Identification of Hub genes and key biomarkers in patients with breast cancer by bioinformatics tools

Abstract

The purpose of our study was to identify key common genes associated with breast cancer and its diagnosis. The data from the three profiles were downloaded from the GEO database and analyzed using several bioinformatics tools. The common differentially expressed genes (DEGs) were determined using the Venn diagram visual presentation. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed via the DAVID site, and protein-protein interaction networks (PPI) were built via the STRING database and visualized with Cytoscape software. Then, we checked the overall survival and expression of key genes using the GEPIA2 database. 663 DEGs were obtained, of which 500 genes were up- regulated and 163 were down-regulated. According to GO and KEGG analyses these DEGs were mainly enriched in positive gene regulation, the phosphatidylinositol 3kinase/protein kinase B pathway, angiogenesis, cell division, mitotic spindle assembly checkpoint signaling, and mitotic sister chromatid segregation. In addition, eight hub genes were selected, one of which was associated with decreased overall patient survival and was significantly expressed in cancer tissue relative to normal tissue. Finally, analysis using Network Analyst revealed that UBE2C's regulation involves crucial interactions with eleven miRNAs and seven transcription factors, providing insights into its complex coregulatory network. In summary, the gene UBE2C (Ubiquitin Conjugating Enzyme E2 C) can be an excellent biomarker for breast cancer diagnosis and targeted gene therapy.