| 范裕裕,索玉平,晋雨楠,等.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,2024,28(11):2173-2178. |
| 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 |
| Constructing a prognostic model for sumoylation related genes in endometrial cancer based on bioinformatics |
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| DOI：10.3969/j.issn.1009-6469.2024.11.012 |
| 中文关键词: 子宫内膜肿瘤 类泛素化 预后模型 肿瘤免疫微环境 |
| 英文关键词: Endometrial neoplasms Sumoylation Prognostic model Tumor immune microenvironment |
| 基金项目:国家自然科学基金资助项目( 61975105) |
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| 摘要点击次数: 474 |
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| 中文摘要: |
| 目的探讨类泛素化( SUMO)对子宫内膜癌( UCEC)病人预后及肿瘤免疫微环境的影响。方法自 2024年 1―2月， 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；构建蛋白质相互作用网络筛选 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，按病人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 0.66、0.71和 0.72；Nomogram列线图的 C-index为 0.75，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差异有统计学意义。结论构建的 SUMO相关基因的生存预后模型可以准确预测 UCEC病人的预后。 |
| 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 From January to February 2024, the TCGA database and GeneCards database were used toscreen for differentially expressed genes related to SUMO (SRGs). Functional enrichment analysis was used to determine biologicalfunctions. Constructing protein interaction networks was used 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 intohigh and low risk groups based on their median risk score. The predictive performance of the model through Kaplan Meier survival analysis and ROC curve was evaluated, and a Nomogram column chart in combination with clinical indicators was established. The relationship between SUMO related genes and tumor immune microenvironment was analyze 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 theprognostic models for 1, 3, and 5 years were 0.66, 0.71, and 0.72, respectively. The C-index of the Nomogram column chart was 0.75,demonstrating good predictive performance. There were significant differences in the tumor immune microenvironment between thehigh 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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