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Nanopore Whole-Genome Sequencing for Rapid, Comprehensive Molecular Diagnostics of Brain Tumors in Adult Patients

Halldorsson, S.; Nagymihaly, R. M.; Bope, C. D.; Lund-Iversen, M.; Niehusmann, P.; Lien-Dahl, T.; Pahnke, J.; Bruning, T.; Kongelf, G.; Patel, A.; Sahm, F.; Euskirchen, P.; Leske, H.; Vik-Mo, E. O.

2026-04-24 pathology
10.64898/2026.04.23.26351563 medRxiv
Show abstract

Background: Classification of central nervous system (CNS) tumors has become increasingly complex, raising concerns about the sustainability of comprehensive molecular diagnostics. We have evaluated nanopore whole genome sequencing (nWGS) as a single workflow to replace multiple diagnostic assays. Methods: We performed nWGS on DNA extracted from 90 adult CNS tumor samples (58 retrospective, 32 prospective) and compared the results to findings from standard of care (SoC) diagnostic work-up. Analysis was done through an automated workflow that consolidated diagnostically and therapeutically relevant genomic alterations, including copy-number variation, structural, and single-nucleotide variants, chromosomal aberrations, gene fusions, and methylation-based classification. Results: nWGS supported final diagnostic classification in all samples with >15% tumor cell content, requiring ~3 hours of hands-on library preparation, parallel sample processing, and sequencing times within 72 hours. Methylation-based classification was available within 1 hour and was concordant with the integrated final diagnosis in 89% of cases (80/90). All diagnostically relevant copy-number variations, single-nucleotide variants, and gene fusions were concordant with SoC testing. MGMT promoter methylation status matched in 94% of cases. In addition, nWGS identified prognostic and potentially actionable variants that were not reported or covered by SoC. Conclusions: nWGS delivers comprehensive genetic and epigenetic results with a fast turn-around compared to standard methods. This enables efficient, accurate, and scalable molecular diagnostics of CNS tumors using a single platform. This data supports its implementation in routine clinical practice and may be extended to other cancer types requiring complex genomic profiling.

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