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| 024 | 7 | _ | |a 10.1093/noajnl/vdaf159 |2 doi |
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| 100 | 1 | _ | |a Taylor, Aaron Michael |0 0000-0002-2544-5888 |b 0 |
| 245 | _ | _ | |a A feasibility study of enzymatic methylation sequencing of cell-free DNA from cerebrospinal fluid of pediatric central nervous system tumor patients for molecular classification. |
| 260 | _ | _ | |a Oxford |c 2025 |b Oxford University Press |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 520 | _ | _ | |a Array-based DNA methylation profiling is the gold standard for central nervous system (CNS) tumor molecular classification, but requires over 100 ng input DNA from surgical tissue. Cell-free tumor DNA (cfDNA) in cerebrospinal fluid (CSF) offers an alternative for diagnosis and disease monitoring. This study aimed to test the utilization of enzymatic DNA methylation sequencing (EM-seq) methods to overcome input DNA limitations.We used the NEBNext EM-seq v2 kit on various amounts of cfDNA, as low as 0.1 ng, extracted from archival CSF samples of 10 patients with CNS tumors. Tumor classification was performed via MNP-Flex using CpG sites overlapping those on the MethylationEPIC array.EM-seq provided sufficient genomic coverage for 10 and 1 ng input DNA samples to generate global DNA methylation profiles. Samples with 0.1 ng input showed lower coverage due to read duplication. Methylation levels for CpG sites with at least 5× coverage were highly correlated across various input DNA amounts, indicating that lower input cfDNA can still be used for tumor classification. The MNP-Flex classifier, trained on tissue DNA methylation data, successfully predicted CNS tumor types for 7 out of 10 CSF samples using EM-seq methylation data with only 1 ng of input cfDNA, consistent with diagnoses based on tissue MethylationEPIC classification and/or histopathology. Additionally, we detected focal and arm-level copy number alterations previously identified via clinical cytogenetics of tumor tissue.This study demonstrated the feasibility of CNS tumor molecular classification based on CSF using the EM-seq approach, and establishes potential sample quality limitations for future studies. |
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| 650 | _ | 7 | |a CNS tumor classification |2 Other |
| 650 | _ | 7 | |a MNP-flex |2 Other |
| 650 | _ | 7 | |a cell-free DNA |2 Other |
| 650 | _ | 7 | |a enzymatic methylation sequencing |2 Other |
| 650 | _ | 7 | |a molecular diagnosis |2 Other |
| 700 | 1 | _ | |a Lombardi, Jody T |b 1 |
| 700 | 1 | _ | |a Patel, Areeba Jamilkhan |0 P:(DE-He78)79506056c05e539af84edf040f0a93ad |b 2 |u dkfz |
| 700 | 1 | _ | |a Tamariz, Ariella |b 3 |
| 700 | 1 | _ | |a Martin, Jonathan |0 0000-0003-3180-2084 |b 4 |
| 700 | 1 | _ | |a Bookland, Markus J |0 0000-0003-4422-8376 |b 5 |
| 700 | 1 | _ | |a Hersh, David S |0 0000-0003-1177-2201 |b 6 |
| 700 | 1 | _ | |a Cantor, Evan |0 0000-0001-7302-9734 |b 7 |
| 700 | 1 | _ | |a Song, Xianyuan |b 8 |
| 700 | 1 | _ | |a Sahm, Felix |0 P:(DE-He78)a1f4b408b9155beb2a8f7cba4d04fe88 |b 9 |u dkfz |
| 700 | 1 | _ | |a Ng, Patrick Kwok-Shing |0 0000-0003-0364-7443 |b 10 |
| 700 | 1 | _ | |a Gell, Joanna J |b 11 |
| 700 | 1 | _ | |a Lau, Ching C |0 0000-0001-9173-8366 |b 12 |
| 773 | _ | _ | |a 10.1093/noajnl/vdaf159 |g Vol. 7, no. 1, p. vdaf159 |0 PERI:(DE-600)3009682-0 |n 1 |p vdaf159 |t Neuro-oncology advances |v 7 |y 2025 |x 2632-2498 |
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