Introduction

Canine cancer genome sequencing studies are unearthing new candidate diagnostic, prognostic, and predictive biomarkers. Development and rigorous validation of genomic diagnostics is thus increasingly important for enabling new biomarkers to be confidently leveraged in research and the clinic.

Methods

We have designed a next-generation sequencing, hybrid-capture, canine gene panel covering 482,000 base pairs of 120 genes associated with canine or human cancer. We are performing analytical validation via reproducibility (inter-batch, -instrument, and -operator), sensitivity (limit-of-detection and limit-of-blank), specificity (interfering substances, probe specificity, cross-contamination), and concordance (cross-platform and -tissue, positive/negative percent agreement) testing. We are also constructing and validating a cloud-based bioinformatic pipeline utilizing truthset and cross-platform genomic data for confident calling of single nucleotide variants, copy number variants, and internal tandem duplications in tumor cells from fine needle aspirates and formalin fixed paraffin embedded tissue.

We are determining diagnostic yield in >200 tumor, tissue, and breed types. Candidate somatic, pathogenic mutations are annotated with diagnostic, prognostic, and predictive associations based on a “knowledgebase” comprising 1,680 biomarker associations curated through natural language and manual processing of 272 canine publications in addition to inference via translated protein alignments and conservation scoring from the Catalogue of Somatic Mutations in Cancer (COSMIC) and from curation of 394 human publications (in the Clinical Interpretation of Variants in Cancer database, CIViC).

Results

Data to be presented.

Conclusion

We have developed a sensitive and specific gene sequencing panel capable of detecting candidate biomarkers in a wide range of canine cancer and tissue types.

Funding Information

These studies have been funded by Vidium Animal Health, a subsidiary of the Translational Genomics Research Institute (TGen).