Microarray Profiling of Human Renal Cell Carcinoma: Identification for Potential Biomarkers and Critical Pathways

Abstract

Aims: The aim of this study was to screen several novel genes associated with renal cell carcinoma (RCC), and analyze the gene functions and signal pathways which were critical to RCCs with DNA microarray. Methods: The gene expression profile of GSE781 was downloaded from Gene Expression Omnibus database, including 9 RCC samples and 9 healthy controls. Compared with the control samples, differentially expressed genes (DEGs) of RCC was identified the by packages in R. The selected DEGs were further analyzed using bioinformatics methods. Gene ontology (GO) enrichment analysis was performed using Gene Set Analysis Toolkit and protein-protein interaction (PPI) network was constructed with prePPI. Then, pathway enrichment analysis to PPI network was performed using WebGestalt software. Results: A total of 429 DEGs were down-regulated and 418 DEGs were up-regulated in RCC samples compared to healthy controls. A total of 11 remarkable enhanced functions and 13 suppressed functions were identified. PPI nodes of high degrees, such as JAK2, IL8, BMPR2, FN1 and NCR1, were obtained. The DEGs were classified and significantly enriched in cytokine and cytokine receptor pathway. Conclusion: The hub genes we find from RCC samples are not only bio-markers, but also may provide the groundwork for a combination therapy approach for RCCs.

Keywords

• Microarray profiling
• Renal cell carcinoma
• Differentially expressed genes