Annekathrin Kratz

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

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.

TERT Promoter Mutations and Risk of Recurrence in Meningioma

The World Health Organization (WHO) classification and grading system attempts to predict the clinical course of meningiomas based on morphological parameters. However, because of high interobserver variation of some criteria, more reliable prognostic markers are required. Here, we assessed the TERT promoter for mutations in the hotspot regions C228T and C250T in meningioma samples from 252 patients. Mutations were detected in 16 samples (6.4% across the cohort, 1.7%, 5.7%, and 20.0% of WHO grade I, II, and III cases, respectively). Data were analyzed by t test, Fishers exact test, log-rank test, and Cox proportional hazard model. All statistical tests were two-sided. Within a mean follow-up time in surviving patients of 68.1 months, TERT promoter mutations were statistically significantly associated with shorter time to progression (P < .001). Median time to progression among mutant cases was 10.1 months compared with 179.0 months among wild-type cases. Our results indicate that the inclusion of molecular data (ie, analysis of TERT promoter status) into a histologically and genetically integrated classification and grading system for meningiomas increases prognostic power. Consequently, we propose to incorporate the assessment of TERT promoter status in upcoming grading schemes for meningioma.

Methylation-based classification of benign and malignant peripheral nerve sheath tumors

AbstractThe vast majority of peripheral nerve sheath tumors derive from the Schwann cell lineage and comprise diverse histological entities ranging from benign schwannomas and neurofibromas to high-grade malignant peripheral nerve sheath tumors (MPNST), each with several variants. There is increasing evidence for methylation profiling being able to delineate biologically relevant tumor groups even within the same cellular lineage. Therefore, we used DNA methylation arrays for methylome- and chromosomal profile-based characterization of 171 peripheral nerve sheath tumors. We analyzed 28 conventional high-grade MPNST, three malignant Triton tumors, six low-grade MPNST, four epithelioid MPNST, 33 neurofibromas (15 dermal, 8 intraneural, 10 plexiform), six atypical neurofibromas, 43 schwannomas (including 5 NF2 and 5 schwannomatosis associated cases), 11 cellular schwannomas, 10 melanotic schwannomas, 7 neurofibroma/schwannoma hybrid tumors, 10 nerve sheath myxomas and 10 ganglioneuromas. Schwannomas formed different epigenomic subgroups including a vestibular schwannoma subgroup. Cellular schwannomas were not distinct from conventional schwannomas. Nerve sheath myxomas and neurofibroma/schwannoma hybrid tumors were most similar to schwannomas. Dermal, intraneural and plexiform neurofibromas as well as ganglioneuromas all showed distinct methylation profiles. Atypical neurofibromas and low-grade MPNST were indistinguishable with a common methylation profile and frequent losses of CDKN2A. Epigenomic analysis finds two groups of conventional high-grade MPNST sharing a frequent loss of neurofibromin. The larger of the two groups shows an additional loss of trimethylation of histone H3 at lysine 27 (H3K27me3). The smaller one retains H3K27me3 and is found in spinal locations. Sporadic MPNST with retained neurofibromin expression did not form an epigenetic group and most cases could be reclassified as cellular schwannomas or soft tissue sarcomas. Widespread immunohistochemical loss of H3K27me3 was exclusively seen in MPNST of the main methylation cluster, which defines it as an additional useful marker for the differentiation of cellular schwannoma and MPNST.

Radiomic subtyping improves disease stratification beyond key molecular, clinical, and standard imaging characteristics in patients with glioblastoma

Background The purpose of this study was to analyze the potential of radiomics for disease stratification beyond key molecular, clinical, and standard imaging features in patients with glioblastoma. Methods Quantitative imaging features (n = 1043) were extracted from the multiparametric MRI of 181 patients with newly diagnosed glioblastoma prior to standard-of-care treatment (allocated to a discovery and a validation set, 2:1 ratio). A subset of 386/1043 features were identified as reproducible (in an independent MRI test-retest cohort) and selected for analysis. A penalized Cox model with 10-fold cross-validation (Coxnet) was fitted on the discovery set to construct a radiomic signature for predicting progression-free and overall survival (PFS and OS). The incremental value of a radiomic signature beyond molecular (O6-methylguanine-DNA methyltransferase [MGMT] promoter methylation, DNA methylation subgroups), clinical (patients age, KPS, extent of resection, adjuvant treatment), and standard imaging parameters (tumor volumes) for stratifying PFS and OS was assessed with multivariate Cox models (performance quantified with prediction error curves). Results The radiomic signature (constructed from 8/386 features identified through Coxnet) increased the prediction accuracy for PFS and OS (in both discovery and validation sets) beyond the assessed molecular, clinical, and standard imaging parameters (P ≤ 0.01). Prediction errors decreased by 36% for PFS and 37% for OS when adding the radiomic signature (compared with 29% and 27%, respectively, with molecular + clinical features alone). The radiomic signature was-along with MGMT status-the only parameter with independent significance on multivariate analysis (P ≤ 0.01). Conclusions Our study stresses the role of integrating radiomics into a multilayer decision framework with key molecular and clinical features to improve disease stratification and to potentially advance personalized treatment of patients with glioblastoma.

GAIN OF 12P ENCOMPASSING CCND2 IS ASSOCIATED WITH GEMISTOCYTIC HISTOLOGY IN IDH MUTANT ASTROCYTOMAS

Felix Sahm1,2 · Andrey Korshunov2 · Daniel Schrimpf1,2 · Damian Stichel1,2 · David T. W. Jones3 · David Capper1,2 · Christian Koelsche1,2 · David Reuss1,2 · Annekathrin Kratz1,2 · Kristin Huang1,2 · Annika K. Wefers1,2 · Matthias Schick4 · Melanie Bewerunge‐Hudler4 · Michel Mittelbronn5 · Michael Platten6,7,8 · Daniel Hänggi9 · Astrid Jeibmann10 · Andreas Unterberg11 · Christel Herold‐Mende11 · Stefan M. Pfister3,12 · Sebastian Brandner13 · Wolfgang Wick6,14 · Andreas von Deimling1,2