ArticleiScience2021
A network approach reveals driver genes associated with survival of patients with triple-negative breast cancer.
Article in iScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Transcriptomic landscape of Gallbladder cancer reveals altered pathways related to cell cycle and Aurora kinase.Scientific reports · 2026Article
- Comparative Phosphoproteomic Profiling and Network-based Interactome Analysis of GRK5 and GRK6.Cell biochemistry and biophysics · 2026Article
- Integrated systems biology reveals an 8-gene signature predicting early-stage lung adenocarcinoma progression and patient survival.Scientific reports · 2025Article
- The Role of Non-Coding Regions in Breast Cancer: From Gene Regulation to Therapeutic Implications.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Inflammation-related 5-hydroxymethylation signatures as markers for clinical presentations of coronary artery disease.Cardiovascular diabetology · 2025Article
- Proteomic analysis of Alzheimer's disease cerebrospinal fluid reveals alterations associated withScience translational medicine · 2024Article
- Proteomic Network Analysis of Alzheimer's Disease Cerebrospinal Fluid Reveals Alterations Associated withmedRxiv : the preprint server for health sciences · 2023Article
- Redefining normal breast cell populations using long noncoding RNAs.Nucleic acids research · 2023Article
- Batch Correction and Harmonization of -Omics Datasets with a Tunable Median Polish of Ratio.Frontiers in systems biology · 2023Article
- Overview of triple negative breast cancer prognostic signatures in the context of data science-driven clinico-genomics research.Annals of translational medicine · 2022Article
- Article
- Machine learning assisted analysis of breast cancer gene expression profiles reveals novel potential prognostic biomarkers for triple-negative breast cancer.Computational and structural biotechnology journal · 2022Article
- CDKN2A-mediated molecular subtypes characterize the hallmarks of tumor microenvironment and guide precision medicine in triple-negative breast cancer.Frontiers in immunology · 2022Article
- Analysis of type 2 diabetes mellitus-related genes by constructing the pathway-based weighted network.IET systems biologyArticle
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Authors and funding
5 authors.
Funding
Abstract
We aimed to identify triple-negative breast cancer (TNBC) drivers that regulate survival time as predictive signatures that improve TNBC prognostication. Breast cancer (BrCa) transcriptomic tumor biopsies were analyzed, identifying network communities enriched with TNBC-specific differentially expressed genes (DEGs) and correlated strongly to TNBC status. Two anticorrelated modules correlated strongly to TNBC subtype and survival. Querying module-specific hubs and DEGs revealed transcriptional changes associated with high survival. Transcripts were nominated as biomarkers and tested as combinatoric ratios using receiver operator characteristic (ROC) analysis to assess survival prediction. ROC test rounds integrated genes with established interactions to hubs and DEGs of key modules, improving prediction. Finally, we tested whether integration of literature-derived genes for implicated hallmark cancer processes could improve prediction of survival. Complementary coexpression, differential expression, genetic interaction, and survival stratification integrated by ROC optimization uncovered a panel of "linchpin survival genes" predictive of patient survival, representing gene interactions in hallmark cancer processes.
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