Department of Computer Science, Princeton University, Princeton, NJ, 08540, USA.
Department of Biomedical Informatics, Emory University, Atlanta, GA, 30322, USA.
Nat Commun. 2020 Feb 5;11(1):729. doi: 10.1038/s41467-020-14367-0.
The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancer across 38 tumor types, we perform multi-faceted pathway and network analyses of non-coding mutations across 2583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project that was motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes. While few non-coding genomic elements are recurrently mutated in this cohort, we identify 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We find that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing is primarily altered by non-coding mutations in this cohort, and samples containing non-coding mutations in well-known RNA splicing factors exhibit similar gene expression signatures as samples with coding mutations in these genes. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.
在过去的十年中，癌症驱动蛋白编码基因突变的目录大大扩展。然而，非编码癌症驱动突变的特征还不太清楚，只有少数反复出现的非编码突变被报道，最著名的是 TERT 启动子突变。在这里，作为 ICGC/TCGA 全基因组泛癌分析（PCAWG）联盟的一部分，该联盟聚合了来自 38 种肿瘤类型的 2658 种癌症的全基因组测序数据，我们对 27 种肿瘤类型的 2583 种全癌症基因组中的非编码突变进行了多方面的途径和网络分析，这些基因组是由 ICGC/TCGA PCAWG 项目编译的，该项目的动机是途径和网络分析在优先考虑蛋白质编码基因中的稀有突变方面取得了成功。虽然在这个队列中很少有非编码基因组元件经常发生突变，但我们确定了 93 个基因，这些基因中含有非编码突变，这些突变聚集成几个相互作用的蛋白质模块。其中包括与 TP53、TLE4 和 TCF4 中 mRNA 表达降低相关的启动子突变。我们发现，生物过程中编码和非编码突变的比例不同，染色质重塑和增殖途径主要由编码突变改变，而发育途径，包括 Wnt 和 Notch，由编码和非编码突变共同改变。在这个队列中，RNA 剪接主要由非编码突变改变，并且在这些基因中含有非编码突变的样本与含有这些基因中编码突变的样本表现出相似的基因表达特征。这些分析提供了一个新的可能的癌症基因和机制的组合，这些基因和机制被非编码突变改变，并提供了对可能的治疗靶点的额外癌症脆弱性的深入了解。
