Transcriptome analysis of triple negative breast cancer based on public database

Abstract

Triple negative breast cancer (TNBC) is a pathological type with high malignancy in breast cancer. Because the estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 appear histologically negative, the treatment effect of the existing drug is not ideal. Exploring the TNBC related pathological markers is one of hot spots in the research field of breast cancer. TNBC related gene sets are obtained from gene expression omnibus (GEO) database for transcriptome analysis, including principal component analysis, screening differentially expressed genes (DEGs), gene function enrichment analysis and signal pathway enrichment analysis, protein interaction network construction, weighted gene coexpression network analysis (WGCNA), etc. The results show that there are significantly differentially expressed genes (DEGs) between TNBC and non TNBC population. These DEGs are mainly enriched in the biological processes related to epidermal growth and differentiation, growth and development of mammary epithelial cells, and in molecular functions related to transcription factor binding and estrogen signal transduction pathways. The results of protein interaction network and weighted gene coexpression network analysis are integrated and TFF1, FOXA1, AGR2 and AGR3 are predicted as the key genes involved in the pathological phenotype of TNBC. The study of transcriptome analysis based on TNBC gene set in public database may provide certain theoretical research basis to reveal the potential biomarkers for pathogenesis of TNBC, and the derived disease diagnosis and therapeutic targets or molecular regulation mechanisms.