ArticleiScience2024
Network-based approach elucidates critical genes in BRCA subtypes and chemotherapy response in triple negative breast cancer.
Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- UNITe: exploiting conserved links between oncogenesis and homeostasis to identify novel cancer drivers.Frontiers in oncology · 2026Article
- Delineating novel diagnostic biomarkers and therapeutic targets for oral submucosal fibrosis: an integrative multi-omics and machine learning approach.Frontiers in bioinformatics · 2026Article
- Breast cancer pathogenesis, diagnosis and treatment: a comprehensive review.Frontiers in oncology · 2026Review
- Network-based approach identifies key genes associated with tumor heterogeneity in HPV positive and negative head and neck cancer patients.Scientific reports · 2025Article
- Characterizing the pan-cancer role of exosomal miRNAs in metastasis across cancers.Computational and structural biotechnology journal · 2025Article
- Protocol for identifying key genes using network-based approach as an alternative to differential expression analysis.STAR protocols · 2024Article
- Characterizing the role of exosomal miRNAs in metastasis.bioRxiv : the preprint server for biology · 2024Article
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Abstract
Breast cancers (BRCA) exhibit substantial transcriptional heterogeneity, posing a significant clinical challenge. The global transcriptional changes in a disease context, however, are likely mediated by few key genes which reflect disease etiology better than the differentially expressed genes (DEGs). We apply our network-based tool PathExt to 1,059 BRCA tumors across 4 subtypes to identify key mediator genes in each subtype. Compared to conventional differential expression analysis, PathExt-identified genes exhibit greater concordance across tumors, revealing shared and subtype-specific biological processes; better recapitulate BRCA-associated genes in multiple benchmarks, and are more essential in BRCA subtype-specific cell lines. Single-cell transcriptomic analysis reveals a subtype-specific distribution of PathExt-identified genes in multiple cell types from the tumor microenvironment. Application of PathExt to a TNBC chemotherapy response dataset identified subtype-specific key genes and biological processes associated with resistance. We described putative drugs that target key genes potentially mediating drug resistance.
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