Decoding molecular signatures and identifying therapeutic targets in triple-negative breast cancer subtypes using omics and network analysis

利用组学和网络分析解码三阴性乳腺癌亚型的分子特征并识别治疗靶点

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Abstract

Triple-negative breast cancer (TNBC) is the most aggressive form of breast cancer. It is resistant to therapeutic applications, making it very difficult to manage. Most patients continue to receive chemotherapy. The main challenges in treating TNBC arise from its histopathological, transcriptomic, and genomic heterogeneity. While subtype classification was once essential for understanding TNBC's diverse behavior, it is now crucial to thoroughly evaluate the molecular characteristics of each subtype to improve TNBC management. Our study employed a multi-omics approach utilizing transcriptomic data to compare TNBC subtype-specific cell lines with normal breast epithelial cell lines. Our goal was to find out essential transcription factors (TFs) regulating cancer-related pathways, subtype-specific marker genes, and their key TFs. We identified a common set of genes involved in cancer related pathways and examined their alteration level with driver mutations in each subtype. Our findings indicate that, based on alteration patterns, survivability, differential gene and protein level expressions, the genes ERBB3, ERBB4, HLA-B, AKT1, GNAS, FGFR4, PIK3R3 and AXIN2 emerge as primary risk factors in TNBC. These genes, associated with specific subtypes, are potential markers and should be the focus of further studies, paving the way for personalized anticancer treatment strategies for TNBC patients.

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