Pharoah, Paul D.P.

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 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.

Abstract Our understanding of ovarian cancer is complicated by disease heterogeneity. There are five major histological types, each with alterations in different pathways and distinct clinical outcomes. Even within these histological types there is clinical and molecular heterogeneity. The Ovarian Tumor Tissue Analysis (OTTA) consortium was established to validate prognostic markers for ovarian cancer in a large population of patients to allow stratification by histological type and molecular subtype. OTTA is currently a collaboration among 38 studies and has tissue microarrays (TMAs) from over 8,000 tumors available for immunohistochemical (IHC) analysis. In addition formalin fixed paraffin embedded (FFPE) tissue on slides or cores are available from the majority of OTTA studies for DNA and RNA analysis. Approximatley 60% of the cases are part of the Ovarian Cancer Association Consortium (OCAC) and have genotype data on over 200,000 single nucleotide polymorphisms and extensive epidemiological data. We recently performed IHC analysis of 12 markers using centralised staining and scoring to reduce heterogeneity and improve power to validate biomarkers. We showed that estrogen receptor and progesterone receptor were prognostic markers for endometrioid and high-grade serous carcinomas by performing the first robust subtype-specific analyses of these biomarkers in nearly 3000 patients. In contrast, FOLR1 expression was not associated with survival in 1507 high-grade serous carcinomas. We have shown that FFPE material from OTTA is suitable for RNA expression analysis on high through-put platforms such as the NanoString GX system. Expression analysis of 50 candidate genes in 244 high grade serous ovarian cancer cases has validated prognostic markers identified by The Cancer Genome Atlas (TCGA) project and investigated a series of novel candidate genes. IHC and RNA expression profiling from formalin fixed paraffin embedded (FFPE) tumor tissue is being used to better subclassify the ovarian tumors for further analysis. We would welcome groups with collections of ovarian tumor samples and corrsponding clinical data to join OTTA and participate in ongoing collaborative projects. Citation Format: Susan J. Ramus, Martin Köbel, Weiva Sieh, Michael S. Anglesio, Joshua Millstein, David D. Bowtell, James D. Brenton, Estrid Høgdall, Paul DP Pharoah, Ellen L. Goode, David G. Huntsman. The ovarian tumor tissue analysis (OTTA) consortium. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: From Concept to Clinic; Sep 18-21, 2013; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2013;19(19 Suppl):Abstract nr A27.

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 Survival in epithelial ovarian cancer (EOC) is influenced by the host immune response, yet the key genetic determinants of inflammation and immunity that affect prognosis are not known. The nuclear factor-κB (NF-κB) transcription factor family plays an important role in many immune and inflammatory responses, including the response to cancer. We studied common inherited variation in 210 genes in the NF-κB family in 10,084 patients with invasive EOC (5,248 high-grade serous, 1,452 endometrioid, 795 clear cell, and 661 mucinous) from the Ovarian Cancer Association Consortium. Associations between genotype and overall survival were assessed using Cox regression for all patients and by major histology, adjusting for known prognostic factors and correcting for multiple testing (threshold for statistical significance, P < 2.5 × 10−5). Results were statistically significant when assessed for patients of a single histology. Key associations were with caspase recruitment domain family, member 11 (CARD11) rs41324349 in patients with mucinous EOC [HR, 1.82; 95% confidence interval (CI), 1.41–2.35; P = 4.13 × 10−6] and tumor necrosis factor receptor superfamily, member 13B (TNFRSF13B) rs7501462 in patients with endometrioid EOC (HR, 0.68; 95% CI, 0.56–0.82; P = 2.33 × 10−5). Other associations of note included TNF receptor–associated factor 2 (TRAF2) rs17250239 in patients with high-grade serous EOC (HR, 0.84; 95% CI, 0.77–0.92; P = 6.49 × 10−5) and phospholipase C, gamma 1 (PLCG1) rs11696662 in patients with clear cell EOC (HR, 0.43; 95% CI, 0.26–0.73; P = 4.56 × 10−4). These associations highlight the potential importance of genes associated with host inflammation and immunity in modulating clinical outcomes in distinct EOC histologies. Cancer Epidemiol Biomarkers Prev; 23(7); 1421–7. ©2014 AACR.

Abstract The presence of regulatory T cells (Treg) in solid tumors is known to play a role in patient survival in ovarian cancer and other malignancies. We assessed inherited genetic variations via 749 tag single-nucleotide polymorphisms (SNP) in 25 Treg-associated genes (CD28, CTLA4, FOXP3, IDO1, IL10, IL10RA, IL15, 1L17RA, IL23A, IL23R, IL2RA, IL6, IL6R, IL8, LGALS1, LGALS9, MAP3K8, STAT5A, STAT5B, TGFB1, TGFB2, TGFB3, TGFBR1, TGRBR2, and TGFBR3) in relation to ovarian cancer survival. We analyzed genotype and overall survival in 10,084 women with invasive epithelial ovarian cancer, including 5,248 high-grade serous, 1,452 endometrioid, 795 clear cell, and 661 mucinous carcinoma cases of European descent across 28 studies from the Ovarian Cancer Association Consortium (OCAC). The strongest associations were found for endometrioid carcinoma and IL2RA SNPs rs11256497 [HR, 1.42; 95% confidence interval (CI), 1.22–1.64; P = 5.7 × 10−6], rs791587 (HR, 1.36; 95% CI, 1.17–1.57; P = 6.2 × 10−5), rs2476491 (HR, = 1.40; 95% CI, 1.19–1.64; P = 5.6 × 10−5), and rs10795763 (HR, 1.35; 95% CI, 1.17–1.57; P = 7.9 × 10−5), and for clear cell carcinoma and CTLA4 SNP rs231775 (HR, 0.67; 95% CI, 0.54–0.82; P = 9.3 × 10−5) after adjustment for age, study site, population stratification, stage, grade, and oral contraceptive use. The rs231775 allele associated with improved survival in our study also results in an amino acid change in CTLA4 and previously has been reported to be associated with autoimmune conditions. Thus, we found evidence that SNPs in genes related to Tregs seem to play a role in ovarian cancer survival, particularly in patients with clear cell and endometrioid epithelial ovarian cancer. Cancer Immunol Res; 2(4); 332–40. ©2014 AACR.

ABSTRACTGenes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene‐environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P‐values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci.

Abstract Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70 917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46 450 breast cancer cases and 42 461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P < 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P < 10−4) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P < 10−8. Results from the second analytic approach were consistent with those from the first (P > 10−10). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.

Abstract Background: Ovarian cancer is a leading cause of cancer-related death among women. In an effort to understand contributors to disease outcome, we evaluated single-nucleotide polymorphisms (SNP) previously associated with ovarian cancer recurrence or survival, specifically in angiogenesis, inflammation, mitosis, and drug disposition genes. Methods: Twenty-seven SNPs in VHL, HGF, IL18, PRKACB, ABCB1, CYP2C8, ERCC2, and ERCC1 previously associated with ovarian cancer outcome were genotyped in 10,084 invasive cases from 28 studies from the Ovarian Cancer Association Consortium with over 37,000-observed person-years and 4,478 deaths. Cox proportional hazards models were used to examine the association between candidate SNPs and ovarian cancer recurrence or survival with and without adjustment for key covariates. Results: We observed no association between genotype and ovarian cancer recurrence or survival for any of the SNPs examined. Conclusions: These results refute prior associations between these SNPs and ovarian cancer outcome and underscore the importance of maximally powered genetic association studies. Impact: These variants should not be used in prognostic models. Alternate approaches to uncovering inherited prognostic factors, if they exist, are needed. Cancer Epidemiol Biomarkers Prev; 22(5); 987–. ©2013 AACR.

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.