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

Area of Science:

• Oncology
• Bioinformatics
• Genomics

Background:

• Triple-negative breast cancer (TNBC) accounts for 15% of breast cancer deaths and is characterized by aggressive behavior, high proliferation, and metastasis.
• Understanding the genetic complexity of TNBC is crucial for developing effective therapeutic strategies.

Purpose of the Study:

• To introduce an integrative network methodology for identifying key candidate genes in TNBC.
• To uncover central hub genes and their regulatory transcription factors involved in TNBC pathogenesis.
• To explore the functional pathways associated with identified TNBC-related genes.

Main Methods:

• Construction of a central gene network by refining candidate genes from various databases.
• Identification of hub genes (SRC, EGFR, JUN, CTNNB1, MYC) using topological parameters (degree, betweenness centrality, closeness centrality, clustering coefficient).
• Validation of hub genes via molecular complex detection cluster analysis and construction of a regulatory network using MatInspector to identify transcription factors (ZF02, MZF1, PLAG).
• Functional enrichment pathway analysis using ClueGo.

Main Results:

• Five hub genes (SRC, EGFR, JUN, CTNNB1, MYC) were identified as central players in TNBC.
• Common transcription factors ZF02, MZF1, and PLAG were found to activate these hub genes.
• Functional enrichment analysis revealed significant roles for hub genes in toxicity-associated and physiochemical pathways.

Conclusions:

• The identified hub genes represent potential molecular and therapeutic targets for TNBC.
• This study provides a foundation for developing personalized medicine approaches for triple-negative breast cancer.
• The integrative network methodology offers a novel approach to understanding complex diseases like TNBC.