Paul Pharoah and colleagues report the results of a large genome-wide association study of ovarian cancer. They identify new susceptibility loci for different epithelial ovarian cancer histotypes and use integrated analyses of genes and regulatory features at each locus to predict candidate susceptibility genes, including OBFC1. To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC.

Purpose: An understanding of the etiologic heterogeneity of ovarian cancer is important for improving prevention, early detection, and therapeutic approaches. We evaluated 14 hormonal, reproductive, and lifestyle factors by histologic subtype in the Ovarian Cancer Cohort Consortium (OC3). Patients and Methods: Among 1.3 million women from 21 studies, 5,584 invasive epithelial ovarian cancers were identified (3,378 serous, 606 endometrioid, 331 mucinous, 269 clear cell, 1,000 other). By using competing-risks Cox proportional hazards regression stratified by study and birth year and adjusted for age, parity, and oral contraceptive use, we assessed associations for all invasive cancers by histology. Heterogeneity was evaluated by likelihood ratio test. Results: Most risk factors exhibited significant heterogeneity by histology. Higher parity was most strongly associated with endometrioid (relative risk [RR] per birth, 0.78; 95% CI, 0.74 to 0.83) and clear cell (RR, 0.68; 95% CI, 0.61 to 0.76) carcinomas (P value for heterogeneity [P-het] < .001). Similarly, age at menopause, endometriosis, and tubal ligation were only associated with endometrioid and clear cell tumors (P-het ≤ .01). Family history of breast cancer (P-het = .008) had modest heterogeneity. Smoking was associated with an increased risk of mucinous (RR per 20 pack-years, 1.26; 95% CI, 1.08 to 1.46) but a decreased risk of clear cell (RR, 0.72; 95% CI, 0.55 to 0.94) tumors (P-het = .004). Unsupervised clustering by risk factors separated endometrioid, clear cell, and low-grade serous carcinomas from high-grade serous and mucinous carcinomas. Conclusion: The heterogeneous associations of risk factors with ovarian cancer subtypes emphasize the importance of conducting etiologic studies by ovarian cancer subtypes. Most established risk factors were more strongly associated with nonserous carcinomas, which demonstrate challenges for risk prediction of serous cancers, the most fatal subtype.

Associations between circulating concentrations of oestrogens, progesterone, and androgens with breast cancer and related risk factors in premenopausal women are not well understood. We aimed to characterise these associations with a pooled analysis of data from seven studies. Individual participant data for prediagnostic sex hormone and sex hormone-binding globulin (SHBG) concentrations were contributed from seven prospective studies. We restricted analyses to women who were premenopausal and younger than 50 years at blood collection, and to women with breast cancer diagnosed before age 50 years. We estimated odds ratios (ORs) with 95% CIs for breast cancer associated with hormone concentrations by conditional logistic regression in cases and controls matched for age, date of blood collection, and day of cycle, with stratification by study and further adjustment for cycle phase. We examined associations of hormones with risk factors for breast cancer in control women by comparing geometric mean hormone concentrations in categories of these risk factors, adjusted for study, age, phase of menstrual cycle, and body-mass index (BMI). All statistical tests were two-sided. We included data for up to 767 women with breast cancer and 1699 controls in the risk analyses. Breast cancer risk was associated with a doubling in concentrations of oestradiol (OR 1·19, 95% CI 1·06-1·35), calculated free oestradiol (1·17, 1·03-1·33), oestrone (1·27, 1·05-1·54), androstenedione (1·30, 1·10-1·55), dehydroepiandrosterone sulphate (1·17, 1·04-1·32), testosterone (1·18, 1·03-1·35), and calculated free testosterone (1·08, 0·97-1·21). Breast cancer risk was not associated with luteal phase progesterone (doubling in concentration OR 1·00, 95% CI 0·92-1·09), and adjustment for other factors had little effect on any of these ORs. Cross-sectional analyses in control women showed several associations of sex hormones with breast cancer risk factors. Circulating oestrogens and androgens are positively associated with the risk for breast cancer in premenopausal women.

Evidence suggests that the hormonal milieu of pregnancy is an important determinant of subsequent cancer and other chronic diseases in both the mother and the offspring. Many of the existing maternity and birth cohorts include specimens drawn only once during pregnancy. How well a single blood specimen collected during a pregnancy characterizes exposure to these hormones throughout gestation, and also in subsequent pregnancies, is not well understood. We used serial serum samples from 71 pregnant women (25 primiparous, 25 multiparous, and 21 with two consecutive pregnancies) with natural, complication-free pregnancies and a healthy offspring at term who participated in a population-based screening trial for congenital infections in Finland between January 1st, 1988 and June 30, 1989 and provided a blood sample in each trimester. Hormone levels were more strongly correlated between consecutive trimesters of a pregnancy than between the 1st and 3rd trimester (e.g., estradiol, rT1 vs. T2 = 0.51 and rT2 vs. T3 = 0.60, p < 0.01; rT1 vs. T3 = 0.32, p < 0.05). Concentrations of sRANKL remained stable throughout gestation, whereas estradiol, estrone, progesterone, testosterone, prolactin, and osteoprotegerin increased throughout pregnancy. First trimester hormone concentrations explained less of the variation in the third trimester on their own than second trimester hormone levels (e.g. estradiol R2 T1 = 16 % and R2 T2 = 42 %). Addition of maternal (e.g., smoking) and/or child characteristics (e.g., sex) improved the accuracy of the 3rd trimester estimates for some of the hormones. One hormone measurement in early pregnancy, in conjunction with maternal and fetal characteristics, permits estimation of 3rd trimester hormone concentrations. Therefore, single hormone measurements available from maternity cohorts are suitable to quantify hormone exposure during pregnancy. To our knowledge, we provide the first data on correlations between hormone concentrations both across trimesters of a single pregnancy, as well as between two subsequent pregnancies.

In addition to HPV, high parity and hormonal contraceptives have been associated with cervical cancer (CC). However, most of the evidence comes from retrospective case-control studies. The aim of this study is to prospectively evaluate associations between hormonal factors and risk of developing cervical intraepithelial neoplasia grade 3 (CIN3)/carcinoma in situ (CIS) and invasive cervical cancer (ICC). We followed a cohort of 308,036 women recruited in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study. At enrollment, participants completed a questionnaire and provided serum. After a 9-year median follow-up, 261 ICC and 804 CIN3/CIS cases were reported. In a nested case-control study, the sera from 609 cases and 1,218 matched controls were tested for L1 antibodies against HPV types 11,16,18,31,33,35,45,52,58, and antibodies against Chlamydia trachomatis and Human herpesvirus 2. Multivariate analyses were performed to estimate hazard ratios (HR), odds ratios (OR) and corresponding 95% confidence intervals (CI). The cohort analysis showed that number of full-term pregnancies was positively associated with CIN3/CIS risk (p-trend = 0.03). Duration of oral contraceptives use was associated with a significantly increased risk of both CIN3/CIS and ICC (HR = 1.6 and HR = 1.8 respectively for ≥15 years versus never use). Ever use of menopausal hormone therapy was associated with a reduced risk of ICC (HR = 0.5, 95%CI: 0.4–0.8). A non-significant reduced risk of ICC with ever use of intrauterine devices (IUD) was found in the nested case-control analysis (OR = 0.6). Analyses restricted to all cases and HPV seropositive controls yielded similar results, revealing a significant inverse association with IUD for combined CIN3/CIS and ICC (OR = 0.7). Even though HPV is the necessary cause of CC, our results suggest that several hormonal factors are risk factors for cervical carcinogenesis. Adherence to current cervical cancer screening guidelines should minimize the increased risk of CC associated with these hormonal risk factors.

Purpose: About 60% of ovarian cancers are diagnosed at late stage, when 5-year survival is less than 30% in contrast to 90% for local disease. This has prompted search for early detection biomarkers. For initial testing, specimens taken months or years before ovarian cancer diagnosis are the best source of information to evaluate early detection biomarkers. Here we evaluate the most promising ovarian cancer screening biomarkers in prospectively collected samples from the European Prospective Investigation into Cancer and Nutrition study. Experimental Design: We measured CA125, HE4, CA72.4, and CA15.3 in 810 invasive epithelial ovarian cancer cases and 1,939 controls. We calculated the sensitivity at 95% and 98% specificity as well as area under the receiver operator curve (C-statistic) for each marker individually and in combination. In addition, we evaluated marker performance by stage at diagnosis and time between blood draw and diagnosis. Results: We observed the best discrimination between cases and controls within 6 months of diagnosis for CA125 (C-statistic = 0.92), then HE4 (0.84), CA72.4 (0.77), and CA15.3 (0.73). Marker performance declined with longer time between blood draw and diagnosis and for earlier staged disease. However, assessment of discriminatory ability at early stage was limited by small numbers. Combinations of markers performed modestly, but significantly better than any single marker. Conclusions: CA125 remains the single best marker for the early detection of invasive epithelial ovarian cancer, but can be slightly improved by combining with other markers. Identifying novel markers for ovarian cancer will require studies including larger numbers of early-stage cases. Clin Cancer Res; 22(18); 4664–75. ©2016 AACR. See related commentary by Skates, p. 4542