Identification of Hub Genes Associated With Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34660292", "kind": "science-record", "revision": 4, "content_hash": "sha256:c209e5f6639904dce8f1c7a7df41c8fb3e83b9350c05c45f6738a5a342749f9e", "created_at": "2026-11-01T17:36:19Z", "updated_at": "2026-11-01T22:04:58Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Hub Genes Associated With Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis.", "doi": "10.3389/fonc.2021.726655", "pmid": "34660292", "authors": ["Hao Huang", "Ling Zhu", "Chao Huang", "Yi Dong", "Liangliang Fan", "Lijian Tao", "Zhangzhe Peng", "Rong Xiang"], "journal": "Frontiers in oncology", "year": 2021, "abstract": "BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is a common genitourinary cancer type with a high mortality rate. Due to a diverse range of biochemical alterations and a high level of tumor heterogeneity, it is crucial to select highly validated prognostic biomarkers to be able to identify subtypes of ccRCC early and apply precision medicine approaches.\nMETHODS: Transcriptome data of ccRCC and clinical traits of patients were obtained from the GSE126964 dataset of Gene Expression Omnibus and The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) database. Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) screening were applied to detect common differentially co-expressed genes. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analysis, survival analysis, prognostic model establishment, and gene set enrichment analysis were also performed. Immunohistochemical analysis results of the expression levels of prognostic genes were obtained from The Human Protein Atlas. Single-gene RNA sequencing data were obtained from the GSE131685 and GSE171306 datasets.\nRESULTS: In the present study, a total of 2,492 DEGs identified between ccRCC and healthy controls were filtered, revealing 1,300 upregulated genes and 1,192 downregulated genes. Using WGCNA, the turquoise module was identified to be closely associated with ccRCC. Hub genes were identified using the maximal clique centrality algorithm. After having intersected the hub genes and the DEGs in GSE126964 and TCGA-KIRC dataset, and after performing univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses, ALDOB, EFHD1, and ESRRG were identified as significant prognostic factors in patients diagnosed with ccRCC. Single-gene RNA sequencing analysis revealed the expression profile of ALDOB, EFHD1, and ESRRG in different cell types of ccRCC.\nCONCLUSIONS: The present results demonstrated that ALDOB, EFHD1, and ESRRG may act as potential targets for medical therapy and could serve as diagnostic biomarkers for ccRCC.", "claims": [{"id": "claim-method", "statement": "Univariate Cox regression analysis was performed to screen the genes significantly associated with overall survival (OS) in the TCGA-KIRC dataset. The OS-related genes with p < 0.1 were included in the least absolute shrinkage and selection operator (LASSO) regression analysis by using the R package “glmnet” (version 4.1-2). Then, a multivariate Cox regression model analysis was performed to establish a Cox proportional hazards regression prognostic model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34660292", "locator": "sections[8] \"Identification and Verification of Prognostic Gene Signatures\" paragraph 2", "quote": "Univariate Cox regression analysis was performed to screen the genes significantly associated with overall survival (OS) in the TCGA-KIRC dataset. The OS-related genes with p < 0.1 were included in the least absolute shrinkage and selection operator (LASSO) regression analysis by using the R package “glmnet” (version 4.1-2). Then, a multivariate Cox regression model analysis was performed to establish a Cox proportional hazards regression prognostic model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . 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Further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "ALDOB, EFHD1, and ESRRG were identified as independent prognostic factors and used to establish a prognostic model for ccRCC.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34660292", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "After having intersected the hub genes and the DEGs in GSE126964 and TCGA-KIRC dataset, and after performing univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses, ALDOB, EFHD1, and ESRRG were identified as significant prognostic factors in patients diagnosed with ccRCC."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "ALDOB, EFHD1, and ESRRG were identified as independent prognostic factors and used to establish a prognostic model for ccRCC.", "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:34660292"], "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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Immunohistochemical analysis results of the expression levels of"], "order_basis": "paper_text_order:989", "id": "assay:1"}, {"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ed from The Human Protein Atlas. Single-gene RNA sequencing data were obtained from the GSE131685 and GS", "n patients diagnosed with ccRCC. Single-gene RNA sequencing analysis revealed the expression profile of", "n Atlas; GSEA, gene set enrichment analysis. RNA-seq data of TCGA-KIRC and corresponding clinical", "https://portal.gdc.cancer.gov/). 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