Objective

The object of this study was to test the hypothesis that BRAF is a low-risk susceptibility gene for low malignant potential (LMP) ovarian cancer. A recent study of the relationship between BRAF polymorphisms and malignant melanoma identified strong linkage disequilibrium across the BRAF gene with one of the three most common haplotypes (haplotype C) having a population attributable risk of approximately 1.6%. We therefore hypothesized that the same BRAF haplotype may confer an increased risk of serous ovarian tumors of low malignant potential.

Methods

We genotyped 383 cases of LMP ovarian cancer, including 234 of serous histology, and 987 controls for seven SNPs, representative of the most common BRAF gene haplotypes, using MALDI-TOF mass spectrometry.

Results

Haplotype information was obtained for 369 LMP ovarian cancer cases and 983 healthy controls. None of the haplotypes were found to be associated with risk of LMP ovarian cancer (OR for haplotype C 0.81, 95% CI = 0.54-1.22), or with the risk of serous LMP ovarian cancer (OR for haplotype C 0.90, 95% CI = 0.56-1.45).

Conclusion

We found no evidence to suggest that BRAF is a low-risk LMP ovarian cancer susceptibility gene.

Background

Previous studies on the association between reproductive factors and ovarian cancer survival are equivocal, possibly due to small sample sizes.

Methods

Using data on 11,175 people diagnosed with primary invasive epithelial ovarian, fallopian tube, or primary peritoneal cancer (ovarian cancer) from 16 studies in the Ovarian Cancer Association Consortium (OCAC), we examined the associations between survival and age at menarche, combined oral contraceptive use, parity, breastfeeding, age at last pregnancy, and menopausal status using Cox proportional hazard models. The models were adjusted for age at diagnosis, race/ethnicity, education level, and OCAC study and stratified on stage and histotype.

Results

During the mean follow-up of 6.34 years (SD = 4.80), 6,418 patients passed away (57.4%). There was no evidence of associations between the reproductive factors and survival among patients with ovarian cancer overall or by histotype.

Conclusions

This study found no association between reproductive factors and survival after an ovarian cancer diagnosis.

Impact

Reproductive factors are well-established risk factors for ovarian cancer, but they are not associated with survival after a diagnosis of ovarian cancer.

Objective

To evaluate the association between hysterectomy and ovarian cancer, and to understand how hormone therapy (HT) use and endometriosis affect this association.

Methods

We conducted a pooled analysis of self-reported data from 11 case-control studies in the Ovarian Cancer Association Consortium (OCAC). Women with (n = 5350) and without ovarian cancer (n = 7544) who never used HT or exclusively used either estrogen-only therapy (ET) or estrogen+progestin therapy (EPT) were included. Risk of invasive epithelial ovarian cancer adjusted for duration of ET and EPT use and stratified on history of endometriosis was determined using odds ratios (ORs) with 95% confidence intervals (CIs).

Results

Overall and among women without endometriosis, there was a positive association between ovarian cancer risk and hysterectomy (OR = 1.19, 95% CI 1.09-1.31 and OR = 1.20, 95% CI 1.09-1.32, respectively), but no association upon adjusting for duration of ET and EPT use (OR = 1.04, 95% CI 0.94-1.16 and OR = 1.06, 95% CI 0.95-1.18, respectively). Among women with a history of endometriosis, there was a slight inverse association between hysterectomy and ovarian cancer risk (OR = 0.93, 95% CI 0.69-1.26), but this association became stronger and statistically significant after adjusting for duration of ET and EPT use (OR = 0.69, 95% CI 0.48-0.99).

Conclusions

The hysterectomy-ovarian cancer association is complex and cannot be understood without considering duration of ET and EPT use and history of endometriosis. Failure to take these exposures into account in prior studies casts doubt on their conclusions. Overall, hysterectomy is not risk-reducing for ovarian cancer, however the inverse association among women with endometriosis warrants further investigation.

Generally, risk stratification models for cancer use effect estimates from risk/protective factor analyses that have not assessed potential interactions between these exposures. We have developed a 4-criterion framework for assessing interactions that includes statistical, qualitative, biological, and practical approaches. We present the application of this framework in an ovarian cancer setting because this is an important step in developing more accurate risk stratification models. Using data from 9 case-control studies in the Ovarian Cancer Association Consortium, we conducted a comprehensive analysis of interactions among 15 unequivocal risk and protective factors for ovarian cancer (including 14 non-genetic factors and a 36-variant polygenic score) with age and menopausal status. Pairwise interactions between the risk/protective factors were also assessed. We found that menopausal status modifies the association among endometriosis, first-degree family history of ovarian cancer, breastfeeding, and depot-medroxyprogesterone acetate use and disease risk, highlighting the importance of understanding multiplicative interactions when developing risk prediction models.

Background

Prediction of contralateral breast cancer (CBC) risk is challenging due to moderate performances of the known risk factors. We aimed to improve our previous risk prediction model (PredictCBC) by updated follow-up and including additional risk factors.

Methods

We included data from 207,510 invasive breast cancer patients participating in 23 studies. In total, 8225 CBC events occurred over a median follow-up of 10.2 years. In addition to the previously included risk factors, PredictCBC-2.0 included CHEK2 c.1100delC, a 313 variant polygenic risk score (PRS-313), body mass index (BMI), and parity. Fine and Gray regression was used to fit the model. Calibration and a time-dependent area under the curve (AUC) at 5 and 10 years were assessed to determine the performance of the models. Decision curve analysis was performed to evaluate the net benefit of PredictCBC-2.0 and previous PredictCBC models.

Results

The discrimination of PredictCBC-2.0 at 10 years was higher than PredictCBC with an AUC of 0.65 (95% prediction intervals (PI) 0.56-0.74) versus 0.63 (95%PI 0.54-0.71). PredictCBC-2.0 was well calibrated with an observed/expected ratio at 10 years of 0.92 (95%PI 0.34-2.54). Decision curve analysis for contralateral preventive mastectomy (CPM) showed the potential clinical utility of PredictCBC-2.0 between thresholds of 4 and 12% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers.

Conclusions

Additional genetic information beyond BRCA1/2 germline mutations improved CBC risk prediction and might help tailor clinical decision-making toward CPM or alternative preventive strategies. Identifying patients who benefit from CPM, especially in the general breast cancer population, remains challenging.

There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium.

Menopausal hormone therapy (MHT) is associated with an elevated risk of breast cancer in postmenopausal women. To identify genetic loci that modify breast cancer risk related to MHT use in postmenopausal women, we conducted a two-stage genome-wide association study (GWAS) with replication. In stage I, we performed a case-only GWAS in 731 invasive breast cancer cases from the German case-control study Mammary Carcinoma Risk Factor Investigation (MARIE). The 1,200 single nucleotide polymorphisms (SNPs) showing the lowest P values for interaction with current MHT use (within 6 months prior to breast cancer diagnosis), were carried forward to stage II, involving pooled case-control analyses including additional MARIE subjects (1,375 cases, 1,974 controls) as well as 795 cases and 764 controls of a Swedish case-control study. A joint P value was calculated for a combined analysis of stages I and II. Replication of the most significant interaction of the combined stage I and II was performed using 5,795 cases and 5,390 controls from nine studies of the Breast Cancer Association Consortium (BCAC). The combined stage I and II yielded five SNPs on chromosomes 2, 7, and 18 with joint P values <6 × 10(-6) for effect modification of current MHT use. The most significant interaction was observed for rs6707272 (P = 3 × 10(-7)) on chromosome 2 but was not replicated in the BCAC studies (P = 0.21). The potentially modifying SNPs are in strong linkage disequilibrium with SNPs in TRIP12 and DNER on chromosome 2 and SETBP1 on chromosome 18, previously linked to carcinogenesis. However, none of the interaction effects reached genome-wide significance. The inability to replicate the top SNP × MHT interaction may be due to limited power of the replication phase. Our study, however, suggests that there are unlikely to be SNPs that interact strongly enough with MHT use to be clinically significant in European women.

Background

Parity is associated with decreased risk of invasive ovarian cancer; however, the relationship between incomplete pregnancies and invasive ovarian cancer risk is unclear. This relationship was examined using 15 case-control studies from the Ovarian Cancer Association Consortium (OCAC). Histotype-specific associations, which have not been examined previously with large sample sizes, were also evaluated.

Methods

A pooled analysis of 10 470 invasive epithelial ovarian cancer cases and 16 942 controls was conducted. Odds ratios (ORs) and 95% confidence intervals (CIs) for the association between incomplete pregnancies and invasive epithelial ovarian cancer were estimated using logistic regression. All models were conditioned on OCAC study, race and ethnicity, age, and education level and adjusted for number of complete pregnancies, oral contraceptive use, and history of breastfeeding. The same approach was used for histotype-specific analyses.

Results

Ever having an incomplete pregnancy was associated with a 16% reduction in ovarian cancer risk (OR = 0.84, 95% CI = 0.79 to 0.89). There was a trend of decreasing risk with increasing number of incomplete pregnancies (2-sided Ptrend < .001). An inverse association was observed for all major histotypes; it was strongest for clear cell ovarian cancer.

Conclusions

Incomplete pregnancies are associated with a reduced risk of invasive epithelial ovarian cancer. Pregnancy, including incomplete pregnancy, was associated with a greater reduction in risk of clear cell ovarian cancer, but the result was broadly consistent across histotypes. Future work should focus on understanding the mechanisms underlying this reduced risk.

Because both ovarian and breast cancer are hormone-related and are known to have some predisposition genes in common, we evaluated 11 of the most significant hits (six with confirmed associations with breast cancer) from the breast cancer genome-wide association study for association with invasive ovarian cancer. Eleven SNPs were initially genotyped in 2927 invasive ovarian cancer cases and 4143 controls from six ovarian cancer case-control studies. Genotype frequencies in cases and controls were compared using a likelihood ratio test in a logistic regression model stratified by study. Initially, three SNPs (rs2107425 in MRPL23, rs7313833 in PTHLH, rs3803662 in TNRC9) were weakly associated with ovarian cancer risk and one SNP (rs4954956 in NXPH2) was associated with serous ovarian cancer in non-Hispanic white subjects (P-trend < 0.1). These four SNPs were then genotyped in an additional 4060 cases and 6308 controls from eight independent studies. Only rs4954956 was significantly associated with ovarian cancer risk both in the replication study and in combined analyses. This association was stronger for the serous histological subtype [per minor allele odds ratio (OR) 1.07 95% CI 1.01-1.13, P-trend = 0.02 for all types of ovarian cancer and OR 1.14 95% CI 1.07-1.22, P-trend = 0.00017 for serous ovarian cancer]. In conclusion, we found that rs4954956 was associated with increased ovarian cancer risk, particularly for serous ovarian cancer. However, none of the six confirmed breast cancer susceptibility variants we tested was associated with ovarian cancer risk. Further work will be needed to identify the causal variant associated with rs4954956 or elucidate its function.

Alterations in stromal tissue components can inhibit or promote epithelial tumorigenesis. Decorin (DCN) and lumican (LUM) show reduced stromal expression in serous epithelial ovarian cancer (sEOC). We hypothesized that common variants in these genes associate with risk. Associations with sEOC among Caucasians were estimated with odds ratios (OR) among 397 cases and 920 controls in two U.S.-based studies (discovery set), 436 cases and 1,098 controls in Australia (replication set 1) and a consortium of 15 studies comprising 1,668 cases and 4,249 controls (replication set 2). The discovery set and replication set 1 (833 cases and 2,013 controls) showed statistically homogeneous (P_{heterogeneity}≥0.48) decreased risks of sEOC at four variants: DCN rs3138165, rs13312816 and rs516115, and LUM rs17018765 (OR = 0.6 to 0.9; P_trend = 0.001 to 0.03). Results from replication set 2 were statistically homogeneous (P_{heterogeneity}≥0.13) and associated with increased risks at DCN rs3138165 and rs13312816, and LUM rs17018765: all ORs = 1.2; P_trend≤0.02. The ORs at the four variants were statistically heterogeneous across all 18 studies (P_{heterogeneity}≤0.03), which precluded combining. In post-hoc analyses, interactions were observed between each variant and recruitment period (P_interaction≤0.003), age at diagnosis (P_interaction = 0.04), and year of diagnosis (P_interaction = 0.05) in the five studies with available information (1,044 cases, 2,469 controls). We conclude that variants in DCN and LUM are not directly associated with sEOC, and that confirmation of possible effect modification of the variants by non-genetic factors is required.