Artikel
Genetic and epigenetic profiling of spinal meningiomas
Genetisches und epigenetisches Profiling von spinalen Meningeomen
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Autoren
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Franz Lennard Ricklefs
- Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurochirurgie, Hamburg, Deutschland
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Krys Fita
- Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurochirurgie, Hamburg, Deutschland
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Malte Mohme
- Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurochirurgie, Hamburg, Deutschland
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Manfred Westphal
- Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurochirurgie, Hamburg, Deutschland
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Christian Mawrin
- Universitätsklinkum Magdeburg, Institut für Neuropathologie, Magdeburg, Deutschland
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Ulrich Schüller
- Universitätsklinikum Hamburg-Eppendorf, Institut für Neuropathologie, Hamburg, Deutschland
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Sven Oliver Eicker
- Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurochirurgie, Hamburg, Deutschland
| Veröffentlicht: | 25. Mai 2022 |
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Gliederung
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Objective: Spinal meningiomas account for 1.2-12 % of all meningiomas and 25-45 % of all spinal tumours. About 20 % of intracranial, but only 4.6 % of spinal meningiomas recur and require additional treatment. Whereas the classification of intracranial meningiomas has evolved considerably in recent years and uses genetic as well as epigenetic parameters, the classification of spinal meningiomas is based solely on histopathological findings. By embedding epi-/genetic features, the prognosis of intracranial meningiomas could be significantly improved, which is still lacking for spinal meningiomas. In our work, we integrated genetic [S1] and epigenetic parameters into the classification of spinal meningiomas in order to better predict the risk of meningioma recurrence and to guide decisions on adjuvant treatment.
Methods: We performed methylation profiles (850k / EPIC array) from 36 spinal meningiomas as well as targetd panel next generation sequencing (NGS) of 32 matching tumors. 497 intracranial meningiomas were used as a reference cohort. Copy number variations (CNV) were inferred from the methylation data. Principal component (PCA) and t-SNE analysis were conducted. Clinical and histopathological parameters (location, size, recurrence, WHO°, pathological subtype) were correlated with methylation signatures, that were additionally classified using the DKFZ brain tumour classifier.
Results: The methylation signature of spinal meningiomas matched to that of intracranial meningiomas (36/36), although subgroup assignment was achieved in only 8/36 cases [S1] . PCA and t-SNE analysis revealed that the remaining spinal meningioms (28/36) appear to form an individual methylation subgroup. NGS revealed mutations in NF2 (15/32), AKT1 E17 (5/32) and PIK3CA, TRAF7, POLR2A and SMARC in (1/32). Interestingly, we were able to identify a methylation-based arrangement of spinal meningiomas in accordance to their localization. CNV revealed q22 losses, known from cranial meningiomas.
Conclusion: Spinal meningiomas can be correctly identified by their global methylation profile. Yet, they seem to have their own subgroups marked by distinct chromosomal variations, which may allow an improved prognosis that could lead to a better guidance for adjuvant therapy.
