ID #171 Validation of Ultrarapid Classification of Pediatric CNS Tumors Using Nanopore Sequencing
Derek Wong, Juan Santana, Zirui Zhou, Ariel Long, Munashe Holloman, Matthew Lueder, Monica Pomaville, Stephen Master, Angela Viaene, Theodore Laetsch, Adam Resnick, Feng Xu, Mariarita Santi, Peter Madsen, Phillip Storm, Marilyn LiAbstract
Introduction
Intraoperative diagnosis of CNS tumors, which currently relies on frozen sections, is essential for surgical decision-making. However, its ability to provide a specific diagnosis is limited. Recent studies have shown that Nanopore sequencing can provide ultrarapid molecular classifications with the potential to inform intraoperative decision-making.
Methods
A total of 46 pediatric CNS tumors were sequenced using Nanopore rapid sequencing chemistry and analyzed with two published classifiers (Sturgeon/MethyLYZER). Results were compared with the histopathologic and molecularly informed integrated diagnosis and with DNA methylation-based classification (Illumina EPIC array).
Results
Using Nanopore sequencing, 43/46 cases achieved confident classification (score >0.8), while three cases were inconclusive, yielding concordance rates of 97.7% (42/43) with the integrated diagnosis, and 95.1% (39/41) with array-based classifications. Of the three (3/46) inconclusive cases, all three failed both Nanopore and array-based classifications: due to low tumor content (2/3) or the tumor subtype was not represented in the classifiers (1/3) suggesting these cases are not suitable for methylation classification. In one case, the methylation array failed to classify the tumor, whereas Sturgeon correctly classified it as a SEGA. Eight discordant classifications, often within the same tumor family, were observed between Sturgeon and MethyLYZER; Sturgeon was consistent with the integrated diagnosis in four cases, MethyLYZR in three, and neither was correct in one. The median time to Nanopore-based classification was 8 minutes, with a median of 1,354 CpGs required for classification. Genome-wide CNV profiles were concordant with clinically reported CNVs in all evaluated cases (20/20).
Conclusions
Our study demonstrates that Nanopore sequencing provides ultrarapid CNS tumor classification with greater than 95% concordance with the integrated diagnosis. This technology presents an ideal platform for intraoperative molecular classification of pediatric CNS tumors. Additional prospective studies are needed to optimize the workflow and to assess the clinical utility of ultrarapid intraoperative sequencing.