with OS was assessed using a principal component gene-level test (adjusting for study site, age and population sub-structure based on the first eigenvector from EigenStrat), followed by the aggregation of the gene-level p-values using the Gamma method with a soft truncation threshold of 0.15. Empirical p-values were determined using permutation methods. Of the 2,573 GSs assessed, 30 GSs had a p-value < 0.01. The top GSs were related to: mismatch repair (p = 3.0E-4), platelet formation (p=0.001), leukocyte adhesive activation (p=0.002), antigen processing and presentation of endogenous antigens (p = 0.002) or peptide antigens (p = 0.002), platinum pathway (p = 0.003), aging and lifespan (p = 0.004, p = 0.007), immune system development (p = 0.004) and somatic diversification (p=0.007). These results illustrate the usefulness of GSA for the development of novel hypotheses that can be followed-up with additional clinical or functional studies. Moreover, application of GSA to survival from EOC allowed the detection of significant GSs (and the corresponding genes/SNPs within these GSs) that impact OS that were not detected by assessing each SNP individually, where the smallest p-value from single SNP analysis of the GWAS for OS was 1.3E-05. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2738. doi:10.1158/1538-7445.AM2011-2738

Abstract The etiology of ovarian cancer is poorly understood but there is clearly a heritable component. Efforts to identify susceptibility alleles rarely consider interactions among alleles or their joint effects because it quickly becomes computationally intractable. In this study, we sought to identify multi-SNP effects jointly with a pathway-based analysis (GSEA-SNP) of 1,952 EOC cases and 2,042 frequency-matched controls genotyped with the Illumina 610K array. All subjects were self-reported non-Hispanic non-Jewish Caucasians, with SNP and sample call rates > 95%. Subjects with ambiguous gender, unresolved identical genotypes and < 80% European ancestry were excluded. SNPs with MAF < 1% were excluded. Missing genotypes were inferred using Mach based on the HapMap CEU population. SNPs not within introns were annotated to genes within 100 bp. We retrieved the following databases of gene sets (GSs) from a compiled database, MsigDB: human chromosome and cytogenetic band, chemical and genetic perturbations, canonical pathways, microRNA binding targets, transcription factor targets (TFT), cancer gene neighborhood (CGN), Cancer modules and Gene Ontology. The GSEA-SNP approach calculates and rank orders the trend statistic for association between each SNP and EOC risk. The Enrichment Score (ES) estimates the overrepresentation of top-ranked SNPs for each GS; the statistical significance was estimated using 10,000 permutations. The ES was normalized according to the size of GS to yield Normalized Enrichment Score (NES). The false discovery (FDR) rate was estimated using NES to adjust for multiple hypothesis testing. A total of 5181 gene-sets were included in the analysis. When controlling the FDR at 15%, 14 of the GSs were highly enriched with association signals, including two chromosomal regions, 8q13 (p = 0.0055, FDR = 0.15) and 6p24 (p = 0.0012, FDR = 0.08). BIOCARTA_LYM_PATHWAY, a pathway related to cell adhesion and diapedesis of lymphocytes, was also significant (p = 0.0002, FDR = 0.12). A TFT GS, composed of genes with promoter regions around transcription start sites containing the motif GGCNRNWCTTYS, was associated with risk (p = 0.0004, FDR = 0.08). Currently, no known transcription factors bind to this computationally predicted motif. Molecular function of double stranded RNA binding was also enriched (p = 0.005, FDR = 0.10). The remaining enriched sets were CGN sets, for which the neighborhoods around the cancer genes were originally defined using correlation of gene expression from 4 large data sets of various cancer types. The enriched CGN included: CD48 (p = 0.011), CD53 (p = 0.009), CD97 (p = 0.011), INPP5D (p = 0.010), PTPN6 (p = 0.008), VAV1 (p = 0.011), ITGAL (p = 0.012), PTPRC (p = 0.012), and STAT6 (p = 0.010). In summary, these analyses detected biologically plausible GSs related to etiology of EOC, highlighting SNPs in core enrichment groups that were not identified using individual SNP tests. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4729. doi:10.1158/1538-7445.AM2011-4729

Abstract Background: Genome-wide association studies (GWAS) for epithelial ovarian cancer (EOC), the most lethal gynecologic malignancy, have identified novel susceptibility loci. GWAS for survival after EOC have had more limited success. The association of each single-nucleotide polymorphism (SNP) individually may not be well suited to detect small effects of multiple SNPs, such as those operating within the same biologic pathway. Gene set analysis (GSA) overcomes this limitation by assessing overall evidence for association of a phenotype with all measured variation in a set of genes. Methods: To determine gene sets associated with EOC overall survival, we conducted GSA using data from two large GWAS (N cases = 2,813, N deaths = 1,116), with a novel Principal Component-Gamma GSA method. Analysis was completed for all cases and then separately for high-grade serous histologic subtype. Results: Analysis of the high-grade serous subjects resulted in 43 gene sets with P < 0.005 (1.7%); of these, 21 gene sets had P < 0.10 in both GWAS, including intracellular signaling pathway (P = 7.3 × 10−5) and macrolide binding (P = 6.2 × 10−4) gene sets. The top gene sets in analysis of all cases were meiotic mismatch repair (P = 6.3 × 10−4) and macrolide binding (P = 1.0 × 10−3). Of 18 gene sets with P < 0.005 (0.7%), eight had P < 0.10 in both GWAS. Conclusion: This research detected novel gene sets associated with EOC survival. Impact: Novel gene sets associated with EOC survival might lead to new insights and avenues for development of novel therapies for EOC and pharmacogenomic studies. Cancer Epidemiol Biomarkers Prev; 21(3); 529–36. ©2012 AACR.

Abstract Background: Single nucleotide polymorphisms (SNP) in microRNA-related genes have been associated with epithelial ovarian cancer (EOC) risk in two reports, yet associated alleles may be inconsistent across studies. Methods: We conducted a pooled analysis of previously identified SNPs by combining genotype data from 3,973 invasive EOC cases and 3,276 controls from the Ovarian Cancer Association Consortium. We also conducted imputation to obtain dense coverage of genes and comparable genotype data for all studies. In total, 226 SNPs within 15 kb of 4 miRNA biogenesis genes (DDX20, DROSHA, GEMIN4, and XPO5) and 23 SNPs located within putative miRNA binding sites of 6 genes (CAV1, COL18A1, E2F2, IL1R1, KRAS, and UGT2A3) were genotyped or imputed and analyzed in the entire dataset. Results: After adjustment for European ancestry, no overall association was observed between any of the analyzed SNPs and EOC risk. Conclusions: Common variants in these evaluated genes do not seem to be strongly associated with EOC risk. Impact: This analysis suggests earlier associations between EOC risk and SNPs in these genes may have been chance findings, possibly confounded by population admixture. To more adequately evaluate the relationship between genetic variants and cancer risk, large sample sizes are needed, adjustment for population stratification should be carried out, and use of imputed SNP data should be considered. Cancer Epidemiol Biomarkers Prev; 20(8); 1793–7. ©2011 AACR.