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<p>The neuropathological workup of brain tumors requires high diagnostic accuracy under considerable time pressure. The integrated histological and molecular classification according to WHO standards represents the basis for prognostic rating and therapy planning. However, conventional molecular methods are often associated with prolonged turnaround times. In this context, nanopore sequencing has emerged as a&#xa0;promising tool to accelerate molecular brain tumor diagnostics. Nanopore sequencing enables real-time analysis of native DNA and allows direct detection of DNA methylation patterns and copy number variations in addition to sequence information. Within a&#xa0;few hours after sample acquisition, sufficient molecular data are generated to enable initial tumor classification. Automated interpretation is performed using deep-learning-based classification models that compare nanopore-derived methylation profiles with comprehensive reference datasets of defined brain tumor entities. This approach enables standardized, reproducible, same-day molecular diagnostics that can be performed in parallel with conventional histopathological processing. Beyond tissue-based analysis, the combination of nanopore sequencing and liquid biopsy from cerebrospinal fluid samples offers new perspectives for minimally invasive diagnostics, particularly for nonresectable tumors or longitudinal disease monitoring. Despite limitations related to low concentrations of circulating tumor DNA, this technology represents a&#xa0;promising extension of modern neuro-oncological diagnostics.</p>

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Nanopore-Sequenzierung zur ultraschnellen molekularen Hirntumordiagnostik

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月30日

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  • Alexander Miller-Michlits,
  • Adelheid Wöhrer

摘要

The neuropathological workup of brain tumors requires high diagnostic accuracy under considerable time pressure. The integrated histological and molecular classification according to WHO standards represents the basis for prognostic rating and therapy planning. However, conventional molecular methods are often associated with prolonged turnaround times. In this context, nanopore sequencing has emerged as a promising tool to accelerate molecular brain tumor diagnostics. Nanopore sequencing enables real-time analysis of native DNA and allows direct detection of DNA methylation patterns and copy number variations in addition to sequence information. Within a few hours after sample acquisition, sufficient molecular data are generated to enable initial tumor classification. Automated interpretation is performed using deep-learning-based classification models that compare nanopore-derived methylation profiles with comprehensive reference datasets of defined brain tumor entities. This approach enables standardized, reproducible, same-day molecular diagnostics that can be performed in parallel with conventional histopathological processing. Beyond tissue-based analysis, the combination of nanopore sequencing and liquid biopsy from cerebrospinal fluid samples offers new perspectives for minimally invasive diagnostics, particularly for nonresectable tumors or longitudinal disease monitoring. Despite limitations related to low concentrations of circulating tumor DNA, this technology represents a promising extension of modern neuro-oncological diagnostics.