Identifying Molecular Determinants and Therapeutic Targets in Luminal B Breast Cancer: A Systems Biology Approach

Background & Objective: Luminal B breast cancer (LBBC) is on the rise worldwide, with both incidence and mortality rates steadily increasing. Early detection proves difficult due to its aggressive characteristics, most notably its heightened proliferation rate and the complex interplay of molecular biomarkers, particularly in more advanced stages.Methods: Data Sources: In the present study, we conducted an in-silico analysis of LBBC cell lines using the Gene Expression Omnibus (GEO) microarray dataset, which includes ۳۰ LBBC and ۱۱ normal samples. Analysis Tools: Differentially expressed genes (DEGs) were identified using RStudio. A series of analyses, including cancer data interrogation via pan-cancer analysis, eXpression۲Kinases (X۲K), and the Cancer Dependency Map (DepMAP), was carried out to elucidate the underlying signaling pathways, transcription factors (TFs), and kinases, as well as to perform stemformatics analysis. Protein–protein interaction (PPI) networks were reconstructed using STRING and Cytoscape, enabling the identification of co-expressed and hub genes through the cytoHubba plug-in.Results: Of note, FGF۲, EGFR, ADIPOQ, LIPE, MET, IGF۱, FGF۱, EGF, FGF۷, and PPARG were identified as the top ۱۰ hub genes; RELA, PPARG, CTCF, EGR۱, and NFE۲L۲ were detected as predominant TFs in LBBC; and CDK۱, CDK۲, MAPK۳, CSNK۲A۱, and MAPK۱۴ were identified as potential biomarkers through hub gene clustering. Further analysis indicated hsa-mir-۲۲۱-۳p and hsa-mir-۲۹a-۳p as key miRNAs targeting LBBC-related genes.Conclusion: Collectively, our findings highlighted LBBC-associated genes, TFs, miRNAs, and pathways as prospective biomarkers, providing insights into LBBC diagnosis and therapeutic approaches.

کلیدواژه ها:

Breast neoplasms ، Biomarkers ، Cancer Stem Cells ، Computational Biology