Real-time nanopore methylation and genomic profiling for pediatric cancer | LC26

Abstract
Nanopore-based DNA methylation profiling has become a clinically deployable platform for real-time molecular cancer diagnostics. In pediatric neuro-oncology, we pioneered intraoperative methylation-based classification using nanopore sequencing with Sturgeon, now integrated into routine care and delivering molecular subclassification of central nervous system (CNS) tumors within 90 minutes. Prospective evaluation showed that intraoperative molecular diagnoses at times altered surgical strategy and reduced the need for second-look surgeries, demonstrating real-world clinical utility in time-critical settings. Building on this, we expanded nanopore-based methylation classification to additional pediatric malignancies with high diagnostic complexity. We developed Tucan, a deep-learning classifier for pediatric solid tumors, trained on 3,907 methylation profiles spanning 91 diagnostic entities. Retrospective validation on 514 samples and prospective evaluation in routine diagnostics demonstrated accurate molecular classification within hours, including clinically relevant diagnostic refinements. In parallel, we developed an integrated nanopore DNA-based diagnostic workflow for pediatric hematological malignancies, in which Lamprey serves as the methylation-based classification algorithm. Lamprey was trained on more than 5,400 methylation arrays covering over 40 lymphoid and myeloid leukemia subtypes and achieved high classification accuracy in retrospective validation cohorts. Combined with Adaptive Sampling-based sequencing, this workflow enables simultaneous methylation-based classification and comprehensive genomic characterization, including detection of gene fusions, copy number alterations, and mutations, with all results available within 24 hours of sample acquisition. Together, these approaches establish a unified, single-assay framework for rapid molecular diagnostics across CNS tumors, solid tumors, and leukemias, demonstrating how nanopore sequencing can replace multi-assay workflows while delivering clinically actionable results within hours.

Biography
Lennart Kester is a molecular biologist and group leader at the Princess Maxima Center for Pediatric Oncology. His research focuses on developing real-time molecular diagnostics using nanopore sequencing and machine learning, with a particular emphasis on DNA methylation-based tumor classification. His work has led to the clinical implementation of intraoperative nanopore sequencing for pediatric brain tumors and the development of rapid diagnostic frameworks for solid and hematological malignancies.