文章摘要
范裕裕,索玉平.基于生物信息学构建子宫内膜癌类泛素化相关基因的预后模型[J].安徽医药,待发表.
基于生物信息学构建子宫内膜癌类泛素化相关基因的预后模型
投稿时间:2024-04-22  录用日期:2024-05-15
DOI:
中文关键词: 子宫内膜癌  SUMO  预后模型  肿瘤免疫微环境
英文关键词: 
基金项目:国家自然科学基金项目(面上项目,No:61975105)
作者单位地址
范裕裕 山西医科大学 山西省太原市迎泽区山西省人民医院
索玉平* 山西省人民医院 
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中文摘要:
      目的:探讨类泛素化(Sumoylation,SUMO)对子宫内膜癌(Uterine Corpus Endometrial Carcinoma,UCEC)患者预后及肿瘤免疫微环境的影响。方法:TCGA数据库与GeneCards数据库筛选SUMO相关差异基因(SRGs);功能富集分析确定生物学功能;构建蛋白互作网络筛选Hub基因;通过单因素Cox回归、Lasso回归分析逐步筛选预后基因并构建生存预后模型,按患者的风险评分中位数将其分成高、低风险两组。通过 Kaplan-Meier生存分析和ROC曲线评价模型的预测性能,结合临床指标建立Nomogram 列线图。 结合ESTIMATE 算法分析SUMO相关基因与肿瘤免疫微环境关系。结果:共获得48个SRGs,GO 和 KEGG 富集分析表明SRGs 主要富集于与细胞核功能相关的信号通路;从SRGs中筛选出4个SUMO预后相关基因,预后模型 1、3、5 年依赖 ROC 曲线下面积(AUC)分别为 0.663、0.710和0.717;Nomogram 列线图的 C-index 为0.748,表现出良好的预测效能;高低风险评分组之间肿瘤免疫微环境具有显著差异。结论:本研究构建的SUMO相关基因的生存预后模型可以准确预测UCEC患者的预后。
英文摘要:
      Objective:To explore the effects of Sumoylation(SUMO) on the prognosis and tumor immune microenvironment of endometrial cancer (UCEC) patients. Methods: The TCGA database and GeneCards database were used to screen for differentially expressed genes related to SUMO(SRGs).Functional enrichment analysis to determine biological functions; Constructing protein interaction networks to screen Hub genes. Through single factor Cox regression and Lasso regression analysis,prognostic genes were gradually screened and a survival prognosis model was constructed. Patients were divided into high and low risk groups based on their median risk score. Evaluate the predictive performance of the model through Kaplan Meier survival analysis and ROC curve,and establish a Nomogram column chart in combination with clinical indicators. Analyze the relationship between SUMO related genes and tumor immune microenvironment using the ESTIMATE algorithm. Results: A total of 48 SRGs were obtained, and GO and KEGG enrichment analysis showed that SRGs were mainly enriched in signaling pathways related to nuclear function; Four SUMO prognostic related genes were screened from SRGs, and the area under the ROC curve (AUC) of the prognostic models for 1, 3, and 5 years were 0.663, 0.710, and 0.717, respectively; The C-index of the Nomogram column chart is 0.748, demonstrating good predictive performance; There are significant differences in the tumor immune microenvironment between the high and low risk scoring groups.Conclusion: The survival prognosis model of SUMO related genes constructed in this study can accurately predict the prognosis of UCEC patients.
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