Abstract
Renal cell carcinoma (RCC) is one of the most common malignancies in the urinary system, among which the proportion of clear cell RCC (ccRCC) is over 80%. This study aims to explore potential signaling pathways and key biomarkers that drive RCC progression. The RCC GEO Datasets GSE15641 was featured to screen differentially expressed genes (DEGs). The pathway enrichment and functional annotation of differentially expressed genes were analyzed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the Gene Ontology (GO). We screened Hub genes from DEGs using protein-protein interaction (PPI) networks and Cytoscape software. The survival and diagnostic analysis of these hub genes was performed to evaluate their potential prognostic and diagnostic value for ccRCC. In GSE15641 dataset, 598 DEGs were captured according to screening criteria (406 up-regulated genes and 192 down-regulated genes). Meanwhile, 15 hub genes were screened out from DEGs using PPI and Cytoscape. Kaplan Meier and ROC curve analysis identified three potential prognostic and diagnostic biomarkers (TGFB1, TIMP1 and VIM) for ccRCC from 15 hub genes. Gene set enrichment analysis (GSEA) revealed that these three dysregulated genes are mainly enriched in primary immunodeficiency, ECM receptor interaction, cytokine receptor interaction and natural killer cell-mediated cytotoxicity pathway. In summary, our findings discovered pivotal gene expression signatures and signaling pathways in the progression of ccRCC. TGFB1, TIMP1 and VIM might contribute to the progression of ccRCC, which could have potential as biomarkers or therapeutic targets for ccRCC.