Association of genetic polymorphisms of ER-alpha and the estradiol-synthesizing enzyme genes CYP17 and CYP19 with breast cancer risk in Chinese women.
Estrogen plays a role in breast cancer development, and genetic polymorphisms in estrogen receptor gene ER-alpha and genes regulating estrogen biosynthesis and metabolisms are associated with the risk of breast cancer in women in western countries. Therefore, we hypothesized that SNPs in ER-alpha and other estrogen-metabolizing genes contribute to breast cancer risk in Chinese women. In this study, we genotyped polymorphisms in the regulatory regions of ER-alpha (rs3798577) and other two estrogen-metabolizing enzyme genes CYP17 (rs743572) and CYP19 (rs10046) among 300 breast cancer cases and 390 controls in a Chinese population. Crude and adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were calculated by unconditional logistic regression analyses to estimate breast cancer risk associated with these polymorphisms. We found that the T allele frequency of ER-alpha was significantly higher in cases (59.8%) than controls (54.5%) (P = 0.047), but no significant difference was found in the genotype distribution. However, postmenopausal breast cancer risk was associated with the CYP17 TC genotype (aOR = 1.77, 95% CI = 1.11-2.83) compared with the TT genotype. The CYP19 variant TC + TT genotypes were associated with both overall cancer risk (TT + TC vs. TT aOR = 1.73, 95% CI = 1.13-2.65) and premenopausal cancer risk (TT + TC vs. TT aOR = 1.78, 95% CI = 1.03-3.09), particularly for ER +/PR + tumors. Furthermore, there were joint effects between CYP19 T and ER-alpha T variant genotypes (aOR = 1.67, 95% CI = 1.03-2.69 for CYP19 TC + TT vs. CC among ER-alpha T variant carriers) and between CYP19 T and CYP17 C variant genotypes (aOR = 1.77, 95% CI = 1.11-2.83 for CYP19 TC + TT vs. CC among CYP17 variant C carriers). This study provides evidence that polymorphisms CYP17 rs743572, CYP19 rs10046 and ER-alpha rs3798577 are associated with breast cancer risk among Chinese women.
Zhang, L; Gu, L; Qian, B; Hao, X; Zhang, W; Wei, Q; Chen, K
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