Among the cancers unique to women, ovarian cancer has the highest mortality rate. Despite the public health importance of the disease, the epidemiology is poorly understood. We propose to systematically test the hypothesis that common genetic polymorphisms for enzymes that catalyze pathways of estrogen and catechol estrogen formation represent risk factors for epithelial ovarian cancer. This hypothesis will be tested in a large case-control study conducted at the Mayo Clinic Rochester, Mayo Clinic Jacksonville, and Duke University in North Carolina. We anticipate recruitment of a total of 1372 incident cases (1217 Caucasian and 155 African American). Clinic based controls matched on age, race, and state of residence will be identified through General Internal Medicine Clinics at Mayo and through Random Digit Dialing in North Carolina. Ovarian cancer risk factors will be obtained through a structured interview with all cases and controls. Blood samples orbuccal cells will be obtained as a source of DNA to detect known, functionally significant polymorphisms in genes for cytochrome P450 1A1 (CYP1A1), cytochrome P450 1B1 (CYP1B1), catechol 0-methyltransferase (COMT), sulfotransferase 1A1 (SULT1A1), glutathione S-transferase (GST) Ml, GST P1, and GST Ti as well as NAD(P)H:quinone oxidoreductase (NQO1). The analytic approach entails comparison of frequencies of alleles and genotypes for each of the genetically polymorphic enzymes studied with: a) expected population allele and genotype frequencies estimated from age- and race-matched control women using conditional logistic regression. In addition, we propose to evaluate the extent that measured non-genetic factors (e.g., reproductive history and oral contraceptive use) might modify or confound any observed association between these candidate genes and ovarian cancer risk. There is evidence from the breast cancer literature that these genetic polymorphisms are important risk factors. It is innovative, plausible, and important to evaluate similar associations with epithelial ovarian cancer. The results could have profound implications for our understanding of the disease.
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