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The Use of Reverse Phase Protein Arrays (RPPA) to Explore Protein Expression Variation within Individual Renal Cell Cancers
Published on: January 22, 2013
Imaging the clear cell renal cell carcinoma proteome
Todd M Morgan1, Erin H Seeley, Oluwole Fadare
1Department of Urologic Surgery, Vanderbilt University Medical Center, Nashville, Tennessee.
The Journal of Urology
|September 27, 2012
Summary
Imaging mass spectrometry effectively identified protein signatures in clear cell renal cell carcinoma (ccRCC) tissue, distinguishing it from normal tissue with high accuracy. This technique shows promise for discovering novel ccRCC biomarkers.
Area of Science:
- Oncology
- Biomarker Discovery
- Proteomics
Background:
- Clear cell renal cell carcinoma (ccRCC) biomarker identification is hindered by protein expression heterogeneity.
- Imaging mass spectrometry (IMS) offers spatial peptide distribution analysis.
- IMS can potentially overcome tissue heterogeneity challenges in ccRCC biomarker discovery.
Purpose of the Study:
- To determine if IMS can identify and map protein signatures specific to ccRCC.
- To assess the accuracy of IMS in differentiating ccRCC from normal renal tissue.
Main Methods:
- Construction of tissue microarrays with matched tumor and normal ccRCC tissues.
- Analysis using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS).
- Cross-validation, mass spectrometry/mass spectrometry sequencing for peptide identification, and immunohistochemistry for validation.
Main Results:
- Peptide signatures differentiating ccRCC from normal tissue were identified with high classification accuracy (94.7%–100% per spot/core).
- Cross-validation demonstrated robust accuracy (82.6%–92.4% per spot/core).
- Vimentin, histone 2A.X, and α-enolase were identified as overexpressed proteins in ccRCC, confirmed by immunohistochemistry.
Conclusions:
- IMS successfully identified and mapped specific peptides that accurately distinguish malignant from normal renal tissue.
- IMS presents a novel, high-throughput approach for ccRCC biomarker discovery.
- Spatial peptide signatures may offer advantages over traditional biomarkers for heterogeneous tumors like ccRCC.
