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pmid:38937666
Screening of potential hub genes involved in Kidney Wilms tumor via bioinformatics analysis and experimental validation.
Qiang Zeng · Tingting Liu · Lilu Qin · Chen Wang · Guangbei Peng · Zhong Liu · Junfeng Tao
BMC cancer · 2024 doi:10.1186/s12885-024-12541-x
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Experiment
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Data
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Complete file
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Improving patient outcomes requires advances in understanding and targeting the multiple genes and cellular control pathways, but its pathogenesis is currently not well-researched. We aimed to identify the potential molecular biological mechanism of WT and develop new prognostic markers and molecular targets by comparing gene expression profiles of Wilms tumors and fetal normal kidneys.\nMETHODS: Differential gene expression analysis was performed on Wilms tumor transcriptomic data from the GEO and TARGET databases. For biological functional analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were utilized. Out of 24 hub genes identified, nine were found to be prognostic-related through univariate Cox regression analysis. These nine genes underwent LASSO regression analysis to enhance the predictive capability of the model. The key hub genes were validated in the GSE73209 datasets, and cell function experiments were conducted to identify the genes' functions in WiT-49 cells.\nRESULTS: The enrichment analysis revealed that DEGs were significantly involved in the regulation of angiogenesis and regulation of cell differentiation. 24 DEGs were identified through PPI networks and the MCODE algorithm, and 9 of 24 genes were related to WT patients' prognosis. EMCN and CCNA1 were identified as key hub genes, and related to the progression of WT. Functionally, over-expression of EMCN and CCNA1 knockdown inhibited cell viability, proliferation, migration, and invasion of Wilms tumor cells.\nCONCLUSIONS: EMCN and CCNA1 were identified as key prognostic markers in Wilms tumor, suggesting their potential as therapeutic targets. Differential gene expression and enrichment analyses indicate significant roles in angiogenesis and cell differentiation.", "claims": [{"id": "claim-method", "statement": "The LASSO regression algorithm was used for feature selection, and 10-fold cross-validation was used to determine the parameters among which the key genes associated with the patient survival cycle were screened.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38937666", "locator": "sections[8] \"Construction and identification of the prognostic risk model\" paragraph 2", "quote": "The LASSO regression algorithm was used for feature selection, and 10-fold cross-validation was used to determine the parameters among which the key genes associated with the patient survival cycle were screened."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. 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A risk-score formula was developed: Riskscore=(-0.1614)*EMCN+ (0.0378)*CCNA1 (lambda.min = 0.0743)."}, {"asset": "source:pmid:38937666", "locator": "sections[21] \"Construction of the prognostic risk model and analysis\" paragraph 3", "quote": "Notably, the overall survival of WT patients in the low-risk group surpassed that of patients in the high-risk group (p = 0.00794, HR = 2.107) (Fig. 6D)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "LASSO regression identified EMCN and CCNA1 as the two hub genes associated with overall survival in Wilms tumor, and the resulting risk model separated patients by overall-survival outcome.", "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:38937666"], "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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