Type I endometrial cancer, the most common gynecological cancer among U.S. women, is considered a model of hormonal carcinogenesis that is strongly influenced by modifiable lifestyle factors. While endometrial cancer shares common reproductive and menstrual risk factors with the hormonally-regulated cancers of the breast and ovary, the temporal relationships between these exposures and cancer risk differs for each site. The diverse associations suggest the existence of important, but undefined biologic mechanisms that are tissue type-specific. Consequently, these etiologic differences have emerged as challenges for chemopreventive measures. Carcinogenic processes such as mutation, proliferation, and apoptosis affect the rate of 'tissue aging'with the number of precancerous cells increasing multiplicatively over time. Historical events and exposures differentially affect the rate of increase for a specific cancer. Biomathematical models relating epidemiologic risk factors to endometrial cancer can provide a structure with which to view the process of carcinogenesis. Such insight could provide additional avenues of experimental and/or epidemiologic research for treatment or prevention of endometrial cancer among healthy women as well as breast cancer patients undergoing hormonal therapies. Obtaining accurate risk estimates and determining how etiologic factors jointly affect risk are important aspects in cancer modeling. Thus, we will quantify the joint and temporal effects of established reproductive and lifestyle risk factors on cumulative incidence of Type I endometrial cancer by developing an endometrial cancer risk prediction log-incidence model in the Nurses'Health Study that will be validated among female participants of the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial.
Type I endometrial cancer is considered a model of hormonal carcinogenesis that shares common reproductive and menstrual risk factors with the hormonally-regulated cancers of the breast and ovary. However, the temporal relationship between these exposures and cancer risk differ for each site suggesting the existence of important, but unknown tissue type-specific mechanisms, which have, in turn, posed a challenge for chemopreventive measures. The aim of this application is to provide additional avenues of experimental and/or epidemiologic research by creating biomathematical models to relate epidemiologic risk factors to endometrial cancer that can provide a structure with which to view the process of cancer development.
|Kotsopoulos, Joanne; Prescott, Jennifer; De Vivo, Immaculata et al. (2014) Telomere length and mortality following a diagnosis of ovarian cancer. Cancer Epidemiol Biomarkers Prev 23:2603-6|