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  • Title: Variants in estrogen metabolism and biosynthesis genes and urinary estrogen metabolites in women with a family history of breast cancer.
    Author: Greenlee H, Chen Y, Kabat GC, Wang Q, Kibriya MG, Gurvich I, Sepkovic DW, Bradlow HL, Senie RT, Santella RM, Ahsan H.
    Journal: Breast Cancer Res Treat; 2007 Mar; 102(1):111-7. PubMed ID: 16850246.
    Abstract:
    We examined associations between polymorphisms in genes related to estrogen metabolism (CYP1B1 codon 432G --> C rs#1056836, CYP1B1 codon 453A --> G rs#1800440, COMT codon 158G --> A rs#4680) and biosynthesis (CYP17 T --> C promoter rs#743572, CYP19 exon 4 TTTA repeat) and urinary estrogen metabolites (2-hydroxyestrogens (2-OHE), 16alpha-hydroxyestrone (16alpha-OHE1), and their ratio) in a pilot study of 64 pre- and post-menopausal women with a family history of breast cancer. Women were participants in the Metropolitan New York Registry of Breast Cancer Families, one of six international sites of the National Cancer Institute's Breast Cancer Family Registry. We used linear regression to examine the effects of genetic variants on log-transformed urinary estrogen metabolites. After adjusting for menopausal status, BMI, and age, carriers of the CYP1B1 codon 453G variant allele had 31.0% lower levels of 2-OHE (P-value = 0.05) and 40.2% lower levels of 16alpha-OHE1 (P = 0.01). Results were similar after restricting the analyses to pre-menopausal women (n = 41). Consistent with other studies, among pre-menopausal women, carriers of the COMT codon 158A variant allele had increased 2-OHE levels (P = 0.03) and an increased 2-OHE/16alpha-OHE1 ratio (P = 0.04); carriers of the CYP17 C promoter variant allele had increased 2-OHE levels (P = 0.08). To our knowledge this is the first report showing associations between the CYP1B1 codon 453G variant allele and urinary 2-OHE and 16alpha-OHE1 metabolites. Further larger studies should be conducted to confirm these results. Future identification of individuals with genetic polymorphisms that affect estrogen metabolism and biosynthesis may help characterize women at higher breast cancer risk and could guide breast cancer prevention strategies for those individuals.
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