Literature DB >> 33179738

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

Tao Wang1,2, Shasha Ruan3, Xiaolu Zhao4, Xiaohui Shi2, Huajing Teng2, Jianing Zhong5, Mingcong You6, Kun Xia1,7,8, Zhongsheng Sun2,9,10, Fengbiao Mao11.   

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.
© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.

Entities:  

Year:  2020        PMID: 33179738     DOI: 10.1093/nar/gkaa1033

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  20 in total

1.  Comprehensive evaluation of computational methods for predicting cancer driver genes.

Authors:  Xiaohui Shi; Huajing Teng; Leisheng Shi; Wenjian Bi; Wenqing Wei; Fengbiao Mao; Zhongsheng Sun
Journal:  Brief Bioinform       Date:  2022-03-10       Impact factor: 11.622

2.  CircleBase: an integrated resource and analysis platform for human eccDNAs.

Authors:  Xiaolu Zhao; Leisheng Shi; Shasha Ruan; Wenjian Bi; Yifan Chen; Lin Chen; Yifan Liu; Mingkun Li; Jie Qiao; Fengbiao Mao
Journal:  Nucleic Acids Res       Date:  2022-01-07       Impact factor: 16.971

3.  Genetic association and single-cell transcriptome analyses reveal distinct features connecting autoimmunity with cancers.

Authors:  Shasha Li; Chenyang Lu; Yuan Zhang; Xiaolu Zhao; Kequan Lin; Xiufang Kong; David Fox; Lixiang Xue; Lichao Sun; Yi Liu; Fengbiao Mao
Journal:  iScience       Date:  2022-06-17

4.  Inferring Potential Cancer Driving Synonymous Variants.

Authors:  Zishuo Zeng; Yana Bromberg
Journal:  Genes (Basel)       Date:  2022-04-27       Impact factor: 4.141

5.  DeepND: Deep multitask learning of gene risk for comorbid neurodevelopmental disorders.

Authors:  Ilayda Beyreli; Oguzhan Karakahya; A Ercument Cicek
Journal:  Patterns (N Y)       Date:  2022-06-02

6.  Integrated Bioinformatic Analysis of SARS-CoV-2 Infection Related Genes ACE2, BSG and TMPRSS2 in Aerodigestive Cancers.

Authors:  Chaobin He; Xin Hua; Shuxin Sun; Shaolong Li; Jun Wang; Xin Huang
Journal:  J Inflamm Res       Date:  2021-03-10

7.  The 2021 Nucleic Acids Research database issue and the online molecular biology database collection.

Authors:  Daniel J Rigden; Xosé M Fernández
Journal:  Nucleic Acids Res       Date:  2021-01-08       Impact factor: 16.971

8.  driveR: a novel method for prioritizing cancer driver genes using somatic genomics data.

Authors:  Ege Ülgen; O Uğur Sezerman
Journal:  BMC Bioinformatics       Date:  2021-05-24       Impact factor: 3.169

9.  A Network-Centric Framework for the Evaluation of Mutual Exclusivity Tests on Cancer Drivers.

Authors:  Rafsan Ahmed; Cesim Erten; Aissa Houdjedj; Hilal Kazan; Cansu Yalcin
Journal:  Front Genet       Date:  2021-11-26       Impact factor: 4.599

10.  The Identification of Stemness-Related Genes in the Risk of Head and Neck Squamous Cell Carcinoma.

Authors:  Guanying Feng; Feifei Xue; Yingzheng He; Tianxiao Wang; Hua Yuan
Journal:  Front Oncol       Date:  2021-06-11       Impact factor: 6.244

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