Exploring the dynamics of Programmed Death-Ligand 1 in canine lymphoma: unraveling mRNA amount, surface membrane expression and plasmatic levels.

Introduction: Programmed Death-Ligand 1 is a well-known immune checkpoint molecule. Recent studies evaluated its expression in different canine cancer types through different laboratory techniques. The present study aims to evaluate the surface membrane protein expression (mPD-L1) by means of flow cytometry (FC) in different canine lymphoma immunophenotypes. Furthermore, in a subset of cases, mRNA and plasmatic soluble protein (sPD-L1) have been assessed in the same patient, and correlations among results from the three analyses investigated. Methods: Samples obtained for diagnostic purpose from untreated dogs with a confirmed lymphoma immunophenotype were included: surface protein was assessed via FC and quantified with median fluorescence index ratio (MFI ratio), gene expression was evaluated by real time quantitative polymerase chain reaction (RT-qPCR) and plasmatic concentration of soluble protein (sPD-L1) measured with ELISA. Statistical analyses were performed to investigate any difference among FC immunophenotypes, updated Kiel cytological classes, and in the presence of blood infiltration. Results: Considering FC, most B-cell lymphomas (BCL) were positive, with higher MFI ratios than other subtypes (81%, median MFI ratio among positive samples = 1.50, IQR 1.21-2.03, range 1.01-3.47). Aggressive T-cell lymphomas had a lower percentage of positive samples (56%) and showed low expression (median MFI ratio in positive samples = 1.14, IQR 1.07-1.32, range 1.02-2.19), while T-zone lymphomas (TZL) were frequently positive (80%) but with low expression (median MFI ratio in positive samples = 1.19, IQR 1.03-1.46, range 1.02-6.03). Cellular transcript and sPD-L1 were detected in all samples, without differences among immunophenotypes. No correlation between results from different techniques was detected, but sPD-L1 resulted significantly increased in FC-negative lymphomas (p = 0.023). Discussion: PD-L1 molecule is involved in canine lymphoma pathogenesis, with differences among immunophenotypes detected by FC. Specifically, BCL have the highest expression and aggressive T-cell lymphomas the lowest, whereas TZL need further investigations.

Flow Cytometric Features of B- and T-Lmphocytes in Reactive Lymph Nodes Compared to Their Neoplastic Counterparts in Dogs.

An in-depth knowledge of non-neoplastic patterns is fundamental to diagnose neoplasia. In the present study, we described the flow cytometric (FC) cell size (FSC) and fluorescence intensity (MFI) of B- and T-lymphocytes in 42 canine reactive lymph nodes and 36 lymphomas. Proliferative activity (Ki67%) in reactive lymph nodes was also reported. Reactive lymph nodes were composed of a mixed population of small and large T (CD5+) and B (CD21+) cells. Small T-cells were larger in size than small B-cells, and large T-cells were larger than large B-cells. Small T-cells were composed of CD5+CD21- and CD5+CD21+dim subpopulations. Large B-cells were <20% in reactive lymph nodes and >20% in lymphomas and showed a higher FSC in lymphomas than in reactive lymph nodes. Large T-cells were <4% in reactive lymph nodes and >4% in lymphomas and showed a higher CD5 MFI in lymphomas (if expressed) compared to reactive lymph nodes. A subset of CD5+CD21+dim lymphocytes was recognized in addition to CD5+CD21- and CD5-CD21+ cells. In T-zone lymphomas, neoplastic cells had higher FSC and CD21 MFI values than small CD5+CD21+dim cells in reactive lymph nodes. Ki67% values were higher than those reported in normal lymph nodes, and largely overlapped with those reported in low-grade lymphomas and partially in high-grade lymphomas. Our results may contribute to making a less operator-dependent FC differential between lymphoma and reactive lymph nodes.

A method to test antibody cross-reactivity toward animal antigens for flow cytometry.

The availability of cross-reacting antibodies and/or of antibodies working in flow cytometry is a major issue in the veterinary field. One of the main problems is the availability of certain positive controls. With this brief communication, we report an method to quickly screen a wide number of products without the need to look for positive biological samples. We propose this approach as a first step to select the best antibodies to test on biological specimens.