Translationally relevant animal models are essential for the successful translation of basic science findings into clinical medicine. While rodent models are widely accessible, there are numerous limitations that prevent the extrapolation of findings to human medicine. One approach to overcome these limitations is to use animal models that are genetically diverse and naturally develop disease. For example, pet dogs spontaneously develop diseases that recapitulate the natural progression seen in humans and live in similar environments alongside humans. Thus, dogs represent a useful animal model for many areas of research. Despite the value of the canine model, species specific reagent limitations have hampered in depth characterization of canine immune cells, which constrains the conclusions that can be drawn from canine immunotherapy studies. To address this need, we used single-cell RNA sequencing to characterize the heterogeneity of circulating leukocytes in healthy dogs (n = 7) and osteosarcoma (OS) affected dogs (n = 10). We present a cellular atlas of leukocytes in healthy dogs, then employ the dataset to investigate the impact of primary OS tumors on the transcriptome of circulating leukocytes. We identified 36 unique cell populations amongst dog circulating leukocytes, with a remarkable amount of heterogeneity in CD4 T cell subtypes. In our comparison of healthy dogs and dogs with OS, we identified relative increases in the abundances of polymorphonuclear (PMN-) and monocytic (M-) myeloid-derived suppressor cells (MDSCs), as well as aberrations in gene expression within myeloid cells. Overall, this study provides a detailed atlas of canine leukocytes and investigates how the presence of osteosarcoma alters the transcriptional profiles of circulating immune cells.
CITATION STYLE
Ammons, D. T., Harris, R. A., Hopkins, L. S., Kurihara, J., Weishaar, K., & Dow, S. (2023). A single-cell RNA sequencing atlas of circulating leukocytes from healthy and osteosarcoma affected dogs. Frontiers in Immunology, 14. https://doi.org/10.3389/fimmu.2023.1162700
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