Project 2: Multi-Omics of high-risk MM

项目2：高风险MM的多组学

基本信息

批准号：
10706328
负责人：
Esteban Braggio
金额：
$ 33.98万
依托单位：
MAYO CLINIC ARIZONA
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-01 至 2026-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10706328
关键词：
Accounting Address Atlases Automobile Driving Biological Blood Bone Marrow Caring Cells Clinic Clinical Clinical Data Clinical Trials Collaborations Complex Complex Analysis Core Facility DNA DNA sequencing Data Data Analyses Data Analytics Data Set Disease Disease Outcome Environment Epigenetic Process Event Evolution Generations Genes Genetic Genome Genomics Goals Immune Immuno-Chemotherapy Immunophenotyping Individual Link Maps Marrow Mass Spectrum Analysis Mononuclear Multiomic Data Multiple Myeloma Mutation Network-based Outcome Pathogenesis Pathway interactions Patients Pattern Phase II Clinical Trials Phenotype Pilot Projects Population Positioning Attribute Process Proteome RNA Relapse Resistance Resolution Resources Rewards Role Sampling Sampling Studies Series Specimen Technology Time Variant Work biobank bioinformatics tool clinical database clinical phenotype clinical risk data integration data resource deep learning design drug sensitivity epigenome experience gene environment interaction gene interaction high risk high risk population immunoregulation improved insight lipidome mRNA sequencing metabolome multidisciplinary multiple omics neoplastic cell patient population personalized approach response single cell analysis therapeutically effective transcriptome transcriptomics translational clinical trial treatment response tumor tumor-immune system interactions ultra high resolution whole genome

项目摘要

PROJECT SUMMARY/ABSTRACT While our own extensive studies have confirmed the significant role of the disrupted genome in Multiple Myeloma (MM), they have also re-emphasized the gaps in understanding, and the importance of immune regulation and gene-environment interaction. It is indeed likely that the evolution of MM, both before or during therapy, is the result of a complex interplay of biological perturbations driven by genetic changes and environmental influences. Our past work has also demonstrated that studying small numbers of patients at great depth can be as rewarding for scientific understanding as studies of superficial genomic events in thousands of patients. Thus we will strive to generate the first, longitudinal, translational clinical trial and comprehensive data resource of environmental genetic interactions for the highest-risk MM population. It is these patients who continue to rapidly fail highly effective therapeutics for reasons which are still completely opaque. New and bold approaches using state-of-the-art technology are required to reverse this decades-old lack of progress. Our hypothesis is that analysis of data capturing gene-environment interactions at high resolution will reveal insights into biological pathways influencing MM responsiveness to therapy and subsequent outcomes. First, we will leverage a carefully studied and homogeneously treated high-risk group of “double hit” patients in a Phase 2 clinical trial with large control clinical databases and bio-repositories to derive, for each patient, a detailed map of environmental gene interactions linked to clinical outcome over time. Second, we will perform a series of complex analyses to identify MM-associated changes in and across the genome, transcriptome, epigenome, immune environment, proteome, lipidome and metabolome. Third, we will study these samples at the highest resolution technically feasible today, and seek to define gene-environment interaction changes over time that associate with response to therapy. Finally, high resolution data capturing these interaction changes and clinical response data will be linked to improve our understanding of the mechanisms underlying MM variability among patients in regards to disease outcomes. This comprehensive resource will enable a more individualized approach to clinical surveillance and therapy for MM.

项目概要/摘要虽然我们自己的广泛研究已经证实了被破坏的基因组在多种疾病中的重要作用骨髓瘤（MM），他们还重新强调了理解上的差距以及免疫的重要性 MM 的进化确实可能是在之前或期间发生的。治疗，是由遗传变化驱动的生物扰动复杂相互作用的结果我们过去的工作还表明，对少数患者进行研究。对于科学理解来说，深入的研究与对表面基因组事件的研究一样有益。因此，我们将努力开展第一个纵向转化临床试验和最高风险 MM 人群环境遗传相互作用的综合数据资源。这些患者的高效治疗继续迅速失败，原因仍然完全不明需要采用最先进技术的新的、大胆的方法来扭转这个已有数十年历史的现象。缺乏进步。我们的假设是，对高分辨率捕获基因-环境相互作用的数据进行分析将揭示深入了解影响 MM 对治疗反应和后续结果的生物学途径。我们将利用经过仔细研究和同质治疗的高风险“双重打击”患者群体具有大型对照临床数据库和生物存储库的 2 期临床试验，为每位患者得出一个其次，我们将进行与临床结果相关的环境基因相互作用的详细图谱。一系列复杂的分析，以确定基因组、转录组中和跨基因组、转录组、第三，我们将研究这些样本。当今技术上可能的最高分辨率，并寻求定义基因与环境相互作用的变化最后，高分辨率数据捕获这些相互作用。变化和临床反应数据将联系起来，以提高我们对潜在机制的理解 MM 患者在疾病结果方面的变异性将能够实现这一综合资源。 MM 临床监测和治疗的更个性化方法。