Integrative network-based approach identifies central genetic and transcriptomic elements in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) has gained considerable attention as it oversteps about 15% of the deaths caused by breast cancer in women and is well known for its aggressive impact, high proliferation rate, intensity of tumor, and metastasis. In this study, we have given a new insight into TNBC, by introducing an integrative network methodology to understand the complexity of the candidate genes in TNBC. In the course of this analysis, the central network was constructed by refining the candidate genes present in the various databases. Eventually, the hub genes SRC, EGFR, JUN, CTNNB1, and MYC were derived using distinct topological parameters such as degree, betweenness centrality, closeness centrality, and clustering coefficient, which implicated a central role in TNBC. Furthermore, the identified hub genes were validated by utilizing molecular complex detection cluster analysis. A regulatory network was constructed to locate the transcriptional factors regulating these hub genes via MatInspector. Interestingly, we characterized that ZF02, MZF1, and PLAG are the common transcription factors which activate the hub genes. Moreover, a functional enrichment pathway was obtained from ClueGo, which depicted that all the hub genes have a significant role in toxicity-associated pathways as well as physiochemical featured pathways. In a nutshell, these prioritized genes could be the way out to uncover the molecular and therapeutic targets, leading to the development of personalized medicine for TNBC.