gms | German Medical Science

72. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC)
Joint Meeting mit der Polnischen Gesellschaft für Neurochirurgie

Deutsche Gesellschaft für Neurochirurgie (DGNC) e. V.

06.06. - 09.06.2021

Spinal intradural tumours – epigenetic analysis of a case series

Spinale intradurale Tumore – epigenetische Aufarbeitung einer Fallserie

Meeting Abstract

  • presenting/speaker Mats Leif Moskopp - Vivantes Klinikum Friedrichshain, Klinik für Neurochirurgie, Berlin, Deutschland; TU Dresden, Medizinische Fakultät Carl Gustav Carus, Institut für Physiologie, Dresden, Deutschland
  • David Capper - Charité Universitätsmedizin, Department of Neuropathology, Berlin, Deutschland; German Cancer Consortium (DKTK), Partner Site Berlin, German Cancer Research Center (DKFZ), Heidelberg, Deutschland
  • Frank L. Heppner - Charité Universitätsmedizin, Department of Neuropathology, Berlin, Deutschland; Humboldt Universität Berlin, Cluster of Excellence, NeuroCure, Berlin, Deutschland; German Center for Neurodegenerative Diseases (DZNE), Berlin, Deutschland
  • Robert Krempien - Helios Klinikum Berlin-Buch, Klinik für Strahlentherapie und Radioonkologie, Berlin, Deutschland
  • presenting/speaker Dag Moskopp - Vivantes Klinikum Friedrichshain, Klinik für Neurochirurgie, Berlin, Deutschland

Deutsche Gesellschaft für Neurochirurgie. 72. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), Joint Meeting mit der Polnischen Gesellschaft für Neurochirurgie. sine loco [digital], 06.-09.06.2021. Düsseldorf: German Medical Science GMS Publishing House; 2021. DocP146

doi: 10.3205/21dgnc432, urn:nbn:de:0183-21dgnc4322

Veröffentlicht: 4. Juni 2021

© 2021 Moskopp et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe



Objective: DNA methylation-based classification of central nervous system (CNS) tumors using DNA methylation arrays (EPIC) is a new technique that allows precise tumor characterisation resulting in defining novel tumor entities and/or changing of diagnosis (reclassification) in around 10-15% of traditionally diagnosed CNS tumors. We present a case series of epigenetically analyzed spinal intradural tumors and highlight the role of EPIC-based classification for such tumors.

Methods: In the years 2018-2019 a total of 1792 operations, including 756 spinal procedures, were performed at our department. Among these, we identified a group of 13 patients with spinal intradural tumors. EPIC analysis was performed either by recommendation of the tumor board or the neuropathologists in charge. Primary data of EPIC methylation arrays were reanalyzed with the latest classifier version 11b4 as of 11/2020.

Results: Five out of 13 spinal cases metachronically disclosed cerebral tumors of a seemingly different entity as well; one case could not be classified first hand. EPIC data helped to identify two cases of primary spinal manifestation of diffuse midline glioma, K27M mutant, one intradural metastasis of a gliosarkoma, one case of intradural malignant meningioma metastasis and one case of an exceedingly rare spinal cord MN1 fusion associated tumor, compatible with an astroblastoma, MN1 altered. While in three cases the EPIC analysis was instrumental to bring forward a distinct diagnostic entity, in two cases the EPIC data helped to assign the respective metastatic lesions to its primary tumor source. Four of five patients died within the first year after diagnosis. EPIC analysis did not change the intended treatment (combined radio-chemotherapy/radiotherapy) or the time point of secondary treatment for the described five patients.

Conclusion: EPIC classification is a most precise and essential novel neuropathological diagnostic method. Here, we report of 13 intraspinal intradural tumor cases. In 5 of 13 cases an EPIC analysis was performed due to a nonconclusive diagnosis using conventional, non-molecular neuropathological methods. In 3 out of 13 cases EPIC analysis identified rare tumor entities with less than 300 published cases. Our data illustrates the necessity of EPIC analysis as an essential tool allowing to overcome traditional limitations of neuropathological diagnostics. Only applying precise diagnostic classification will allow to guarantee the adequate applicatoin of future therapeutic approaches.