Matsuno, Rayna K.

Abstract Purpose: Ovarian cancer is a heterogeneous disease that can be divided into multiple subtypes with variable etiology, pathogenesis, and prognosis. We analyzed DNA methylation profiling data to identify biologic subgroups of ovarian cancer and study their relationship with histologic subtypes, copy number variation, RNA expression data, and outcomes. Experimental Design: A total of 162 paraffin-embedded ovarian epithelial tumor tissues, including the five major epithelial ovarian tumor subtypes (high- and low-grade serous, endometrioid, mucinous, and clear cell) and tumors of low malignant potential were selected from two different sources: The Polish Ovarian Cancer study, and the Surveillance, Epidemiology, and End Results Residual Tissue Repository (SEER RTR). Analyses were restricted to Caucasian women. Methylation profiling was conducted using the Illumina 450K methylation array. For 45 tumors array copy number data were available. NanoString gene expression data for 39 genes were available for 61 high-grade serous carcinomas (HGSC). Results: Consensus nonnegative matrix factorization clustering of the 1,000 most variable CpG sites showed four major clusters among all epithelial ovarian cancers. We observed statistically significant differences in survival (log-rank test, P = 9.1 × 10−7) and genomic instability across these clusters. Within HGSC, clustering showed three subgroups with survival differences (log-rank test, P = 0.002). Comparing models with and without methylation subgroups in addition to previously identified gene expression subtypes suggested that the methylation subgroups added significant survival information (P = 0.007). Conclusions: DNA methylation profiling of ovarian cancer identified novel molecular subgroups that had significant survival difference and provided insights into the molecular underpinnings of ovarian cancer. See related commentary by Ishak et al., p. 5729

Abstract Some studies show that childbearing at older age is associated with lower risk of endometrial cancer, but whether the association is independent of number of children or other factors still requires clarification. We pooled individual-level data from epidemiologic studies in the Epidemiology of Endometrial Cancer Consortium (E2C2). Data on age at last birth and/or last pregnancy were available from 14 studies: 11 case-control studies and 3 cohort studies; the latter were analyzed using a nested case-control design. A total of 9,613 endometrial cancer cases and 17,112 controls were included in the analysis. The majority of women were White (82%) and older than 55 years (69%). We estimated the effects of age at last birth using data from 12 studies and age at last pregnancy using data from 10 studies on the risk of endometrial cancer by calculating odds ratios (OR) and 95% confidence intervals (95% CI) using logistic regression models. Potential confounders included in the analysis were race, body mass index, parity, age at menarche, age at first birth, oral contraceptive use, postmenopausal hormone use, smoking status, and report of diabetes. After adjusting for potential confounders, a reduction in endometrial cancer risk was observed in women with increasing age at last birth (P trend <0.0001) and age at last pregnancy (P trend <0.0001). The OR per five-year increase in age at last birth and age at last pregnancy was 0.90 (95%CI: 0.86, 0.94) and 0.91 (95% CI: 0.87, 0.95), respectively. Women who had their last child at an age >40 years were at a 34% decreased risk compared with women who had their last child at an age <25 years (95% CI: 0.52, 0.82). Compared to women with age at last pregnancy <25 years, those with age at last pregnancy >40 years had a 30% decreased risk of endometrial cancer (95%CI: 0.57, 0.86). Inverse associations were observed for Whites and Asians in race-specific analysis and also in analysis restricted to women with at least 2 births. In this large pooled analysis, we show that late age at last birth or last pregnancy is a strong and independent protective factor for endometrial cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 1900. doi:10.1158/1538-7445.AM2011-1900