A simple and robust methylation test for risk stratification of patients with juvenile myelomonocytic leukemia.

Juvenile myelomonocytic leukemia (JMML) is a rare myelodysplastic/myeloproliferative neoplasm that develops during infancy and early childhood. The array-based international consensus definition of DNA methylation has recently classified patients with JMML into the following three groups: high methylation (HM), intermediate methylation (IM), and low methylation (LM). To develop a simple and robust methylation clinical test, 137 patients with JMML have been analyzed using the Digital Restriction Enzyme Analysis of Methylation (DREAM), which is a next-generation sequencing based methylation analysis. Unsupervised consensus clustering of the discovery cohort (n=99) using the DREAM data has identified HM and LM subgroups (HM_DREAM, n=35; LM_DREAM; n=64). Of the 98 cases that could be compared with the international consensus classification, 90 cases of HM (n=30) and LM (n=60) had 100% concordance with the DREAM clustering results. For the remaining eight cases classified as the IM group, four cases were classified into the HM_DREAM group and four cases into the LM_DREAM group. A machine-learning classifier has been successfully constructed using a Support Vector Machine (SVM), which divided the validation cohort (n=38) into HM (HM_SVM; n=18) and LM (LM_SVM; n=20) groups. Patients with the HM_SVM profile had a significantly poorer 5-year overall survival rate than those with the LM_SVM profile. In conclusion, a robust methylation test has been developed using the DREAM analysis for patients with JMML. This simple and straightforward test can be easily incorporated in diagnosis to generate a methylation classification for patients so that they can receive risk-adapted treatment in the context of future clinical trials.