Abstract
Background: The Breast Cancer Association Consortium (BCAC) is an international collaboration that was established to provide large sample sizes for examining genetic associations. We conducted combined analyses on all single-nucleotide polymorphisms (SNPs) whose associations with breast cancer have been investigated by at least three participating groups. Methods: Data from up to 12 studies were pooled for each SNP ( ADH1C I350V, AURKA F31I, BRCA2 N372H, CASP8 D302H, ERCC2 D312N, IGFBP3 −202 c > a , LIG4 D501D, PGR V660L, SOD2 V16A, TGFB1 L10P, TP53 R72P, XRCC1 R399Q, XRCC2 R188H, XRCC3 T241M, XRCC3 5′ UTR, and XRCC3 IVS7-14). Genotype frequencies in case and control subjects were compared, and genotype-specific odds ratios for the risk of breast cancer in heterozygotes and homozygotes for the rare allele compared with homozygotes for the common allele were estimated with logistic regression. Statistical tests were two-sided. Results: The total number of subjects for analysis of each SNP ranged from 12 013 to 31 595. For five SNPs— CASP8 D302H, IGFBP3 −202 c > a , PGR V660L, SOD2 V16A, and TGFB1 L10P—the associations with breast cancer were of borderline statistical significance ( P = .016, .060, .047, .056, and .0088 respectively). The remaining 11 SNPs were not associated with breast cancer risk; genotype-specific odds ratios were close to unity. There was some evidence for between-study heterogeneity ( P <.05) for four of the 11 SNPs ( ADH1C I350V, ERCC2 D312N, XRCC1 R399Q, and XRCC3 IVS5-14). Conclusion: Pooling data within a large consortium has helped to clarify associations of SNPs with breast cancer. In the future, consortia such as the BCAC will be important in the analysis of rare polymorphisms and gene × gene or gene × environment interactions, for which individual studies have low power to identify associations, and in the validation of associations identified from genome-wide association studies.
Breast Cancer Single-Nucleotide Polymorphisms: Statistical Significance and Clinical Utility