Mutographs differentiating the racial and temporal incidence of multiple myeloma

项目摘要/摘要 非洲裔美国人(AA)多发性骨髓瘤(MM)的发病率高于欧洲裔美国人 (EA)由于遗传易感性或环境暴露，或两者兼而有之。MM之前有两个前驱体阶段， 未确定意义的单克隆性伽马病(MGUS)和阴燃骨髓瘤(SMM)也是 AA增加。我们已经使用欧洲MM样本表明，在 疾病的遗传起源以及可检测到先兆临床阶段的时间。这是至关重要的 了解这些早期进化步骤的遗传基础，如果我们要真正理解 AA中的MM。在MM遗传起始后的进化过程中，遗传命中是积累的 随着时间的推移，提供了突变特征的独特考古指纹。vbl.使用 基于先验知识的高级计算机算法分析全基因组测序 我们已经能够提取在不同时间活跃的突变图 积分。这项分析已经在EA中表明MM是由在 疾病的早期、中期和晚期进化阶段。我们飞行员数据的一个关键发现是识别 作为生发中心反应中的免疫反应的结果而发生的突变图，以及这 因种族不同而不同。我们将解决这样的假设，即AA中观察到的MM过量的主要贡献者 与EA相比，是由于GC Mutograph可以识别的过度免疫反应，即 活跃在疾病的早期进化阶段。准确提取早期互译图序列样本 需要从相同的个案中提取。SMM以每年10%的速度转变为MM， 提供了一种系统，可以在没有治疗的情况下在不同的时间点获取样本。至 为了解决我们的假设，我们将从AA SMM的新WGS数据中生成多重图，并将它们与 使用SMM的EA的现有数据集，以及我们将从中推断的大量预先存在的MM集 直接的祖先。我们还将建立SMM病例的纵向队列研究，并研究 对AA和EA进行计时和比较。除了遗传突变图外，我们还将描述和 骨髓免疫微环境中T细胞反应的免疫突变图谱比较 用流式细胞术进行鉴定。为了提供到外部环境的链接，我们将描述 根据肠道菌群的16S rRNA测序得出的细菌物种特征，并将发现与基因 和T细胞互动图。这项研究将确定基因组、免疫和环境特征对 在AA中观察到MM的更高风险，并将为MM的免疫反应提供新的见解 发病机制，为生成有效的干预策略开辟了道路。 1

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