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◆ Clinical Cancer Research2026-01-26· Glioma

Redefining Treatment Paradigms for Glioma in Adolescents and Young Adults: Population-Based Evidence for Molecular Classification

Shanqiang Qu, Qiuming Pan, Xin Zhang, Jing Wang, Hongrui Li, Yudi Huang, Kuilin Liao, Zhi Ye, Yilamujiang Ainiwan, Guozhong Yi, Zhiyong Li, Junlu Liu, Xiaomin Hou, Haiyan Xu, Zhuoyang Chen, Fen Mei, Tao Liu, Xi’an Zhang, Songtao Qi, Guanglong Huang

原始摘要(英文原文)· Original abstract
PURPOSE: Gliomas represent the second most common malignancy and leading cause of cancer death in adolescents and young adults (AYA; ages 15-39 years), yet their molecular landscape remains incompletely characterized. This study aims to characterize the molecular landscape of primary gliomas in AYAs by integrating multi-omics data. EXPERIMENTAL DESIGN: We recruited a cohort of patients with histopathologically diagnosed primary gliomas. The data encompassed clinical, imaging, histopathologic, genomic testing, and survival outcome data. The correlations of clinicopathologic features, molecular characteristics, and anatomic heterogeneity with prognosis were evaluated. RESULTS: Adult-type gliomas (66.2%) predominated, but pediatric-type gliomas constituted 23.6%, exhibiting distinct clinicopathologic profiles: pediatric-type tumors harbored frequent H3.3 (51.9%), TP53 (35.1%), and BRAF mutations (22.8%), whereas adult-type showed isocitrate dehydrogenase (IDH, 72.5%) and TP53 alterations (48.6%). IDH and H3.3/BRAF mutations were mutually exclusive. Anatomically, midline involvement (18.3%) correlated with younger age (≤25 years, P = 0.019), frontal gliomas were predominantly IDH mutations (58.3%), and midline tumors were enriched H3.3 K27M mutations (52.5%). Survival analysis revealed that H3.3 K27M-mutant high-grade gliomas had the poorest prognosis (median survival: 16 months), whereas BRAF-driven low-grade gliomas showed favorable outcomes. Pediatric-type molecular alterations are enriched in AYA gliomas. IDH wild-type tumors require sequencing to detect pediatric-type drivers (e.g., H3.3/BRAF mutations). CONCLUSIONS: The treatment strategies for AYA gliomas should be determined by molecular classification rather than age-based stratification. Adult-type and pediatric-type gliomas exhibit distinct biological and driver profiles. AYA gliomas exhibit significant molecular-anatomic heterogeneity, with specific anatomic regions demonstrating enrichment of molecular signatures.
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