Translational and Clinical Trial Correlates Core

项目摘要 翻译和临床相关核心（TCCC）的目标是提供所需的专业知识和资源 对作为我们计划一部分的研究项目和临床研究进行质量相关分析， 罗宾计划。为了实现这一目标，我们组建了一个多学科团队， 采购和生物库，免疫测定，免疫基因组学，蛋白质组学，放射组学和最先进的 计算生物学和生物统计学方法。在目标1中，技术合作中心将提供高度标准化和 获得、处理和生物样本库样本的经验证程序。这将确保提供编目齐全的 和具有最佳细胞活力的临床注释样品。在目标2中，技术合作中心将促进获得国家- 最先进的平台，用于对收集到的 生物标本这将提供一个广泛的分子评估的变化，发生在响应 治疗及其对反应的贡献。在目标3中，技术合作中心将提供获取尖端技术的途径， 用于处理、分析和解释高通量数据的计算资源。先进 生物信息学将由免疫治疗和精确免疫肿瘤学中心提供。 计算免疫学平台和定量健康科学系（QHS）将协助 统计分析。促进数据管理和分析的统一， 将有一名指定的数据资源经理（CC的Kendy/Emory的Switchenko）。本次集中 这种方法将确保项目和临床研究之间的最佳数据收集、分析和共享。

PROJECT SUMMARY The goal of the Translational & Clinical Correlates Core (TCCC) is to provide the expertise and resources needed to conduct quality correlative analyses for the research projects and clinical studies proposed as part of our ROBIN Program. To accomplish this, we have assembled a multidisciplinary team with expertise in tissue procurement and biobanking, immune assays, immunogenomics, proteomics, radiomics, and state-of-the-art computational biology and biostatistics approaches. In Aim 1, the TCCC will provide highly standardized and validated procedures to procure, process and biobank specimens. This will ensure availability of well-catalogued and clinically annotated samples with optimal cell viability. In Aim 2, the TCCC will facilitate access to state-of- the-art platforms for the comprehensive molecular, pathologic, and immunologic profiling of collected biospecimens. This will provide a broad molecular assessment of the changes that occur in response to treatment and their contributions to response. In Aim 3, the TCCC will provide access to cutting-edge computational resources for the processing, analysis and interpretation of high-throughput data. Advanced bioinformatics will be provided by the Center for Immunotherapy and Precision Immuno-Oncology’s Computational Immunology Platform, and the Department of Quantitative Health Sciences (QHS) will assist with the statistical analyses. To facilitate harmonization of data management and analysis each participating institute will have a designated Data Resource Manager (Kattan for CC/Switchenko for Emory). This centralized approach will ensure optimal data collection, analysis, and sharing among projects and clinical studies.