Literature DB >> 28968730

Identifying mutual exclusivity across cancer genomes: computational approaches to discover genetic interaction and reveal tumor vulnerability.

Yulan Deng1, Shangyi Luo1, Chunyu Deng1, Tao Luo1, Wenkang Yin1, Hongyi Zhang1, Yong Zhang1, Xinxin Zhang1, Yujia Lan1, Yanyan Ping1, Yun Xiao1, Xia Li1.   

Abstract

Systematic sequencing of cancer genomes has revealed prevalent heterogeneity, with patients harboring various combinatorial patterns of genetic alteration. In particular, a phenomenon that a group of genes exhibits mutually exclusive patterns has been widespread across cancers, covering a broad spectrum of crucial cancer pathways. Recently, there is considerable evidence showing that, mutual exclusivity reflects alternative functions in tumor initiation and progression, or suggests adverse effects of their concurrence. Given its importance, numerous computational approaches have been proposed to study mutual exclusivity using genomic profiles alone, or by integrating networks and phenotypes. Some of them have been routinely used to explore genetic associations, which lead to a deeper understanding of carcinogenic mechanisms and reveals unexpected tumor vulnerabilities. Here, we present an overview of mutual exclusivity from the perspective of cancer genome. We describe the common hypothesis underlying mutual exclusivity, summarize the strategies for the identification of significant mutually exclusive patterns, compare the performance of representative algorithms from simulated data sets and discuss their common confounders.

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Year:  2019        PMID: 28968730     DOI: 10.1093/bib/bbx109

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  8 in total

1.  Identifying collateral and synthetic lethal vulnerabilities within the DNA-damage response.

Authors:  Pietro Pinoli; Sriganesh Srihari; Limsoon Wong; Stefano Ceri
Journal:  BMC Bioinformatics       Date:  2021-05-15       Impact factor: 3.169

2.  A pan-cancer atlas of cancer hallmark-associated candidate driver lncRNAs.

Authors:  Yulan Deng; Shangyi Luo; Xinxin Zhang; Chaoxia Zou; Huating Yuan; Gaoming Liao; Liwen Xu; Chunyu Deng; Yujia Lan; Tingting Zhao; Xu Gao; Yun Xiao; Xia Li
Journal:  Mol Oncol       Date:  2018-10-02       Impact factor: 6.603

3.  Identifying Mutually Exclusive Gene Sets with Prognostic Value and Novel Potential Driver Genes in Patients with Glioblastoma.

Authors:  Qian Gao; Yan Cui; Yanan Shen; Yanyan Li; Xue Gao; Yanfeng Xi; Tong Wang
Journal:  Biomed Res Int       Date:  2019-11-05       Impact factor: 3.411

4.  An Effective Graph Clustering Method to Identify Cancer Driver Modules.

Authors:  Wei Zhang; Yifu Zeng; Lei Wang; Yue Liu; Yi-Nan Cheng
Journal:  Front Bioeng Biotechnol       Date:  2020-04-07

5.  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

6.  gcMECM: graph clustering of mutual exclusivity of cancer mutations.

Authors:  Ying Hu; Chunhua Yan; Qingrong Chen; Daoud Meerzaman
Journal:  BMC Bioinformatics       Date:  2021-12-14       Impact factor: 3.169

7.  A systematic analysis of genetic interactions and their underlying biology in childhood cancer.

Authors:  Josephine T Daub; Saman Amini; Denise J E Kersjes; Xiaotu Ma; Natalie Jäger; Jinghui Zhang; Stefan M Pfister; Frank C P Holstege; Patrick Kemmeren
Journal:  Commun Biol       Date:  2021-10-06

Review 8.  Cross-Talk between p53 and Wnt Signaling in Cancer.

Authors:  Qiyun Xiao; Johannes Werner; Nachiyappan Venkatachalam; Kim E Boonekamp; Matthias P Ebert; Tianzuo Zhan
Journal:  Biomolecules       Date:  2022-03-15
  8 in total

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