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How Sugar Molecules on Dog Antibodies Could Reveal Clues About Lymphoma

Principal Investigator: Sarah Caddy

Baker Institute for Animal Health
Sponsor: American Kennel Club Canine Health Foundation
Grant Number: 03565-A
Title: How Sugar Molecules on Dog Antibodies Could Reveal Clues About Lymphoma
Project Amount: $30,000
Project Period: December 2025 to November 2026

DESCRIPTION (provided by applicant):

Canine B cell lymphoma is the most common hematologic cancer in dogs, yet its immunological features remain poorly understood. A deeper understanding of immune regulation in this disease could reveal new diagnostic or prognostic markers. One important and understudied aspect of immune function is antibody glycosylation, the attachment of complex sugars (glycans) to antibodies, which influences antigen recognition and immune activation. In humans, abnormal antibody glycosylation on B cells has been linked to more aggressive lymphoma subtypes. However, similar studies have not yet been conducted in dogs.


This project aims to investigate whether antibody glycosylation is altered in dogs with B cell lymphoma and how these patterns differ from healthy dogs. We have developed sensitive techniques, including mass spectrometry and novel lectin-based ELISAs, to profile glycan structures on canine antibodies. Our study will prospectively recruit dogs diagnosed with lymphoma at Cornell University Hospital for Animals, alongside age-matched healthy controls. Residual clinical samples will be used to identify and quantify glycans on antibodies on the surface of B cells and antibodies in circulation. Statistical analysis will identify any glycan signatures associated with lymphoma status.


This pilot study will provide the first baseline characterization of antibody glycosylation in canine B cell lymphoma. Findings will inform future studies exploring whether specific glycan patterns correlate with poorer prognosis, as in humans. By identifying relevant glycosylation changes, this work has the potential to lay the foundation for improved prognostic biomarkers and disease stratification to greatly enhance clinical decision-making.