Comprehensive identification of germline-somatic interactions

种系-体细胞相互作用的综合鉴定

基本信息

批准号：
10656304
负责人：
Ludmil B Alexandrov
金额：
$ 44.09万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-07-01 至 2027-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10656304
关键词：
Address Adult Affect Age Age of Onset Attention Bioinformatics Cancer Biology Cell physiology Clinical Communities Computer software DNA Repair Data Data Set Detection Development Diagnosis Disease Drug Screening Early Diagnosis Event Evolution Gene Expression Regulation Genes Genetic Genetic Variation Genome Genomics Germ-Line Mutation Goals Heterogeneity Human Immune Immune system Immunity Immunologic Surveillance Immunotherapy Individual Inherited Inter-tumoral heterogeneity Literature Malignant Childhood Neoplasm Malignant Neoplasms Molecular Morbidity - disease rate Mutagenesis Mutation Mutation Analysis Nature Normal tissue morphology Oncogenes Oncogenic Online Systems Outcome Pathway interactions Patients Pattern Penetrance Population Prevention therapy Process Prognosis Progression-Free Survivals Research Research Personnel Resources Retinoblastoma Role Sample Size Selection Criteria Shapes Signal Pathway Somatic Mutation Source Statistical Methods Survival Rate Technology Testing Tumor Biology Tumor Suppressor Proteins Validation Variant anticancer research bioinformatics pipeline bioinformatics tool cancer genome cancer genomics cancer predisposition cancer prevention cancer risk cancer therapy clinical phenotype clinically relevant cloud based computing resources design disorder risk exome fitness genetic profiling genetic variant genomic data genomic profiles insight inter-individual variation loss of function meetings molecular phenotype mortality neoplastic cell next generation sequencing novel personalized intervention response risk variant success targeted treatment tool treatment response tumor tumor progression tumorigenesis whole genome

项目摘要

Cancer remains a significant source of morbidity and mortality worldwide. Advances in next generation sequencing technologies have allowed extensive profiling of the genetic variants present in tumors and revealed daunting levels of inter-tumoral heterogeneity. Tumor genomic datasets have been extensively mined to reveal germline risk variants and to characterize heterogeneous patterns of somatic alteration that drive tumor progression. However, little attention has been given to interactions between genetic background and somatic changes, which could represent a major driver of heterogeneity. New evidence suggests that germline-somatic interactions are prevalent and our preliminary data support that some such interactions directly influence individual disease risk and potential to respond to therapies. This proposal will develop computational strategies to identify germline-somatic interactions and to characterize them in the context of molecular and clinical phenotypes, enabling new understanding of their role in inter-tumoral heterogeneity. Germline-somatic interactions have been challenging to study due to the limited amount of available data. To address this challenge, we have compiled tumor genomic data from public sources to boost our sample size to almost 45,000 tumor whole-exome and whole-genome sequences. Our analysis will focus on three major forces that shape the tumor genome: (i) the mutational processes that generate somatic mutations, (ii) the molecular organization of oncogenic pathways which determines the genes that can effectively drive cancer, and (iii) the immune system which acts as a selective force throughout tumor development. We will focus hypothesis testing with strict criteria for selecting germline variants and somatically altered genes likely to interact based on established tumor biology. To identify and characterize germline-somatic interactions we will: 1) Elucidate germline variants affecting the somatic mutational landscapes of human cancers 2) Reveal germline variants that modify somatic activation of hallmark oncogenic pathways 3) Establish the role of pathway-specific variant burden in cancer predisposition, overall survival, and response to immunotherapy Our team of co-investigators includes strong complementary expertise in analysis of mutational processes, genetic variation effects on molecular pathways and immunity, cancer biology, statistical methods and bioinformatic software dissemination. Careful attention will be given to statistical considerations including power, controlling false discovery rates, and validation in independent datasets. This proposal will produce A) novel bioinformatics tools designed specifically to detect and annotate germline-somatic interactions, B) new understanding of the contribution of germline variation to tumor progression, and C) a set of validated germline- somatic interactions affecting cancer risk, tumor evolution and immunotherapy response.

癌症仍然是全球发病率和死亡率的重要来源。下一代的进步测序技术允许对肿瘤中存在的遗传变异物进行广泛的分析，并揭示了肿瘤间异质性的艰巨水平。肿瘤基因组数据集已被广泛开采以揭示种系风险变异并表征驱动肿瘤的体细胞改变的异质模式进展。但是，很少关注遗传背景与躯体之间的相互作用变化，这可能代表了异质性的主要驱动力。新的证据表明种系及相互作用很普遍，我们的初步数据支持某些这种交互直接影响个体疾病的风险和对疗法反应的潜力。该建议将制定计算策略识别种系互相互作用并在分子和临床的背景下表征它们表型，使他们对它们在肿瘤间异质性中的作用有了新的了解。由于可用数据量有限，种系及其对研究的挑战。到应对这一挑战，我们已经从公共来源收集了肿瘤基因组数据，以使我们的样本量增加到近45,000个肿瘤全外观和全基因组序列。我们的分析将集中于三大力量这种塑造肿瘤基因组：（i）产生躯体突变的突变过程，（ii）分子组织致癌途径的组织，该途径确定可以有效驱动癌症的基因，以及（iii）免疫系统在整个肿瘤发育中充当选择性力。我们将集中于假设检验有严格的标准，用于选择种系变体和可能基于相互作用的体体改变基因建立的肿瘤生物学。为了识别和表征种系互动，我们将： 1）阐明影响人类癌症躯体突变景观的种系变体 2）揭示种系变体，以改变标志性致癌途径的体细胞激活 3）确定途径特异性变异负担在癌症易感性，整体生存和反应中的作用进行免疫疗法我们的共同投资者团队在分析突变过程中包括强大的补充专业知识，遗传变异对分子途径和免疫力，癌症生物学，统计方法和生物信息学软件传播。仔细注意统计考虑因素，包括权力，控制错误的发现率和独立数据集中的验证。该提议将产生a）小说专门旨在检测和注释种系互动的生物信息学工具，b）了解种系变异对肿瘤进展的贡献，c）一组经过验证的种系影响癌症风险，肿瘤进化和免疫疗法反应的体细胞相互作用。