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Updated: May 4, 2026
The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers
Published on: January 22, 2013
Evaluation of reverse phase protein array (RPPA)-based pathway-activation profiling in 84 non-small cell lung cancer
Ramesh Ummanni1, Heiko A Mannsperger1, Johanna Sonntag1
1Division of Molecular Genome Analysis, German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany.
Abstract:
The reverse phase protein array (RPPA) approach was employed for a quantitative analysis of 71 cancer-relevant proteins and phosphoproteins in 84 non-small cell lung cancer (NSCLC) cell lines and by monitoring the activation state of selected receptor tyrosine kinases, PI3K/AKT and MEK/ERK1/2 signaling, cell cycle control, apoptosis, and DNA damage. Additional information on NSCLC cell lines such as that of transcriptomic data, genomic aberrations, and drug sensitivity was analyzed in the context of proteomic data using supervised and non-supervised approaches for data analysis. First, the unsupervised analysis of proteomic data indicated that proteins clustering closely together reflect well-known signaling modules, e.g. PI3K/AKT- and RAS/RAF/ERK-signaling, cell cycle regulation, and apoptosis. However, mutations of EGFR, ERBB2, RAF, RAS, TP53, and PI3K were found dispersed across different signaling pathway clusters. Merely cell lines with an amplification of EGFR and/or ERBB2 clustered closely together on the proteomic, but not on the transcriptomic level. Secondly, supervised data analysis revealed that sensitivity towards anti-EGFR drugs generally correlated better with high level EGFR phosphorylation than with EGFR abundance itself. High level phosphorylation of RB and high abundance of AURKA were identified as candidates that can potentially predict sensitivity towards the aurora kinase inhibitor VX680. Examples shown demonstrate that the RPPA approach presents a useful platform for targeted proteomics with high potential for biomarker discovery. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.
Insights
Reverse phase protein array (RPPA) analysis of 84 non-small cell lung cancer (NSCLC) cell lines reveals protein signaling modules and identifies potential biomarkers for drug sensitivity, aiding biomarker discovery.
Area of Science:
- Proteomics
- Cancer Biology
- Biomarker Discovery
Background:
- Non-small cell lung cancer (NSCLC) is a major cause of cancer mortality.
- Understanding the molecular mechanisms driving NSCLC is crucial for developing targeted therapies.
- Quantitative proteomic analysis can provide insights into signaling pathways and potential drug targets.
Purpose of the Study:
- To quantitatively analyze 71 cancer-relevant proteins and phosphoproteins in 84 NSCLC cell lines using RPPA.
- To correlate proteomic data with transcriptomic, genomic, and drug sensitivity data.
- To identify potential biomarkers for predicting drug response in NSCLC.
Main Methods:
- Reverse phase protein array (RPPA) for quantitative proteomic analysis.
- Analysis of signaling pathways including receptor tyrosine kinases, PI3K/AKT, and MEK/ERK1/2.
- Integration of proteomic data with transcriptomic, genomic, and drug sensitivity data.
- Supervised and unsupervised machine learning approaches for data analysis.
Main Results:
- Unsupervised analysis revealed distinct signaling modules (e.g., PI3K/AKT, RAS/RAF/ERK) but scattered mutations.
- EGFR and ERBB2 amplification correlated with proteomic clustering, not transcriptomic.
- Drug sensitivity correlated better with EGFR phosphorylation than abundance.
- High RB phosphorylation and AURKA abundance predicted sensitivity to VX680.
Conclusions:
- RPPA is a valuable platform for targeted proteomics in NSCLC research.
- Proteomic profiling can reveal signaling pathway alterations and identify potential biomarkers.
- Phosphorylation levels are critical indicators for predicting drug sensitivity in NSCLC.
- This study highlights the potential for RPPA in biomarker discovery for NSCLC treatment.
