Detection of genetic abnormalities in clinical tumor samples allows for increased diagnostic precision and improved prognosis assessment. We analyze high-resolution genetic data to identify genomic imbalances, structural variations, and mutations at the nucleotide level. The current project will contribute to increased knowledge of mechanisms behind osteosarcoma development. More specifically, we will screen for SNVs, indels, and SV such as already reported and novel gene fusions. We have gained access to two large osteosarcoma datasets that will be used to validate our recent findings in osteosarcoma (https://10.1002/path.6219 and https://10.1016/j.labinv.2023.100283). These data suggest that osteosarcoma is a biologically and genetically heterogeneous disease. In children and adolescents, structural variants affecting the TP53 are a common phenomenon. These result in the creation of TP53 promoter gene fusions and are associated with a highly rearranged genome. Cases with few genetic alterations and/or affecting adults instead display other types of gene fusions or SNVs underlying tumor development. Handling of personal data (which genetic data is) takes place in accordance with the EU General Data Protection Regulation (GDPR). The study has been reviewed and approved by the Swedish Ethics Review Authority (Dnr 2023-01550-01).