Genome-wide pathway analysis of breast cancer
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The aim of this study was to identify candidate single-nucleotide polymorphisms (SNPs) that might affect susceptibility to breast cancer and then elucidate their potential mechanisms and generate SNP-to-gene-to-pathway hypotheses. A genome-wide association study (GWAS) dataset of breast cancer that included 453,852 SNPs from 1,145 breast cancer patients and 1,142 control subjects of European descent was used in this study. The identify candidate causal SNPs and pathways (ICSNPathway) method was applied to the GWAS dataset. ICSNPathway analysis identified 16 candidate SNPs, 13 genes, and 7 pathways, which together revealed 7 hypothetical biological mechanisms. The strongest hypothetical biological mechanism was that rs3168891 and rs2899849 alter the role of MBIP in the inactivation of mitogen-activated protein kinase (MAPK) (p < 0.001; false discovery rate (FDR) = 0.038). The second strongest mechanism was that rs2229714 modulates RPS6KA1 to affect its role in growth hormone signaling (p = 0.001; FDR = 0.039). The third strongest mechanism was that rs2230394 modulates ITGB1 to regulate the PTEN pathway and hsa04360 (axon guidance pathway) (p < 0.001; FDR = 0.039, 0.041). Use of the ICSNPathway to analyze breast cancer GWAS data identified 16 candidate SNPs, 13 genes (including MBIP, RPS6KA1, and ITGB1), and 7 pathways that might contribute to the susceptibility of patients to breast cancer.
KeywordsBreast cancer Genome-wide association study Pathway-based analysis
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