Screening Potential Biomarkers of Breast Cancer Based on Bioinformatics

Breast cancer (BRCA) is a common cancer, and incidence is highest among women with cancer. This study chose gene expression profile of GSE65194, GSE42568, GSE7904 and GSE10810 from GEO databases in order to screen potential biomarkers of breast cancer. There are 393 samples, including 331 cancer samples and 62 normal samples. We screened the differentially expressed genes (DEGs) from four groups between BRCA samples and normal samples, then 150 common DEGs were detected, including 37 upregulated genes and 113 downregulated genes. Next this study used Database for Annotation Visualization and Integrated Discovery (DAVID) performed Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) pathway analysis. Moreover, we selected 15 core genes with high connectivity, including CCNB1, CDC20, BUB1B, AURKA, CDK1 and RRM2. The Kaplan Meier plotter (KM plotter) analyzed these six core genes survival rate. Finally, this study analyzed that all six genes were significantly expressed in BRCA. In conclusion, the bioinformatics analysis demonstrated that the six core genes CCNB1, CDK1, BUB1B, CDC20, AURKA and RRM2 might promote the development of BRCA, that could became new biomarkers for diagnosis and medications of BRCA.