We investigate somatic mutation patterns in canine tumors using bioinformatics methods, contributing to the growing field of comparative oncology research.
Helix Comparative is a bioinformatics research group based in San Juan, Puerto Rico. We study computational methods for analyzing somatic mutations in canine cancers, with the goal of contributing to the broader field of comparative oncology.
Our work focuses on understanding how existing bioinformatics algorithms and publicly available databases can be applied to canine tumor genomic data. We study the compatibility of different sequencing data formats, evaluate neoantigen prediction methodologies, and investigate how computational approaches to cancer genomics translate across species.
We believe that advancing computational methods for veterinary oncology creates opportunities for both animal health and translational insights relevant to human cancer research.
Comparative oncology is a growing field that studies naturally occurring cancers in animals — especially dogs — to gain insights that benefit both veterinary and human medicine.
Dogs develop many of the same cancer types as humans — lymphoma, melanoma, osteosarcoma, and more. These cancers arise spontaneously, just like in people, making them valuable for understanding how cancer works across species.
The canine and human genomes share approximately 94% of their DNA. Many of the genes involved in cancer — TP53, BRAF, KIT, and others — are remarkably similar between the two species, which means discoveries in one can inform the other.
Research in canine oncology helps accelerate breakthroughs for humans while also improving treatment options for our pets. Clinical trials in veterinary medicine can provide insights in 1–2 years versus 5–10 years in human trials.
Just as genomic testing has transformed human oncology, next-generation sequencing is now being used to profile tumors in dogs — identifying specific mutations that can guide treatment decisions and open doors to precision medicine for pets.
Modern cancer genomics generates massive amounts of data. Bioinformatics — the use of computational methods to analyze biological data — is essential for turning raw sequencing output into meaningful insights about a tumor's biology.
Helix Comparative contributes to this field by developing and testing computational methods for analyzing canine cancer genomic data. Our goal is to help advance the tools and approaches that make comparative oncology research more accessible.
We welcome inquiries from researchers, academic institutions, and laboratories working in canine genomics or comparative oncology.