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Juvenile myelomonocytic leukemia (JMML), a rare and aggressive myelodysplastic/myeloproliferative neoplasm that occurs in infants and during early childhood, is characterized by excessive myelomonocytic cell proliferation. More than 80% of patients harbor germ line and somatic mutations in RAS pathway genes (eg, ,, ,, and ), and previous studies have identified several biomarkers associated with poor prognosis. However, the molecular pathogenesis of 10% to 20% of patients and the relationships among these biomarkers have not been well defined. To address these issues, we performed an integrated molecular analysis of samples from 150 JMML patients. RNA-sequencing identified tyrosine kinase fusions (, and ) in 3 of 16 patients (18%) who lacked canonical RAS pathway mutations. Crizotinib, an ALK/ROS1 inhibitor, markedly suppressed fusion-positive JMML cell proliferation in vitro. Therefore, we administered crizotinib to a chemotherapy-resistant patient with the fusion who subsequently achieved complete molecular remission. In addition, crizotinib also suppressed proliferation of JMML cells with canonical RAS pathway mutations. Genome-wide methylation analysis identified a hypermethylation profile resembling that of acute myeloid leukemia (AML), which correlated significantly with genetic markers with poor outcomes such as gene mutations, 2 or more genetic mutations, an AML-type expression profile, and expression. In summary, we identified recurrent activated fusions in JMML patients without canonical RAS pathway gene mutations and revealed the relationships among biomarkers for JMML. Crizotinib is a promising candidate drug for the treatment of JMML, particularly in patients with fusions.

A novel MEF2D-BCL9 fusion we identified characterizes a novel subset of pediatric ALL, predicts poor prognosis, and may be a candidate for novel molecular targeting.

Purpose: 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. Experimental Design: 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). Results: 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. Conclusions: 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.

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Insertional mutagenesis is an important risk with all genetically modified cell therapies, including chimeric antigen receptor (CAR)-T cell therapy used for hematological malignancies. Here we describe a new tagmentation-assisted PCR (tag-PCR) system that can determine the integration sites of transgenes without using restriction enzyme digestion (which can potentially bias the detection) and allows library preparation in fewer steps than with other methods. Using this system, we compared the integration sites of CD19-specific CAR genes in final T cell products generated by retrovirus-based and lentivirus-based gene transfer and by the piggyBac transposon system. The piggyBac system demonstrated lower preference than the retroviral system for integration near transcriptional start sites and CpG islands and higher preference than the lentiviral system for integration into genomic safe harbors. Integration into or near proto-oncogenes was similar in all three systems. Tag-PCR mapping is a useful technique for assessing the risk of insertional mutagenesis.

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