Brain tumor classification from FFPE samples using nanopore methylation sequencing
Galina Feinberg-Gorenshtein, Assaf Grunwald, Carlo Vermeulen, Nurit Gal Mark, Elena Shinderman-Maman, Adva Levy-Barda, Keren Shichrur, Michal Hameiri-Grossman, Orli Michaeli, Shira Amar, Suzanna Fichman, Abraham Natan, Tali Siegal, Shlomit Yust-Katz, Hanna Weiss, Osnat Konen

TL;DR
This study shows how nanopore sequencing can classify brain tumors from FFPE samples, making precision oncology more accessible in clinical settings.
Contribution
A validated protocol for ONT-based methylation sequencing using FFPE tissue, enabling tumor classification from small, low-input samples.
Findings
FFPE samples can be successfully classified with high concordance to neuropathological diagnoses using ONT sequencing.
Methylation loss due to formalin fixation is modest and does not significantly affect classification accuracy.
Fixation time correlates with methylation degradation, suggesting a limit of ≤3–4 days for optimal results.
Abstract
Oxford Nanopore Technology (ONT)-based methylation sequencing is emerging as a powerful approach for the rapid and accurate classification of brain tumors, an essential component of precision oncology. However, its broader clinical adoption has been limited by reliance on fresh-frozen (FF) tissue, whereas the vast majority of clinical specimens are formalin-fixed paraffin-embedded (FFPE). In this study, we address this limitation by evaluating the effects of FFPE processing on DNA methylation profiles and introducing a validated protocol for ONT-based classification using DNA extracted directly from pathology-marked regions on stained FFPE slides. This approach enables the targeted selection of tumor-rich areas following histological assessment, thereby improving DNA input quality and tumor content. We demonstrate that even small, low-input samples (≥25 ng) can be successfully…
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Taxonomy
TopicsGlioma Diagnosis and Treatment · Cancer Genomics and Diagnostics · Epigenetics and DNA Methylation
