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Updated: Dec 14, 2025
The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers
Published on: January 22, 2013
Identifying the novel key genes in renal cell carcinoma by bioinformatics analysis and cell experiments
Yeda Chen1, Di Gu1, Yaoan Wen1
1Department of Urology, Minimally Invasive Surgery Center, The First Affiliated Hospital of Guangzhou Medical University, Guangdong Key Laboratory of Urology, Kangda Road 1#, Haizhu District, Guangzhou, 510230 Guangdong China.
Background:
Although major driver gene have been identified, the complex molecular heterogeneity of renal cell cancer (RCC) remains unclear. Therefore, more relevant genes need to be identified to explain the pathogenesis of renal cancer.
Methods:
Microarray datasets GSE781, GSE6344, GSE53000 and GSE68417 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by employing GEO2R tool, and function enrichment analyses were performed by using DAVID. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using STRING and Cytoscape. Survival analysis was performed using GEPIA. Differential expression was verified in Oncomine. Cell experiments (cell viability assays, transwell migration and invasion assays, wound healing assay, flow cytometry) were utilized to verify the roles of the hub genes on the proliferation of kidney cancer cells (A498 and OSRC-2 cell lines).
Results:
A total of 215 DEGs were identified from four datasets. Six hub gene (SUCLG1, PCK2, GLDC, SLC12A1, ATP1A1, PDHA1) were identified and the overall survival time of patients with RCC were significantly shorter. The expression levels of these six genes were significantly decreased in six RCC cell lines(A498, OSRC-2, 786- O, Caki-1, ACHN, 769-P) compared to 293t cell line. The expression level of both mRNA and protein of these genes were downregulated in RCC samples compared to those in paracancerous normal tissues. Cell viability assays showed that overexpressions of SUCLG1, PCK2, GLDC significantly decreased proliferation of RCC. Transwell migration, invasion, wound healing assay showed overexpression of three genes(SUCLG1, PCK2, GLDC) significantly inhibited the migration, invasion of RCC. Flow cytometry analysis showed that overexpression of three genes(SUCLG1, PCK2, GLDC) induced G1/S/G2 phase arrest of RCC cells.
Conclusion:
Based on our current findings, it is concluded that SUCLG1, PCK2, GLDC may serve as a potential prognostic marker of RCC.
Insights
This study identifies SUCLG1, PCK2, and GLDC as key genes in renal cell cancer (RCC) pathogenesis. Overexpression of these genes inhibits RCC proliferation and migration, suggesting their potential as prognostic markers for kidney cancer.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Renal cell cancer (RCC) exhibits complex molecular heterogeneity, necessitating the identification of novel driver genes.
- Understanding the molecular basis of RCC is crucial for developing targeted therapies.
Purpose of the Study:
- To identify novel genes involved in renal cell cancer (RCC) pathogenesis.
- To investigate the potential of identified genes as prognostic markers for RCC.
Main Methods:
- Analysis of Gene Expression Omnibus (GEO) datasets (GSE781, GSE6344, GSE53000, GSE68417) to identify differentially expressed genes (DEGs).
- Construction and analysis of protein-protein interaction (PPI) networks using STRING and Cytoscape.
- In vitro experiments including cell viability, migration, invasion, and flow cytometry assays to validate the role of hub genes in RCC cell lines.
Main Results:
- Identification of 215 DEGs, with six hub genes (SUCLG1, PCK2, GLDC, SLC12A1, ATP1A1, PDHA1) significantly associated with shorter overall survival in RCC patients.
- Downregulation of SUCLG1, PCK2, and GLDC mRNA and protein expression in RCC tissues and cell lines.
- Overexpression of SUCLG1, PCK2, and GLDC inhibited RCC cell proliferation, migration, and invasion, and induced cell cycle arrest.
Conclusions:
- SUCLG1, PCK2, and GLDC are significantly downregulated in renal cell cancer (RCC) and play critical roles in tumor progression.
- These three genes show potential as prognostic biomarkers for renal cell cancer (RCC).
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