Translational and Clinical Trial Correlates Core

项目总结 翻译与临床相关核心(TCCC)的目标是提供所需的专业知识和资源 对我们的研究项目和临床研究项目进行质量相关分析 罗宾计划。为了做到这一点，我们组建了一个拥有组织专业知识的多学科团队。 采购和生物库、免疫分析、免疫基因组学、蛋白质组学、放射组学和最新技术 计算生物学和生物统计学方法。在目标1中，TCCC将提供高度标准化和 采购、加工和生物库标本的有效程序。这将确保提供经过良好编目的 以及具有最佳细胞活力的临床注释样本。在AIM 2中，TCCC将促进访问- -ART平台，用于全面的分子、病理和免疫学分析 生物群落。这将提供对响应的变化的广泛的分子评估 治疗及其对反应的贡献。在AIM 3中，TCCC将提供接触尖端技术的途径 用于处理、分析和解释高通量数据的计算资源。进阶 生物信息学将由免疫治疗和精密免疫肿瘤学中心提供 计算免疫学平台，定量健康科学部将协助 统计分析。为协调各参与机构的数据管理和分析工作 将有一名指定的数据资源管理员(CC为卡坦/埃默里为Switchenko)。这个集中式 该方法将确保在项目和临床研究之间进行最佳的数据收集、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.