Kohei Fukuoka1, Yasin Mamatjan2, Ruth Tatevossian3, Michal Zapotocky1, Scott Ryall4, Ana Guerreiro Stucklin1,5, Julie Bennett1, Liana Figueiredo Nobre1, Anthony Arnoldo6, Betty Luu7, Ji Wen3, Kaicen Zhu8, Alberto Leon9, Dax Torti9, Trevor J Pugh9,10,11, Lili-Naz Hazrati12, Normand Laperriere13, James Drake14, James T Rutka14, Peter Dirks14, Abhaya V Kulkarni14, Michael D Taylor14, Ute Bartels1, Annie Huang1, Gelareh Zadeh2, Kenneth Aldape2, Vijay Ramaswamy1, Eric Bouffet1, Matija Snuderl8, David Ellison3, Cynthia Hawkins12, Uri Tabori1. 1. Division of Haematology/Oncology, Department of Paediatrics, The Hospital for Sick Children, Toronto, Ontario, Canada. 2. Princess Margaret Cancer Centre and MacFeeters-Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada. 3. Department of Pathology, St Jude Children's Research Hospital, Memphis, Tennessee, USA. 4. Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada. 5. Deparment of Oncology and Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland. 6. Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada. 7. Program in Developmental and Stem Cell Biology, Arthur and Sonia Labatt Brain Tumour Research Centre, Hospital for Sick Children, Toronto, Ontario, Canada. 8. Department of Pathology, New York University Langone Health and Medical Center, New York, New York, USA. 9. PM-OICR Translational Genomics Laboratory, Ontario Institute for Cancer Research, Toronto, Ontario, Canada. 10. Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada. 11. Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. 12. Division of Pathology, The Hospital for Sick Children, Toronto, Ontario, Canada. 13. Department of Radiation Oncology, Princess Margaret Hospital, Toronto, Ontario, Canada. 14. Division of Neurosurgery, The Hospital for Sick Children, Toronto, Ontario, Canada.
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.
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.
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