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Rapid-CNS2: Rapid comprehensive adaptive nanopore-sequencing of CNS tumors, a proof of concept study

Patel, A. J.; Dogan, H.; Payne, A.; Sievers, P.; Schoebe, N.; Schrimpf, D.; Stichel, D.; Holmes, N.; Euskirchen, P.; Hench, J.; Frank, S.; Rosenstiel-Goidts, V.; Ratliff, M.; Etminan, N.; Unterberg, A.; Dieterich, C.; Herold-Mende, C.; Pfister, S. M.; Wick, W.; Schlesner, M.; Loose, M.; von Deimling, A.; Sill, M.; Jones, D. T.; Sahm, F.

2021-08-10 pathology
10.1101/2021.08.09.21261784
Show abstract

BackgroundThe 2021 WHO classification of central nervous system tumors includes multiple molecular markers and patterns that are recommended for routine diagnostic use in addition to histology. Sequencing infrastructures for complete molecular profiling require considerable investment, while batching samples for sequencing and methylation profiling can delay turnaround time. We introduce RAPID-CNS2, a nanopore adaptive sequencing pipeline that enables comprehensive mutational, methylation and copy number profiling of CNS tumours with a single, cost-effective sequencing assay. It can be run for single samples and offers highly flexible target selection that can be personalized per case with no additional library preparation. MethodsUtilizing ReadFish, a toolkit enabling targeted nanopore sequencing without the need for library enrichment, we sequenced DNA from 22 diffuse glioma samples on a MinION device. Target regions comprised our Heidelberg brain tumor NGS panel and pre-selected CpG sites for methylation classification using an adapted random forest classifier. Pathognomonic alterations, copy number profiles, and methylation classes were called using a custom bioinformatics pipeline. The resulting data were compared to their corresponding standard NGS panel sequencing and EPIC methylation array results. ResultsComplete concordance with the EPIC array was found for copy number profiles. The vast majority (94%) of pathognomonic mutations were congruent with standard NGS panel-seq data. MGMT promoter status was correctly identified in all samples. Methylation families from the random forest classifier were detected with 96% congruence. Among the alterations decisive for rendering a WHO 2021 classification-compatible integrated diagnosis, 97% of the alterations were consistent over the entire cohort (completely congruent in 19/22 cases and sufficient for unequivocal diagnosis in all 22 samples). ConclusionsRAPID-CNS2 provides a swift and highly flexible alternative to conventional NGS and array-based methods for SNV/InDel analysis, detection of copy number alterations, target gene methylation analysis (e.g. MGMT) and methylation-based classification. The turnaround time of [~]5 days for this proof-of-concept study can be further shortened to < 24h by optimizing target sizes and enabling real-time computational analysis. Expected advances in nanopore sequencing and analysis hardware make the prospect of integrative molecular diagnosis in an intra-operative setting a feasible prospect in future. This low-capital approach would be cost-efficient for low throughput settings or in locations with less sophisticated laboratory infrastructure, and invaluable in cases requiring immediate diagnoses.

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