Rapid-CNS2: Nanopore-Based Platform Delivers Intraoperative Molecular Brain Tumour Profiling in 30 Minutes
A prospective multicentre validation of Rapid-CNS2, an adaptive nanopore sequencing workflow, demonstrated real-time methylation classification and copy number profiling of CNS tumours within a 30-minute intraoperative window, with comprehensive molecular profiling available within 24 hours. Validated on 301 samples including 18 sequenced intraoperatively, the accompanying MNP-Flex classifier achieved 99.6% accuracy across over 78,000 samples spanning five technologies. This platform has the potential to transform neurosurgical decision-making by providing actionable molecular data during the procedure itself.
The original study
Prospective, multicenter validation of a platform for rapid molecular profiling of central nervous system tumors.
- Authors
- Patel A, Göbel K, Ille S, Hinz F, Schoebe N, Bogumil H, et al.
- Journal
- Nature medicine
- Type
- Journal Article, Multicenter Study, Validation Study
- PMID
- 40133526
Original abstract
Molecular data integration plays a central role in central nervous system (CNS) tumor diagnostics but currently used assays pose limitations due to technical complexity, equipment and reagent costs, as well as lengthy turnaround times. We previously reported the development of Rapid-CNS2, an adaptive-sampling-based nanopore sequencing workflow. Here we comprehensively validated and further developed Rapid-CNS2 for intraoperative use. It now offers real-time methylation classification and DNA copy number information within a 30-min intraoperative window, followed by comprehensive molecular profiling within 24 h, covering the complete spectrum of diagnostically and therapeutically relevant information for the respective entity. We validated Rapid-CNS2 in a multicenter setting on 301 archival and prospective samples including 18 samples sequenced intraoperatively. To broaden the utility of methylation-based CNS tumor classification, we developed MNP-Flex, a platform-agnostic methylation classifier encompassing 184 classes. MNP-Flex achieved 99.6% accuracy for methylation families and 99.2% accuracy for methylation classes with clinically applicable thresholds across a global validation cohort of more than 78,000 frozen and formalin-fixed paraffin-embedded samples spanning five different technologies. Integration of these tools has the potential to advance CNS tumor diagnostics by providing broad access to rapid, actionable molecular insights crucial for personalized treatment strategies.