骨肉瘤和软组织肉瘤Hub基因的挖掘及其诊断和预后分析

来源期刊：广州医药 | 350-359 发布时间：2024-05-17 收稿时间：2025/11/13 18:48:56 阅读量：26

作者：: 岳浩,

刘飞飞,

阮玉山,

李绍波,

任莉荣,

关键词：: 骨肉瘤软组织肉瘤差异表达基因; osteosarcoma soft-tissue sarcoma differentially expressed genes

DOI：: 10.3969/j.issn.1000-8535.2024.04.003

收稿时间：: 2023-10-25
修订日期：
接收日期：
引用总数：: 0

目的探讨骨肉瘤（OS）和软组织肉瘤（STS）的关键核心基因（Hub基因）及其潜在作用,为肿瘤诊断和预后提供新依据。方法从基因表达综合数据库（GEO）获得OS数据集GSE16088及STS数据集GSE21122,采用GEO2R在线工具筛选GSE16088和GSE21122数据集的差异表达基因（DEGs）。通过韦恩图获得2个数据集共同DEGs。选取2个数据集中差异表达最显著的上调和下调基因各20个,分别绘制聚类热图。通过使用注释、可视化和综合发现数据库（DAVID）对2个数据集的共同DEGs进行功能（GO）和通路（KEGG）富集分析。构建蛋白互作网络并使用最大中心度（MCC）算法筛选排名最前的10个基因作为潜在的关键Hub基因。采用受试者工作特征（ROC）曲线探讨关键Hub基因对肉瘤患者的诊断价值。通过Kaplan-Meier Plotter进行生存期分析。通过实时荧光定量PCR技术对得分靠前的5个Hub基因进行验证。结果 GSE16088数据集筛选出5 210个DEGs,其中上调和下调的DEGs分别为1 028、4 182个;GSE21122数据集共筛选出1 224个DEGs,其中上调和下调的DEGs分别为451、773个;2个数据集共获得498个共同DEGs。共同DEGs参与到多个生物学过程和信号通路。基于PPI网络和MCC算法最终获得10个关键Hub基因,ROC曲线验证结果符合预期,且生存期分析10个关键Hub基因与肉瘤预后显著相关（P<0.05）。Hub基因在mRNA表达水平和生物信息学分析结果一致（P<0.05）。结论 10个关键Hub基因可用于肉瘤的诊断和预后,为后续免疫治疗提供新视野。

Objective To explore the Hub genes of osteosarcoma（OS）and soft tissue sarcoma（STS）and their potential roles,and to provide evidence for tumor diagnosis and prognosis．Methods The GSE16088 dataset and the GSE21122 dataset were screened in the Gene Expression Omnibus database of the National Center for Biotechnology Information in the United States．The online editing tool GEO2R was used to screen the DEGs of the GSE16088 dataset and the GSE21122 dataset and the Veen map was drawn to find the common DEGs of the GSE16088 dataset and the GSE21122 dataset．20 up-regulated and 20 down-regulated genes with the most significant differential expression were selected from 2 datasets,and heatmaps were drawn for each．The Database for Annotation,Visualization and Integrated Discovery was used to perform GO function enrichment analysis and KEGG pathway enrichment analysis on DEGs of GSE16088 dataset and GSE21122 dataset．PPI network of DEGs was constructed by STRING．PPI sub-modules and Hub genes with high connectivity were screened．Maximal clique centrality（MCC）score was used to select the Hub genes in the protein interaction network．The predictive value of 10 Hub genes in sarcoma patients was analyzed by receiver operating characteristic（ROC）curve．Survival analysis was performed by means of the Kaplan-Meier Plotter．The top five core genes were verified by real-time fluorescence quantitative PCR．Results A total of 5 210 genes were screened in GSE16088 dataset,including 1 028 and 4 182 genes with upregulated and downregulated expression．A total of 1 224 genes were selected from the GSE21122 dataset,including 451 and 773 genes with upregulated and downregulated expression．The cluster heatmap was used to show the top 20 DEGs with high and low expression in GSE16088 and GSE21122 datasets．By differential analysis of gene expression between the two datasets,498 co-DEGs were obtained．GO and KEGG enrichment showed that common DEGs were associated．Ten Hub genes were obtained by PPI and MCC algorithm,the ROC curve verification results were as expected．Survival analysis showed that 10 Hub genes were significantly associated with the prognosis of sarcoma（P<0.05）．The mRNA expression level of Hub genes was the same as the results of bioinformatics analysis（P<0.05）．Conclusions The 10 Hub genes can be used for the diagnosis and prognosis of osteosarcoma,and provide a new vision for subsequent immunotherapy．

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