gms | German Medical Science

73. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC)
Joint Meeting mit der Griechischen Gesellschaft für Neurochirurgie

Deutsche Gesellschaft für Neurochirurgie (DGNC) e. V.

29.05. - 01.06.2022, Köln

Deciphering the methylation signature of circulating extracellular vesicle DNA for CNS tumour classification

Entschlüsselung der Methylierungssignatur von zirkulierender extrazellulärer Vesikel-DNA zur Klassifizierung von ZNS-Tumoren

Meeting Abstract

  • presenting/speaker Franz Lennard Ricklefs - Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurochirurgie, Hamburg, Deutschland
  • presenting/speaker Tammo Ricklefs - Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurochirurgie, Hamburg, Deutschland
  • Cecile Maire - Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurochirurgie, Hamburg, Deutschland
  • Amanda Salviano da Silva - Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurochirurgie, Hamburg, Deutschland
  • Kathrin Wollmann - Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurochirurgie, Hamburg, Deutschland
  • Thomas Sauvigny - Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurochirurgie, Hamburg, Deutschland
  • Lasse Dührsen - Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurochirurgie, Hamburg, Deutschland
  • Ulrich Schüller - Universitätsklinikum Hamburg-Eppendorf, Institut für Neuropathologie, Hamburg, Deutschland
  • Manfred Westphal - Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurochirurgie, Hamburg, Deutschland
  • Katrin Lamszus - Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurochirurgie, Hamburg, Deutschland

Deutsche Gesellschaft für Neurochirurgie. 73. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), Joint Meeting mit der Griechischen Gesellschaft für Neurochirurgie. Köln, 29.05.-01.06.2022. Düsseldorf: German Medical Science GMS Publishing House; 2022. DocV006

doi: 10.3205/22dgnc006, urn:nbn:de:0183-22dgnc0067

Published: May 25, 2022

© 2022 Ricklefs et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at http://creativecommons.org/licenses/by/4.0/.


Outline

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Objective: Genome-wide methylation profiling has recently been developed into a tool that allows subtype tumor classification in central nervous system (CNS) tumors. We previously showed that extracellular vesicle (EV) DNA faithfully reflects the tumor methylation class, including information on the IDH mutation and MGMT promoter methylation status. Furthermore we showed that circulating plasma EVs are elevated in CNS tumor patients in comparison to healthy controls with tumor related protein profiles. In our ongoing work, we investigated, whether the methylation signatures of circulating EV DNA as well as cfDNA can be used for liquid biopsy approaches for CNS tumor detection and classification.

Methods: We isolated DNA from patients suffering from Glioblastoma (GBM), Meningioma (MGN) and cerebral metastases (CM) from circulating EVs (n=27), cfDNA (n=27) and tissue DNA (n=90). Patients undergoing epileptic surgery as well as aneurysm clipping were used as non-tumorous controls (HD, n= 7). EVs were classified by nanoparticle analysis (NTA), immunoblotting, imaging flow cytometry (IFCM) and electron microscopy.

Results: Isolated DNA showed higher molecular DNA in EV DNA in comparison to cfDNA, while HD or tumor patients showed not differences in their corresponding DNA size profiles. Next, we performed genome-wide methylation profiling by 850k Illumina EPIC array on all DNA analytes and tumor entities. Linear models and empirical Bayes methods identified significant differential methylated CPGs (GBM vs. HD, MGN, vs HD, CM vs. HD), that revealed tumor specific signatures to detect and discriminate different CNS tumor entities. Visualization of differential methylated CPGs by dimension reduction (PCA, t-SNE, Umap) verified tumor specific clusters. cfDNA and EV-DNA comparisons each revealed their own differential CPG profile.

Conclusion: Our study shows that the methylation signature of circulating EV DNA and cfDNA can be used to separate healthy individuals from tumor patients with the goal to augment standard-of-care imaging to improve tumor detection, classification and surveillance.