Citations

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 Purpose: Chemotherapy resistance remains a major challenge in the treatment of ovarian cancer. We hypothesize that germline polymorphisms might be associated with clinical outcome. Experimental Design: We analyzed approximately 2.8 million genotyped and imputed SNPs from the iCOGS experiment for progression-free survival (PFS) and overall survival (OS) in 2,901 European epithelial ovarian cancer (EOC) patients who underwent first-line treatment of cytoreductive surgery and chemotherapy regardless of regimen, and in a subset of 1,098 patients treated with ≥4 cycles of paclitaxel and carboplatin at standard doses. We evaluated the top SNPs in 4,434 EOC patients, including patients from The Cancer Genome Atlas. In addition, we conducted pathway analysis of all intragenic SNPs and tested their association with PFS and OS using gene set enrichment analysis. Results: Five SNPs were significantly associated (P ≤ 1.0 × 10−5) with poorer outcomes in at least one of the four analyses, three of which, rs4910232 (11p15.3), rs2549714 (16q23), and rs6674079 (1q22), were located in long noncoding RNAs (lncRNAs) RP11-179A10.1, RP11-314O13.1, and RP11-284F21.8, respectively (P ≤ 7.1 × 10−6). ENCODE ChIP-seq data at 1q22 for normal ovary show evidence of histone modification around RP11-284F21.8, and rs6674079 is perfectly correlated with another SNP within the super-enhancer MEF2D, expression levels of which were reportedly associated with prognosis in another solid tumor. YAP1- and WWTR1 (TAZ)-stimulated gene expression and high-density lipoprotein (HDL)-mediated lipid transport pathways were associated with PFS and OS, respectively, in the cohort who had standard chemotherapy (pGSEA ≤6 × 10−3). Conclusions: We have identified SNPs in three lncRNAs that might be important targets for novel EOC therapies. Clin Cancer Res; 21(23); 5264–76. ©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 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 Background. Transmembrane transport (GO:0055085) is the process whereby a solute/hormone/ion/iron is transported from one side of a membrane to the other. Disruption of these processes leads to defects in homeostasis which contributes to cancer risk. We hypothesized that germline single nucleotide polymorphisms (SNPs) in the cellular transport genes are associated with EOC risk and histopathology subtype. Methods. We genotyped 305 SNPs from 120 cellular transport related genes in 14,525 cases and 23,448 controls of European ancestry, 387 African, and 2,388 Asian ancestries from 43 studies in the Ovarian Cancer Association Consortium (OCAC). A custom Illumina iSelect designed for the Collaborative Oncological Gene-environment Study (COGS) was used. For women of European ancestry, both invasive cancers combined and the four main histological subtypes (serous (n=8,369), mucinous (n=943), endometroid (n=2,067) and clear cell (n=1,024) carcinoma) were analyzed, while for women of African and Asian ancestry only the serous subtype was analyzed adjusting for study site and first 5 principal components. Odds ratios and 95% confidence intervals were calculated using unconditional logistic regression. We fitted a log-additive genetic model. Results. In women of European ancestry, the strongest evidence of an association for all invasive EOCs was the iron transport gene, HEPH rs17216603 (OR=0.85, 95%CI=0.78-0.93, P=2.8x10−4), which was also the most significant association for serous histological subtype (OR=0.81, 95%CI=0.73-0.91, P=2.0x10−4). For endometrioid EOC, the strongest association was observed in the glucuronidation gene, UGT1A5 rs11563251 (OR=0.82, 95%CI=0.73-0.92, P=6.6x10−4). For clear cell and mucinous EOC, the thyroid hormone transport protein, SERPINA7 rs1804495 showed the strongest associations (OR=1.06, 95%CI=1.06-1.38, P=0.0041) and (OR=0.85, 95%CI=0.73-0.98, P=0.0407), respectively. For women of African ancestry, the strongest association for serous EOC was the glutathione conjugation gene, MGST rs6488840 (OR=0.55, 95%CI=0.37-0.82, P=0.0035). This SNP was not significant in women of European or Asian ancestry. In women of Asian ancestry, the HEPH rs17216603 (OR=1.45, 95%CI=1.15-1.83, P=0.0019) demonstrated the strongest association, although the directionality of risk was reversed compared to European women. Conclusions. Our results suggest that variation in transmembrane transport genes may influence EOC risk and histopathologic subtype in women of European, African and Asian ancestries, highlighting the differences in the disease etiology across populations. Additional epidemiological and functional studies are warranted to elucidate translational and clinical utility of these associations. Citation Format: Ganna Chornokur, Jonathan Tyrer, Hui-Yi Lin, Gang Han, Xiaotao Qu, Chen Zhihua, Ya-Yu Tsai, Ellen L. Goode, Julie M. Cunningham, Edwin Iversen, Susan J. Ramus, Andrew Berchuk, Joellen M. Schildkraut, Alvaro Monteiro, Simon A. Gayther, Steven A. Narod, Paul Pharoah, Thomas A. Sellers, Catherine M. Phelan. Variation in transmembrane transport genes influence epithelial ovarian cancer risk and histopathologic subtype. [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 3644. doi:10.1158/1538-7445.AM2013-3644

Abstract Background: Circadian rhythms of biological processes are regulated by endogenous clock genes and clock-controlled genes. Aberrant expression of circadian clock genes may have important consequences on the transactivation of downstream targets that control the cell cycle and cellular proliferation potentially promoting carcinogenesis. Animal models indicate that several circadian rhythm genes are expressed in the ovaries, where they influence and are influenced by estrous cycles. The goal of the current study was to examine the association of circadian gene variants and epithelial ovarian cancer (EOC) risk. Methods: Thirty-one SNPs from five circadian genes (i.e., ARNTL, CRY2, KLF10, NPAS2, PER3, TIMELESS) were genotyped in 14,736 cases and 23,448 control women of European ancestry from 43 studies in the Ovarian Cancer Association Consortium (OCAC), on a custom Illumina iSelect designed for the Collaborative Oncological Gene-Environment Study (COGS). 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, SNP analyses were conducted using unconditional logistic regression under a log-additive model. All analyses were adjusted for study site and population substructure. Results: Eleven SNPs were found to be associated with ovarian cancer risk. The SNPs most associated with serous cancer risk were KLF10 rs2513928 (OR=.95 p=6.1x10−3), rs2513927 (OR=1.05 p=6.1x10−3), rs2511703 (OR=1.05 p=9.8x10−3), rs3191333 (OR=1.05, p=1.5x10−2) and NPAS2 rs13012930 (OR=.95, p=3.5x10−2). Endometroid cancer risk was significantly associated with ARNTL SNPs rs10732458 (OR=1.3, p=1.0x10−2) and rs7117836 (OR=1.2, p=4.6x10−2), while clear cell cancer risk was associated with ARNTL rs1562438 (OR=.88, p=1.5x10−2), rs1026071 (OR=.89, p=1.8x10−2), and rs3816360 (OR=.91, p=4.8x10−2) and KLF10 rs2388232 (OR=1.1, p=3.3x10−2). No variants were significantly associated with mucinous cancer risk. Four SNPs in KLF10 were associated with cancer invasiveness; they were rs2513928 (OR=.95, p=1.8x10−3), rs3191333 (OR=1.04, p=1.4x10−2), rs2513927 (OR=1.04, p=1.9x10−2), and rs2511703 (OR=1.03, p=2.8x10−2). Conclusions: Data from the current study suggest that polymorphisms in circadian genes ARNTL, KLF10, and NPAS2 are significantly associated with ovarian cancer histopathologic subtypes and invasiveness. These findings merit further investigation and replication. Funding: R01 CA149429 Citation Format: Heather Jim, Jonathan Tyrer, Hui-Yi Lin, Gang Han, Xiaotao Qu, Ellen L. Goode, Zhihua Chen, Ya-Yu Tsai, Julie M. Cunningham, Edward Iversen, Susan Ramus, Andrew Berchuck, Joellen Schildkraut, Alvaro Monteiro, Simon Gayther, Steven A. Narod, Thomas A. Sellers, Paul Pharoah, Catherine M. Phelan. Variation in circadian rhythm genes influence epithelial ovarian cancer risk and invasiveness. [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 4850. doi:10.1158/1538-7445.AM2013-4850 Note: This abstract was not presented at the AACR Annual Meeting 2013 because the presenter was unable to attend.

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.

Abstract Background: There are several well-established environmental risk factors for ovarian cancer, and recent genome-wide association studies have also identified six variants that influence disease risk. However, the interplay between such risk factors and susceptibility loci has not been studied. Methods: Data from 14 ovarian cancer case–control studies were pooled, and stratified analyses by each environmental risk factor with tests for heterogeneity were conducted to determine the presence of interactions for all histologic subtypes. A genetic “risk score” was created to consider the effects of all six variants simultaneously. A multivariate model was fit to examine the association between all environmental risk factors and genetic risk score on ovarian cancer risk. Results: Among 7,374 controls and 5,566 cases, there was no statistical evidence of interaction between the six SNPs or genetic risk score and the environmental risk factors on ovarian cancer risk. In a main effects model, women in the highest genetic risk score quartile had a 65% increased risk of ovarian cancer compared with women in the lowest [95% confidence interval (CI), 1.48–1.84]. Analyses by histologic subtype yielded risk differences across subtype for endometriosis (Phet < 0.001), parity (Phet < 0.01), and tubal ligation (Phet = 0.041). Conclusions: The lack of interactions suggests that a multiplicative model is the best fit for these data. Under such a model, we provide a robust estimate of the effect of each risk factor that sets the stage for absolute risk prediction modeling that considers both environmental and genetic risk factors. Further research into the observed differences in risk across histologic subtype is warranted. Cancer Epidemiol Biomarkers Prev; 22(5); 880–90. ©2013 AACR.

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