AML with myelodysplasia-related changes (AML-MRC) is a subtype of AML known to have adverse prognosis. The karyotype abnormalities in AML-MRC have been well established; however, relatively little has been known about the role of gene mutation profiles by next generation sequencing. 177 AML patients (72 AML-MRC and 105 non-MRC AML) were analyzed by NGS panel covering 53 AML related genes. AML-MRC showed statistically significantly higher frequency of TP53 mutation, but lower frequencies of mutations in NPM1, FLT3-ITD^Low, FLT3-ITD^High, FLT3-TKD, NRAS, and PTPN11 than non-MRC AML. Supervised tree-based classification models including Decision tree, Random forest, and XGboost, and logistic regression were used to evaluate if the mutation profiles could be used to aid the diagnosis of AML-MRC. All methods showed good accuracy in differentiating AML-MRC from non-MRC AML with AUC (area under curve) of ROC ranging from 0.69 to 0.78. Additionally, logistic regression indicated 3 independent factors (age and mutations of TP53 and FLT3) could aid the diagnosis AML-MRC. Using weighted factors, a AML-MRC risk scoring equation was established for potential application in clinical setting: +1x(Age ≥ 65) + 3 x (TP53 mutation) – 2 x (FLT3 mutation). Using a cutoff score of 0, the accuracy of the risk score was 0.76 with sensitivity of 0.77 and specificity of 0.75 for predicting the diagnosis of AML-MRC. Further studies with larger sample sizes are warranted to further evaluate the potential of using gene mutation profiles to aid the diagnosis of AML-MRC.

AML 伴骨髓增生异常相关变化 (AML-MRC) 是已知预后不良的 AML 亚型。AML-MRC 的核型异常已被很好地确定；然而，对于下一代测序的基因突变谱的作用知之甚少。177 名 AML 患者（72 名 AML-MRC 和 105 名非 MRC AML）通过涵盖 53 个 AML 相关基因的 NGS panel 进行分析。AML-MRC 显示出统计学上显着更高的TP53突变频率，但在NPM1、FLT3 -ITD ^Low、FLT3 -ITD ^High、FLT3 -TKD、NRAS 和 PTPN11 中的突变频率较低比非 MRC AML。使用决策树、随机森林和 XGboost 等基于监督的树分类模型和逻辑回归来评估突变谱是否可用于辅助 AML-MRC 的诊断。所有方法在区分 AML-MRC 和非 MRC AML 方面表现出良好的准确性，ROC 的 AUC（曲线下面积）范围为 0.69 至 0.78。此外，逻辑回归表明 3 个独立因素（年龄和 TP53 和 FLT3 突变）可以帮助诊断 AML-MRC。使用加权因子，建立了一个 AML-MRC 风险评分方程，以用于临床环境中的潜在应用：+1x（A ge ≥ 65）+ 3 x（TP53突变）– 2 x（FLT3突变）。使用截止分数 0，风险评分的准确性为 0.76，敏感性为 0.77，特异性为 0.75，用于预测 AML-MRC 的诊断。需要更大样本量的进一步研究，以进一步评估使用基因突变谱来帮助诊断 AML-MRC 的潜力。