Molecular Profiling of Pediatric Medulloblastoma in Argentina: Integrating Techniques for Precision Diagnosis in Resource-Constrained Settings

Abstract

Background: Medulloblastoma (MB) is the most common malignant pediatric brain tumor, characterized by substantial molecular and clinical heterogeneity. Although molecular subgrouping is essential for risk stratification and treatment decisions, such approaches remain limited in low- and middle-income countries. Methods: We conducted a comprehensive molecular characterization of 84 pediatric MB cases from Argentina using a cost-effective, integrative diagnostic workflow combining immunohistochemistry, fluorescence in-situ hybridization, Sanger sequencing and NanoString-based gene expression profiling. Tumors were classified according to the 2021 WHO guidelines, and molecular groups were assessed for associations with risk, histology, anatomic location and overall survival (OS). Results: The non-WNT/non-SHH group predominated (60.7%), followed by SHH-activated (27.4%) and WNT-activated (10.7%) groups. SHH TP53- tumors were more prevalent among infants, while WNT tumors were exclusive to older children and adolescents. Genetic alterations were group-specific: CTNNB1 mutations and chromosome 6 monosomy were restricted to WNT tumors, while MYCN and isochromosome 17q alterations were significantly associated with the non-WNT/non-SHH group; however MYCN association with the latter molecular group was driven by Group 4 MB. On the other hand, MYC amplification, though enriched in Group 3, was also detected in Group 4 cases. SHH TP53+ tumors displayed a strong association with very high biological risk and poor OS, while WNT tumors showed favorable outcomes. Importantly, our pipeline resolved 89% of molecular classifications using low-cost techniques alone, with NanoString serving to clarify ambiguous cases. Conclusions: This is the first molecular characterization of pediatric MB in Argentina. We demonstrate that a tiered approach using conventional molecular tools can achieve high diagnostic accuracy, enabling meaningful group stratification and prognostic prediction in resource-constrained settings. These findings confirm feasibility and clinical utility of molecular diagnostics and strengthen the notion that efforts should be made in this direction in resource-limited environments to support their integration into routine MB management across diverse healthcare systems.