Identification of Key Genes and Prognostic Analysis between Chromophobe Renal Cell Carcinoma and Renal Oncocytoma by Bioinformatic Analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31998788", "kind": "science-record", "revision": 7, "content_hash": "sha256:458eb1dc0cb65d929f909916956699e54ca83b840d569b11f283b627a4dabcb6", "created_at": "2026-11-01T15:40:55Z", "updated_at": "2026-11-01T22:01:14Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Key Genes and Prognostic Analysis between Chromophobe Renal Cell Carcinoma and Renal Oncocytoma by Bioinformatic Analysis.", "doi": "10.1155/2020/4030915", "pmid": "31998788", "authors": ["Hongwei Wu", "Lijing Fan", "Haiping Liu", "Baozhang Guan", "Bo Hu", "Fanna Liu", "Berthold Hocher", "Lianghong Yin"], "journal": "BioMed research international", "year": 2020, "abstract": "The present techniques of clinical and histopathological diagnosis hardly distinguish chromophobe renal cell carcinoma (ChRCC) from renal oncocytoma (RO). To identify differentially expressed genes (DEGs) as effective biomarkers for diagnosis and prognosis of ChRCC and RO, three mRNA microarray datasets (GSE12090, GSE19982, and GSE8271) were downloaded from the GEO database. Functional enrichment analysis of DEGs was performed by DAVID. STRING and Cytoscape were applied to construct the protein-protein interaction (PPI) network and key modules of DEGs. Visualized plots were conducted by the R language. We downloaded clinical data from the TCGA database and the influence of key genes on the overall survival of ChRCC was performed by Kaplan-Meier and Cox analyses. Gene set enrichment analysis (GSEA) was utilized in exploring the function of key genes. A total of 79 DEGs were identified. Enrichment analyses revealed that the DEGs are closely related to tissue invasion and metastasis of cancer. Subsequently, 14 hub genes including ESRP1, AP1M2, CLDN4, and CLDN7 were detected. Kaplan-Meier analysis indicated that the low expression of CLDN7 and GNAS was related to the worse overall survival in patients with ChRCC. Univariate Cox analysis showed that CLDN7 might be a helpful biomarker for ChRCC prognosis. Subgroup analysis revealed that the expression of CLDN7 showed a downtrend with the development of the clinical stage, topography, and distant metastasis of ChRCC. GSEA analysis identified that cell adhesion molecules cams, B cell receptor signaling pathway, T cell receptor signaling pathway, RIG-I like receptor signaling pathway, Toll-like receptor signaling pathway, and apoptosis pathway were associated with the expression of CLDN7. In conclusion, ESRP1, AP1M2, CLDN4, PRSS8, and CLDN7 were found to distinguish ChRCC from RO. Besides, the low expression of CLDN7 was closely related to ChRCC progression and could serve as an independent risk factor for the overall survival in patients with ChRCC.", "claims": [{"id": "claim-method", "statement": "The association between key genes and the overall survival of ChRCC patients was done by the Kaplan–Meier method. Clinical data (65 ChRCC samples) were downloaded from TCGA.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31998788", "locator": "sections[8] \"2.6. Survival Analysis of Key Genes by TCGA\" paragraph 2", "quote": "The association between key genes and the overall survival of ChRCC patients was done by the Kaplan–Meier method."}, {"asset": "source:pmid:31998788", "locator": "sections[15] \"3.5. 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