摘要
目的构建基于N6-甲基腺嘌呤(N6-methyladenosine,m6A)相关基因的喉鳞状细胞癌(laryngeal squamous cell carcinoma,LSCC)预后预测模型。方法从TCGA数据库下载LSCC RNA-seq数据及相关临床数据,利用R4.0.3软件筛选并提取LSCC组织中显著差异表达的m6A相关基因(P<0.05)。利用Lasso回归算法构建预后预测模型,并根据风险评分公式计算各临床样本的风险系数,取中位数将样本分为高风险组和低风险组,然后使用Kaplan-Meier生存曲线和受试者工作特征(receiver operating characteristic,ROC)曲线评估该模型效能,并进一步使用单因素及多因素COX回归分析对该预后预测模型进行独立预后分析。结果LSCC组织中显著差异表达的m6A相关基因共有9个(METTL3、YTHDF1、YTHDC2、ALKBH5、HNRNPC、RBM15、WTAP、FTO和KIAA1429),在此基础之上利用Lasso回归算法构建了预后预测模型。Kaplan-Meier生存曲线显示高风险组的总体生存率明显低于低风险组,且两组的5年生存率之间比较,差异有统计学意义(P<0.01)。ROC曲线显示该模型具有较好的敏感度和特异性(AUC>0.7)。独立预后分析显示该评分模型可作为独立预后因素(P=0.000)对LSCC患者的预后进行预测。结论本研究构建了基于m6A相关基因的预后预测模型,且可作为独立的预后因素。
Objective To construct a prognostic predication model of laryngeal squamous cell carcinoma(LSCC)based on the expression of N6-methyladenosine(m6A)-related genes.Methods The original RNA-seq data and clinical data of LSCC patients were downloaded from the TCGA database,and significantly differentially expressed m6A-related genes was screened by R4.0.3(P<0.05).Lasso regression algorithm was applied to construct a prognostic predication model.Based on the median of the risk coefficient,LSCC patients were divided into high-risk group and low-risk group.Then the Kaplan-Meier survival curves and the receiver operating characteristic curve(ROC)were performed to evaluate the effectiveness of the model.Finally,univariate and multivariate COX regression analysis were used to perform independent prognostic analysis.Results There are 9 m6A-related genes significantly differentially expressed in LSCC tissues(METTL3,YTHDF1,YTHDC2,ALKBH5,HNRNPC,RBM15,WTAP,FTO,KIAA1429).And a prognostic prediction model was constructed using Lasso regression algorithm.The Kaplan-Meier survival curve showed that the overall survival rate of the high-risk group was significantly lower than which of the low-risk group,and there was a statistical difference in the 5-year survival rate between the two groups(P<0.01).The area under the ROC curve(AUC)showed that the model possessed good sensitivity and specificity(AUC>0.7).And independent prognostic analysis showed that the model could be an independent prognostic factor(P=0.000)to predict the prognosis of LSCC patients.Conclusion This study successfully constructed a prognostic prediction model based on m6A-related genes,which could be used as an independent prognostic factor to predict the prognosis of LSCC patients.
作者
韩弈垣
王雪梅
贺晴
曹晓林
Han Yiyuan;Wang Xuemei;He Qing(The Forth Clinical Medical College of Zhejiang Chinese Medical University,Zhejiang 310053,China)
出处
《医学研究杂志》
2021年第6期88-93,共6页
Journal of Medical Research
基金
浙江省医药卫生科技计划项目(2015KYB284)。
作者简介
通讯作者:曹晓林,主任医师,副教授,硕士生导师,电子信箱:doctorcaoxiaolin@163.com。
