Related Experiment Video
Updated: Jan 12, 2026
13:24
Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
Published on: April 11, 2016
12.2K
Brain tumor classification from FFPE samples using nanopore methylation sequencing
Galina Feinberg-Gorenshtein1, Assaf Grunwald2, Carlo Vermeulen3
1The Rina Zaizov Division of Pediatric Hematology-Oncology, Schneider Children's Medical Center of Israel, P.O. Box 559, Petach Tikva, Israel.
NAR Cancer
|November 3, 2025
Summary
Oxford Nanopore Technology (ONT) methylation sequencing can now classify brain tumors using formalin-fixed paraffin-embedded (FFPE) tissue. This new protocol works even with small DNA samples from stained slides, improving cancer diagnostics.
Area of Science:
- Molecular Oncology
- Genomics
- Pathology
Background:
- Oxford Nanopore Technology (ONT)-based methylation sequencing offers rapid brain tumor classification for precision oncology.
- Clinical adoption is hindered by the need for fresh-frozen (FF) tissue, unlike the common formalin-fixed paraffin-embedded (FFPE) specimens.
Purpose of the Study:
- To evaluate FFPE processing effects on DNA methylation profiles.
- To develop and validate a protocol for ONT-based brain tumor classification using DNA from FFPE slides.
Main Methods:
- DNA extraction from pathology-marked regions on stained FFPE slides.
- Targeted selection of tumor-rich areas post-histological assessment.
- ONT-based methylation sequencing for classification.
Main Results:
- Successful classification of brain tumors from low-input DNA (≥25 ng) extracted from FFPE tissue.
- High concordance between ONT classification and neuropathological diagnoses.
- Modest methylation loss due to formalin fixation, but robust classification performance.
- Correlation between methylation degradation and formalin fixation time (≤3-4 days recommended).
Conclusions:
- A validated protocol enables accurate methylation-based tumor classification from routine FFPE tissue.
- This expands accessibility of ONT diagnostics into standard clinical workflows.
- Facilitates timely treatment decisions, even with limited or urgent tissue samples.
