Bioinformatics and functional analyses of key genes and pathways in human clear cell renal cell carcinoma

Abstract

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer. The present study was conducted to explore the mechanisms and identify the potential target genes for ccRCC using bioinformatics analysis. The microarray data of GSE15641 were screened on Gene-Cloud of Biotechnology Information (GCBI). A total of 32 ccRCC samples and 23 normal kidney samples were used to identify differentially expressed genes (DEGs) between them. Subsequently, the clustering analysis and functional enrichment analysis of these DEGs were performed, followed by protein-protein interaction (PPI) network, and pathway relation network. Additionally, the most significant module based on PPI network was selected, and the genes in the module were identified as hub genes. Furthermore, transcriptional level, translational level and survival analyses of hub genes were performed to verify the results. A total of 805 genes, 403 upregulated and 402 downregulated, were differentially expressed in ccRCC samples compared with normal controls. The subsequent bioinformatics analysis indicated that the small molecule metabolic process and the metabolic pathway were significantly enriched. A total of 7 genes, including membrane metallo-endopeptidase (MME), albumin (ALB), cadherin 1 (CDH1), prominin 1 (ROM1), chemokine (C-X-C motif) ligand 12 (CXCL12), protein tyrosine phosphatase receptor type C (PTPRC) and intercellular adhesion molecule 1 (ICAM1) were identified as hub genes. In brief, the present study indicated that these candidate genes and pathways may aid in deciphering the molecular mechanisms underlying the development of ccRCC, and may be used as therapeutic targets and diagnostic biomarkers of ccRCC.

A systematic analysis of molecular mechanisms in non-metastatic renal cancer delineates affected regulatory pathways and genes in tumor growth

“…The gene regulates antigen receptor signaling in immune cells including T cells and B cells (44,58). The results concur with other researches which has shown that the PTPRC gene was expressed highly in kidney tumors (46,60). Interestingly, several studies reported that PTPRC was identified as a hub gene with a high degree being used as a biomarker to screen renal cancer status (44, 61).…”

The Role of CXCL12 in Kidney Diseases: A Friend or Foe?

“…Both Wu et al [61] and Wang et al’s [62] teams showed that CXCL12 was one of the central potential target genes and biomarkers of cc-RCC, contributing to deciphering the molecular mechanisms of cc-RCC occurrence as well as being used as a diagnostic biomarker and therapeutic target for cc-RCC. The genetic polymorphisms of CXCL12/CXCR4 are related to the increased sensitivity of Chinese to RCC, indicating a new risk factor for RCC in the Chinese population [63].…”

Identification of Seven Cell Cycle-Related Genes with Unfavorable Prognosis and Construction of their TF-miRNA-mRNA regulatory network in Breast Cancer

“…Excitingly, the rapid expansion of biological microarray analysis greatly promotes the understanding of driver genes and functional pathways in BC by screening DEGs between tumor and normal tissues in the gene expression profiles of tumors [4]. Increasing data in various cancers have led to the identification of specific genes or pathways that play important roles in the biology and prognosis of tumors via the use of microarrays and bioinformatics methods [5][6][7][8]. Although significant expression of DEGs in BC has been reported in some previous studies [9][10][11][12], those individual studies provide a relatively limited amount of data regarding carcinogenesis.…”