Clinical impact of combined epigenetic and molecular analysis of pediatric low-grade gliomas. Issue 10 (3rd April 2020) - Fukuoka, Kohei; Mamatjan, Yasin; Tatevossian, Ruth; Zapotocky, Michal; Ryall, Scott; Stucklin, Ana Guerreiro; Bennett, Julie; Nobre, Liana Figueiredo; Arnoldo, Anthony; Luu, Betty; Wen, Ji; Zhu, Kaicen; et al.
Abstract: Background: 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. Methods: 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. Results: 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). Conclusion: 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.