Mutographs differentiating the racial and temporal incidence of multiple myeloma

区分多发性骨髓瘤种族和时间发病率的突变特征

• 批准号: 10217670
• 负责人: Gareth John Morgan
• 金额: $ 123.48万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-11 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10217670
• 关键词: 16S ribosomal RNA sequencing; Address; Adenine; Affinity; African American; Age of Onset; Alabama; American; Antigens; Archaeology; Biocompatible Materials; Biological; Biometry; Bone Marrow; Cancer Center; Case Study; Chronic; Chronology; Clinical; Collection; Comprehensive Cancer Center; Computational algorithm; Cross-Sectional Studies; DNA; Data; Data Set; Deaminase; Disease; Environment; Environmental Exposure; Epidemiology; Etiology; European; Event; Exposure to; Fingerprint; Generations; Genetic; Genetic Predisposition to Disease; Genomics; Goals; Immune; Immune response; Immunologics; Immunosuppression; Incidence; Indiana; Individual; Induced Mutation; Inflammation; Infrastructure; Intervention; Knowledge; Link; Longitudinal cohort study; Malignant Neoplasms; Mediating; Memorial Sloan-Kettering Cancer Center; Molecular; Molecular Abnormality; Monoclonal gammopathy of uncertain significance; Multiple Myeloma; Mutation; New York; Pathogenesis; Pathologic Mutagenesis; Phase; Play; Process; Prospective cohort study; Race; Reaction; Risk; Role; Sampling; Series; Structure of germinal center of lymph node; System; T cell response; T-Lymphocyte; Therapeutic; Time; Universities; anticancer research; base; biobank; early onset; effective intervention; genetic variant; genome sequencing; gut microbiome; gut microbiota; high risk; immunological status; insight; microbiome; pre-clinical; premalignant; racial difference; racial disparity; racial diversity; racial population; reconstruction; response; tumor-immune system interactions; whole genome

PROJECT SUMMARY/ABSTRACT African Americans (AA) have a higher incidence of multiple myeloma (MM) compared to European Americans (EA) due to genetic predisposition, environmental exposure or both. MM is preceded by two precursor phases, monoclonal gammopathy of undetermined significance (MGUS) and smoldering myeloma (SMM) that are also increased in AA. We have shown using European MM samples that there is a long lag period between the genetic initiation of the disease and the time at which precursor clinical stages are detectable. It is critical to understand the genetic basis of these early evolutionary steps if we are to truly understand the excess risk of MM in AA. During the evolutionary progression of MM after genetic initiation, genetic hits are accumulated providing a unique archeological fingerprint of the mutational signatures or “mutographs” over time. Using whole genome sequencing (WGS) analyzed with advanced computer algorithms based on a-priori knowledge of the timing of acquired genetic variants we have been able to extract mutographs active at different time points. This analysis has shown in EA that MM is shaped by mutational processes variably active during the early, intermediate and late evolutionary phases of disease. A key finding of our pilot data is the identification of a mutograph occurring as a consequence of the immune response in the germinal center reaction and this differs by race. We will address the hypothesis that a major contributor to the observed excess of MM in AA compared to EA is due to an excess immune response that can be recognized by a GC mutograph that is active in the early evolutionary phases of disease. To accurately extract early mutographs sequential samples from the same individual cases are needed. SMM, which transforms to MM at a rate of 10% per annum, provides a system where samples can be obtained at different time points in the absence of treatment. To address our hypothesis we will generate mutographs from new WGS data from AA SMM and compare them to existing datasets of EA with SMM as well as from a large pre-existing set of MM from which we will infer ancestry directly. We will also establish a longitudinal cohort study of SMM cases and study mutographs over time and compare the profiles between AA and EA. In addition to genetic mutographs we will characterize and compare immunological mutographs of T-cell response in the bone marrow immune microenvironment identified using a flow-cytometric approach. To provide a link to the external environment we will characterize bacterial species signatures derived from 16S rRNA sequencing of the gut flora, and link findings to the genetic and T-cell mutographs. This study will identify genomic, immune and environmental signatures responsible for the higher risk of MM observed among AAs and will provide new insights into the immune response in MM pathogenesis, opening the way for the generation of effective intervention strategies. 1

项目总结/摘要 与欧洲裔美国人相比，非洲裔美国人（AA）的多发性骨髓瘤（MM）发病率更高 (EA)遗传易感性、环境暴露或两者兼而有之。MM之前有两个前体阶段， 意义不明的单克隆丙种球蛋白病（MGUS）和郁积性骨髓瘤（SMM）， 在AA中增加。我们使用欧洲MM样本表明， 疾病的遗传起始和可检测到前驱临床阶段的时间。至关重要 了解这些早期进化步骤的遗传基础，如果我们要真正了解过度的风险， MM在AA。在遗传起始后MM的进化过程中，遗传命中累积 随着时间的推移提供突变签名或“突变图”的独特考古学指纹。使用 全基因组测序（WGS）分析与先进的计算机算法的基础上先验知识 获得性遗传变异的时间，我们已经能够提取在不同时间活跃的mutographs 点这种分析表明，在EA中，MM是由突变过程形成的，这些突变过程在治疗过程中非常活跃。 疾病的早期、中期和晚期进化阶段。我们的试点数据的一个关键发现是识别 作为生发中心反应中免疫反应的结果而发生的变异图， 因种族而异。我们将讨论一个假设，即在AA中观察到的MM过量的主要原因是 与EA相比，是由于过度的免疫反应，可以通过GC突变图识别， 在疾病的早期进化阶段很活跃。为了准确地提取早期mutographs序列样本 同样的个案。SMM以每年10%的速度转化为MM， 提供了一种系统，其中可以在不进行处理的情况下在不同的时间点获得样品。到 为了解决我们的假设，我们将从AA SMM的新WGS数据中生成mutgraphs，并将其与 现有的EA数据集与SMM以及从一个大的预先存在的MM集，我们将从中推断 祖先直接。我们还将建立一个SMM病例的纵向队列研究， 时间，并比较AA和EA之间的轮廓。除了遗传变异图，我们将描述和 比较骨髓免疫微环境中T细胞应答的免疫学变化图 使用流式细胞术方法鉴定。为了提供与外部环境的联系，我们将描述 从肠道植物群的16 S rRNA测序中获得的细菌物种特征，并将发现与遗传 和T细胞变异图这项研究将确定基因组，免疫和环境签名负责 在AA中观察到MM的风险较高，并将为MM的免疫反应提供新的见解 发病机制，开辟了有效的干预策略的产生方式。 1