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Updated: Aug 7, 2026
The Use of Reverse Phase Protein Arrays (RPPA) to Explore Protein Expression Variation within Individual Renal Cell Cancers
Published on: January 22, 2013
Gene expression profiling of renal cell carcinoma: a DNA macroarray analysis
Jon A J Lovisolo1, Barbara Casati, Libero Clerici
1Division of Urology, Ospedale Galmarini, Piazza Zanaboni, Tradate, Italy. jon.lovis@jhu.edu
Objective:
To examine differences in gene expression levels between renal cell carcinoma (RCC) tissue and 'normal' appearing renal tissue using a commercially available DNA macroarray.
Materials And Methods:
Tissue was obtained from 47 consecutive radical nephrectomies, 29 of which were eligible. DNA macroarrays were analysed on the tumour and normal-appearing control tissue to measure the expression of 1185 cancer-related genes. The group of samples was also stratified according to the presence or absence of granular cells and according to tumour grade. Quantitative real-time polymerase-chain reaction (PCR) was also performed on seven key genes present on the macroarray.
Results:
In all, 444 genes were over-expressed and 33 genes were under-expressed. Using selection criteria reduced the list to nine that were significantly over-expressed and 23 that were under-expressed. These significant genes belonged to the families of oncogenes, growth factors, interleukins, receptors, immune system components, cytoskeleton, matrix proteins and intracellular modulators, or they coded for proteins involved in DNA transcription and RNA translation, DNA repair, protein turnover, and metabolism of carbohydrates and lipids. There were differences in gene expression according to the presence or absence of granular cells and according to tumour grade. Using quantitative real-time PCR there was over-expression of epidermal growth factor receptor, c-myc, transforming growth factor-alpha, vascular endothelial growth factor and vimentin, and under-expression of TYRO3 protein tyrosine kinase. The von Hippel-Lindau gene was under-expressed but not significantly.
Conclusions:
A procedure for collecting and storing fresh renal tissue and subsequent gene expression profiling of RCC and normal renal tissue was established. A commercially available DNA macroarray coupled with the significance analysis of macroarrays allowed the identification of sets of differentially expressed cancer-related genes that were characteristic of RCC, compared with apparently normal renal tissue, and which distinguished among subgroups divided according to tumour grade and histological subtype. Quantitative PCR is important to validate the results of macroarray experiments.
Insights
This study identified key gene expression differences in renal cell carcinoma (RCC) compared to normal kidney tissue. These findings highlight potential biomarkers for RCC and its subtypes, aiding in diagnosis and understanding cancer development.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Renal cell carcinoma (RCC) is a significant health concern.
- Understanding gene expression in RCC is crucial for diagnosis and treatment.
- Previous studies have explored gene expression, but comprehensive analysis in comparison to normal tissue is ongoing.
Purpose of the Study:
- To investigate differential gene expression between RCC and normal renal tissues.
- To identify cancer-related genes altered in RCC using DNA macroarrays.
- To correlate gene expression patterns with tumor grade and histological subtypes.
Main Methods:
- Analysis of gene expression in 29 RCC and matched normal renal tissues using DNA macroarrays (1185 cancer-related genes).
- Stratification of samples based on granular cell presence and tumor grade.
- Validation of key gene expression changes using quantitative real-time polymerase-chain reaction (PCR).
Main Results:
- Identified 444 over-expressed and 33 under-expressed genes in RCC compared to normal tissue.
- Significantly, nine genes were over-expressed and 23 were under-expressed.
- Differential expression patterns were observed based on granular cells and tumor grade.
- Quantitative PCR confirmed over-expression of EGFR, c-myc, TGF-α, VEGF, and vimentin, and under-expression of TYRO3.
Conclusions:
- Established a robust method for fresh renal tissue collection and gene expression profiling of RCC.
- DNA macroarrays and statistical analysis successfully identified characteristic differentially expressed genes in RCC.
- Quantitative PCR is essential for validating macroarray findings and understanding RCC heterogeneity.
