基于TCGA和LASSO回归的胃癌预后lncRNA预测模型构建

Establishment of lncRNA predictive model based on TCGA and LASSO for prognosis of gastric cancer

目的利用癌症基因组图谱(TCGA)数据库筛选胃癌预后相关关键长链非编码RNA(lncRNA)并构建预测模型,为判断胃癌患者预后情况提供参考依据。方法下载TCGA数据库中407例胃癌组织样本的RNA-Seq数据和443例胃腺癌患者临床及预后资料,对胃癌组织与癌旁组织差异表达lncRNA进行分析,采用Cox比例风险回归模型及最小化绝对收缩和选择算子(LASSO)回归算法构建预测模型并对模型预测的有效性进行验证。采用多因素Cox回归模型分析该预测模型是否为胃癌独立的预后因素。结果纳入的368例胃癌样本中筛选出382个差异表达lncRNA。基于Cox&LASSO回归算法,构建和验证了25-lncRNA标志物模型;在训练集与验证集中,该模型的曲线下面积分别为0.719和0.672,且高风险组患者的总生存期(OS)明显低于低风险组患者(P<0.05)。多因素Cox回归分析显示,25-lncRNA标志物模型在322例具有完整临床及预后资料的病例中是影响OS的独立因素(HR=2.614,P=5.64E-07)。结论本研究确定了一个25-lncRNA标志物的风险评分模型,可作为独立预后因素对胃癌患者预后进行预测。

Objective Using the Cancer Genome Atlas(TCGA)database to screen key long non-coding RNA(lncRNA)of gastric cancer's prognosis and construct a predictive model to provide a reference for judging the prognosis of gastric cancer patients.Methods Based on the R programming language,the TCGA database was used to download 407 cases of gastric adenocarcinoma RNA-Seq,and 443 patients'clinical and prognosis data.The differences in lncRNAs between gastric cancer tissues and adjacent tissues were analyzed.Cox proportional hazards regression model and least absolute shrinkage and selection operator(LASSO)regression algorithm were used to construct predictive model.Multivariate Cox regression model was used to analyze whether the prediction model was an independent prognostic factor for gastric cancer.Results A total of 368 gastric cancer cases were included in this study,and 382 differentially expressed lncRNAs related to the prognosis of gastric cancer were screened.Based on Cox proportional hazards regression model and LASSO regression algorithm,25 key lncRNAs related to the prognosis of gastric cancer were identified,and a 25-lncRNA model was constructed based on them.In the training and validation sets,the model's area under the curve was 0.719 and 0.672,and the overall survival(OS)of patients in the high-risk group was significantly reduced compared with patients in the low-risk group(P<0.05).Multivariate Cox regression analysis showed that the 25-lncRNA model was an independent prognostic factor in 322 cases with complete clinical and prognostic data(HR=2.614,P=5.64E-07).Conclusion This study identified a risk score model with 25 lncRNAs markers,and this model can be used as an independent prognostic factor to predict the prognosis of patients with gastric cancer.