Comprehensive prediction of robust synthetic lethality between paralog pairs in cancer cell lines
Comprehensive prediction of robust synthetic lethality between paralog pairs in cancer cell lines
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DOI：
10.1016/j.cels.2021.08.006
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发表时间：
2021-12-15
期刊：
影响因子：
9.3
通讯作者：
Ryan, Colm J.
中科院分区：
文献类型：
--
作者：
De Kegel, Barbara;Quinn, Niall;Ryan, Colm J.
成对的旁系同源物可能具有共同的功能，因此显示合成的致死相互作用。由于大多数人类基因具有可识别的旁系同源物，因此利用旁系同源物之间的合成致死性可能是靶向癌症中的基因丢失的广泛适用的方法。然而，迄今为止，只有一个有偏见的人类parabolites对的子集进行了合成致死性测试。在这里，通过分析700多个癌细胞系的全基因组CRISPR筛选和分子谱，我们确定了预测旁系同源物之间合成致死性的特征，包括共享的蛋白质-蛋白质相互作用和进化保守性。我们开发了一个基于这些特征的机器学习分类器，以预测哪些paramentum对最有可能是合成致命的，并解释为什么。我们表明，我们的分类器准确地预测了癌细胞系中组合CRISPR筛选的结果，并且还可以区分多个细胞系中合成致死的对与细胞系特异性的对。本文的透明同行评审过程的记录包括在补充信息中。
Pairs of paralogs may share common functionality and, hence, display synthetic lethal interactions. As the majority of human genes have an identifiable paralog, exploiting synthetic lethality between paralogs may be a broadly applicable approach for targeting gene loss in cancer. However, only a biased subset of human paralog pairs has been tested for synthetic lethality to date. Here, by analyzing genome-wide CRISPR screens and molecular profiles of over 700 cancer cell lines, we identify features predictive of synthetic lethality between paralogs, including shared protein-protein interactions and evolutionary conservation. We develop a machine-learning classifier based on these features to predict which paralog pairs are most likely to be synthetic lethal and to explain why. We show that our classifier accurately predicts the results of combinatorial CRISPR screens in cancer cell lines and furthermore can distinguish pairs that are synthetic lethal in multiple cell lines from those that are cell-line specific. A record of this paper's transparent peer review process is included in the supplemental information.