ID #330 CNS tumor type prevalence according to age group: an analysis of 21,000 cases confirmed by methylation profiling, with a focus on adolescents and young adults
Adriana Fonseca, Leeor Yefet, Omkar Singh, Christopher Dampier, Karen Dazelle, Michelle Lam, Zied Abdullaev, Hye-Jung Chung, Martha Quezado, Mark Raffeld, Jeffrey Gagan, Ina Lee, MacLean Nasrallah, Julie Bennett, Eric Bouffet, Dipak Poria, Pieter Wesseling, Martin Van den Bent, Patrick Wen, Pascale Varlet, Arnault Tauziède-Espariat, Ida Cristiane, Gelareh Zadeh, Kenneth AldapeAbstract
Background
Approximately 12,000 adolescents and young adults (ages 15-39, AYAs) are diagnosed with a primary central nervous system (CNS) tumor each year. DNA methylation profiling has transformed CNS tumor classification by refining diagnostic accuracy and identifying biologically distinct subtypes, but its application has not been systematically evaluated in the AYA population. In this study, we examined the spectrum of CNS tumor types across age groups, with a focus on the AYA population.
Methods
We assembled a large dataset of CNS tumor samples with age annotations and methylation profiles matching with high confidence to a CNS tumor type using the NCI/Bethesda classifier. Prevalence of tumor type, methylation class and DNA copy number aberrations were compared across age strata (pediatric, AYA and adult).
Results
The cohort of 21,099 CNS tumors included 5139 tumors from AYAs (24%), which showed a mixed pattern, with tumors typical of childhood (e.g. medulloblastoma) as well as those common in older adults (e.g. glioblastoma). Several tumor types were specifically enriched in the AYA, including IDH-mutant astrocytoma, pleomorphic xanthoastrocytoma, posterior fossa group B ependymoma, and diffuse hemispheric glioma, H3 G34-mutant, among others. Distinct methylation subclasses of multiple tumor types were observed in the AYA, and patterns of genomic aberrations showed age-specific distributions.
Conclusion
Large-scale methylation profiling revealed unique classification patterns of CNS tumors in AYAs, with specific tumor types, subclasses, and genomic alterations enriched in this population. These data may serve as a valuable reference resource for better understanding the spectrum of CNS tumors affecting AYA patients.