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Updated: Jul 28, 2026

Methyl-binding DNA capture Sequencing for Patient Tissues

Methyl-binding DNA capture Sequencing for Patient Tissues

Published on: October 31, 2016

M-PACT aprovecha los metilomas de ADN libre de células para lograr una clasificación robusta de tumores cerebrales

Kyle S Smith^1,2, Tom T Fischer^3,4,5,6,7, Katie Han^1,2

¹Center of Excellence in Neuro-Oncology Sciences (CENOS), St. Jude Children's Research Hospital, Memphis, TN, USA.

|February 17, 2026

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.

Palabras clave:

ADN libre de células metilación del ADN tumores cerebrales redes neuronales profundas diagnóstico oncología genómica bioinformática

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