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

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36093523", "kind": "science-record", "revision": 5, "content_hash": "sha256:df6ad2e0240b356d570149cc317d97d5850225e07b764b1b624331b5e59650c8", "created_at": "2026-11-01T18:15:20Z", "updated_at": "2026-11-01T22:50:04Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics analysis and identification of genes and pathways involved in patients with Wilms tumor.", "doi": "10.21037/tcr-22-1847", "pmid": "36093523", "authors": ["Yufeng Li", "Haizhou Tang", "Zhenwen Huang", "Huaxing Qin", "Qin Cen", "Fei Meng", "Liang Huang", "Lifang Lin", "Jian Pu", "Di Yang"], "journal": "Translational cancer research", "year": 2022, "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.\nMethods: 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.\nResults: 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.\nConclusions: 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.", "claims": [{"id": "claim-method", "statement": "Applying the “limma” package (18) (https://bioconductor.org/packages/limma/) in the R statistics environment, DEGs were then extracted from GSE66405, GSE73209, and GSE11151, respectively. FDR ≤0.05 and |log2 fold change (FC)| ≥1 were set as the thresholds for DEGs. Finally, the “Robust Rank Aggregate” package (19) in R language was applied to identify common DEGs among those from the expression profile data sets.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36093523", "locator": "sections[3] \"Microarray data information and DEGs identification\" paragraph 2", "quote": "Applying the “limma” package (18) (https://bioconductor.org/packages/limma/) in the R statistics environment, DEGs were then extracted from GSE66405, GSE73209, and GSE11151, respectively. FDR ≤0.05 and |log2 fold change (FC)| ≥1 were set as the thresholds for DEGs. Finally, the “Robust Rank Aggregate” package (19) in R language was applied to identify common DEGs among those from the expression profile data sets."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The Wilms tumor gene expression profile of GSE66405, GSE73209, and GSE11151 were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/), and the raw expression data were downloaded as a series matrix file.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36093523", "locator": "sections[3] \"Microarray data information and DEGs identification\" paragraph 2", "quote": "The Wilms tumor gene expression profile of GSE66405, GSE73209, and GSE11151 were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/), and the raw expression data were downloaded as a series matrix file."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The analysis identified 474 common differentially expressed genes across the three Wilms tumor microarray expression profiles.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36093523", "locator": "sections[10] \"Identification of DEGs in Wilms tumor\" paragraph 2", "quote": "A total of 474 common DEGs were identified, including 82 up- and 392 down-regulated genes in Wilms tumor tissues, compared to normal tissues."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The analysis identified 474 common differentially expressed genes across the three Wilms tumor microarray expression profiles.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:36093523"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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