摘要
目的 通过利用生物信息学开发糖酵解相关基因以预测胃癌(gastric cancer,GC)患者预后。方法 使用癌症基因组图谱数据库中GC患者信使核糖核酸表达谱数据,通过进行基因集富集分析以鉴定GC组织和正常组织间显著差异的基因集。通过最小绝对收缩和选择算子回归分析构建糖酵解相关基因预测GC患者预后的模型,并使用Kaplan-Meier分析、受试者工作特征曲线、单因素及多因素Cox回归分析验证模型预测性能。采用基因集变异分析分析高低风险组间生物途径状态的差异。结果 获得15个糖酵解相关基因(PFKFB2、UHRF1、ACYP1、CLDN9、STC1、EFNA3、NUP50、ADH4、ANGPTL4、PKP2、VCAN、HIF1A、LHX9、ANKZF1、ALDH3A2)与GC患者预后相关。根据15个基因特征风险评分,通过Cox回归分析将患者分为高风险组和低风险组。这15个基因标记是GC患者预后的独立生物标志物,低风险评分的GC患者预后更好。结合基因标记和临床预后因素的列线图可有效预测总生存期及无疾病生存期。结论 建立的15个糖酵解相关基因标记可作为预测GC患者预后的可靠工具,可能为GC提供潜在的糖酵解治疗靶点。
Objective To construct a glycolysis-related gene model for predicting the prognosis of gastric cancer(GC)patients based on bioinformatics.Methods The messenger RNA expression profiles of GC patients were analyzed in The Cancer Genome Atlas program,and gene sets with significant differences between GC tissues and normal tissues were verified using gene set enrichment analysis.A glycolysis-related genes model for predicting the prognosis of GC patients was constructed using least absolute shrinkage and selection operator regression analysis,and the predictive performance of the model was validated using Kaplan-Meier survival analysis,receiver operating characteristic curve,and univariate and multivariate Cox regression analysis.Gene set variation analysis was performed to analyze the differences in biological pathway states between high-risk and low-risk groups.Results Fourteen glycolysis-related genes(PFKFB2,UHRF1,ACYP1,CLDN9,STC1,EFNA3,NUP50,ADH4,ANGPTL4,PKP2,VCAN,HIF1A,LHX9,ANKZF1,ALDH3A2)were identified as prognostic markers for GC patients.Based on a risk score derived from these 15 gene features using Cox regression analysis,patients were classified into high-risk and low-risk groups.These 15 gene markers were independent biomarkers for predicting the prognosis,and patients with a low-risk score had a better prognosis.The combination of gene markers and clinical prognostic factors in a Nomogram effectively predicted overall survival and disease-free survival.Conclusion The established panel of 15 glycolysis-related gene markers can serve as reliable tools for predicting the prognosis of GC patients and may provide potential targets for glycolysis-targeted therapy in GC.
作者
赵旭辉
黄小敏
达德转
许焱
崔晓东
李红玲
Zhao Xuhui;Huang Xiaomin;Da Dezhuan;Xu Yan;Cui Xiaodong;Li Hongling(First School of Clinical Medical,Gansu University of Chinese Medicine,Lanzhou 730000,China;Department of Oncology,Gansu Provincial Hospital,Lanzhou 730000,China)
出处
《临床荟萃》
CAS
2024年第1期20-29,共10页
Clinical Focus
基金
甘肃省人民医院院内科研基金项目——EBV-miRNA-BART6-5p介导TGF-β/SMAD4信号通路促进胃癌细胞糖酵解的机制研究(22GSSYD-37)。
关键词
胃肿瘤
预后
预测模型
糖酵解
stomach neoplasms
prognostic
predictive models
glycolysis
