Integrated Multiomic Profiling Enhances Risk Stratification and Prognostication in Canine Osteosarcoma

Standardized treatment regimens prescribed to both species do not address the complexity of the disease and thus have resulted in stagnant patient outcomes for more than 30 years. Here we present the first multiomic dataset created from a large outcome-linked biobank of canine OS treatment-naïve primary tumors utilizing a computational framework designed to interrogate each dataset individually, and to compare and integrate findings.

This work demonstrates the presence of MYC amplification as a poor prognostic indicator and as well as alterations in DNA damage repair, metabolism, and cell cycle genes that are shared with humans. Further, we show relationships between the local tumor immune microenvironment, TP53 mutations, MYC status and global gene methylation patterns that further highlight the complexity of the disease and provide new insight into the utility of prognostic biomarkers and potential druggable targets for future study.