Analyses of canine cancer mutations and treatment outcomes using real-world clinico-genomics data of 2119 dogs

This study aims to expand the value of canine models by systematically characterizing genetic mutations in tumors and their response to targeted treatments using artificial intelligence (AI). We collect and analyze survival outcomes for 2119 tumor-bearing dogs and the prognostic effect of genomic alterations in a subset of 1108 dogs, comprising the largest clinico-genomic dataset of canine cancers to date. Our analysis identifies a novel prognostic concordance between canines and humans in several key oncogenes, including TP53 and PIK3CA. We also find that several targeted treatments designed for humans are associated with a positive prognosis when used to treat canine tumors with specific genomic alterations, underscoring the value of canine models in advancing drug discovery for personalized oncology.