ArticleBioMed research international2021
Bioinformatics Analysis of ZBTB16 as a Prognostic Marker for Ewing's Sarcoma.
Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Integrative analyses of bulk microarray data to discover genes, pathways, and immune infiltration characteristics associated with targeting of Ewing sarcoma.Journal of cancer research and clinical oncology · 2023Article
- COL8A1 Predicts the Clinical Prognosis of Gastric Cancer and Is Related to Epithelial-Mesenchymal Transition.BioMed research international · 2022Article
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9 authors.
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Abstract
objectiveThe purpose of this study is to identify novel biomarkers for the prognosis of Ewing's sarcoma based on bioinformatics analysis.
methodsThe GSE63157 and GSE17679 datasets contain patient and healthy control microarray data that were downloaded from the Gene Expression Omnibus (GEO) database and analyzed through R language software to obtain differentially expressed genes (DEGs). Firstly, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment, protein-protein interaction (PPI) networks, and Cytoscape Molecular Complex Detection (MCODE) plug-in were then used to compute the highest scores of the module. After survival analysis, the hub genes were lastly obtained from the two module genes.
resultsA total of 1181 DEGs were identified from the two GSEs. Through MCODE and survival analysis, we obtain 53 DEGs from the module and 29 overall survival- (OS-) related genes. ZBTB16 was the only downregulated gene after Venn diagrams. Survival analysis indicates that there was a significant correlation between the high expression of ZBTB16 and the OS of Ewing's sarcoma (ES), and the low expression group had an unfavorable OS when compared to the high expression group.
conclusionsHigh expression of ZBTB16 may serve as a predictor biomarker of poor prognosis in ES patients.
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