Screening and identification of key biomarkers in bladder carcinoma: Evidence from bioinformatics analysis

Abstract

Bladder cancer (BC) is one of the most common urogenital malignancies. However, present studies of its multiple gene interaction and cellular pathways remain unable to accurately verify the genesis and the development of BC. The aim of the present study was to investigate the genetic signatures of BC and identify its potential molecular mechanisms. The gene expression profiles of GSE31189 were downloaded from the Gene Expression Omnibus database. The GSE31189 dataset contained 92 samples, including 52 BC and 40 non-cancerous urothelial cells. To further examine the biological functions of the identified differentially expressed genes (DEGs), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed, and a protein-protein interaction (PPI) network was mapped using Cytoscape software. In total, 976 DEGs were identified in BC, including 457 upregulated genes and 519 downregulated genes. GO and KEGG pathway enrichment analyses indicated that upregulated genes were significantly enriched in the cell cycle and the negative regulation of the apoptotic process, while the downregulated genes were mainly involved in cell proliferation, cell adhesion molecules and oxidative phosphorylation pathways (P<0.05). From the PPI network, the 12 nodes with the highest degrees were screened as hub genes; these genes were involved in certain pathways, including the chemokine-mediated signaling pathway, fever generation, inflammatory response and the immune response nucleotide oligomerization domain-like receptor signaling pathway. The present study used bioinformatics analysis of gene profile datasets and identified potential therapeutic targets for BC.

Keywords: bladder cancer; differentially expressed genes; microarray analysis; protein-protein interaction network.

Figure 1.

DEG analysis of the GSE31189 data set. DEGs were identified using the Linear Models for Microarray Analysis package. Blue indicates downregulated genes, red indicates upregulated genes and black indicates genes with unchanged expression. DEG, differentially expressed gene; FC, fold-change; down, downregulated; no, no change; up, upregulated.

Figure 2.

GO analysis of upregulated genes of the GSE31189 data set. GO, Gene Ontology; MF, molecular function; CC, cellular component; BP, biological process.

Figure 3.

GO analysis of downregulated genes of the GSE31189 data set. GO, Gene Ontology; MF, molecular function; CC, cellular component; BP, biological process.

Figure 4.

KEGG pathway enrichment analysis. KEGG, Kyoto Encyclopedia of Genes and Genomes; BP, biological process; CC, cellular component; TNF, tumor necrosis factor; AGE-RAGE, advanced glycation end product-receptor for AGE.

Figure 5.

Protein-protein interaction network of differentially expressed genes. Red nodes denote upregulated genes, green nodes denote downregulated genes.

Figure 6.

One significant module selected from the protein-protein interaction network. Red nodes denote upregulated genes, green nodes denote downregulated genes.

Figure 7.

Hub genes expression heat map in the GSE31189 data set. Red indicates upregulation and green indicates downregulation.

Figure 8.

Association between mRNA expression and overall survival rate in patients with bladder cancer (using the PrognoScan database). P<0.05 was used as the threshold. NOD2, nucleotide binding oligomerization domain containing 2; S100A9, S100 calcium binding protein A9; CXCL1, C-X-C motif chemokine ligand 1; CXCR2, C-X-C motif chemokine receptor 2; HR, hazard ratio.