Background and Aim: Specific tumor biomarkers are useful for the early diagnosis of cancer or can predict the recurrence of neoplastic disease in humans and animals. Lymphoma in dogs could be classified into B-, T-, and NK-cell origins. T-cell lymphoma has the worst prognosis with a shorter survival time and disease-free interval. This study aimed to identify the differential serum protein expressions of canine B-And T-cell lymphomas compared with healthy dogs using a tandem mass tag (TMT)-based quantitative proteomics. Materials and Methods: Serum samples were collected from 20 untreated canine lymphomas (14 B-cells and 6 T-cells) and four healthy control dogs. Sera peptides from each sample were processed for TMT 10-plex tagging and analyzed using liquid chromatography-mass spectrometry (MS). Differential proteome profiling was then compared between lymphoma and control. Results: We discovered 20 elevated and 14 decreased serum proteins in the lymphoma group relative to the healthy group. Six candidate increased proteins in canine lymphomas were beta-Actin cytoplasmic 1 (ACTB, p=0.04), haptoglobin (p=0.002), beta-2 microglobulin (β2M, p=0.007), beta-2 glycoprotein 1 (APOH, p=0.03), metalloproteinase inhibitor 1 (TIMP-1, p=0.03), and CD44 antigen (p=0.02). When compared between B-And T-cell lymphomas, B-cell phenotypes had upregulated immunoglobulin (Ig) heavy chain V region GOM (p=0.02), clusterin (p=0.01), apolipoprotein C1 (APOC1, p=0.05), and plasminogen (p=0.02). Conclusion: These findings were investigated quantitative serum proteomes between B-And T-cell lymphomas using TMT-based MS. ACTB, β2M, APOH, TIMP-1, CD44 antigen, Ig heavy chain V region GOM, and APOC1 are novel candidate proteins and might serve as a lymphoma biomarker in dogs. However, evaluation with an increased sample size is needed to confirm their diagnostic and prognostic ability.
CITATION STYLE
Fonghem, P., Pisitkun, T., Rattanapinyopituk, K., Sirivisoot, S., & Rungsipipat, A. (2022). Investigation of proteomic profiles in canine lymphoma using tandem mass tag-based quantitative proteomics approach. Veterinary World, 15(5), 1333–1340. https://doi.org/10.14202/vetworld.2022.1333-1340
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