基于TCGA数据库分析m6A调节因子甲基化修饰对肺腺癌预后的影响

Analysis of the effect of m6A methylation regulatory factors on the prognosis oflung adenocarcinoma based on TCGA database

目的通过生物信息学分析探究m6A甲基化调节因子在肺腺癌中的表达及预后。方法通过TCGA数据库下载516例肺腺癌患者的转录组数据及其临床数据,使用R软件分析比较肺腺癌组织和癌旁组织中20个m6A甲基化调节因子的表达差异,并通过单变量Cox回归分析进行生存分析。通过Consensus Cluster Plus R非监督类的方法进行m6A聚类生存分析。结果16个m6A甲基化调节因子在肺腺癌中差异表达,其中有5个m6A甲基化调节因子(IGF2BP1、IGF2BP3、HNRNPC、RBMX、YTHDC2)与肿瘤分期、7个m6A甲基化调节因子(IGF2BP1、IGF2BP3、HNRNPC、RBMX、METTL3、YTHDF2、METTL14)与T期和2个m6A甲基化调节因子(IGF2BP3、YTHDC2)与N期显著相关。Cox回归分析结果表明6个m6A甲基化调节因子(IGF2BP1、IGF2BP2、IGF2BP3、HNRNPA2B1、HNRNPC、RBM15)是影响肺腺癌患者预后的独立危险因素。结论m6A甲基化调节因子与肺腺癌进展有关,6个m6A甲基化调节因子可以作为预测肺腺癌患者预后的潜在生物标志物。

Objective To investigate the expression and prognosis of m6A methylation regulatory factors in lung adenocarcinoma by bioinformatics analysis.Methods The transcriptome data and clinical data of 516 cases of lung adenocarcinoma were downloaded from TCGA database.The expression differences of 20 m6A methylation regulatory factors in lung adenocarcinoma tissues and paracancerous tissues were compared using R software analysis,and survival analysis was performed by univariate Cox regression analysis.Consensus Cluster Plus R method was used to perform m6A cluster survival analysis.Results Sixteen m6A methylation regulatory factors were differentially expressed in lung adenocarcinoma,of which 5 m6A methylation regulatory factors(IGF2BP1,IGF2BP3,HNRNPC,RBMX,YTHDC2)were significantly associated with tumor stage,7 m6A methylation regulatory factors(IGF2BP1,IGF2BP3,HNRNPC,RBMX,METTL3,YTHDF2,METTL14)were significantly associated with T stage,and 2 m6A methylation regulatory factors(IGF2BP3,YTHDC2)were significantly associated with N stage.Cox regression analysis showed that 6 m6A methylation regulatory factors(IGF2BP1,IGF2BP2,IGF2BP3,HNRNPA2B1,HNRNPC,RBM15)were independent prognostic factors of lung adenocarcinoma.Conclusion m6A methylation regulatory factors are associated with the progression of lung adenocarcinoma.In addition,the 6 m6A methylation regulatory factors can be used as potential biomarkers to predict the prognosis of lung adenocarcinoma patients.