Robust methylation-based classification of brain tumors using nanopore sequencing

DNA methylation-based classification of cancer provides a comprehensive molecular approach to diagnose tumors. In fact, DNA methylation profiling of human brain tumors already profoundly impacts clinical neuro-oncology. However, current implementations using hybridization microarrays are time-consuming and costly. We recently reported on shallow nanopore whole-genome sequencing for rapid and cost-effective generation of genome-wide 5-methylcytosine profiles as input to supervised classification using random forests complemented by a medium-resolution copy number profile derived from the same raw data. Here, we demonstrate that this approach allows to discriminate a wide spectrum of primary brain tumors using public reference data of 82 distinct tumor entities. We developed a pseudo-probability score as a confidence score for interpretation in a clinical context. Using bootstrap sampling in a discovery cohort of N = 56 cases, we find that a minimum set of 1,000 random CpG features is sufficient for high-confidence classification by ad hoc random forests for most cases and demonstrate robustness across laboratories with matching results in 13/13 cases. When applying the confidence score threshold to an independent validation series (N = 111), the method demonstrated 100% specificity for the remaining 93 cases. In a prospective benchmarking (N = 15), median time to results was 21.1 hours. In conclusion, nanopore sequencing allows robust and rapid methylation-based classification across the full spectrum of brain tumors. The integrated confidence score facilitates possible clinical implementation, while requiring further prospective evaluation. ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Trial U1111-1239-3456 ### Funding Statement The study was funded by the Brain Tumour Charity (UK) - GN-000694 ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The local ethics committee (Charité Universitätsmedizin Berlin, Berlin, Germany; EA2/041/18) approved generation of prospective data in the context of this study. All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes The current nanoDx classification and analysis pipeline (version v.0.2.1 was used for preprocessing of all sequencing data) and the source code for the outlined RF implementation and to reproduce all analyses and figures in this manuscript will be publicly available upon publication. Raw sequencing data from the discovery cohort will be deposited at the European Genome-phenome archive (accession tba). Methylation microarray raw data and methylation calls from the validation cohort will be deposited at ArrayExpress (accession tba).