Multi-omic measurement of mutually exclusive loss-of-function enriches for candidate synthetic lethal gene pairs

BMC Genomics

Research Article

Mark Wappett¹  James R. Bradford²  Austin Dulak³  Jonathan R. Dry³  Abdullatif Al-Watban⁴  Zheng Rong Yang⁴ 

[1] Oncology Innovative Medicines, AstraZeneca, Macclesfield, UK;Oncology Innovative Medicines, AstraZeneca, Macclesfield, UK;Present address: Department of Oncology, University of Sheffield, Sheffield, UK;Oncology Innovative Medicines, AstraZeneca, Waltham, USA;School of Biosciences, University of Exeter, Exeter, UK;

关键词: Bioinformatics;    Transcriptomics;    Synthetic lethality;    R;    Epigenetics;    Functional genomics;    Cancer;    Cell line;   

DOI  :  10.1186/s12864-016-2375-1

 received in 2015-08-27, accepted in 2016-01-06,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundIdentification of synthetic lethal interactions in cancer cells could offer promising new therapeutic targets. Large-scale functional genomic screening presents an opportunity to test large numbers of cancer synthetic lethal hypotheses. Methods enriching for candidate synthetic lethal targets in molecularly defined cancer cell lines can steer effective design of screening efforts. Loss of one partner of a synthetic lethal gene pair creates a dependency on the other, thus synthetic lethal gene pairs should never show simultaneous loss-of-function. We have developed a computational approach to mine large multi-omic cancer data sets and identify gene pairs with mutually exclusive loss-of-function. Since loss-of-function may not always be genetic, we look for deleterious mutations, gene deletion and/or loss of mRNA expression by bimodality defined with a novel algorithm BiSEp.ResultsApplying this toolkit to both tumour cell line and patient data, we achieve statistically significant enrichment for experimentally validated tumour suppressor genes and synthetic lethal gene pairings. Notably non-reliance on genetic loss reveals a number of known synthetic lethal relationships otherwise missed, resulting in marked improvement over genetic-only predictions. We go on to establish biological rationale surrounding a number of novel candidate synthetic lethal gene pairs with demonstrated dependencies in published cancer cell line shRNA screens.ConclusionsThis work introduces a multi-omic approach to define gene loss-of-function, and enrich for candidate synthetic lethal gene pairs in cell lines testable through functional screens. In doing so, we offer an additional resource to generate new cancer drug target and combination hypotheses. Algorithms discussed are freely available in the BiSEp CRAN package at http://cran.r-project.org/web/packages/BiSEp/index.html.

【 授权许可】

CC BY   
© Wappett et al. 2016