摘要
Abstract
Objective To identify key genes and explore their potential molecular targets related to prognosis in knee osteoarthritis(KOA)by using bioinformatics approaches.Methods Gene expression datasets were obtained from the Gene Expression Omnibus(GEO)database,including GSE12021(9 normal controls and 9 KOA samples),GSE55235(10 normal controls and 9 KOA samples),GSE82107(7 normal controls and 10 KOA samples),GSE29746(11 normal controls and 11 KOA samples),and GSE55457(10 normal controls and 10 KOA samples).Differentially expressed genes(DEGs)were identified using the Limma package in R,and their expression patterns were visualized through heatmaps and volcano plots.Cross-analysis was conducted to determine KOA-associated DEGs.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses were performed to explore the biological roles and potential mechanisms of these genes.A protein-protein interaction(PPI)network was constructed using the STRING database,and core genes were identified using three algorithms(CytoHubba,MCODE,and CytoNCA)within Cytoscape 3 software.To further validate the reliability of the core genes,receiver operating characteristic(ROC)curve analysis was employed,and predictive performance was examined across the five datasets(GSE12021,GSE55235,GSE82107,GSE29746,GSE55457).Results A total of 238 KOA-related DEGs were identified.ROC curve analysis showed that six genes(ATF3,IL-6,JUN,PTGS2,MYC,and SOCS3)showed an area under the curve(AUC)greater than 0.7 across all datasets,indicating their strong diagnostic potential.These genes are likely to play critical roles in the pathogenesis and prognosis of KOA and may represent novel therapeutic targets.Conclusion ATF3,IL-6,JUN,PTGS2,MYC,and SOCS3 and other genes are involved in the pathogenesis and prognosis of KOA,and may serve as novel therapeutic targets.The PPI network constructed through the STRING database further revealed the complex interactions between these genes and provided new insights into the molecular mechanism of KOA.The core genes screened based on various algorithms of Cytoscape 3 provide a theoretical basis for subsequent clinical research and targeted therapy.Finally,ROC validation confirmed the potential diagnostic utility of these genes in KOA.关键词
膝骨关节炎/生物信息学/GEO/核心基因Key words
knee osteoarthritis/bioinformatics/GEO/core gene分类
医药卫生
