Reproducibility and Crossplatform Validation of Reverse-Phase Protein Array Data

被引:6
|
作者
Byron, Adam [1 ]
机构
[1] Univ Edinburgh, Inst Genet & Mol Med, Canc Res UK Edinburgh Ctr, Edinburgh, Midlothian, Scotland
关键词
Biomarkers; Bioinformatics; Data evaluation; Data integration; Data normalization; Data validation; Protein microarray; Proteomics; Reproducibility; Reverse-phase protein array; CANCER-CELL LINES; PATHWAY-ACTIVATION; MICROARRAYS; PROTEOMICS; NORMALIZATION; TECHNOLOGIES; PERSPECTIVE; METASTASIS; INHIBITORS; PREDICTION;
D O I
10.1007/978-981-32-9755-5_10
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:181 / 201
页数:21
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