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. 2022 Aug;11(8):2843-2857.
doi: 10.21037/tcr-22-1847.

Bioinformatics analysis and identification of genes and pathways involved in patients with Wilms tumor

Affiliations

Bioinformatics analysis and identification of genes and pathways involved in patients with Wilms tumor

Yufeng Li et al. Transl Cancer Res. 2022 Aug.

Abstract

Background: Wilms tumor is the most common childhood kidney malignant tumor. However, the genes and signaling pathways associated with the disease remain incompletely understood.

Methods: GSE66405, GSE73209, and GSE11151 were collected from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were detected using R software. A protein-protein interaction (PPI) network was constructed using the STRING database, and the clustering modules and hub genes were analyzed with the Cytoscape software. Genes functional enrichment analyses were performed using the package "clusterProfiler" in R software, and the gene set enrichment analysis (GSEA) analysis was performed using GSEA v4.1.0 software.

Results: Respectively, 3,092, 620, and 3,567 DEGs were screened in GSE66405, GSE73209, and GSE11151, with a total of 474 common DEGs detected in three expression profiles. For the common DEGs, the top 30 significant results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analyses were presented. Furthermore, five modules were found as the most related modules to Wilms tumor. GO term and KEGG pathway enrichment analyses of the genes in all the modules identified 10 GO terms and 5 KEGG pathways as significantly enriched. The top 10 hub DEGs of the PPI network were ALB, CDH1, EGF, AQP2, REN, SLC2A2, SPP1, UMOD, NPHS2, and FOXM1, with ALB identified as the highest degree. GSEA results showed 11 pathways were correlated with ALB expression in GSE66405 and 10 pathways were related to the expression of the ALB gene in GSE73209.

Conclusions: Our study revealed robust gene signatures in Wilms tumor. Dysregulations of the signaling pathways were associated with the development and progression of the Wilms tumor, and 10 hub genes may play important roles in its diagnosis and therapy.

Keywords: Wilms tumor; differentially expressed genes (DEGs); hub genes; pathways.

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Conflict of interest statement

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-22-1847/coif). The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
Normalization of GSE data. (A) GSE66405 data before normalization; (B) GSE73209 data before normalization; (C) GSE11151 data before normalization; (D) GSE66405 data after normalization; (E) GSE73209 data after normalization; (F) GSE11151 data after normalization. The Y-axis stands for the relative mRNA level and the X-axis represents individual sample.
Figure 2
Figure 2
Volcano plots and heat maps of DEGs. (A-C) Volcano plots of DEGs in expression profiling data GSE66405, GSE73209, and GSE11151, respectively. Red and green dots represent up-regulated and down-regulated DEGs respectively, and black dots represent non DEGs. (D-F) Heat maps of DEGs in GSE66405, GSE73209, and GSE11151, respectively. DEGs, differentially expressed genes.
Figure 3
Figure 3
Heat map of 474 common DEGs among Wilms tumor compared with normal controls. DEGs, differentially expressed genes.
Figure 4
Figure 4
PPI network of 474 common DEGs. PPI, protein-protein interaction; DEGs, differentially expressed genes.
Figure 5
Figure 5
The top five significant clustering modules that were identified in the PPI networks. (A) Module 1; (B) module 2; (C) module 3; (D) module 4; (E) module 5. PPI, protein-protein interaction.
Figure 6
Figure 6
Hub genes screened from PPI network. (A) The top 10 hub genes explored by CytoHubba; (B) with a degree of 75, ALB was identified as the highest degree in the PPI network. The X-axis represented the edge degree of the hub genes, and the Y-axis represented the hub genes. PPI, protein-protein interaction.
Figure 7
Figure 7
KEGG and GO pathway enrichment analysis of common DEGs. (A) The top 30 enriched KEGG pathways are presented; (B) the top 30 GO terms associated with biological process are listed. KEGG, Kyoto Encyclopedia of Genes and Genomes; GO, Gene Ontology; DEGs, differentially expressed genes; BP, biological process; MF, molecular function; CC, cellular component.
Figure 8
Figure 8
Signaling pathway enrichment analysis of DEGs in five modules. (A) Significantly enriched five KEGG pathways of genes in modules; (B) GO enrichment of genes in modules. FC, fold change; DEGs, differentially expressed genes; KEGG, Kyoto Encyclopedia of Genes and Genomes; GO, Gene Ontology.
Figure 9
Figure 9
GSEA enrichment analysis between ALB gene high expression data and ALB low expression data in expression profiling data. (A) GSE66405; (B) GSE73209. KEGG, Kyoto Encyclopedia of Genes and Genomes; GSEA, gene set enrichment analysis.

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