CA: Tissue Procurement, Pathology, and Biomedical Informatics

该核心的中心目标是提供最佳质量的人体组织处理、保存、加工， 从NSCLC患者中获得的生物样本的形态学表征， 确保采集参数注释准确、详细的方式。它将进一步收集 相关的病理学、人口统计学和临床结局数据，以确保出色的数据分析质量 得出关于不同生物分子的效用的生物学上合理的和临床上有意义的结论 正在调查这种专门的“虚拟”组织资源将取代“遗留”肺癌组织 HLMCC的资源来创建一个全面的关系数据库， 内部和外部领域。由此建立的框架将作为一个整合机制 在项目中，促进莫菲特癌症中心内共享资源的最佳利用， 组织采购和分配按照既定的机构和肺癌孢子 指南核心将提供高质量的收集和石蜡包埋组织的组织分析 用于潜在下游组织微阵列构建和免疫组织化学表征的块。 这些职能中的每一项都将严格遵守美国病理学家学会（CAP）的规定。 使用预先确定的共同数据元素进行离散字段数据输入的指导方针。一个重要的重点 将被放置在高通量技术和癌症微基因组学使用激光捕获微 解剖新的方法将得到验证和采用， 大分子（DMA、RNA和蛋白质）用于靶分子分析。核心将有效地利用组织 微阵列提供了一种机制，用于发现结果预测模型， 原位定量分析

The central goal of this core is to provide optimal quality human tissue handling, preservation, processing, and morphologic characterization of bio-specimens obtained from patients suffering from NSCLC in a manner that ensures accurate and detailed annotation of collection parameters. It will further collect associated pathologic, demographic and clinical outcomes data to ensure outstanding quality data analysis yielding biologically plausible and clinically meaningful conclusions on the utility of the diverse biomolecules being investigated. This specialized "virtual" tissue resource will subsume the "legacy" lung cancer tissue resource at HLMCC to create a comprehensive relational database that seamlessly integrates across internal and external domains. The framework thus established will serve as an integrating mechanism among projects, facilitating optimal utilization of shared resources within the Moffitt Cancer Center, and tissue procurement and distribution in accordance with established institutional and lung cancer SPORE guidelines. The core will provide high quality collection and tissue analysis of paraffin embedded tissue blocks for potential downstream tissue micro-array construction and immuno-histochemical characterization. Each of these functions will be carried out in strict compliance with College of American Pathologists (CAP) guidelines with discrete field data entry using pre-identified common data elements. A significant emphasis will be placed on high throughput technologies and cancer micro-genomics using laser capture micro dissection. New methodologies will be validated and incorporated to harvest small quantities of macromolecules (DMA, RNA and protein) for target molecule analysis. The core will efficiently utilize tissue micro arrays to provide a mechanism for discovery of outcomes predictor models when coupled with quantitative in situ analysis.