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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. !

摘要