Canine Tumor Registry Expands Understanding of Cancer Risk

A collaborative team from the University of Liverpool’s Veterinary Data Science Group and the University of Las Palmas de Gran Canaria has developed a large open-source database of canine tumors. Containing over one million records, this extensive dataset provides a new foundation for investigating how factors such as breed, genetics, and neutering practices may influence cancer risk in dogs.

The resource was built through a combination of expertise in veterinary pathology, data science, epidemiology, and clinical practice. By working closely with diagnostic laboratories and employing advanced data extraction and standardization methods, the researchers created a unified collection of diagnostic information that was previously scattered across private systems. This integration, achieved through the Small Animal Veterinary Surveillance Network (SAVSNET), allows consistent and meaningful analysis of trends in pet cancer.

According to David Killick, senior author on the study published in Veterinary and Comparative Oncology, “It is important to understand risks for cancers—and this applies to pets too. But for dogs and cats, most cancer diagnosis data sit in private veterinary labs, inaccessible for research. Working through SAVSNET, we wanted to see whether we could bring together large volumes of these data into one meaningful, research-ready database.”

“This tumor registry is a major step toward better understanding cancer risk in pets. In addition to allowing better identification of breed related risk of specific tumor types, early analyses have raised the question of how neutering practices may influence risks of particular cancers. The scale of the data also opens new possibilities for exploring the genetic basis of these cancers.”

The registry includes data from more than 200 breeds and over 150 types of tumors, creating opportunities to study rare cancers and less common breeds in depth. According to first author Jose Rodríguez Torres, “Analyzing cancer diagnoses is well established in human medicine, but similar work in animals has lagged behind due to fragmented data. This study is a leading step forward. With more than 200 breeds and more than 150 tumor types represented, these data can now be explored by researchers worldwide to better understand cancer risk across many tumor–breed combinations.”

A publicly available summary of the data enables veterinarians, researchers, and owners to explore patterns of tumor risk more clearly.