1. OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers
- Author
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Tao Wang, Huajing Teng, Zhong Sheng Sun, Fengbiao Mao, Mingcong You, Shasha Ruan, Xiaolu Zhao, Jianing Zhong, Kun Xia, and Xiaohui Shi
- Subjects
Carcinogenesis ,AcademicSubjects/SCI00010 ,Population ,Druggability ,Computational biology ,Biology ,Genome ,03 medical and health sciences ,0302 clinical medicine ,Neoplasms ,Databases, Genetic ,Genetics ,Humans ,Database Issue ,Exome ,education ,Gene ,Exome sequencing ,030304 developmental biology ,Internet ,0303 health sciences ,education.field_of_study ,Computational Biology ,Molecular Sequence Annotation ,Oncogenes ,Precision medicine ,Neoplasm Proteins ,Gene Expression Regulation, Neoplastic ,030220 oncology & carcinogenesis ,Mutation ,human activities ,Algorithms ,Metabolic Networks and Pathways ,Software ,Neutral mutation - 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.
- Published
- 2020