摘要
目的 研究细胞膜张力相关基因(Cell membrane tension-related genes, CMTRGs)对肝细胞癌(Hepatocellular carcinoma, HCC)患者预后的影响。方法 从癌症基因组图谱数据库下载HCC患者的RNA测序数据、临床信息及体细胞突变数据,利用单因素Cox回归分析、LASSO回归、多因素Cox回归分析构建预后模型,基于风险评分将患者分为高、低风险组。通过Kaplan-Meier生存曲线分析及受试者工作特征(Receiver operating characteristic,ROC)曲线对模型效能进行评估,结合风险评分和临床特征构建列线图并评估列线图效能。对风险差异表达基因进行差异表达基因本体(Gene ontology, GO)、京都基因与基因组百科全书(Kyoto encyclopedia of genes and genome, KEGG)和单样本基因集富集(Single sample gene set enrichment analysisss, ssGSEA)分析。比较两组间免疫检查表达以及对免疫治疗反应性的差异。通过基因表达数据库获得HCC单细胞测序数据(Single-cell RNA sequencing, scRNA-seq),以揭示HCC的细胞浸润,用拟时序分析探讨细胞间的相互作用。结果 构建由3个基因(PDCD6IP、CFL1、EPO)组成的预后模型,Kaplan-Meier生存曲线表明CMTRGs高风险组总体生存较差(P<0.001);ROC曲线显示此预后模型1、3、5年的AUC均>0.60,该模型对HCC患者的预后有较好的预测作用,通过单因素Cox回归分析显示,临床分期(HR=2.836,95%CI:1.934~4.158,P<0.001)、风险评分(HR=1.234,95%CI:1.170~1.303,P<0.001)均与患者的预后密切相关。多因素Cox回归分析显示风险评分(HR=1.189,95%CI:1.122~1.260,P<0.001)和临床分期(HR=2.229,95%CI:1.487~3.342,P<0.001)均是HCC患者的独立预测因子。纳入风险评分的列线图(HR=2.033,95%CI:1.265~3.267,P=0.003)对HCC患者的预后有较好的预测性能。功能富集分析表明高风险组主要富集在肿瘤及机械转导相关通路上;免疫相关性分析得出高风险组在免疫逃逸相关通路中上调(P<0.05),免疫抑制细胞浸润增加(P<0.05),免疫检查点高表达(P<0.05),从免疫治疗中获益更少(P<0.05)。scRNA-seq分析提示HCC中有免疫细胞耗竭现象,拟时序分析发现内皮细胞有向成纤维细胞转化的趋势。结论 通过整合生物信息学分析,构建由PDCD6IP、CFL1、EPO组成的预后模型,基于模型构建的风险评分和列线图有助于HCC患者的预后评估及临床决策。
Objective To investigate the impact of cell membrane tension-related genes(CMTRGs)on the prognosis of hepatocellular carcinoma(HCC)patients.Methods RNA sequencing data,clinical information and somatic mutation data of HCC patients were obtained from The Cancer Genome Atlas database.Prognostic models were constructed using univariate Cox regression,LASSO regression and multivariate multivariate Cox regression.The patients were stratified into high-and low-risk groups based on risk scores.Model performance was evaluated via Kaplan-Meier survival analysis and receiver operating characteristic(ROC)curves.A nomogram integrating risk scores and clinical features was developed,and its predictive accuracy was validated.Differentially expressed genes were analyzed using Gene Ontology(GO),Kyoto Encyclopedia of Genes and Genomes(KEGG)and single-sample gene set enrichment analysis(ssGSEA).Differences in immune checkpoint expression and immunotherapy responsiveness between thegroups were compared.Single-cell RNA sequencing(scRNA-seq)data from the Gene Expression Omnibus(GEO)database were employed to characterize cellular infiltration in HCC,and pseudotime trajectory analysis was conducted to explore cell-cell interactions.Results A prognostic model comprising three genes(PDCD6IP,CFL1,EPO)was established.Kaplan-Meier survival curves demonstrated significantly poorer overall survival in the CMTRGs high-risk group(P<0.001).ROC curves showed AUC values>0.60 for 1-,3-and 5-year survival predictions,confirming the model′s robust prognostic utility.Univariate Cox regression identified clinical stage(HR=2.836,95%CI:1.934-4.158,P<0.001)and risk score(HR=1.234,95%CI:1.170-1.303,P<0.001)as significant prognostic factors.Multivariate Cox analysis confirmed that both risk score(HR=1.189,95%CI:1.122-1.260,P<0.001)and clinical stage(HR=2.229,95%CI:1.487-3.342,P<0.001)were independent predictors of HCC prognosis.The nomogram incorporating risk scores(HR=2.033,95%CI:1.265-3.267,P=0.003)exhibited strong predictive performance.Functional enrichment analysis revealed significant enrichment of tumorigenesis and mechanotransduction pathways in the high-risk group.Immune-related analyses indicated upregulated immune evasion pathways(P<0.05),increased infiltration of immunosuppressive cells(P<0.05),elevated immune checkpoint expression(P<0.05),and reduced immunotherapy benefits(P<0.05)in the high-risk group.scRNA-seq analysis highlighted immune cell exhaustion in HCC,and pseudotime trajectory analysis suggested a potential transition of endothelial cells toward fibroblasts.Conclusion By integrating bioinformatics approaches,a prognostic model based on PDCD6IP,CFL1 and EPO was established.The risk score and nomogram derived from this model provide valuable tools for prognostic assessment and clinical decision-making in HCC patients.
作者
卡丽玛·木合塔尔
伊雯
张莉
Kalima Muhetaer;YI Wen;ZHANG Li(Department1 of Comprehensive Internal Medicine,the First Affiliated Hospital of Xinjiang Medical University,Urumqi 830054,China)
出处
《新疆医科大学学报》
2025年第5期579-593,598,共16页
Journal of Xinjiang Medical University
基金
新疆维吾尔自治区重点研发计划项目(2020B03003,2020B03003-3)。
关键词
细胞膜张力
肝细胞癌
预后模型
肿瘤微环境
免疫
cell membrane tension
hepatocellular carcinoma
prognostic model
tumor microenvironment
immunity
