Prediction and analysis of novel key genes ITGAX, LAPTM5, SERPINE1 in clear cell renal cell carcinoma through bioinformatics analysis

Abstract

Background: Clear Cell Renal Cell Carcinoma (CCRCC) is the most aggressive subtype of Renal Cell Carcinoma (RCC) with high metastasis and recurrence rates. This study aims to find new potential key genes of CCRCC.

Methods: Four gene expression profiles (GSE12606, GSE53000, GSE68417, and GSE66272) were downloaded from the Gene Expression Omnibus (GEO) database. The TCGA KIRC data was downloaded from The Cancer Genome Atlas (TCGA). Using GEO2R, the differentially expressed genes (DEG) in CCRCC tissues and normal samples were analyzed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed in DAVID database. A protein-protein interaction (PPI) network was constructed and the hub gene was predicted by STRING and Cytoscape. GEPIA and Kaplan-Meier plotter databases were used for further screening of Key genes. Expression verification and survival analysis of key genes were performed using TCGA database, GEPIA database, and Kaplan-Meier plotter. Receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of key genes in CCRCC, which is plotted by R software based on TCGA database. UALCAN database was used to analyze the relationship between key genes and clinical pathology in CCRCC and the methylation level of the promoter of key genes in CCRCC.

Results: A total of 289 up-regulated and 449 down-regulated genes were identified based on GSE12606, GSE53000, GSE68417, and GSE66272 profiles in CCRCC. The upregulated DEGs were mainly enriched with protein binding and PI3K-Akt signaling pathway, whereas down-regulated genes were enriched with the integral component of the membrane and metabolic pathways. Next, the top 35 genes were screened out from the PPI network according to Degree, and three new key genes ITGAX, LAPTM5 and SERPINE1 were further screened out through survival and prognosis analysis. Further results showed that the ITGAX, LAPTM5, and SERPINE1 levels in CCRCC tumor tissues were significantly higher than those in normal tissues and were associated with poor prognosis. ROC curve shows that ITGAX, LAPTM5, and SERPINE1 have good diagnostic value with good specificity and sensitivity. The promoter methylation levels of ITGAX, LAPTM5 and SERPINE1 in CCRCC tumor tissues were significantly lower than those in normal tissues. We also found that key genes were associated with clinical pathology in CCRCC.

Conclusion: ITGAX, LAPTM5, and SERPINE1 were identified as novel key candidate genes that could be used as prognostic biomarkers and potential therapeutic targets for CCRCC.

Keywords: Bioinformatical analysis; CCRCC; Differentially expressed genes; Protein-protein interaction.

Figure 1. Flow chart of data collection, processing, analysis and verification in this study.

Figure 2. Screening of differentially expressed genes.

(A–D) The volcano plot of all DEGs respectively in GSE12606, GSE53000, GSE68417, and GSE66272 datasets. Red and green nodes represent up-regulated genes and down-regulated genes, respectively. (E–F) 738 DEGs were identified in four profile datasets (GSE12606, GSE53000, GSE68417, and GSE66272), 289 upregulated genes, 449 downregulated genes.

Figure 3. Enrichment analysis of GO and KEGG with up-regulated DEG.

(A) The biological process of GO analysis showed that the up-regulation of DEGs was mainly related to cell adhesion, inflammatory response, signal transduction, and immune response. (B) The enrichment analysis of up-regulated DEGs cell components is mainly related to the cellular exosomes, integral component of membrane, plasma membrane, and integral component of plasma membrane. (C) The molecular function of GO analysis showed that the up-regulation of DEGs was mainly related to protein binding, identical protein bind, ATP binding capacity, and protein homodimerization activity. (D) The KEGG pathways related to the up-regulation of DEGs expression mainly include the PI3K-Akt signaling pathway, focal adhesion, pathways in cancer, and HIF-1 signaling pathway. (E) The biological process of GO analysis showed that the downregulation of DEGs was mainly related to oxidation–reduction process proteolysis, ion transmembrane transport, response to the drug, and ion transport. (F) The enrichment analysis of down-regulated DEGs cell components is mainly related to integral components of membrane, plasma membrane, cellular exosomes, and integral component of plasma membrane. (G) The molecular function of GO analysis showed that the downregulation of DEGs was mainly related to protein homodimerization activity, calcium ion binding, oxidoreductase activity, and sequence-specific DNA binding. (H) The KEGG pathways related to the down-regulation of DEGs expression mainly include metabolic pathway, Biosynthesis of antibiotics, Carbon metabolism, and Aldosterone-regulated sodium reabsorption.

Figure 4. PPI network and GO enrichment analysis of key genes.

(A) The PPI network is constructed, including up-regulated genes and down-regulated genes, and considers that the confidence level ≥ 0.4 is significant for PPI. (B–C) GO enrichment analysis of all DEGs in PPI network. (D) PPI network of the top 35 DEGs according to the degree (degree ≥ 37). (E) GO enrichment analysis of the top 35 DEGs.

Figure 5. Key gene expression between normal kidney and CCRCC tissues.

(A–C) Box plot showing the expression of ITGAX, LAPTM5, SERPINE1 in GEPIA database. These three genes are highly expressed in CCRCC. (D–F) In the TCGA database, compared with adjacent normal tissues, the expression of ITGAX, LAPTM5, SERPINE1 mRNA in 72 pairs of CCRCC tissues increased significantly. (G–I) The expression of ITGAX, LAPTM5, SERPINE1 are significantly increased in Oncomine Gumz renal database. * P < 0.05, ** P < 0.01, *** P < 0.001. (J–L) The box plot showing the promoter methylation levels of ITGAX, LAPTM5 and SERPINE1 in the UALCAN database. P < 0.01.

Figure 6. The relationship between ITGAX, LAPTM5, and SERPINE1 expression and clinical pathology of CCRCC.

(A–C) Boxplot showing that ITGAX, LAPTM5, and SERPINE1 mRNA expression were significantly related to pathological grades, and patients in grade 4 have the highest expression in CCRCC according to UALCAN databases. (D–F) Boxplot showing that the expression of ITGAX, LAPTM5, and SERPINE1 mRNA in CCRCC samples are significantly correlated with severe clinical staging and the mRNA expression of ITGAX, LAPTM5, and SERPINE1 were higher in patients with stage 4 according to UALCAN databases. * P < 0.05, ** P < 0.01, *** P < 0.001.

Figure 7. Survival and diagnostic value of ITGAX, LAPTM5, and SERPINE1 in CCRCC.

(A–C) The overall survival of ITGAX, LAPTM5, and SERPINE1.The results showed that the high expression of three key genes in CCRCC was negatively correlated with prognosis. (D) ROC curve of ITGAX (AUC = 96.315, cutoff value = 8.836, Sensitivity = 92.579 Specificity = 91.667). (E) ROC curve of LAPTM5, (AUC = 94.808, cutoff value = 12.983 Sensitivity = 85.158 Specificity = 94.444). (F) ROC curve of SERPINE1, AUC = 76.272, cutoff value = 12,646, Sensitivity = 66.234 Specificity = 75).