Detecting Mutational Signatures of Environmental Mutagens in Heathy Individuals for Personalized Cancer Prevention

项目总结 体细胞突变每天都在人体的每一个细胞中积累。这些突变源于突变 由于环境暴露、生活方式选择、蜂窝机械故障，甚至是正常的过程 细胞活动。每个突变过程都会在人的基因组上印记一种特有的突变模式 体细胞，称为“突变特征”。由于体细胞突变保留在细胞基因组中， 它们的后代，体细胞基因组中突变特征的存在，就是一个“考古印记” 在一个人的一生中起作用的突变过程的活动。最近的发展 的计算工具已经能够从癌症的DNA序列中识别突变特征 并量化个体癌症患者不同突变过程的活性。分析 世界各地数以千计的癌症患者现在已经发现了近80个不同的突变特征。 重要的是，对于这些患者中的每一个，我们现在都知道了导致他们癌症的突变过程 而且，对于其中许多患者，我们可以确定潜在的策略，以减少环境暴露和 预防他们的癌症。然而，有效和及时的癌症预防需要了解突变 在一个健康的人身上运行的过程，以及消除或减少这些过程的活动之前 那个人会患上癌症。不幸的是，目前还没有允许量化的方法 健康个体暴露在环境中的突变特征，因此，有许多机会 个人化的癌症预防被错过了。在这里，我们建议开发一种新的计算方法， 将允许非侵入性地监测健康人正常体细胞组织中的突变特征 个人。我们的方法将直接检测来自低覆盖率的体细胞突变特征 单细胞DNA测序数据，不依赖于体细胞突变的事先鉴定。这一方法将 使用以下单细胞DNA测序数据进行优化和验证：(I)暴露于 环境诱变剂；(Ii)消耗被强烈化学物质污染的水的体内小鼠模型 诱变剂；(3)已确定暴露于已知环境诱变剂的健康个人。总体而言，这 该项目将改变我们监测健康人正常组织中突变过程活动的能力 它将为个性化癌症预防打开大量机会，通过可能的 有针对性的干预措施，减少环境制剂和生活方式选择的诱变暴露。

PROJECT SUMMARY Somatic mutations accumulate daily in every cell of the human body. These mutations originate from mutational processes due to environmental exposures, lifestyle choices, defective cellular machineries, and even normal cellular activities. Each mutational process imprints a characteristic pattern of mutations on the genome of somatic cells, termed “mutational signature”. Since somatic mutations are retained in the genomes of cells and their progenies, the presence of mutational signatures in a somatic genome serves as an “archaeological imprint” of the activities of the mutational processes that were operative during a person’s lifetime. Recent developments of computational tools have allowed identifying mutational signatures from the DNA sequences of cancer samples and quantifying the activities of different mutational processes in individual cancer patients. Analysis of many thousands of cancer patients across the world has now revealed almost 80 distinct mutational signatures. Importantly, for each of these patients, we now know the mutational processes that have caused their cancers and, for many of these patients, we could identify potential strategies to reduce environmental exposures and prevent their cancers. However, an effective and timely cancer prevention requires knowing the mutational processes operating in a healthy individual and eliminating or reducing the activities of these processes before that individual develops cancer. Unfortunately, currently, there are no approaches that allow quantifying mutational signatures of environmental exposures in a healthy individual and, thus, many opportunities for personalize cancer prevention are missed. Here, we propose to develop a novel computational approach that will allow noninvasive monitoring of mutational signatures in easily accessible normal somatic tissues of healthy individuals. Our approach will perform a direct detection of somatic mutational signatures from low coverage single-cell DNA sequencing data without relying on prior identification of somatic mutations. The approach will be optimized and validated using single-cell DNA sequencing data from: (i) in vitro cell lines exposed to environmental mutagens; (ii) an in vivo mouse model consuming water contaminated with a strong chemical mutagen; (iii) healthy individuals with established exposures to known environmental mutagens. Overall, this project will transform our ability to monitor the activities of the mutational processes in normal tissues of healthy individuals and it will open a plethora of opportunities for personalized cancer prevention through possible targeted interventions that reduce mutagenic exposures from environment agents and lifestyle choices.