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一种用于检测肿瘤突变谱差异的不依赖特征的测试揭示了致癌物和祖先效应。

A signature-agnostic test for differences between tumor mutation spectra reveals carcinogen and ancestry effects.

作者信息

Hart Samuel F M, Alcala Nicolas, Feder Alison F, Harris Kelley

机构信息

Department of Genome Sciences, University of Washington, Seattle, USA.

Computational Cancer Genomics Team, International Agency for Research on Cancer (IARC/WHO), Genomic Epidemiology Branch, Lyon, France.

出版信息

bioRxiv. 2025 May 19:2025.05.15.654154. doi: 10.1101/2025.05.15.654154.

Abstract

Mutational signatures contain valuable information about the mutational processes shaping cancer genomes. However, despite dozens of tools to identify signatures in cancer samples, there is not an established metric for statistically comparing mutational signature results and quantifying the overall significance of differences among complex mixtures of signatures. To close this methodological gap, we demonstrate that a signature-agnostic metric for measuring differences in mutation spectra - the aggregate mutation spectrum distance permutation method (AMSD) - can discover differences overlooked by signature analysis. First, we reanalyzed a study of carcinogen exposure in mice, identifying statistically significant shifts in mutation spectra caused by eleven of twenty tested carcinogens. Only three carcinogens were previously reported to induce distinct mutation signatures, suggesting that many carcinogens perturb mutagenesis by altering the composition of endogenous signatures rather than introducing unique signatures. Next, we used human tumor data to determine whether patient ancestry has a measurable impact on tumor mutation spectra, finding significant ancestry-associated differences across ten cancer types: for example, Africans have elevated SBS4 in lung adenocarcinomas, East Asians have elevated SBS16 in esophageal and liver cancers plus elevated SBS10a/b in uterine and colorectal cancers, and Europeans have elevated SBS17b in esophageal cancers plus elevated SBS2/13 in bladder cancers. These examples suggest that AMSD is a robust tool for detecting differences among tumor mutation spectra, complementing signature-based approaches and enabling the discovery of environmental and genetic influences on mutagenesis in large datasets.

摘要

突变特征包含有关塑造癌症基因组的突变过程的宝贵信息。然而,尽管有数十种工具可用于识别癌症样本中的特征,但尚无一种既定的指标来对突变特征结果进行统计学比较,也无法量化复杂特征混合物之间差异的总体显著性。为了填补这一方法学空白,我们证明了一种用于测量突变谱差异的与特征无关的指标——聚集突变谱距离置换法(AMSD)——可以发现特征分析所忽略的差异。首先,我们重新分析了一项关于小鼠致癌物暴露的研究,确定了二十种受试致癌物中的十一种所导致的突变谱的统计学显著变化。此前仅报道了三种致癌物可诱导独特的突变特征,这表明许多致癌物是通过改变内源性特征的组成而非引入独特特征来干扰诱变作用的。接下来,我们使用人类肿瘤数据来确定患者血统是否对肿瘤突变谱有可测量的影响,发现在十种癌症类型中存在与血统相关的显著差异:例如,非洲人肺腺癌中的SBS4升高,东亚人食管癌和肝癌中的SBS16升高,子宫癌和结直肠癌中的SBS10a/b升高,欧洲人食管癌中的SBS17b升高,膀胱癌中的SBS2/13升高。这些例子表明,AMSD是检测肿瘤突变谱差异的强大工具,它补充了基于特征的方法,并能够在大型数据集中发现环境和遗传因素对诱变作用的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26d4/12139916/6807090b6c18/nihpp-2025.05.15.654154v1-f0001.jpg

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