ArticleNucleic acids research2021
OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers.
Article in Nucleic acids research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.
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Who cites it
62 citing papers in PubMed, 107 citations in OpenAlex.
- In silico analysis of driver genes in squamous cell carcinoma of the cervix: insights into their biological functions, prognosis, immune infiltration, and therapy.World journal of surgical oncology · 2026Article
- Pancancer Fine-Mapping of Mutational Intolerance Identifies CHEK1 as an Immunosuppressive Driver in Lung Adenocarcinoma.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- OncoRisk: a state-of-the-art web server for bridging the oncogenic databases and pan-cancer cohorts to the translational oncology.Communications biology · 2026Article
- Exploiting tumor lineage features for precision cancer therapy.Trends in cancer · 2026Review
- An interpretable molecular framework for predicting cancer driver missense mutations.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- CircleBase V2: an eccDNA annotation platform across cancers and species.Nucleic acids research · 2026Article
- A multimodal framework for comprehensive driver variant prediction in cancer.Communications medicine · 2025Article
- Feasibility of long-read sequencing to identify molecular alterations in an Indonesian cohort of locally advanced to advanced nasopharyngeal cancer.Scientific reports · 2025Article
- CanSeer: a translational methodology for developing personalized cancer models and therapeutics.Scientific reports · 2025Article
- Prioritizing genomic variants pathogenicity via DNA, RNA, and protein-level features based on extreme gradient boosting.Human genetics · 2025Article
- Identifying somatic driver mutations in cancer with a language model of the human genome.Computational and structural biotechnology journal · 2025Article
- Proteogenomic analysis reveals non-small cell lung cancer subtypes predicting chromosome instability, and tumor microenvironment.Nature communications · 2024Article
- VCAT: an integrated variant function annotation tools.Human genetics · 2024Article
- HYENA detects oncogenes activated by distal enhancers in cancer.Nucleic acids research · 2024Article
- A panel sequencing dataset of peripheral blood gene variations in pan-cancer.Scientific data · 2024Article
- Gsw-fi: a GLM model incorporating shrinkage and double-weighted strategies for identifying cancer driver genes with functional impact.BMC bioinformatics · 2024Article
- Computational analysis of protein-protein interactions of cancer drivers in renal cell carcinoma.FEBS open bio · 2024Article
- Genome-wide analyses reveal the contribution of somatic variants to the immune landscape of multiple cancer types.PLoS genetics · 2024Article
- Identification and validation of functional roles for three MYC-associated genes in hepatocellular carcinoma.Journal of advanced research · 2023Article
- Evaluation of input data modality choices on functional gene embeddings.NAR genomics and bioinformatics · 2023Article
2 more citing papers are in PubMed but not listed here.
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Authors and funding
10 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The prevalence of neutral mutations in cancer cell population impedes the distinguishing of cancer-causing driver mutations from passenger mutations. To systematically prioritize the oncogenic ability of somatic mutations and cancer genes, we constructed a useful platform, OncoVar (https://oncovar.org/), which employed published bioinformatics algorithms and incorporated known driver events to identify driver mutations and driver genes. We identified 20 162 cancer driver mutations, 814 driver genes and 2360 pathogenic pathways with high-confidence by reanalyzing 10 769 exomes from 33 cancer types in The Cancer Genome Atlas (TCGA) and 1942 genomes from 18 cancer types in International Cancer Genome Consortium (ICGC). OncoVar provides four points of view, 'Mutation', 'Gene', 'Pathway' and 'Cancer', to help researchers to visualize the relationships between cancers and driver variants. Importantly, identification of actionable driver alterations provides promising druggable targets and repurposing opportunities of combinational therapies. OncoVar provides a user-friendly interface for browsing, searching and downloading somatic driver mutations, driver genes and pathogenic pathways in various cancer types. This platform will facilitate the identification of cancer drivers across individual cancer cohorts and helps to rank mutations or genes for better decision-making among clinical oncologists, cancer researchers and the broad scientific community interested in cancer precision medicine.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.