Introduction

Canine cancer genomic biomarker data is increasingly abundant, but remains challenging to access, interpret, and integrate into research or clinical practice. Our objective has been to construct a canine cancer genomic biomarker database through systematic review, meta-analysis, and harmonization of cancer mutation data from canine and human sources.

Methods

Primary canine papers describing cancer genomics and mutations were retrieved through structured searches from public sources, filtered for relevance, and curated to capture mutation-level evidence including mutation annotation (harmonized to CanFam 3.1 and Ensembl v99), evidence type and evidence summary. Human oncology drug biomarkers were curated from literature and databases and were “caninized” using a comparative genomic translator tool. A MySQL relational database was constructed to store and interlink queryable mutation annotations and biomarker associations.

Results

Of thousands of canine papers initially retrieved, ~500 (1983–2021) described diagnostic, prognostic, or predictive relationships of mutations, gene/protein expression, and/or epigenetic changes. One hundred and forty papers describing mutation-based associations were exhaustively curated, yielding over 1000 biomarker associations from >5000 dogs across 42 tumor types. Inference from human databases and more than 400 human oncology publications yielded >800 “caninized” biomarker associations. These biomarker data are now queryable in a relational biomarker database called Vidium Insight that is routinely updated as new data is published.

Conclusion

Clinically relevant genomic biomarkers are abundant in primary canine literature and inferred human data. Systematic consumption of this growing data within a harmonized relational database forms a foundation empowering the use of genomics in canine cancer research, clinical diagnostics, and drug development.

Funding Information

These studies were funded by Vidium Animal Health.