Project Summary Pediatric brain tumors are the most frequent cause of morbidity in children with solid tumors. Importantly, the aggressive therapeutic regiments often lead to debilitating neurological effects. The realization that developmental processes critical to brain development are also deregulated in cancer has provided new hope for understanding and treating brain tumors. Indeed, single cell-RNAseq analyses have further demonstrated the role of defects in lineage determination for pediatric brain tumors. To discover novel drivers of tumorigenesis, we will focus on the function of three-dimensional (3D) genome folding in pediatric brain tumors. Indeed, 3D chromatin interactions are involved in gene expression regulation, and changes in genome folding are linked to cell identity acquisition during development. While there is increasing interest in elucidating the function of 3D genome architecture during developmental processes and in cancer, how the 3D genome is organized in different pediatric brain tumors and its roles in tumor formation and progression are unknown. We hypothesize that disrupted 3D genome folding during embryonic or postnatal development alters gene expression leading to abnormal cell differentiation and tumorigenesis in the developing brain. To test our hypothesis, we will comprehensively interrogate the genomes of pediatric brain tumors for non-coding variants that may affect 3D genome folding. We will use a deep-learning model called Akita that predicts 3D chromatin interaction frequencies from genome sequence alone. Because Akita only requires DNA sequence as input, we can predict the effect of any variant within a single framework that accommodates single-nucleotide variants (SNVs), insertion/deletions (indels), and structural variation (SVs). Akita will be used with pediatric brain whole genome sequences (WGS) from Gabriella Miller Kids First (KF) plus chromatin capture, epigenetic, and expression data from the 4D Nucleome (4DN) and Genotype-Tissue Expression (GTEx) programs in the following aims: 1) Determine the 3D genome architecture of Atypical teratoid/rhabdoid tumor AT/RT tumors. We have initiated our study using AT/RT, tumors thought to be due to defects in early development11 and the most common brain tumor in children less than six months of age. 1.A. We will develop a bioinformatics pipeline that uses Akita to quantify how much a genetic variant is predicted to disrupt 3D chromatin interactions in AT/RT tumors. 1.B. We will validate and determine the functional relevance of 3D genomic folding disruptions observed in AT/RT tumors. 2) Determine the 3D genome architecture of malignant pediatric tumors. We will extend our analyses with Akita to additional malignant pediatric brain tumors, focusing for this pilot project on the most malignant and treatment refractory tumors. This innovative project, using a new deep-learning tool Akita, will lead to, novel research hypotheses and will accelerate the discovery ...