摘要：Women with BRCA1 and BRCA2 gene mutations are at increased risk of breast cancer, compared with women who don’t carry the mutation in familial and somatic condition is remains challenge. The aim of this work is to identify differentially expressed gene patterns related with BRCA1 and BRCA2 gene mutations that significantly expressed in breast cancer drug targets. We have developed microarray meta-analysis to predict differential gene expression lev-els between hereditary BRCA1 mutations linked with sporadic breast cancer, using statistical methods to identify upregulated and downregulated genes to perform meta-analysis; further SVM classifier to identify gene ranks and their associated gene networks helps to classify gene profiles used for drug targets. We have predicted 2381 upregulated and 2057 down regulated genes that sig-nificantly (p-value < 0.01) associated with BRCA1 and BRCA2 related gene mutations. We also predicted that SVM classifiers showing 810 genes signifi-cantly associated with 4 different types of which 592 genes is helpful for pro-tein expression that shows metastatic condition. Based on gene-gene interaction network prediction showing 30 genes is significantly associated with GO terms and many signaling pathways; we mainly use these genes for potential drug targets. Furthermore this result helps predict anticancer drug targets.
