Reverse phase protein array (RPPA) provides investigators with a powerful high-throughput, quantitative, cost-effective technology for functional proteomics studies. It is an antibody-based technique with procedures similar to that of Western blots. RPPA has a wide variety of applications that range from pharmacodynamics and drug sensitivity assessment to biomarker discovery, subtype classification, and prediction of patient prognosis and response to targeted therapy. In this paper, we describe the technology, its limitations, and some solutions to overcome them. We discuss the steps necessary to obtain raw RPPA data and convert them into robust, high-quality, analysis-ready data. We then illustrate the utility of the platform by highlighting some biomarkers and drug responses of cancer cell lines that confirm previous findings, as a means to validate the platform and the methods presented here.
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RPPA SPACE: an R package for normalization and quantitation of Reverse-Phase Protein Array data.
Bioinformatics
November 2022
Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Summary: Reverse-Phase Protein Array (RPPA) is a robust high-throughput, cost-effective platform for quantitatively measuring proteins in biological specimens. However, converting raw RPPA data into normalized, analysis-ready data remains a challenging task. Here, we present the RPPA SPACE (RPPA Superposition Analysis and Concentration Evaluation) R package, a substantially improved successor to SuperCurve, to meet that challenge.
View Article and Find Full Text PDFGeneration of Raw RPPA Data and Their Conversion to Analysis-Ready Data.
Adv Exp Med Biol
December 2019
Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Reverse phase protein array (RPPA) provides investigators with a powerful high-throughput, quantitative, cost-effective technology for functional proteomics studies. It is an antibody-based technique with procedures similar to that of Western blots. RPPA has a wide variety of applications that range from pharmacodynamics and drug sensitivity assessment to biomarker discovery, subtype classification, and prediction of patient prognosis and response to targeted therapy.
View Article and Find Full Text PDFUtility of a Reverse Phase Protein Array to Evaluate Multiple Biomarkers in Diffuse Large B-Cell Lymphoma.
Proteomics Clin Appl
January 2020
Division of Cancer Cell Research, Kanagawa Cancer Center Research Institute, Yokohama, 241-8515, Japan.
Purpose: Diffuse large B-cell lymphoma (DLBCL), the most common non-Hodgkin lymphoma, is a heterogeneous lymphoma with different clinical manifestations and molecular alterations, and several markers are currently being measured routinely for its diagnosis, subtyping, or prognostication by immunohistochemistry (IHC). Here, the utility of a reverse-phase-protein-array (RPPA) as a novel supportive tool to measure multiple biomarkers for DLBCL diagnosis is validated.
Experimental Design: The expression of seven markers (CD5, CD10, BCL2, BCL6, MUM1, Ki-67, and C-MYC) is analyzed by RPPA and IHC using 37 DLBCL tissues, and the correlation between the two methods is determined.
Data mining The Cancer Genome Atlas in the era of precision cancer medicine.
Swiss Med Wkly
June 2016
Dermatology Clinic, University Hospital Zurich, Switzerland.
The Cancer Genome Atlas (TCGA) has given researchers and clinicians unprecedented access to many different cancers through multiple platforms that include exome sequencing, comparative genomic hybridisation (CGH) arrays, DNA methylation arrays, RNA sequencing, reverse protein phase arrays (RPPA), and clinical features. Most data are available to the public in their raw and processed forms; however, analysis and interpretation of these data require specialised training and software. To address this problem, online tools such as cBioportal, canEvolve, GDAC firehose, PROGgeneV2, and UCSC Cancer browser have been developed by various groups to explore and perform analyses on the datasets that are easily understandable by basic researchers and clinicians.
View Article and Find Full Text PDFSparse Bayesian Graphical Models for RPPA Time Course Data.
IEEE Int Workshop Genomic Signal Process Stat
December 2012
Department of Systems Biology, UT MD Anderson Cancer Centre,
Advances in functional proteomic technologies have significantly enriched our knowledge of protein functions and their interactions in bio-molecular pathways. We discuss inference for RPPA (reverse phase protein array) data that measure the expression of the protein markers over time. We exploit the dynamical nature of the experiment to build a directed network of protein interactions.
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