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

基本信息

批准号：
10584470
负责人：
Subhajyoti De
金额：
$ 35.78万
依托单位：
RUTGERS BIOMEDICAL AND HEALTH SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-04-01 至 2025-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10584470
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 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 cancer genomics computer framework epigenomics experimental study genetic association 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

项目摘要

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. !

抽象的在正常发育期间，衰老和癌症，例如癌症，内源性和外部因素和维修缺陷导致不同类型的体细胞突变的积累单核苷酸取代，小插入，拷贝数改变，易位和倍增性变化。尽管基因组中绝大多数的体细胞突变不是疾病驱动因素，但它们的遗传模式变化和相关环境可以提供对过去暴露于诱变剂的机制的见解损害和修复缺陷以及基因组不稳定性的程度，这对于理解疾病很重要病因，最大程度地减少危险环境暴露，还可以预测新兴治疗的功效诸如免疫疗法之类的策略。基于局部已经确定了许多突变签名序列上下文以满足此需求。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上下文都有待理解的表观基因组上下文还有待理解新兴突变特征可以在全基因组上提供关键的互补病因见解比例，仅从序列上下文中就明显了。这是至关重要的，因为（i）许多新兴突变特征的病因目前尚不清楚，（ii）DNA损伤反应和维修取决于组织环境，核心DNA修复基因缺陷通常会导致癌症的发展组织特异性的方式以及（iii）茎和修复程度的差异相同组织中的分化细胞对衰老和疾病的发病率有后果。建造从逻辑上讲，关于我们以前的作品，我们建议开发计算方法，以确定关于组织类型内和跨组织类型的体细胞突变模式的表观基因组情境，并验证使用目标实验进行计算预测。在AIM-1中，我们将发展一个表观基因组的环境新兴突变特征的偏好图。在AIM-2中，我们将确定组织依赖性的基础归因于DNA修复缺陷的突变曲线的差异。在AIM-3中，我们将预测细胞的程度突变的谱系依赖性模式从末端细胞的突变景观中积累。我是目前是一名早期调查员，该提案与我的长期目标保持一致，以确定基本躯体基因组的可突变性和可转化性原理。我们的项目将提供新颖的资源，在开发和衰老期间解决有关基因组完整性问题的知识以及疾病例如癌症。呢