Division of Haematology/Oncology, Department of Paediatrics, The Hospital for Sick Children, Toronto, Ontario, Canada.
Princess Margaret Cancer Centre and MacFeeters-Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada.
Neuro Oncol. 2020 Oct 14;22(10):1474-1483. doi: 10.1093/neuonc/noaa077.
Both genetic and methylation analysis have been shown to provide insight into the diagnosis and prognosis of many brain tumors. However, the implication of methylation profiling and its interaction with genetic alterations in pediatric low-grade gliomas (PLGGs) are unclear.
We performed a comprehensive analysis of PLGG with long-term clinical follow-up. In total 152 PLGGs were analyzed from a range of pathological subtypes, including 40 gangliogliomas. Complete molecular analysis was compared with genome-wide methylation data and outcome in all patients. For further analysis of specific PLGG groups, including BRAF p.V600E mutant gliomas, we compiled an additional cohort of clinically and genetically defined tumors from 3 large centers.
Unsupervised hierarchical clustering revealed 5 novel subgroups of PLGG. These were dominated by nonneoplastic factors such as tumor location and lymphocytic infiltration. Midline PLGG clustered together while deep hemispheric lesions differed from lesions in the periphery. Mutations were distributed throughout these location-driven clusters of PLGG. A novel methylation cluster suggesting high lymphocyte infiltration was confirmed pathologically and exhibited worse progression-free survival compared with PLGG harboring similar molecular alterations (P = 0.008; multivariate analysis: P = 0.035). Although the current methylation classifier revealed low confidence in 44% of cases and failed to add information in most PLGG, it was helpful in reclassifying rare cases. The addition of histopathological and molecular information to specific methylation subgroups such as pleomorphic xanthoastrocytoma-like tumors could stratify these tumors into low and high risk (P = 0.0014).
The PLGG methylome is affected by multiple nonneoplastic factors. Combined molecular and pathological analysis is key to provide additional information when methylation classification is used for PLGG in the clinical setting.
遗传和甲基化分析已被证明可以深入了解许多脑肿瘤的诊断和预后。然而，甲基化谱分析及其与儿科低级别胶质瘤（PLGG）遗传改变的相互作用尚不清楚。
我们对具有长期临床随访的 PLGG 进行了全面分析。总共分析了来自多种病理亚型的 152 例 PLGG，包括 40 例神经节细胞瘤。对所有患者的全分子分析与全基因组甲基化数据和结果进行了比较。为了进一步分析特定的 PLGG 组，包括 BRAF p.V600E 突变型胶质瘤，我们从 3 个大型中心汇编了一个具有临床和遗传定义的肿瘤的额外队列。
无监督层次聚类显示出 5 种新的 PLGG 亚组。这些亚组主要由非肿瘤因素主导，如肿瘤位置和淋巴细胞浸润。中线 PLGG 聚集在一起，而深部半球病变与周围病变不同。突变分布在这些位置驱动的 PLGG 聚类中。一个新的提示高淋巴细胞浸润的甲基化聚类在病理学上得到了证实，与具有类似分子改变的 PLGG 相比，其无进展生存期更差（P = 0.008；多变量分析：P = 0.035）。尽管当前的甲基化分类器在 44%的病例中显示出低置信度，并且在大多数 PLGG 中无法提供信息，但它有助于对罕见病例进行重新分类。将组织病理学和分子信息添加到特定的甲基化亚组，如多形性黄色星形细胞瘤样肿瘤，可以将这些肿瘤分为低风险和高风险（P = 0.0014）。
PLGG 甲基组受多种非肿瘤因素影响。在临床环境中使用甲基化分类对 PLGG 进行分析时，综合分子和病理分析是提供附加信息的关键。
