Epidemiology Program

Molecular Epidemiology of Endometrial Cancer

PI: Chu Chen PhD

It is well established that estrogen exposure increases the risk of endometrial cancer. However, the presence or absence of currently known risk factors for this disease, such as the use of unopposed estrogens or obesity, offers little sensitivity or specificity in predicting which women will go on to develop it. This study tests the hypotheses that the risk of developing endometrial cancer is related to variation in genes that encode for enzymes: 1) involved in the biosynthesis or catabolism of estrogens, or in the response to steroid hormones, and 2) that repair DNA damage generated during estrogen exposure. A population-based case-control study of 803 endometrial cancer cases and 753 controls ages 50-74 years will be conducted in three counties of Western Washington State. This study will build upon a previous case-control study of endometrial cancer (cases=383, controls=450). We will recruit an additional 420 incident cases, diagnosed between 7/03-12/05, who are identified through a population-based cancer registry that is part of the Surveillance, Epidemiology and End Results program, and will use a subset of controls (n=303), identified through random-digit dialing from an ongoing ovarian cancer study. These controls will have intact uteri, and will be similar to the cases in terms of geographic area and age. Cases and controls will be interviewed in person regarding lifestyle and medical history, and a venous blood sample will be obtained. Genomic DNA will be tested for variants in genes involved in 1) the synthesis, catabolism, and response to estrogens; and 2) base excision repair of oxidative DNA damage and nucleotide excision repair of DNA damage caused by bulky adducts. Cases and controls will be compared with respect to the prevalence of putative "high risk" genotypes and results will be interpreted with multiple comparisons taken into account. This study has sufficient statistical power to identify interactions between some of the high-risk genotypes, and to investigate whether the risk associated with some of the genotypes varies by other risk factors, such as exposure to exogenous hormones and obesity. Efforts will also be devoted to generating risk indices through statistical modeling that integrate potential effects of genetic variants in the estrogen metabolism pathway and/or DNA repair pathways.