Srihari Sriganesh, Singla Jitin, Wong Limsoon, Ragan Mark A
Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Queensland, 4072, Australia.
Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Uttarakhand, 247667, India.
Biol Direct. 2015 Oct 1;10:57. doi: 10.1186/s13062-015-0086-1.
Synthetic lethality (SL) refers to the genetic interaction between two or more genes where only their co-alteration (e.g. by mutations, amplifications or deletions) results in cell death. In recent years, SL has emerged as an attractive therapeutic strategy against cancer: by targeting the SL partners of altered genes in cancer cells, these cells can be selectively killed while sparing the normal cells. Consequently, a number of studies have attempted prediction of SL interactions in human, a majority by extrapolating SL interactions inferred through large-scale screens in model organisms. However, these predicted SL interactions either do not hold in human cells or do not include genes that are (frequently) altered in human cancers, and are therefore not attractive in the context of cancer therapy.
Here, we develop a computational approach to infer SL interactions directly from frequently altered genes in human cancers. It is based on the observation that pairs of genes that are altered in a (significantly) mutually exclusive manner in cancers are likely to constitute lethal combinations. Using genomic copy-number and gene-expression data from four cancers, breast, prostate, ovarian and uterine (total 3980 samples) from The Cancer Genome Atlas, we identify 718 genes that are frequently amplified or upregulated, and are likely to be synthetic lethal with six key DNA-damage response (DDR) genes in these cancers. By comparing with published data on gene essentiality (~16000 genes) from ten DDR-deficient cancer cell lines, we show that our identified genes are enriched among the top quartile of essential genes in these cell lines, implying that our inferred genes are highly likely to be (synthetic) lethal upon knockdown in these cell lines. Among the inferred targets are tousled-like kinase 2 (TLK2) and the deubiquitinating enzyme ubiquitin-specific-processing protease 7 (USP7) whose overexpression correlates with poor survival in cancers.
Mutual exclusivity between frequently occurring genetic events identifies synthetic lethal combinations in cancers. These identified genes are essential in cell lines, and are potential candidates for targeted cancer therapy. Availability: http://bioinformatics.org.au/tools-data/underMutExSL
合成致死（SL）是指两个或多个基因之间的遗传相互作用，只有它们的共同改变（如通过突变、扩增或缺失）才会导致细胞死亡。近年来，合成致死已成为一种有吸引力的抗癌治疗策略：通过靶向癌细胞中改变基因的合成致死伙伴，可以选择性地杀死这些细胞，同时使正常细胞免受影响。因此，许多研究试图预测人类中的合成致死相互作用，大多数是通过推断在模式生物中大规模筛选得到的合成致死相互作用来进行外推。然而，这些预测的合成致死相互作用要么在人类细胞中不成立，要么不包括在人类癌症中（频繁）改变的基因，因此在癌症治疗背景下并不具有吸引力。
在这里，我们开发了一种计算方法，可直接从人类癌症中频繁改变的基因推断合成致死相互作用。该方法基于这样的观察：在癌症中以（显著）相互排斥方式改变的基因对可能构成致死组合。利用来自癌症基因组图谱的四种癌症（乳腺癌、前列腺癌、卵巢癌和子宫癌，共3980个样本）的基因组拷贝数和基因表达数据，我们鉴定出718个频繁扩增或上调的基因，这些基因在这些癌症中可能与六个关键的DNA损伤反应（DDR）基因形成合成致死。通过与来自十个DDR缺陷癌细胞系的已发表基因必需性数据（约16000个基因）进行比较，我们表明我们鉴定出的基因在这些细胞系中必需基因的前四分位数中富集，这意味着我们推断出的基因在这些细胞系中被敲低时极有可能是（合成）致死的。推断出的靶点包括类Tousled激酶2（TLK2）和去泛素化酶泛素特异性加工蛋白酶7（USP7），其过表达与癌症患者的不良生存相关。
频繁发生的遗传事件之间的相互排斥性确定了癌症中的合成致死组合。这些鉴定出的基因在细胞系中是必需的，是靶向癌症治疗的潜在候选基因。可用性：http://bioinformatics.org.au/tools-data/underMutExSL
