Background
Animal cancer registries have emerged sporadically since the 1950s, yet most initiatives have lacked long-term sustainability, international standardization, and integration into global cancer surveillance systems. In contrast to human oncology—where population-based registries underpin global monitoring through systems such as GLOBOCAN—animal cancer data remain fragmented and largely underutilized. This gap persists despite compelling evidence that animals, particularly companion animals, share human environments and are exposed to the same complex mixtures of environmental risk factors, including contaminated food and water, outdoor and indoor air pollution, pesticides, and household chemicals. Due to their shorter lifespans and accelerated disease latency, cancer in animals frequently develops earlier than in humans living in the same environments, positioning them as sensitive sentinels for environmentally driven and potentially modifiable cancer risks. In addition, spontaneous tumours in animals represent a unique and underexploited resource for comparative and translational oncology, offering real-world biological models across shared environments.
Objectives
The Global Initiative for Veterinary Cancer Surveillance (GIVCS), funded by the National Council for Scientific and Technological Development, CNPq (Brazil), aims to establish the Global Initiative for Animal Cancer Registries (GIACR): the first AI-powered, open-access, and internationally interoperable platform for animal cancer surveillance. The initiative seeks to standardize and harmonize animal cancer data collection worldwide, enable direct comparison with human cancer distributions, support comparative and translational oncology research, and strengthen cancer surveillance within a One Health framework, particularly in countries lacking structured registries or trained cancer registry professionals.
Methods
Building on prior GIVCS developments, including Vet-ICD-O, a veterinary-adapted tumour classification system explicitly designed for comparability with the human ICD-O, the platform enables harmonized coding of spontaneous animal tumours across species. Artificial intelligence algorithms support automated tumour coding, diagnosis classification, data harmonization, and quality control, reducing manual workload and enhancing interoperability across heterogeneous data sources. The system architecture is inspired by IARC’s CanReg5 software and enables structured data submission from veterinary diagnostic laboratories, academic institutions, and national or regional registries, facilitating ecological and comparative analyses of cancer patterns across species and shared environments.
Results
The registry infrastructure is fully developed and currently in the implementation phase with structured local datasets. The project is progressing toward international testing, utilizing pilot data from multiple countries to validate interoperability, data quality, and cross-country harmonization. Once fully operational, the platform will generate standardized epidemiological reports and interactive dashboards that describe cancer distribution by species, tumor type, geography, and time. These outputs will support comparative analyses between animal and human cancer patterns and enable ecological studies aimed at identifying shared environmental cancer risks across populations and regions.
Conclusions
Establishing a global animal cancer registry advances cancer surveillance, comparative oncology, and One Health policy by recognising animals as sentinels of environmental cancer risk, providing an early-warning system to support preventive, evidence-based environmental and public health decision-making.
Funding: National Council for Scientific and Technological Development, CNPq, Brazil, Process number 444552/2024-3