已知的临床和遗传标记在预测幼年型粒单核细胞白血病(JMML)的病程和结果方面具有局限性。JMML中的DNA甲基化模式与多项研究的结果相关,建议将其作为改善患者分层的生物标志物。然而,缺乏基于DNA甲基化模式对JMML进行分类的标准化方法。我们,因此,试图为JMML中的DNA甲基化亚组定义国际共识,并开发临床实施的分类方法。
使用来自255名JMML患者的已发表DNA甲基化数据来开发和内部验证分类器模型。使用技术验证队列(32名患者)测试了跨平台(EPIC阵列和MethylSeq)的准确性。使用独立队列(47名患者)证明了两种方法对单患者分类的适用性。
汇总分析,已发表的数据确立了三个DNA甲基化亚组作为事实上的标准.不利的预后参数(PTPN11突变,胎儿血红蛋白升高,和年龄较大)在高甲基化(HM)亚组中显着富集。然后开发了一个分类器,该分类器在不同的技术平台上以98%的准确性预测子组。将分类器应用于独立的验证队列证实了HM与次级突变的关联,高复发率,总体生存率(OS)较差,而低甲基化亚组与良好的病程相关。多变量分析确定DNA甲基化亚组是预测OS的唯一重要因素。
这项研究为JMML中的DNA甲基化亚组提供了国际共识定义。我们开发并验证了方法,这些方法将有助于JMML中风险分层临床试验的设计。
Known clinical and genetic markers have limitations in predicting disease course and outcome in juvenile myelomonocytic leukemia (JMML). DNA methylation patterns in JMML have correlated with outcome across multiple studies, suggesting it as a biomarker to improve patient stratification. However, standardized approaches to classify JMML on the basis of DNA methylation patterns are lacking. We, therefore, sought to define an international
consensus for DNA methylation subgroups in JMML and develop classification methods for clinical implementation.
Published DNA methylation data from 255 patients with JMML were used to develop and internally validate a classifier model. Accuracy across platforms (EPIC-arrays and MethylSeq) was tested using a technical validation cohort (32 patients). The suitability of both methods for single-patient classification was demonstrated using an independent cohort (47 patients).
Analysis of pooled, published data established three DNA methylation subgroups as a de facto standard. Unfavorable prognostic parameters (PTPN11 mutation, elevated fetal hemoglobin, and older age) were significantly enriched in the high methylation (HM) subgroup. A classifier was then developed that predicted subgroups with 98% accuracy across different technological platforms. Applying the classifier to an independent validation cohort confirmed an association of HM with secondary mutations, high relapse incidence, and inferior overall survival (OS), while the low methylation subgroup was associated with a favorable disease course. Multivariable analysis established DNA methylation subgroups as the only significant factor predicting OS.
This study provides an international
consensus definition for DNA methylation subgroups in JMML. We developed and validated methods which will facilitate the design of risk-stratified clinical trials in JMML.