This study investigates the molecular mechanisms driving pediatric high-grade glioma (pHGG) pathogenesis through multi-omics analysis of cell cultures and primary tumor samples. The work involves sensitive personal data. Using ATAC-seq and RNA-seq, we delineate differential chromatin accessibility and gene expression profiles between pHGG and normal neural stem cells (NS). Integration of diverse datasets, including exome-seq and methylation arrays, unveils candidate genes and regulatory elements implicated in pHGG progression. Concurrently, analysis of primary tumor samples, encompassing methylation array, RNA-seq, and whole-genome sequencing data alongside clinical parameters, elucidates pHGG heterogeneity and its correlation with clinical outcomes. This comprehensive approach aims to deepen our understanding of pHGG pathogenesis, paving the way for improved diagnosis and therapeutic strategies.