Comprehensive cns tumour molecular diagnostics using third generation sequencing

Abstract The WHO classification of CNS tumours 2021 recommends reporting a wide range of molecular alterations for WHO-compatible diagnoses. Conventional workflows warrant considerable investment and long turnaround times limited by batching. Nanopore sequencing enables long read sequencing, real-time targeting and simultaneous base modification detection with compact devices. Rapid-CNS2- a rapid, comprehensive adaptive sampling based sequencing pipeline with a turnaround time of 5 days was previously described. The ad-hoc methylation classification model employed by Rapid-CNS2 is limited to MNP v11 classes. This study presents an optimised Rapid-CNS2 and validation cohort that successfully reports hard-to-detect variants. We also present a whole genome sequencing workflow that affords direct upload to the MNP website for MNP v12 classification. We sequenced and analysed 156 samples from the Department of Neuropathology, University Hospital Heidelberg using Rapid-CNS2. RESULTS: were compared to NGS panel sequencing and methylation array analyses. Rapid-CNS2 showed improved resolution over NGS panel sequencing for CNAs. High accuracy was obtained for detection of SNV/Indels. Long reads spanning the breakpoint identified clinically relevant fusions in 10/10 cases. Subclonal SVs like EGFR vIII missed by NGS panel sequencing were detected with high confidence. Complete concordance was achieved for MGMT promoter methylation status and methylation classification for MNP v11 classes. The optimized Rapid-CNS2 workflow shortened the turnaround time to 30 hours from sample receipt and minimum input DNA required was reduced to 500ng. For WGS, samples were sequenced for 72h on a Promethion device. WGS enabled accurate reporting of SNVs, CNAs, SVs, MGMT promoter status in addition to MNP v12 classification directly from the website eliminating the need for ad-hoc training of methylation classification models. The presented nanopore sequencing based workflows provide feasible single assay alternatives to conventional molecular diagnostic approaches with the aim to make such analyses more accessible.