PROJECT SUMMARY Pediatric, adolescent, and young adult (AYA) brain cancer is the most lethal form of childhood cancer, with limited treatment options. Through national efforts in the last several years, extensive data on molecular profiles and outcomes of these cancers have been documented, creating a large repository as part of the Childhood Cancer Data Initiative (CCDI). These data provide a unique opportunity to better understand the etiology and molecular mechanisms of pediatric and AYA cancers, especially within the brain, and will enable the identification of new therapeutic avenues. To achieve these results with these public datasets, innovative tools and approaches are required to take advantage of the incredible resource provided. Importantly, as these data have been collected, parallel efforts have been underway through the BRAIN Initiative and other atlas-scale consortia to similarly characterize the cell types that exist in the brain, with a new focus on the human brain. We have been involved in the creation of atlas scale datasets through the brain initiative that specifically characterize human brain development. All brain cancers, but especially those that impact children and AYAs, reactivate cell types and developmental trajectories from normal development. As such, now is an exceptional time to leverage the existing normal data from the developing human brain and to integrate it with pediatric and AYA brain cancer data in order to identify what cell types are similar and different, what gene programs the cancers leverage, and how the cancers interact with normal brain cells to drive their expansion. Thus, we propose a two pronged approach here to (1) explore characteristics inherent within the brain cancer transcriptional datasets in the CCDI and to (2) characterize relevant to cell – cell interactions that could be promoting tumor growth. To do this, we will use novel tools that have enabled us to identify previously unknown regulators of human brain development to similarly identify core regulators of pediatric and AYA brain cancer states. With these network based methods, we will also perform robust comparisons between brain cancers and developmental cell types and states, in the hopes of identifying novel targets that can drive cancer cell differentiation as opposed to tumor progression. We will additionally apply a novel class of informatic tools that enable the discovery of cell – cell communication to identify how these pediatric and AYA tumors are communicating with the rest of the brain; these types of tumor – normal crosstalk have been recently discovered as key drivers of pediatric brain tumors. This approach may identify additional targets in the microenvironment that can be addressed therapeutically. Both approaches will provide orthogonal methods of validating the FDA Relevant Molecular Target List and will provide resources for additional research into these cancers. As such, all analysis from this project will b...