ArticleScientific reports2024
Identification of modules and key genes associated with breast cancer subtypes through network analysis.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Identification of a nuclear transcriptional module associated with ERα and E2F/FOXM1 signaling across PAM50 breast cancer subtypes.Frontiers in oncology · 2026Article
- Gene Expression Profiling to Unveil Novel Biomarkers for Early Diagnosis and Therapies for Breast Cancer.Current topics in medicinal chemistry · 2026Article
- Enhanced ETS1 stability by DNAPKcs orchestrates transcriptional changes during chemoresistance in triple negative breast cancer.NPJ breast cancer · 2025Article
- Cohesive data analysis for the identification of prognostic hub genes and significant pathways associated with HER2 + and TN breast cancer types.Scientific reports · 2025Article
- Clinical Utility of IFIT Proteins in Human Malignancies.Biomedicines · 2025Review
- Therapy-induced senescence is a transient drug resistance mechanism in breast cancer.Molecular cancer · 2025Article
- IFIT3: a crucial mediator in innate immunity and tumor progression with therapeutic implications.Frontiers in immunology · 2025Review
- Online-adjusted evolutionary biclustering algorithm to identify significant modules in gene expression data.Briefings in bioinformatics · 2024Article
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Authors and funding
6 authors.
Funding
Abstract
Breast cancer is the most common malignancy in women around the world. Intratumor and intertumoral heterogeneity persist in mammary tumors. Therefore, the identification of biomarkers is essential for the treatment of this malignancy. This study analyzed 28,143 genes expressed in 49 breast cancer cell lines using a Weighted Gene Co-expression Network Analysis to determine specific target proteins for Basal A, Basal B, Luminal A, Luminal B, and HER2 ampl breast cancer subtypes. Sixty-five modules were identified, of which five were characterized as having a high correlation with breast cancer subtypes. Genes overexpressed in the tumor were found to participate in the following mechanisms: regulation of the apoptotic process, transcriptional regulation, angiogenesis, signaling, and cellular survival. In particular, we identified the following genes, considered as hubs: IFIT3, an inhibitor of viral and cellular processes; ETS1, a transcription factor involved in cell death and tumorigenesis; ENSG00000259723 lncRNA, expressed in cancers; AL033519.3, a hypothetical gene; and TMEM86A, important for regulating keratinocyte membrane properties, considered as a key in Basal A, Basal B, Luminal A, Luminal B, and HER2 ampl breast cancer subtypes, respectively. The modules and genes identified in this work can be used to identify possible biomarkers or therapeutic targets in different breast cancer subtypes.
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