ArticleBioinformatics (Oxford, England)2020
Somatic selection distinguishes oncogenes and tumor suppressor genes.
Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
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Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it, 47 citations in OpenAlex.
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- The impact of AI on modern oncology from early detection to personalized cancer treatment.NPJ precision oncology · 2026Review
- AI-driven CRISPR strategies in breast cancer: Organoid modeling, adaptive editing, and precision delivery.Iranian journal of basic medical sciences · 2026Review
- FAT2 inhibits breast cancer cell migration, invasion, and epithelial-mesenchymal transition through transcriptional upregulation of CLDN19.Frontiers in oncology · 2026Article
- Construction and clinical significance of prognostic risk markers based on cancer driver genes in lung adenocarcinoma.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
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- An Overview of Research Advances in Oncology Regarding the Transcription Factor ATF4.Current drug targets · 2025Review
- Protein structural context of cancer mutations reveals molecular mechanisms and candidate driver genes.Cell reports · 2024Article
- Copy number losses of oncogenes and gains of tumor suppressor genes generate common driver mutations.Nature communications · 2024Article
- Strength of selection in lung tumors correlates with clinical features better than tumor mutation burden.Scientific reports · 2024Article
- Review
- Genome-wide screening and functional validation of methylation barriers near promoters.Nucleic acids research · 2024Article
- Prediction of cancer driver genes and mutations: the potential of integrative computational frameworks.Briefings in bioinformatics · 2024Review
- Source, co-occurrence, and prognostic value of PTEN mutations or loss in colorectal cancer.NPJ genomic medicine · 2023Article
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- RNA-Based Strategies for Cancer Therapy: In Silico Design and Evaluation of ASOs for Targeted Exon Skipping.International journal of molecular sciences · 2023Article
- A workflow to study mechanistic indicators for driver gene prediction with Moonlight.Briefings in bioinformatics · 2023Article
- The organoid as reliable cancer modeling in personalized medicine, does applicable in precision medicine of head and neck squamous cell carcinoma?The pharmacogenomics journal · 2023Review
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
motivationFunctions of cancer driver genes vary substantially across tissues and organs. Distinguishing passenger genes, oncogenes (OGs) and tumor-suppressor genes (TSGs) for each cancer type is critical for understanding tumor biology and identifying clinically actionable targets. Although many computational tools are available to predict putative cancer driver genes, resources for context-aware classifications of OGs and TSGs are limited.
resultsWe show that the direction and magnitude of somatic selection of protein-coding mutations are significantly different for passenger genes, OGs and TSGs. Based on these patterns, we develop a new method (genes under selection in tumors) to discover OGs and TSGs in a cancer-type specific manner. Genes under selection in tumors shows a high accuracy (92%) when evaluated via strict cross-validations. Its application to 10 172 tumor exomes found known and novel cancer drivers with high tissue-specificities. In 11 out of 13 OGs shared among multiple cancer types, we found functional domains selectively engaged in different cancers, suggesting differences in disease mechanisms. AVAILABILITY AND IMPLEMENTATION: An R implementation of the GUST algorithm is available at https://github.com/liliulab/gust. A database with pre-computed results is available at https://liliulab.shinyapps.io/gust. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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