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Lancet Oncol. 2017 May;18(5):682-694. doi: 10.1016/S1470-2045(17)30155-9. Epub 2017 Mar 15.

DNA methylation-based classification and grading system for meningioma: a multicentre, retrospective analysis.

Author information

1
Department of Neuropathology, Institute of Pathology, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany; Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
2
Department of Neuropathology, Institute of Pathology, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany.
3
Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
4
Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
5
Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
6
Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Pediatric Oncology, Haematology and Immunology, Heidelberg University Hospital, Heidelberg, Germany.
7
Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland.
8
Institute of Neurology, Medical University of Vienna, Vienna, Austria.
9
Neurological Institute (Edinger-Institute), Goethe University, Frankfurt, Germany.
10
Division of Molecular Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
11
Brain Tumour Research Group, Institute of Clinical Neurosciences, Southmead Hospital, University of Bristol, Bristol, UK.
12
Department of Pathology, University Hospital Nürnberg, Nürnberg, Germany.
13
Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany.
14
Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany.
15
Genomics and Proteomics Core Facility, Micro-Array Unit, German Cancer Research Center (DKFZ), Heidelberg, Germany.
16
Department of Neuropathology, Otto von Guericke University Magdeburg, Magdeburg, Germany.
17
Department of Neurosurgery, University Hospital Mannheim, Mannheim, Germany.
18
Department of Neurosurgery, Saarland University, Homburg, Germany.
19
Department of Neurosurgery, Evangelische Krankenhaus Bielefeld, Bielefeld, Germany.
20
Department of Neurosurgery, University Hospital Hamburg-Eppendorf, Hamburg, Germany.
21
Department of Neuropathology, University of Bonn, Bonn, Germany.
22
Department of Neuropathology, Charité Medical University, Berlin, Germany.
23
Department of Neuropathology, University Hospital Tübingen, Tübingen, Germany.
24
Department of Neuropathology, University Hospital and University of Zurich, Zurich, Switzerland.
25
Department of Molecular Histopathology, University of Cambridge, Cambridge, UK.
26
Clinical Cooperation Unit Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany; Neurology Clinic, University Hospital Mannheim, Mannheim, Germany.
27
Institute of Neuropathology, University Hospital Münster, Münster, Germany.
28
Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany.
29
Department of Medicine I, CNS Tumours Unit, Medical University of Vienna, Vienna, Austria.
30
Department of Neuropathology, Institute of Pathology, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany; Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany. Electronic address: andreas.vondeimling@med.uni-heidelberg.de.

Abstract

BACKGROUND:

The WHO classification of brain tumours describes 15 subtypes of meningioma. Nine of these subtypes are allotted to WHO grade I, and three each to grade II and grade III. Grading is based solely on histology, with an absence of molecular markers. Although the existing classification and grading approach is of prognostic value, it harbours shortcomings such as ill-defined parameters for subtypes and grading criteria prone to arbitrary judgment. In this study, we aimed for a comprehensive characterisation of the entire molecular genetic landscape of meningioma to identify biologically and clinically relevant subgroups.

METHODS:

In this multicentre, retrospective analysis, we investigated genome-wide DNA methylation patterns of meningiomas from ten European academic neuro-oncology centres to identify distinct methylation classes of meningiomas. The methylation classes were further characterised by DNA copy number analysis, mutational profiling, and RNA sequencing. Methylation classes were analysed for progression-free survival outcomes by the Kaplan-Meier method. The DNA methylation-based and WHO classification schema were compared using the Brier prediction score, analysed in an independent cohort with WHO grading, progression-free survival, and disease-specific survival data available, collected at the Medical University Vienna (Vienna, Austria), assessing methylation patterns with an alternative methylation chip.

FINDINGS:

We retrospectively collected 497 meningiomas along with 309 samples of other extra-axial skull tumours that might histologically mimic meningioma variants. Unsupervised clustering of DNA methylation data clearly segregated all meningiomas from other skull tumours. We generated genome-wide DNA methylation profiles from all 497 meningioma samples. DNA methylation profiling distinguished six distinct clinically relevant methylation classes associated with typical mutational, cytogenetic, and gene expression patterns. Compared with WHO grading, classification by individual and combined methylation classes more accurately identifies patients at high risk of disease progression in tumours with WHO grade I histology, and patients at lower risk of recurrence among WHO grade II tumours (p=0·0096) from the Brier prediction test). We validated this finding in our independent cohort of 140 patients with meningioma.

INTERPRETATION:

DNA methylation-based meningioma classification captures clinically more homogenous groups and has a higher power for predicting tumour recurrence and prognosis than the WHO classification. The approach presented here is potentially very useful for stratifying meningioma patients to observation-only or adjuvant treatment groups. We consider methylation-based tumour classification highly relevant for the future diagnosis and treatment of meningioma.

FUNDING:

German Cancer Aid, Else Kröner-Fresenius Foundation, and DKFZ/Heidelberg Institute of Personalized Oncology/Precision Oncology Program.

PMID:
28314689
DOI:
10.1016/S1470-2045(17)30155-9
[Indexed for MEDLINE]
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