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100 1 _ |a Smith, Kyle S
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245 _ _ |a M-PACT leverages cell-free DNA methylomes to achieve robust classification of pediatric brain tumors.
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520 _ _ |a 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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700 1 _ |a Han, Katie
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700 1 _ |a Kostecka, Anna
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700 1 _ |a Lin, Hong
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700 1 _ |a Dargvainiene, Justina
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700 1 _ |a Gajjar, Amar
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