Identification of Potentially Therapeutic Target Genes in Metastatic Breast Cancer via Integrative Network Analysis
Hazel Jing Yi Leong, Hao Dong Tan, Wei Hsum Yap, Adeline Yoke Yin Chia, Serena Zacchigna, Yin-Quan Tang
Abstract
Objectives: Metastatic breast cancer (MBC) represents a significant cause of morbidity and mortality in patients. However, the molecular mechanism of the disease among MBC patients remains elusive. Methods: An integrated characterization was performed using two independent datasets of normal and malignant breast tissues (GSE29431 and GSE12276), and the differentially expressed genes (DEGs) had been analysed. Network system biology based on the protein–protein interaction (PPI) network was performed using STRING, identified hub genes were confirmed by the Cytoscape and Kaplan–Meier survival analysis to study DEGs of overall survival.  Results: The study identified 159 DEGs which includes 54 up-expressed and 105 down-expressed genes, and network analysis indicate that nucleosome assemble, and cell cycle regulation mediate breast cancer metastasis. HIST1H2BD and KMT2A were recognized as key hub genes regulate cell fate transitions to promote tumor progression and metastasis. Another key hub gene, ITGB1 could drive metastasis by modulating the cell cycle processes through FAK and AKT pathways. KM survival analysis revealed these three hub genes were closely correlated with the overall survival of patients.  Conclusion: This study provides a new deeper insight into better understanding of these hub genes (HIST1H2BD, KMT2A and ITGB1) can potentially be used in novel therapeutic strategies for MBC.