Evaluation of Breast Cancer Susceptibility Loci in Chinese Women
- 1 September 2010
- journal article
- Published by American Association for Cancer Research (AACR) in Cancer Epidemiology, Biomarkers & Prevention
- Vol. 19 (9), 2357-2365
- https://doi.org/10.1158/1055-9965.epi-10-0054
Abstract
Background: Recent genome-wide association studies (GWAS), mostly conducted among women of European ancestry, have identified 16 single-nucleotide polymorphisms (SNP) associated with breast cancer. Methods: We evaluated these SNPs with the risk of breast cancer and further by estrogen receptor status in a population-based study of 6,498 cases and 3,999 controls in Chinese women. We also searched for novel genetic risk variants in four loci, 2q35, 5p12/MRPS30, 8q24.21, and 17q23.2/COX11, in a two-stage study. In stage I, 868 SNPs were analyzed in 2,073 cases and 2,084 controls. In stage II, 58 SNPs selected from stage I were evaluated, including 4,425 cases and 1,915 controls. Results: Statistically significant associations (P < 0.05) were observed for eight GWAS-identified SNPs, including rs4973768 (3p24/SLC4A7), rs889312 (5q11.2MAP3K1), rs2046210 (6q25.1), rs1219648 (10q26.13/FGFR2), rs2981582 (10q26.13/FGFR2), rs3817198 (11p15.5/LSP1), rs8051542 (16q12.1/TOX3), and rs3803662 (16q12.1/TOX3). Two additional SNPs, rs10941679 (5p12/MRPS30) and rs13281615 (8q24.21), showed a marginally significant association. Some of these associations varied by estrogen receptor status. In the fine-mapping analysis, five SNPs showed a consistent association with breast cancer risk in both stages: rs10169372 (2q35), rs283720 (8q24.21), rs10515083 (17q23.2/COX11), rs16955329 (17q23.2/COX11), and rs2787487 (17q23.2/COX11). Conclusions: This study shows that approximately half of the SNPs initially reported from GWAS of breast cancer in European descendants can be directly replicated in Chinese. Our fine-mapping analyses revealed several candidates of risk variants that can be further evaluated in studies with a larger sample size. Impact: Findings from this study may help guide future fine-mapping studies to identify causal variants for breast cancer. Cancer Epidemiol Biomarkers Prev; 19(9); 2357–65. ©2010 AACR.Keywords
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