College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Brief Bioinform. 2019 Jan 18;20(1):254-266. doi: 10.1093/bib/bbx109.
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.
癌症基因组的系统测序揭示了普遍存在的异质性,患者携带各种组合的遗传改变模式。特别是,一组基因表现出相互排斥模式的现象在癌症中广泛存在,涵盖了广泛的关键癌症途径。最近,有相当多的证据表明,相互排斥性反映了肿瘤发生和进展中的替代功能,或者提示它们同时存在的不利影响。鉴于其重要性,已经提出了许多计算方法来仅使用基因组谱或通过整合网络和表型来研究相互排斥性。其中一些方法已被常规用于探索遗传关联,从而更深入地了解致癌机制并揭示出意想不到的肿瘤脆弱性。在这里,我们从癌症基因组的角度概述了相互排斥性。我们描述了相互排斥性的常见假设,总结了识别显著相互排斥模式的策略,比较了模拟数据集的代表性算法的性能,并讨论了它们的常见混杂因素。