NCI Data Jamboree (Project Abstract Submission): Submission #63

Abstract Osteosarcoma is a genetically complex malignancy. While human and canine osteosarcomas share significant molecular similarities, integrating datasets across species and sequencing platforms remains a technical challenge. Overcoming these hurdles is crucial for identifying conserved oncological targets and improving the AI-readiness of comparative genomic data for the broader research community. We aim to develop and validate a robust computational framework for cross-species data integration, specifically focusing on continuous signature scoring models for human and canine osteosarcoma. By utilizing publicly available human osteosarcoma datasets (such as TARGET-OS) and public canine cohorts (such as NCI's DOG² cohort), we will employ expression data scaling techniques, cross-platform normalization, and continuous signature scoring algorithms to harmonize the disparate matrices. Ultimately, we aim to leverage these validated models to develop a cross-species risk assessment application to support clinical decision-making.