Core B: Translational, Cellular and Molecular Analysis

摘要-细胞成像和基因组学核心B 核心B，细胞基因组学和成像核心（CGI），将提供集中的实验处理 服务和主要数据分析的计划项目补助金（PPG）。项目1、2之间的相互作用 和3主要涉及共享生物标本和数据;因此，PPG依赖CGI协调： (1)实验和转化样品管理。 (2)细胞基因组学，包括RNA-seq，单细胞基因组学和空间转录组学。 (3)原代组织培养细胞特性的成像研究。 (4)样品、分子和基因组数据管理。 CGI核心使PPG能够利用分子技术专家、细胞技术专家和生物技术专家的综合专业知识， 生物学家，成像专家和信息学家，以简化数据生产。人体组织生物标本 将在实验室信息管理系统（LIMS）中跟踪活检和类器官。这些样品 将使用CGI优化的标准操作协议进行处理，以促进再现性， 所有项目的一致性。这些方案将涵盖共聚焦显微镜成像、RNA-seq、靶向 DNA测序、空间转录组学和单细胞RNA测序。CGI将产生一个 在一系列癌前病变和工作中，胃微环境的综合景观 与核心C一起进行数据分析，以促进PPG的总体目标。分子、基因组和表观遗传 表征将使研究人员能够对胃癌的驱动因素进行大量研究， 假设精确癌症拦截方法。

ABSTRACT – CELLULAR IMAGING AND GENOMICS CORE B Core B, the Cellular Genomics and Imaging Core (CGI), will provide centralized experimental processing services and primary data analysis for the Program Project Grant (PPG). The interactions between Projects 1, 2 and 3 primarily involve shared biospecimens and data; therefore, the PPG relies on the CGI to coordinate: (1) Experimental and translational sample management. (2) Cellular genomics that includes RNA-seq, single cell genomics and spatial transcriptomics. (3) Imaging studies for cellular characterization of primary tissue cultures. (4) Sample, molecular and genomic data management. The CGI core enables the PPG to leverage the combined expertise of molecular technologists, cellular biologists, imaging experts and informaticians to streamline data production. Biospecimens of human tissue biopsies and organoids will be tracked in a laboratory information management system (LIMS). These samples will be processed using standard operating protocols optimized by the CGI to facilitate reproducibility and consistency across all projects. These protocols will cover confocal microscopy imaging, RNA-seq, targeted DNA sequencing, spatial transcriptomics and single cell RNA sequencing. The CGI will produce a comprehensive landscape of the gastric microenvironment across a range of precancerous conditions and work in tandem with Core C for data analysis to further the PPG overall aims. The molecular, genomic and epigenetic characterization will allow investigators to conduct numerous studies on the drivers of gastric cancer and hypothesize methods for precision cancer interception.