Flow cytometry and clonality evaluation are effective for characterizing feline lymphoma

Photo: Kristina Blokhin/Adobe Stock

Recent research has determined flow cytometry and clonality evaluation as a reliable method for characterizing feline lymphomas. Lymphoma is one of the most prevalent cancers in cats, with almost 30% of all feline cancers being lymphoma cases.¹ Moreover, the size of neoplastic cells is a key factor in determining prognosis, with survival time being dependent on cell size, the study found.² This new cell-sizing method will help provide prognostic insights and affect treatment decisions, according to a news release.¹

Flow cytometry is a technique used for rapidly analyzing multiple parameters of single cells suspended in a solution. It uses lasers to generate scattered and fluorescent light signals, which are read by detectors such as photodiodes or photomultiplier tubes. These light signals are then converted into electronic signals, analyzed by a computer, and written to a standardized data file format (.fcs). Cell populations can be analyzed and/or purified based on their light scattering and fluorescent properties, according to literature on flow cytometry.³ Flow cytometry is commonly used to identify and characterize lymphomas in dogs and humans. Yet, its use in cats has scarcely been explored.¹

For the study, researchers explored the usefulness of flow cytometry and clonality analysis via polymerase chain reaction (PCR) for antigen receptor rearrangement (PARR) for characterizing feline lymphoma and predicting prognosis. They analyzed fine needle aspirates and/or blood samples from 438 feline patients using flow cytometry and PARR, and compared a subset of results from patients with confirmed B- or T-cell lymphomas to cytological or histological evaluations. The most optimal set of flow cytometry parameters, principally forward scatter thresholds, were identified to improve cell size categorization.^1,2

The flow cytometry and clonality evaluation method proved to be 82% concordant with the gold standard of cytology. Specifically, this method exhibited 82% concordance with cytological measurements in a training set and 90% concordance in an independent test set.^1,2

Further research involving more patients revealed notable differences in survival rates. Cats with small-cell lymphomas had the longest survival, with a median of 312 days. Meanwhile, those with medium-cell lymphomas had a median survival time of 189 days. Cats with large-cell lymphomas had the shortest survival of a median of 81 days. The lymphoma subtypes identified through flow cytometry and PARR showed significant variations in survival, highlighting the method’s potential for prognostic assessment.^1,2

“The proposed methodology achieves high concordance with cytological evaluations and provides an additional tool for the characterization and management of feline lymphoproliferative diseases,” the authors wrote.²

The study was conducted by ImpriMed, a precision medicine startup that uses artificial intelligence (AI) in cancer treatments. The company announced an upcoming study on AI-powered prognostication for feline lymphoma that seeks to advance predictive analytics for individualized treatment plans for patients. This recent study establishes a foundation for the forthcoming study, according to a news release.

"We are thrilled to share our breakthrough findings with the veterinary community," Sungwon Lim, ImpriMed’s CEO and co-founder, said in the release.¹ "Our innovative cell-sizing method is a significant advancement in the fight against feline lymphomas, equipping veterinarians nationwide with enhanced tools for accurate diagnosis and effective treatment of this challenging disease.”

References

1. ImpriMed unveils groundbreaking cell-sizing method for high-accuracy feline lymphoma characterization in Veterinary Sciences. News release. ImpriMed. August 12, 2024. Accessed August 12, 2024. [email]
2. Kapoor S, Sen S, Tsang J, et al. Prognostic utility of the flow cytometry and clonality analysis results for feline lymphomas. Veterinary Sciences. 2024;11(8):331. https://doi.org/10.3390/vetsci11080331
3. McKinnon KM. Flow cytometry: An overview. Current Protocols in Immunology. 2018;120(1). 10.1002/cpim.40