Figure 1

The last decade has witnessed the generation of a large volume of canine cancer genomic data. An increasing variety of novel next generation sequencing approaches are being used to analyze the canine tumor genome, ranging from small-targeted panels to broader whole genome-based and multi-platform approaches. This unprecedented growth has spurred the evolution of precision-medicine based research initiatives in veterinary oncology, expanding opportunities for integration of genomic data into hypothesis-driven clinical studies.

Concomitant with this fundamental shift to incorporate genomic data into clinical research, is a growing effort to address persistent challenges that hinder clinical translation of these complex datasets. Continued integration of data infrastructure and analytical tools in response to evolving research paradigms is providing a framework to support continued comparative and translational cancer genomics. This is particularly significant as the importance of studying complex genetic aberrations in the context of the disease and local tumor microenvironment is well-recognized.

The goal of this presentation is to explore the foundational elements that support genomics research initiatives, and how existing paradigms are evolving to support translation of these datasets into clinical studies. Additionally, we will discuss some of the common challenges encountered when analyzing canine cancer genomic datasets and explore emerging opportunities to harness novel technologies in veterinary cancer research to further our understanding of disease biology.