ArticleClinical cancer research : an official journal of the American Association for Cancer Research2021
International Consensus Definition of DNA Methylation Subgroups in Juvenile Myelomonocytic Leukemia.
Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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41 citing papers in PubMed, 58 citations in OpenAlex.
- Efficacy of the Allosteric MEK Inhibitor Trametinib in Relapsed and Refractory Juvenile Myelomonocytic Leukemia: a Report from the Children's Oncology Group.Cancer discovery · 2024Trial
- Genetic Analysis of Genomic and Methylomic Variation and Identification of Multi-Trait Mutants in Rice Carried on Chang'e-5.Plants (Basel, Switzerland) · 2026Article
- Genomic Characterization of Epigenetic Regulator Gene Alterations in Juvenile Myelomonocytic Leukemia Through Whole-Exome Sequencing.Epigenomes · 2026Article
- Clinical Phenotype, Molecular Architecture, and Survival Follow-Up in NRAS- and KRAS-Mutated Juvenile Myelomonocytic Leukemia.Cancers · 2026Article
- Review
- Epigenetic alterations in Myeloid Malignancies.Advances in experimental medicine and biology · 2026Review
- Clinical and molecular characterization of patients with juvenile myelomonocytic leukaemia.British journal of haematology · 2025Article
- Epigenetic risk stratification in juvenile myelomonocytic leukemia by targeted methylation analysis of the BMP4 locus.Clinical epigenetics · 2025Article
- Co-operative epigenetic remodelling by Setd2 deficiency and Kras mutation drives juvenile myelomonocytic leukaemia development and MEK inhibitor sensitivity.British journal of haematology · 2025Article
- Assessment of peripheral blood DNA methylation signatures as pharmacodynamic and predictive biomarkers during azacitidine therapy in juvenile myelomonocytic leukaemia: Results of the EWOG-MESRAT study.British journal of haematology · 2025Article
- Article
- Celebrating Ulrik Ringborg: Multi-Omics-Based Patient Stratification for Precision Cancer Treatment.Biomolecules · 2025Review
- Azacytidine Monotherapy in an Infant With Mosaic NRAS-Driven Juvenile Myelomonocytic Leukemia.Pediatric blood & cancer · 2025Article
- Article
- LNK/Haematologica · 2024Article
- Germline bi-allelicHaematologica · 2024Article
- RAS mutations in myeloid malignancies: revisiting old questions with novel insights and therapeutic perspectives.Blood cancer journal · 2024Review
- Phenotypic profiling of CD34Haematologica · 2024Article
- BH3 mimetics and azacitidine show synergistic effects on juvenile myelomonocytic leukemia.Leukemia · 2024Article
- Decitabine-based treatment strategy improved the outcome of HSCT in JMML: a retrospective cohort study.Frontiers in immunology · 2024Article
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Authors and funding
15 authors at 7 institutions in 3 countries.
Funding
Abstract
purposeKnown 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
designPublished 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).
resultsAnalysis of pooled, published data established three DNA methylation subgroups as a
conclusionsThis 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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