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Cell lines represent the most versatile and widely used models of cancer and, as such, are critical for identifying and advancing new therapies. Strikingly, there is a significant gap in both the number of childhood brain cancer cell lines and their characterisation compared to their adult counterparts. To address this inequity, we established a childhood brain cancer cell line atlas (publicly available at vicpcc.org.au/dashboard) encompassing over 180 childhood CNS-derived cell lines, representing 20 tumour types and 11 molecular subtypes. Cell lines are characterized by whole genome, RNA-sequencing, phospho- and total proteomics, DNA methylation and ATAC-seq analyses. Multi-omic factor analysis revealed distinct lineage-specified classification of our cell line cohort. In parallel, high throughput drug and CRISPR/Cas9 screens were conducted to map the functional dependencies in over 70 childhood CNS cell lines, including 47 paediatric high grade glioma models. These screens identified both lineage and molecular-subtype specific genetic and drug dependencies, underscoring the utility of this wide-scale approach. Machine based learning approaches to predict genotype-phenotype correlations uncovered distinct paediatric-specific biomarkers of growth dependency, highlighting the unique genetic wiring underlying paediatric CNS tumours. Finally, by integrating functional, molecular and drug profiles of paediatric CNS cell lines, we construct a system to prioritize investigation of novel therapeutic target-biomarkers pairs in specific CNS tumour types.