Analysis of differentially expressed genes, clinical value and biological pathways in prostate cancer

Abstract

The present study aimed to investigate the gene expression changes in prostate cancer (PC) and screen the hub genes and associated pathways of PC progression. The authors employed integrated analysis of GSE46602 downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas databases to identify 484 consensual differentially expressed genes (DEGs) in PC, when compared with adjacent normal tissue samples. Functional annotation and pathway analysis were performed. The protein-protein interaction (PPI) networks and module were constructed. RT-qPCR was used to validate the results in clinical PC samples. Survival analysis of hub genes was performed to explore their clinical value. GO analysis results revealed that DEGs were significantly enriched in negative regulation of nitrobenzene metabolic process, extracellular space and protein homodimerization activity. KEGG pathway analysis results revealed that DEGs were most significantly enriched in focal adhesion. The top 10 hub genes were identified to be hub genes from the PPI network, and the model revealed that these genes were enriched in various pathways, including neuroactive ligand-receptor interaction, p53 and glutathione metabolism signaling pathways. RT-qPCR results validated that expression levels of eight genes (PIK3R1, BIRC5, ITGB4, RRM2, TOP2A, ANXA1, LPAR1 and ITGB8) were consistent with the bioinformatics analysis. ITGB4 and RRM2 with genetic alterations exhibited association with a poorer survival rate, compared with those without alterations. These results revealed that PC-related genes and pathways have an important role in tumor expansion, metastasis and prognosis. In summary, these hub genes and related pathways may act as biomarkers or therapeutic targets for PC.

Keywords: GEO; Prostate cancer; TCGA; bioinformatic analysis; differentially expressed genes.

Figure 1

Two volcano plots of DEGs and one Venn diagram of the DEGs screening. For the volcano, the volcano plot on the left (A) is the result of the GEO database and the volcano plot on the right (B) represents the result of the TCGA database. The abscissa is logFC and the ordinate is -log10 (adj. P Value). The red and green spots represent DEGs. The black dots represent genes that are not differentially expressed between PC and control samples. Red: upregulated; green: downregulated. The Venn diagram (C) indicates the number of DEGs in four different datasets and the crossing area indicates the cross-DEGs in different datasets. 168 upregulated and 316 downregulated genes were identified from the data obtained from the TCGA and GEO databases. GEO, Gene Expression Omnibus; TCGA, The Cancer Genome Atlas; PC, prostate cancer; DEG, differentially expressed gene.

Figure 2

Top five Gene Ontology enrichment analysis and KEGG pathways. (A) Biological processes, (B) cellular components, (C) molecular functions and (D) KEGG pathway analysis. KEGG, Kyoto Encyclopedia of Genes and Genome.

Figure 3

PPI network of the DEGs and modular analysis. (A) DEG PPI network complex, (B) module 1 of DEGs from PPI network, (C) module 2 of DEGs from PPI network and (D) module 3 of DEGs from PPI network. Red nodes represent the upregulated DEGs and green nodes represent the downregulated DEGs. Increased node interaction suggests a greater biological significance. PPI, protein-protein interaction; DEG, differentially expressed gene.

Figure 4

The expression levels of eight hub genes were detected in 12 tissues of PC patients and their matched para-cancerous tissue, using reverse transcription-quantitative polymerase chain reaction. GAPDH was used as an internal reference gene for normalization.

Figure 5

Genetic alterations and the prognostic value of differentially expressed genes in prostate cancer. A. Genetic alterations: Red represents amplification, blue represents deep deletion, pink represents mRNA upregulation, gray represents truncating mutation (putative passenger) and green represents missense mutation (putative passenger). B. Kaplan-Meier curves of two hub genes between group with alterations and group without alterations. The Kaplan-Meier survival curves showed the significant prognostic value of ITGB4 and RRM2 alteration regarding survival. Red line represents cases with alterations in query genes. Blue line represents cases without alterations in query genes. The x-axis indicates overall survival time (months) and the y-axis represents the survival rate. These curves were downloaded from cBioPortal.