Berg, David J. Van Den

Abstract Background: Many epithelial ovarian cancer (EOC) risk factors relate to hormone exposure and elevated estrogen levels are associated with obesity in postmenopausal women. Therefore, we hypothesized that gene–environment interactions related to hormone-related risk factors could differ between obese and non-obese women. Methods: We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy, and estrogen use) and assessed whether these interactions differed between obese and non-obese women. Interactions were assessed using logistic regression models and data from 14 case–control studies (6,247 cases; 10,379 controls). Histotype-specific analyses were also completed. Results: SNPs in the following candidate genes showed notable interaction: IGF1R (rs41497346, estrogen plus progesterone hormone therapy, histology = all, P = 4.9 × 10−6) and ESR1 (rs12661437, endometriosis, histology = all, P = 1.5 × 10−5). The most notable obesity–gene–hormone risk factor interaction was within INSR (rs113759408, parity, histology = endometrioid, P = 8.8 × 10−6). Conclusions: We have demonstrated the feasibility of assessing multifactor interactions in large genetic epidemiology studies. Follow-up studies are necessary to assess the robustness of our findings for ESR1, CYP11A1, IGF1R, CYP11B1, INSR, and IGFBP2. Future work is needed to develop powerful statistical methods able to detect these complex interactions. Impact: Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC susceptibility. Cancer Epidemiol Biomarkers Prev; 25(5); 780–90. ©2016 AACR.

Abstract Aberrant glycosylation is a well-described hallmark of cancer. In a previous ovarian cancer case control study that examined polymorphisms in 26 glycosylation-associated genes, we found strong statistical evidence (P = 0.00017) that women who inherited two copies of a single-nucleotide polymorphism in the UDP-N-acetylgalactosamine:polypeptide N-acetylgalactosaminyltransferase, GALNT1, had decreased ovarian cancer risk. The current study attempted to replicate this observation. The GALNT1 single-nucleotide polymorphism rs17647532 was genotyped in 6,965 cases and 8,377 controls from 14 studies forming the Ovarian Cancer Association Consortium. The fixed effects estimate per rs17647532 allele was null (odds ratio, 0.99; 95% confidence interval, 0.92-1.07). When a recessive model was fit, the results were unchanged. Test for hetero geneity of the odds ratios revealed consistency across the 14 replication sites but significant differences compared with the original study population (P = 0.03). This study underscores the need for replication of putative findings in genetic association studies. Cancer Epidemiol Biomarkers Prev; 19(2); 600–4

Abstract We genotyped 13 single nucleotide polymorphisms (SNPs) in the estrogen receptor alpha gene (ESR1) region in three population-based case-control studies of epithelial ovarian cancer conducted in the United States, comprising a total of 1,128 and 1,866 non-Hispanic white invasive cases and controls, respectively. A SNP 19 kb downstream of ESR1 (rs2295190, G-to-T change) was associated with invasive ovarian cancer risk, with a per-T-allele odds ratio (OR) of 1.24 [95% confidence interval (CI), 1.06-1.44, P = 0.006]. rs2295190 is a nonsynonymous coding SNP in a neighboring gene called spectrin repeat containing, nuclear envelope 1 (SYNE1), which is involved in nuclear organization and structural integrity, function of the Golgi apparatus, and cytokinesis. An isoform encoded by SYNE1 has been reported to be downregulated in ovarian and other cancers. rs2295190 was genotyped in an additional 12 studies through the Ovarian Cancer Association Consortium, with 5,279 invasive epithelial cases and 7,450 controls. The per-T-allele OR for this 12-study set was 1.09 (95% CI, 1.02-1.17; P = 0.017). Results for the serous subtype in the 15 combined studies were similar to those overall (n = 3,545; OR, 1.09; 95% CI, 1.01-1.18; P = 0.025), and our findings were strongest for the mucinous subtype (n = 447; OR, 1.32; 95% CI, 1.11-1.58; P = 0.002). No association was observed for the endometrioid subtype. In an additional analysis of 1,459 borderline ovarian cancer cases and 7,370 controls, rs2295190 was not associated with risk. These data provide suggestive evidence that the rs2295190 T allele, or another allele in linkage disequilibrium with it, may be associated with increased risk of invasive ovarian cancer. Cancer Epidemiol Biomarkers Prev; 19(1); 244–50