Computational approaches for identifying epigenomic contexts of somatic mutations

识别体细胞突变表观基因组背景的计算方法

• 批准号: 9902467
• 负责人: Subhajyoti De
• 金额: $ 32.44万
• 依托单位: RBHS -CANCER INSTITUTE OF NEW JERSEY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9902467
• 关键词: Address; Affect; Aging; Biometry; Blood; Cancer Etiology; Cancer Relapse; Cell Differentiation process; Cell Line; Cell Lineage; Cells; Chromatin; Clinical; Computational Biology; DNA Damage; DNA Repair; DNA Repair Gene; DNA Repair Pathway; Data; Defect; Development; Disease; Doctor of Philosophy; Environmental Exposure; Epigenetic Process; Etiology; Evolution; Exposure to; Genome; Genomic DNA; Genomic Instability; Genomics; Goals; Immunotherapy; Incidence; Knowledge; Least-Squares Analysis; Location; Maintenance; Malignant Neoplasms; Maps; Modeling; Mutagenesis; Mutagens; Mutation; Nuclear; Nucleotides; Pathway interactions; Pattern; Ploidies; Point Mutation; Process; Publishing; Radiation Tolerance; Research Personnel; Resources; Role; Somatic Mutation; Source; Tissues; Work; base; cancer genomics; computer framework; epigenomics; experimental study; genome integrity; genome-wide; human tissue; improved; insertion/deletion mutation; insight; markov model; medical schools; novel; preference; public health relevance; random forest; repaired; response; stem; stem cells; tissue stem cells; transcriptomics; treatment strategy

ABSTRACT During normal development, aging, and diseases such as cancer, DNA damage due to endogenous and external factors, and repair defects result in accumulation of different types of somatic mutations including single nucleotide substitutions, small InDels, copy number alterations, translocations, and ploidy changes. While a vast majority of somatic mutations in the genome are not disease drivers, their patterns of genetic changes and associated context can provide insights into past exposure to mutagens, mechanisms of DNA damage and repair defects, and extent of genomic instability, which are important for understanding disease etiology, minimizing hazardous environmental exposure, and also predicting efficacy of emerging treatment strategies such as immunotherapy. A number of mutation signatures have been identified based on local sequence contexts to address this need. But, mechanisms of DNA damage and repair preferences depend on both local sequence and epigenomic contexts, and it remains to be understood whether epigenomic contexts of emerging mutation signatures can provide critical, complementary etiological insights at a genome-wide scale, which are not apparent from sequence contexts alone. This is of fundamental importance, because (i) etiology of many of the emerging mutation signatures is currently unknown, (ii) DNA damage response and repair depends on tissue contexts, and defects in core DNA repair genes often result in cancer development in tissue-specific manner, and (iii) differences in the extent of DNA damage and repair between stem and differentiated cells within the same tissues have consequences for aging and disease incidence rates. Built logically on our previous works, we propose to develop computational approaches to determine the impact of epigenomic contexts on the patterns of somatic mutations within and across tissue types, and validate computational predictions using targeted experiments. In Aim-1, we will develop an epigenomic context preference map for emerging mutation signatures. In Aim-2, we will determine the basis of tissue-dependent differences in mutation profiles attributed to DNA repair defects. In Aim-3, we will predict the extent of cell lineage-dependent patterns of mutation accumulation from the mutational landscape of terminal cells. I am currently an early stage investigator, and the proposal is aligned with my long-term goal to identify fundamental principles of mutability and evolvability of somatic genomes. Our project will deliver novel resources and knowledge for addressing questions regarding genomic integrity during development and aging, and diseases such as cancer. !

摘要 在正常发育、衰老和癌症等疾病期间，由于内源性和内源性DNA损伤， 外部因素和修复缺陷导致不同类型的体细胞突变的积累，包括 单核苷酸取代、小InDel、拷贝数改变、易位和倍性变化。 虽然基因组中的绝大多数体细胞突变不是疾病驱动因素，但它们的基因突变模式可能是疾病的驱动因素。 变化和相关的背景可以提供对过去暴露于诱变剂，DNA的机制， 损伤和修复缺陷，以及基因组不稳定性的程度，这对理解疾病很重要 病因学，最大限度地减少危险环境暴露，并预测新兴治疗的疗效 如免疫疗法。已经基于局部的突变特征识别了许多突变特征。 序列上下文来满足这种需求。但是，DNA损伤和修复偏好的机制取决于 局部序列和表观基因组背景，以及表观基因组背景是否 新出现的突变签名可以在全基因组范围内提供关键的，互补的病因学见解， 规模，这是不明显的序列上下文单独。这是非常重要的，因为（一） 许多新出现的突变特征的病因目前尚不清楚，（ii）DNA损伤反应和 修复取决于组织环境，核心DNA修复基因的缺陷通常会导致癌症的发展， 组织特异性的方式，以及（iii）茎和茎之间DNA损伤和修复程度的差异。 同一组织内的分化细胞对衰老和疾病发病率有影响。建造 逻辑上，我们以前的工作，我们建议发展计算方法来确定的影响， 表观基因组背景下的体细胞突变的模式内和跨组织类型，并验证 使用有针对性的实验进行计算预测。在Aim-1中，我们将开发表观基因组背景 新出现的突变特征的偏好图。在Aim-2中，我们将确定组织依赖性 突变谱的差异归因于DNA修复缺陷。在Aim-3中，我们将预测细胞的范围 来自终末细胞突变景观的突变积累的谱系依赖模式。我是 目前是一个早期阶段的研究者，该提案符合我的长期目标，即确定基本的 体细胞基因组的可变性和进化性原理。我们的项目将提供新的资源， 解决发育和衰老过程中基因组完整性问题的知识，以及疾病 例如癌症。 !