摘要目的:探讨m 6A RNA甲基化调控基因在急性髓细胞白血病（AML）患者预后中的评估价值，为监测AML的疾病发生发展提供思路。 方法:采用回顾性分析方法，从美国国家癌症研究所TARGET数据库获得296例儿童AML患者m 6A甲基化数据及相关临床信息，与GTEx数据库中正常对照比较基因的表达差异，然后使用简单随机抽样法将AML患儿分入训练数据组和验证数据组。在训练组中使用Lasso回归筛选与生存预后相关的m 6A甲基化调控基因，并使用多因素Cox回归构建预后风险评估模型，根据模型计算各患者的风险值（risk score）；在验证组中使用多因素Cox回归，时间依赖的ROC曲线及Kaplan-Meier生存曲线，来验证该风险值的预后评估能力。 结果:22个纳入研究的m 6A甲基化调控基因中，有21个在AML中表达升高。统计分析后构建 ZC3H13、 YTHDC2、 HNRNPA2B1、 METTL3和 METTL5五个基因组成的预后评估模型。根据模型计算出的风险值在训练组（HR：2.72，95% CI：1.54~4.81， P=0.000 6）及验证组（HR：2.01，95% CI：1.14~3.50， P=0.016）中均可独立评估死亡风险，依据风险值划分的高风险组生存率在训练组（ P=0.001 9）和验证组（ P=0.023）中均显著低于低风险组。 结论:m 6A甲基化调控基因与儿童AML发生发展有关联，可能是评估AML患儿预后的潜在指标。

abstractsObjective:To figure out the association between the expression of m 6A RNA methylation regulators and the prognosis of children AML, and provide genetic markers for monitoring the progression and recurrence of AML. Methods:Twenty two m 6A RNA methylation regulators were firstly analyzed using the data from Therapeutically Applicable Research To Generate Effective Treatments(TARGET) database and The Genotype-Tissue Expression(GTEx) database, Wilcoxon rank test was performed to analyze the differentially expression of m 6A RNA methylation regulators between the AML and normal tissue, 296 AML children were divided into training cohort and validation cohort by simple random sampling method, Lasso regression was used to screen out the risk factors and the multivariate Cox regression was applied for establishing prognosis predicting model in training cohort. Kaplan-Meier survival curve, time-dependent ROC curve and multivariate Cox regression were used to estimate the efficiency of risk score calculated by predictive model in validation cohort. Results:Twenty one m 6A genes were up regulated in AML compared to Normal patients. Five m 6A RNA methylation regulators( ZC3H13, YTHDC2, HNRNPA2B1, METTL3, METTL5) were included in final predicting model. Risk score could independently predict the survival of AML patients in training cohort(HR:2.72, 95% CI: 1.54-4.81, P=0.000 6) and validation cohort(HR:2.01, 95% CI:1.14-3.50, P=0.016). Low-risk patients had better prognoses than high-risk patients both in training cohort( P=0.001 9) and validation cohort( P=0.023). Conclusion:This prognosis predicting model constructed by m 6A RNA methylation regulators could independently predict the survival prognosis in AML children, and should be helpful for clinical therapy.