Application of Bioinformatics Analysis to Identify Important Pathways and Hub Genes in Breast Cancer Affected by HER-2

Abstract

Human epidermal growth factor receptor 2 (HER-2) is used as a marker for the diagnosis and prognosis of breast cancer. However, the molecular mechanisms involving HER2 in breast cancer require further study. Herein, we used the bioinformatics approaches to identify important pathways and hub genes in breast cancer affected by HER-2. The results showed that HER-2 is highly expressed in ovarian cancer and is closely related to the overall survival and progression-free survival of breast cancer.  A total of 3014 downregulated genes and 4121 upregulated genes were identified under Gene Expression Omnibus (GEO) database with the GEO2R tool. Among them, the top 10 hub genes including CCNB1, KIF11, BUB1B, TOP2A, ASPM, MAD2L1, BUB1, RRM2, EGFR, and FN1 demonstrated by connectivity degree in the protein-protein interaction (PPI) network were screened out. In Kaplan–Meier plotter survival analysis, the overexpression of CCNB1, EGFR, MAD2L1, ASPM, and RRM2 were shown to be associated with an unfavourable prognosis in HER-2 positive breast cancer patients. In conclusion, we have identified important signalling pathways involving HER-2 that affect breast cancer. These findings could provide new insights outlining mechanisms involving HER-2 gene expression in breast cancer and provides a rationale for the novel treatment of breast cancer.