Statistical Methods For Quantitative Immunohistochemistry Biomarkers

项目总结 免疫组织化学(IHC)广泛应用于肿瘤的分类和指导临床治疗。一个 IHC的主要功能是在肿瘤组织的空间分辨背景下检测标记物，包括 癌变和间质成分、单个细胞类型和亚细胞室。量化 免疫荧光(QIF)越来越多地用于IHC定量可能作为预后的蛋白质 特定癌症治疗的生物标记物或靶点。QIF的一种常见应用是基于幻灯片的同步 利用组织芯片(TMA)分析某些蛋白质的表达，该芯片整合了来自 一大群病人。这项技术与机器阅读器相结合，可以高通量地检测分子 肿瘤组织的概况和新的预后和预测性癌症的快速开发和验证 生物标志物。 我们建议的总体目标是开发一个发现新的IHC的分析框架 改善预测和药物反应预测的生物标志物。新的统计方法将是 量身定做，以利用丰富的和未开发的信息，在细胞水平的蛋白质表达水平。新的QIF IHC 生物标志物将被优化为基于细胞水平蛋白质分布函数的灵活指数 表达或关于IHC信号的空间局部化，被视为空间点模式的标志 癌细胞。拟议的研究将为开发新的生物标志物提供广泛适用的方法 癌症。改进的生物标志物将支持合理招募复发风险较高的患者。 进入生物标记物驱动的临床试验，有可能对临床研究和 降低癌症死亡率。

PROJECT SUMMARY Immunohistochemistry (IHC) is widely used to classify cancer and guide clinical management of patients. A major power of IHC is the detection of markers in the spatially resolved context of tumor tissue, including cancerous and stromal elements, individual cell types, and subcellular compartments. Quantitative Immunofluorescence (QIF) is used increasingly for IHC quantification of proteins that may serve as prognostic biomarkers or targets for specific cancer therapies. A common application of QIF is simultaneous slide-based analysis of certain protein expression using tissue microarrays (TMAs), which incorporate tumor tissues from large cohorts of patients. This technology combined with machine readers allows for high-throughput molecular profiling of tumor tissues and rapid development and validation of new prognostic and predictive cancer biomarkers. The overall goal of our proposal is to develop an analytical framework of for discovery of new IHC biomarkers to improve prognostication and drug response prediction. The new statistical methods will be tailored to use the rich and untapped information on cell-level protein expression levels. Novel QIF IHC biomarkers will be optimized as flexible indices based either on distribution functions of cell-level protein expressions or on the spatial localization of the IHC signals viewed as marks of the spatial point pattern of cancer cells. The proposed studies will yield broadly applicable methods for development of new biomarkers in cancer. The improved biomarkers would support rational recruitment of patients at elevated risk of recurrence into biomarker-driven clinical trials, with a potential to have major near-term impact on clinical research and reduce mortality from cancer.