ArticleNature cancer2026
M-PACT leverages cell-free DNA methylomes to achieve robust classification of pediatric brain tumors.
Article in Nature cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Machine learning and computational approaches to model therapeutic response and resistance in diffuse midline glioma.Journal of neuro-oncology · 2026Review
- Cerebrospinal fluid cell-free DNA sequencing in pediatric CNS tumors: towards liquid molecular neuropathology.Acta neuropathologica · 2026Review
- Circulating tumor DNA precision oncology enables effective and sensitive molecular diagnostics and actionable target detection in pediatric solid tumors - the INFORM experience.Genome medicine · 2026Article
- Cerebrospinal Fluid in Pediatric Neuro-Oncology: Molecular Diagnosis, Disease Monitoring, and Clinical Translation.International journal of molecular sciences · 2026Review
- Enriched methylomes of low-input and fragmented DNA using fragment ligation EXclusive methylation sequencing.Nucleic acids research · 2026Article
- Decoding pediatric brain tumors via CSF-derived methylomes.Nature cancer · 2026Article
- Report from the National Pediatric Cancer Foundation - infantile glioma and other non-embryonal central nervous system tumors: evolving molecular advances and current treatment landscape.Frontiers in oncology · 2026Review
- Capmatinib targeted therapy in MET-fusion driven radiation induced glioma.Frontiers in oncology · 2026Article
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Authors and funding
32 authors.
Funding
Abstract
Cerebrospinal fluid (CSF) liquid biopsies serve as a rich source of tumor-derived cell-free DNA (cfDNA) for evaluating persons with central nervous system (CNS) tumors. However, challenges stemming from trace cfDNA yields and low mutational burden have hindered sensitivity, whereas first-generation clinical assays have relied on genetic alterations as biomarkers. Leveraging the diagnostic utility of DNA methylation classification in CNS tumors, we developed M-PACT (methylation-based predictive algorithm for CNS tumors), a robust deep neural network that accurately classifies tumors from subnanogram-input cfDNA methylomes. Across embryonal CNS tumor benchmarking (n = 79) and validation (n = 58) cohorts, M-PACT achieved 92% and 88% accuracy, respectively. We further showcase M-PACT utility in nonembryonal CNS tumors, balanced tumor genomes and nonmalignant CSF. Beyond classification, this workflow enables methylation-based cellular deconvolution and sensitive copy-number variation detection. Altogether, we provide a blueprint for CNS tumor classification from low-input cfDNA methylomes, motivating prospective validation for future clinical implementation.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.