Department of Neuropathology, Institute of Pathology, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany; Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Department of Neuropathology, Institute of Pathology, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany.
Lancet Oncol. 2017 May;18(5):682-694. doi: 10.1016/S1470-2045(17)30155-9. Epub 2017 Mar 15.
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.
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.
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.
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.
German Cancer Aid, Else Kröner-Fresenius Foundation, and DKFZ/Heidelberg Institute of Personalized Oncology/Precision Oncology Program.
世界卫生组织(WHO)脑肿瘤分类描述了 15 种脑膜瘤亚型。其中 9 种被归入 WHO 分级 I,3 种归入 II 级,3 种归入 III 级。分级仅基于组织学,没有分子标志物。尽管现有的分类和分级方法具有预后价值,但存在一些缺点,例如亚型和分级标准的定义不明确,容易出现主观判断。在这项研究中,我们旨在全面描述脑膜瘤的整个分子遗传学特征,以确定具有生物学和临床意义的亚组。
在这项多中心回顾性分析中,我们研究了来自 10 个欧洲学术神经肿瘤学中心的脑膜瘤的全基因组 DNA 甲基化模式,以确定脑膜瘤的不同甲基化类别。通过 DNA 拷贝数分析、突变分析和 RNA 测序进一步对甲基化类别进行了表征。通过 Kaplan-Meier 法分析甲基化类别的无进展生存期结果。使用 Brier 预测评分比较 DNA 甲基化分类和 WHO 分类方案,在维也纳医科大学(维也纳,奥地利)具有 WHO 分级、无进展生存期和疾病特异性生存期数据的独立队列中进行分析,评估采用替代甲基化芯片的甲基化模式。
我们回顾性地收集了 497 例脑膜瘤和 309 例可能在组织学上类似于脑膜瘤变体的其他颅外骨骼肿瘤样本。未受监督的 DNA 甲基化数据聚类清楚地将所有脑膜瘤与其他颅骨肿瘤区分开来。我们从所有 497 例脑膜瘤样本中生成了全基因组 DNA 甲基化图谱。DNA 甲基化谱区分了与典型突变、细胞遗传学和基因表达模式相关的六个具有临床意义的不同甲基化类别。与 WHO 分级相比,单独和联合甲基化类别的分类更能准确识别具有 WHO I 级组织学的肿瘤中疾病进展风险高的患者,以及 WHO II 级肿瘤中复发风险较低的患者(p=0.0096,来自 Brier 预测检验)。我们在我们的 140 例脑膜瘤患者的独立队列中验证了这一发现。
基于 DNA 甲基化的脑膜瘤分类可捕获更具临床同质性的群体,并且比 WHO 分类更能准确预测肿瘤复发和预后。这里提出的方法对于将脑膜瘤患者分层为观察或辅助治疗组非常有用。我们认为基于甲基化的肿瘤分类对于脑膜瘤的未来诊断和治疗具有重要意义。
德国癌症援助协会、Else Kröner-Fresenius 基金会和 DKFZ/海德堡个体化肿瘤学/精准肿瘤学计划。