Original Article
Systematic identification of key genes and pathways in clear cell renal cell carcinoma on bioinformatics analysis
Abstract
Background: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of adult renal neoplasm and has a poor prognosis owing to a limited understanding of the disease mechanisms. The aim of this study was to explore and identify the key genes and signaling pathways in ccRCC.
Methods: The GSE36895 gene expression profiles were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were then screened using software packages in R. After Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, a proteinprotein interaction (PPI) network of DEGs was constructed with Cytoscape software, and submodules were subsequently analyzed using the MCODE plug-in.
Results: Twenty-nine ccRCC samples and 23 normal samples were incorporated into this study, and a total of 468 DEGs were filtered, consisting of 180 upregulated genes and 288 downregulated genes. The upregulated DEGs were significantly enriched in the immune response, response to wounding, inflammatory response, and response to hypoxia, whereas downregulated genes were mainly enriched in ion transport, anion transport, and monovalent inorganic cation transport biological processes (BPs). According to Molecular Complex Detection analysis in PPI, C1QA, C1QB, C1QC, CCND1 and EGF had higher degrees of connectivity and could participate in the majority of important pathways, such as cytokine-cytokine receptor interactions, the chemokine signaling pathway, and the complement and coagulation cascade pathways.
Conclusions: Our study suggests that C1QA, C1QB, C1QC, CCND1 and EGF may play key roles in the progression of ccRCC, which will be useful for future studies on the underlying mechanisms of ccRCC.
Methods: The GSE36895 gene expression profiles were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were then screened using software packages in R. After Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, a proteinprotein interaction (PPI) network of DEGs was constructed with Cytoscape software, and submodules were subsequently analyzed using the MCODE plug-in.
Results: Twenty-nine ccRCC samples and 23 normal samples were incorporated into this study, and a total of 468 DEGs were filtered, consisting of 180 upregulated genes and 288 downregulated genes. The upregulated DEGs were significantly enriched in the immune response, response to wounding, inflammatory response, and response to hypoxia, whereas downregulated genes were mainly enriched in ion transport, anion transport, and monovalent inorganic cation transport biological processes (BPs). According to Molecular Complex Detection analysis in PPI, C1QA, C1QB, C1QC, CCND1 and EGF had higher degrees of connectivity and could participate in the majority of important pathways, such as cytokine-cytokine receptor interactions, the chemokine signaling pathway, and the complement and coagulation cascade pathways.
Conclusions: Our study suggests that C1QA, C1QB, C1QC, CCND1 and EGF may play key roles in the progression of ccRCC, which will be useful for future studies on the underlying mechanisms of ccRCC.
