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OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers

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.o...

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Autores principales: Wang, Tao, Ruan, Shasha, Zhao, Xiaolu, Shi, Xiaohui, Teng, Huajing, Zhong, Jianing, You, Mingcong, Xia, Kun, Sun, Zhongsheng, Mao, Fengbiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778899/
https://www.ncbi.nlm.nih.gov/pubmed/33179738
http://dx.doi.org/10.1093/nar/gkaa1033
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author Wang, Tao
Ruan, Shasha
Zhao, Xiaolu
Shi, Xiaohui
Teng, Huajing
Zhong, Jianing
You, Mingcong
Xia, Kun
Sun, Zhongsheng
Mao, Fengbiao
author_facet Wang, Tao
Ruan, Shasha
Zhao, Xiaolu
Shi, Xiaohui
Teng, Huajing
Zhong, Jianing
You, Mingcong
Xia, Kun
Sun, Zhongsheng
Mao, Fengbiao
author_sort Wang, Tao
collection PubMed
description 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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spelling pubmed-77788992021-01-06 OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers Wang, Tao Ruan, Shasha Zhao, Xiaolu Shi, Xiaohui Teng, Huajing Zhong, Jianing You, Mingcong Xia, Kun Sun, Zhongsheng Mao, Fengbiao Nucleic Acids Res Database Issue 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. Oxford University Press 2020-11-12 /pmc/articles/PMC7778899/ /pubmed/33179738 http://dx.doi.org/10.1093/nar/gkaa1033 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database Issue
Wang, Tao
Ruan, Shasha
Zhao, Xiaolu
Shi, Xiaohui
Teng, Huajing
Zhong, Jianing
You, Mingcong
Xia, Kun
Sun, Zhongsheng
Mao, Fengbiao
OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers
title OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers
title_full OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers
title_fullStr OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers
title_full_unstemmed OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers
title_short OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers
title_sort oncovar: an integrated database and analysis platform for oncogenic driver variants in cancers
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778899/
https://www.ncbi.nlm.nih.gov/pubmed/33179738
http://dx.doi.org/10.1093/nar/gkaa1033
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