ABSTRACT: Breast cancer is one of the most common malignant tumors in women worldwide. Early diagnosis, treatment, and prognosis of breast cancer are global challenges. Identification of valid predictive diagnosis and prognosis biomarkers and drug targets are crucial for breast cancer prevention. This study characterizes differentially expressed genes (DEGs) based on the TCGA database by using DESeq2, edgeR, and limma. A total of 2032 DEGs, including 1026 up-regulated genes and 1006 down-regulated genes were screened. Followed with WGCNA, PPI analysis, GEPIA 2, and HPA database verification, thirteen hub genes including CDK1, BUB1, BUB1B, CDC20, CCNB2, CCNB1, KIF2C, NDC80, CDCA8, CENPF, BIRC5, AURKB, PLK1,
