Potential Therapeutic Targets in Triple-Negative Breast Cancer Based on Gene Regulatory Network Analysis: A Comprehensive Systems Biology Approach.

Abstract

Background: Triple-negative breast cancer (TNBC) is an aggressive subtype with limited treatment options. This study is aimed at identifying potential therapeutic targets in TNBC using gene regulatory network analysis and a system biology approach. Methods: The GSE38959 dataset was reanalyzed to identify differentially expressed genes (DEGs) in TNBC tissues compared to normal breast samples. Protein-protein interaction networks were constructed, and hub genes were identified. Survival analysis was performed using GEPIA2. Gene regulatory networks were built to identify upstream regulators. Cross-platform verification was conducted using an independent RNA-seq dataset (GSE58135). Expression analysis of prognostic markers in TNBC versus non-TNBC samples was performed using bc-GenExMiner. Results: A total of 943 DEGs were identified in TNBC tissues. CHEK1 and PLK1 were identified as central hub genes, with overexpression correlating with poor prognosis. GABPB1 was identified as the most influential upstream regulator of CHEK1 and PLK1 through gene regulatory network analysis, while JUN exhibited the most interactions among regulators. A total of 302 consistently modulated genes were confirmed through cross-platform verification. The overexpression of CHEK1 and PLK1 in TNBC compared to non-TNBC samples was validated by expression analysis. Conclusion: This study provides insights into the molecular mechanisms of TNBC and suggests CHEK1, PLK1, and their upstream regulators as potential therapeutic targets for TNBC treatment.