Regional mutational signature activities in cancer genomes.
Regional mutational signature activities in cancer genomes.
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癌症基因组中的区域突变签名活性。
DOI：
10.1371/journal.pcbi.1010733
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发表时间：
2022-12
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
--
作者：
癌症基因组包含一系列体细胞突变。这些突变的类型和基因组背景取决于它们的原因，并允许它们归因于特定的突变特征。以前的工作已经表明，突变签名活动在肿瘤发展过程中发生变化，但对突变签名中基因组区域变异性的研究有限。在这里，我们通过使用全基因组泛癌症分析（PCAWG）联盟汇总的数据，构建25种肿瘤类型的2，203个全基因组的突变特征活动的区域概况，扩展了这项工作。我们目前的基因组TrackSig作为扩展的TrackSig R包构建区域签名配置文件使用最佳分割和期望最大化（EM）算法。我们发现，来自20种肿瘤类型的426个基因组显示出至少一个突变特征活动（变点）的变化，306个基因组包含由7个或更多相同肿瘤类型的基因组共享的54个复发性变点中的至少一个。多种肿瘤类型共有五个复发性变点位置。在这些区域内，特定的签名变化通常在相同类型的样品之间是一致的，并且一些但不是全部的特征在于与亚克隆扩增相关的签名。我们发现的变化点不能严格地用基因密度、突变密度或原细胞染色质状态来解释。我们假设，它们反映了一个汇合的因素，包括突变过程的进化时间，体细胞突变率的区域差异，染色质状态的大规模变化，可能是组织类型特异性，和亚克隆扩增过程中染色质可及性的变化。这些结果提供了深入了解DNA损伤和修复过程的区域效应，并可能帮助我们定位癌症发展过程中发生的基因组和表观基因组变化。体细胞突变通过癌症发展积累。这些突变是DNA损伤和DNA修复缺陷的结果;在某些情况下，这些突变来源可以通过将突变归因于不同的突变特征来恢复。突变标记描述了共发生的取代类型的模式（例如，C至A）与各种诱变过程相关。例如，紫外线辐射导致CpC到TpT的取代，吸烟诱变剂与C到A的取代有关。以前的工作表明，癌症基因组中的突变特征活动在癌症发展过程中发生变化。关于它们的活动如何在整个基因组中变化的知之甚少，这与理解DNA损伤和修复缺陷的区域影响有关。我们已经开发了一种生物信息学工具GenomeTrackSig，它使用分割算法来估计大染色体域中的突变签名活动，并确定活动变化的变化点。我们将GenomeTrackSig应用于2，203个癌症基因组，发现426个包含变化点。一些变化点在相同类型的多个样本中重复出现，并且一些变化点还表现出在早期或晚期癌症发展中活跃的特征之间的活性权衡。突变点不能很好地解释基因组因素，通常有助于突变率的变化。我们假设它们是由多种因素共同驱动的，包括在癌症演变过程中可能发生的染色质状态的大规模变化。
Cancer genomes harbor a catalog of somatic mutations. The type and genomic context of these mutations depend on their causes and allow their attribution to particular mutational signatures. Previous work has shown that mutational signature activities change over the course of tumor development, but investigations of genomic region variability in mutational signatures have been limited. Here, we expand upon this work by constructing regional profiles of mutational signature activities over 2,203 whole genomes across 25 tumor types, using data aggregated by the Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium. We present GenomeTrackSig as an extension to the TrackSig R package to construct regional signature profiles using optimal segmentation and the expectation-maximization (EM) algorithm. We find that 426 genomes from 20 tumor types display at least one change in mutational signature activities (changepoint), and 306 genomes contain at least one of 54 recurrent changepoints shared by seven or more genomes of the same tumor type. Five recurrent changepoint locations are shared by multiple tumor types. Within these regions, the particular signature changes are often consistent across samples of the same type and some, but not all, are characterized by signatures associated with subclonal expansion. The changepoints we found cannot strictly be explained by gene density, mutation density, or cell-of-origin chromatin state. We hypothesize that they reflect a confluence of factors including evolutionary timing of mutational processes, regional differences in somatic mutation rate, large-scale changes in chromatin state that may be tissue type-specific, and changes in chromatin accessibility during subclonal expansion. These results provide insight into the regional effects of DNA damage and repair processes, and may help us localize genomic and epigenomic changes that occur during cancer development. Somatic mutations accumulate through cancer development. These mutations are the result of DNA damage and DNA repair deficiencies; in some cases these mutation sources can be recovered by attributing mutations to different mutational signatures. Mutational signatures describe patterns of co-occurring substitution types (e.g., C to A) that are associated with various mutagenic processes. For example, UV radiation causes CpC to TpT substitutions, and smoking mutagens are associated with C to A substitution. Previous work has shown that mutational signature activities in cancer genomes change over the course of a cancer’s development. Less is known about how their activities change across the entire genome, which is relevant for understanding the regional effects of DNA damage and repair deficiencies. We have developed a bioinformatic tool GenomeTrackSig, which uses a segmentation algorithm to estimate mutational signature activities across large chromosomal domains and identify changepoints where activities vary. We apply GenomeTrackSig to 2,203 cancer genomes and find that 426 contain changepoints. Some changepoints recur across multiple samples of the same type, and some also exhibit activity tradeoffs between signatures active in either early or late cancer development. Changepoints cannot be explained well by genomic factors that typically contribute to mutation rate variation. We hypothesize that they are driven by a confluence of factors, including large-scale changes in chromatin state that may occur over cancer evolution.
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影响因子：
3.7
作者：
MASSEY, FJ
通讯作者：
MASSEY, FJ
影响因子：
12.3
作者：
Fortin JP;Hansen KD
通讯作者：
Hansen KD
影响因子：
64.5
作者：
Haradhvala NJ;Polak P;Stojanov P;Covington KR;Shinbrot E;Hess JM;Rheinbay E;Kim J;Maruvka YE;Braunstein LZ;Kamburov A;Hanawalt PC;Wheeler DA;Koren A;Lawrence MS;Getz G
通讯作者：
Getz G
影响因子：
16.6
作者：
Ding Q;Edwards MM;Wang N;Zhu X;Bracci AN;Hulke ML;Hu Y;Tong Y;Hsiao J;Charvet CJ;Ghosh S;Handsaker RE;Eggan K;Merkle FT;Gerhardt J;Egli D;Clark AG;Koren A
通讯作者：
Koren A
影响因子：
30.8
作者：
Akdemir, Kadir C.;Le, Victoria T.;Zhang, Cheng-Zhong
通讯作者：
Zhang, Cheng-Zhong