Abstract B008: Mapping clonal architecture and evolution in pediatric brain cancers

Abstract Brain cancers are the most common solid tumors in children and adolescents and remain the leading cause of disease-related death in these populations. Despite their clinical importance, therapeutic progress has been limited by extensive intra- and inter-tumor heterogeneity. In particular, the clonal architecture and evolutionary dynamics of pediatric brain tumors remain poorly understood. Addressing this knowledge gap is critical, as genetically distinct subclones can shape disease progression, treatment resistance, and clinical outcome. To investigate clonal evolution at the population level, we analyzed longitudinal whole-genome sequencing data from 1, 742 tumors across 27 brain cancer types in 1, 479 pediatric patients from the Children’s Brain Tumor Network. We inferred clonal composition and phylogenetic relationships for each patient and reconstructed the space of tumor phylogenies for the entire cohort using a regularized Gromov-Hausdorff distance. Tumor phylogenetic structure was significantly associated with mutational burden, mutational signatures, cancer classification, and patient's survival status. In longitudinal samples, survival status remained significantly associated with tumor clonal architecture after adjusting for mutational burden, tumor subtype, and anatomical location, underscoring the clinical value of this readout. In contrast, in primary tumors, mutational signatures remained significant after adjusting for mutation count, tumor subtype, anatomical location, and purity, while survival status associations were no longer significant. Mutational signature timing analysis revealed that pediatric brain tumor genetic architecture is shaped by distinct mutational processes acting at different stages of tumor evolution. Truncal somatic mutations were enriched for age-related, defective proofreading, and homologous recombination deficiency signatures, whereas subclonal mutations showed significant contributions from DNA mismatch repair, chemotherapy-related, temozolomide-related, and somatic hypermutation activity signatures. Comparisons of matched longitudinal and primary phylogenetic trees further revealed that deceased patients and those with recurrent or metastatic disease exhibited significantly greater evolutionary divergence, suggesting that primary tumors are less predictive of complete evolutionary trajectories in poor-outcome cases. Together, these findings suggest that pediatric brain tumor evolution is shaped by cancer type and various mutational processes, and that patients with adverse outcomes follow distinct evolutionary trajectories independently of subtype. Our study provides a population-level view of tumor evolution in pediatric brain cancers and highlights the value of genetic clonal dynamics for understanding tumor etiology and progression. Citation Format: Minh A. Nguyen, Pablo G. Cámara. Mapping clonal architecture and evolution in pediatric brain cancers abstract. In: Proceedings of the AACR Special Conference in Cancer Research: Cancer Evolution: The Dynamics of Progression and Persistence; 2025 Dec 4-6; Albuquerque, NM. Philadelphia (PA): AACR; Cancer Res 2025;85 (23Suppl): Abstract nr B008.