ArticleNature genetics2025
Rapid epigenomic classification of acute leukemia.
Article in Nature genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- A platform of serially transplantable AML PDX models covering subgroups for which no cell lines exist.HemaSphere · 2026Article
- ELN vs. IPSS-M in MDS/AML: Which Prognostic System Should Guide Clinical Decision-Making?Cancers · 2026Review
- A genomic and epigenomic lens into the biology of acute lymphoblastic leukaemia.Nature reviews. Cancer · 2026Review
- Putting the I in AML: Artificial Intelligence and Machine Learning in Acute Myeloid Leukemia.Cells · 2026Review
- Multiomic Characterization of a Rare Case of Pediatric Acute Leukemia With a NovelJCO precision oncology · 2026Article
- Menin inhibitors as a treatment for acute leukemia: from bench to the clinic.Blood neoplasia · 2026Review
- Artificial Intelligence for Personalized Management of Acute Myeloid Leukemia.Journal of personalized medicine · 2026Review
- clinTALL: machine learning-driven multimodal subtype classification and treatment outcome prediction in pediatric T-ALL.Genome medicine · 2026Article
- Multiomic State-Transitions Reveal Post-Treatment Transcriptome Desynchronization in Acute Myeloid Leukemia.bioRxiv : the preprint server for biology · 2026Article
- Review
- MOSAIC: Methylation-Oriented Site Analysis and Information Classifier for Robust Epigenomic Classification of Acute Leukemia in Clinical Cohorts with Variable Tumor Purity.medRxiv : the preprint server for health sciences · 2026Article
- Emerging applications of long-read sequencing in hematological malignancies: highlights from the 2025 ASH annual meeting.Biomarker research · 2026Article
- Molecular Characterization of T-Lineage Acute Lymphoblastic Leukemia by an Optimal-Transport Based Multi-Omics Integration Framework.bioRxiv : the preprint server for biology · 2026Article
- A specific stem cell program and CD112 immunological axis dysfunctions underpinning monosomy 7-associated myeloid neoplasms.Signal transduction and targeted therapy · 2026Article
- International testing and refinement of AI algorithms predicting acute leukemia subtypes from routine laboratory data.Nature communications · 2026Article
- Molecular Pathology, Artificial Intelligence, and New Technologies in Hematologic Diagnostics: Translational Opportunities and Practical Considerations.Diagnostics (Basel, Switzerland) · 2026Review
- Celebrating Ulrik Ringborg: Multi-Omics-Based Patient Stratification for Precision Cancer Treatment.Biomolecules · 2025Review
- Nanopore sequencing enables combined detection ofFrontiers in genetics · 2025Article
Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute leukemia requires precise molecular classification and urgent treatment. However, standard-of-care diagnostic tests are time-intensive and do not capture the full spectrum of acute leukemia heterogeneity. Here, we developed a framework to classify acute leukemia using genome-wide DNA methylation profiling. We first assembled a comprehensive reference cohort (n = 2,540 samples) and defined 38 methylation classes. Methylation-based classification matched standard-pathology lineage classification in most cases and revealed heterogeneity in addition to that captured by genetic categories. Using this reference, we developed a neural network (MARLIN; methylation- and AI-guided rapid leukemia subtype inference) for acute leukemia classification from sparse DNA methylation profiles. In retrospective cohorts profiled by nanopore sequencing, high-confidence predictions were concordant with conventional diagnoses in 25 out of 26 cases. Real-time MARLIN classification in patients with suspected acute leukemia provided accurate predictions in five out of five cases, which were typically generated within 2 h of sample receipt. In summary, we present a framework for rapid acute leukemia classification that complements and enhances standard-of-care diagnostics.
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