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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
Identification of key genes and pathways in renal cell carcinoma through expression profiling data
Xiaoxia Liu1, Jinling Wang, Guiling Sun
1Department of Nephrology, Affiliated Hospital of Weifang Medical University, Weifang, Shandong, China.
Background/Aims:
To isolate key genes and pathways in renal cell carcinoma (RCC), which might reveal more evidences on the regulation network and contribute to pathogenic mechanisms of RCC.
Methods:
Microarray data of GSE34676, GSE23926 and GSE48008 were downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) and differentially expressed miRNAs were respectively screened using Limma package, followed by the selection of CNV associated genes and miRNAs. A multi-molecular regulation interaction network was constructed, and significant modules were subsequently isolated from the network by Molecular Complex Detection (Mcode) of Cytoscape. Finally, GO terms and KEGG pathways of these genes and miRNAs in significant modules were enriched using DAVID.
Results:
Total 403 DEGs and 231 differentially expressed miRNAs were screened in RCC samples and normal group. Moreover, 1369 genes and 68 miRNAs were isolated by CNV analysis. Besides, a total of 59 miRNAs and 209 genes that related to 340 interaction pairs were analyzed and used to construct the network and 2 significant modules were identified. In the modules, CAV1 and CAV2 were shown to correlate with RCC. GNAI1, GPSM2 and GNAO1 were likely involved in the regulation of RCC through G protein signal transduction. Besides, G-protein coupled receptor protein signaling pathway, focal adhesion, MAPK signaling pathway and neuroactive ligand receptor interaction were enriched.
Conclusion:
Our study suggests that several crucial genes including CAV1,CAV2, GNAI1, GPSM2, and GNAO1 and pathways may play key roles in RCC progression.
Insights
This study identifies key genes like CAV1, CAV2, GNAI1, GPSM2, and GNAO1 involved in renal cell carcinoma (RCC) progression. These findings offer insights into the complex regulatory networks driving RCC pathogenesis.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Renal cell carcinoma (RCC) pathogenesis involves complex regulatory networks.
- Identifying key genes and pathways is crucial for understanding RCC.
Purpose of the Study:
- To identify key genes and pathways in renal cell carcinoma (RCC).
- To elucidate the regulation network and pathogenic mechanisms of RCC.
Main Methods:
- Downloaded and analyzed microarray data from Gene Expression Omnibus (GSE34676, GSE23926, GSE48008).
- Screened differentially expressed genes (DEGs) and miRNAs, and selected copy number variation (CNV) associated genes/miRNAs.
- Constructed a multi-molecular interaction network and identified significant modules using Cytoscape and MCODE.
Main Results:
- Identified 403 DEGs, 231 differentially expressed miRNAs, 1369 CNV-associated genes, and 68 CNV-associated miRNAs.
- Constructed a network of 59 miRNAs and 209 genes, identifying two significant modules.
- Found CAV1, CAV2, GNAI1, GPSM2, and GNAO1 associated with RCC, potentially via G protein signaling and enriched pathways like MAPK signaling.
Conclusions:
- CAV1, CAV2, GNAI1, GPSM2, and GNAO1 are suggested as crucial genes in RCC progression.
- The study provides evidence for key pathways involved in RCC pathogenesis.
