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反相蛋白阵列数据的可重复性和跨平台验证。

Reproducibility and Crossplatform Validation of Reverse-Phase Protein Array Data.

机构信息

Cancer Research UK Edinburgh Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.

出版信息

Adv Exp Med Biol. 2019;1188:181-201. doi: 10.1007/978-981-32-9755-5_10.

Abstract

Reverse-phase protein array (RPPA) technology is a high-throughput antibody- and microarray-based approach for the rapid profiling of levels of proteins and protein posttranslational modifications in biological specimens. The technology consumes small amounts of samples, can sensitively detect low-abundance proteins and posttranslational modifications, enables measurements of multiple signaling pathways in parallel, has the capacity to analyze large sample numbers, and offers robust interexperimental reproducibility. These features of RPPA experiments have motivated and enabled the use of RPPA technology in various biomedical, translational, and clinical applications, including the delineation of molecular mechanisms of disease, profiling of druggable signaling pathway activation, and search for new prognostic markers. Owing to the complexity of many of these applications, such as developing multiplex protein assays for diagnostic laboratories or integrating posttranslational modification-level data using large-scale proteogenomic approaches, robust and well-validated data are essential. There are many distinct components of an RPPA workflow, and numerous possible technical setups and analysis parameter options exist. The differences between RPPA platform setups around the world offer opportunities to assess and minimize interplatform variation. Crossplatform validation may also aid in the evaluation of robust, platform-independent protein markers of disease and response to therapy.

摘要

反相蛋白质阵列(RPPA)技术是一种基于抗体和微阵列的高通量方法,可快速分析生物样本中蛋白质和蛋白质翻译后修饰的水平。该技术消耗的样品量少,能够灵敏地检测低丰度蛋白质和翻译后修饰,支持同时测量多个信号通路,具有分析大量样本的能力,并提供稳健的实验间可重复性。这些特点促使并使 RPPA 技术在各种生物医学、转化和临床应用中得到应用,包括疾病分子机制的阐明、药物靶标信号通路激活的分析以及新的预后标志物的寻找。由于这些应用的复杂性,例如为诊断实验室开发多重蛋白质检测方法,或使用大规模蛋白质基因组学方法整合翻译后修饰水平数据,稳健且经过良好验证的数据至关重要。RPPA 工作流程有许多不同的组成部分,存在许多可能的技术设置和分析参数选项。世界各地 RPPA 平台设置之间的差异为评估和最小化平台间差异提供了机会。跨平台验证还有助于评估疾病和治疗反应的稳健、独立于平台的蛋白质标志物。

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