Integrative Copy-Number and Dependency Mapping in Canine High-Grade Nodal Lymphoma Identifies Candidates for Targeted Therapy.

High-grade nodal lymphomas (HGNL) in dogs are aggressive malignancies and important comparative models for human non-Hodgkin lymphoma; however, their copy-number architecture remains incompletely defined. This study applied high-density SNP arrays optimized for FFPE DNA to 90 canine HGNLs (77 B-cell [BCL], 13 T-cell [TCL]) to map genome-wide copy-number alterations (CNAs) and recurrent copy-number altered regions (CNARs), and to integrate them with candidate gene drivers and potential therapeutic targets. Across immunophenotypes, CNAs were dominated by gains on CFA13, syntenic to human 8q24 and encompassing MYC and additional oncogenes, supporting conserved MYC-driven programs in aggressive lymphoma. BCLs displayed a markedly higher CNA burden and broader CNAR genome coverage (~24%) than TCLs (6.8%); TCL CNARs were fewer and shorter, suggesting reliance on a limited set of highly impactful lesions rather than widespread chromosomal instability. CNAR analysis demonstrated distinct genomic divergence between BCLs and TCLs with minimal regional overlap. The underrepresentation of deletion events likely reflects reduced sensitivity for detecting losses in FFPE-derived DNA rather than a purely biological absence. Integration of CNAR genes with human DepMap dependency data and DGIdb identified eight druggable genes linked to 17 antineoplastic agents, nominating both repurposable drugs already used in canine lymphoma and new candidates (e.g., proteasome and HDAC inhibitors, pathway modulators) for biomarker-guided trials. These findings define distinct yet partially convergent copy-number architectures in canine B- and T-cell HGNL, refine the catalogue of recurrent lesions, and uncover actionable genomic alterations with cross-species therapeutic relevance. These exploratory findings require validation in larger, multicenter cohorts using orthogonal methods before they can support translational applications.