Objectives: To elucidate the potential role of CD3+CD56+ NKT-like cells in the pathogenesis of primary Sjögren's syndrome (pSS).
Methods: We enrolled pSS patients and healthy controls and examined the peripheral population, the surface chemokine receptors and the proinflammatory cytokine production of NKT-like cells by flow cytometry. The infiltration of NKT-like cells in the labial salivary gland (LSG) was examined by immunofluorescence. Serum and tissue levels of CX3CL1 were detected by Cytometric Bead Array and immunohistochemistry, respectively. The chemotaxis of NKT-like cells was examined by transwell migration assay.
Results: Peripheral NKT-like cells from pSS patients were significantly lower than those from HC (3.09±2.35% vs. 5.37±4.06%, p=0.0002), which was negatively correlated with European League Against Rheumatism Sjögren's Syndrome Disease Activity index. NKT-like cells infiltrated into the LSG of pSS patients. Serum and LSG epithelial CX3CL1 levels were higher in pSS patients than those in HC, which promoted the chemotaxis of the NKT-like cells. NKT-like cells from pSS patients expressed a higher level of CD69, and secreted high level of TNF-α and IFN-γ, which was promoted by CX3CL1 in vitro.
Conclusions: NKT-like cells decreased in peripheral and infiltrated into the LSG of the pSS patients, which could be driven by CX3CL1-CX3CR1 axis. NKT-like cells might be implicated in the pathogenesis of pSS.
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http://dx.doi.org/10.55563/clinexprheumatol/uzzz6d | DOI Listing |
Front Immunol
December 2024
Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy.
Background: The phosphodiesterase 4 (PDE4) inhibitor apremilast downregulates the production of IL-23 and other pro-inflammatory cytokines involved in the pathogenesis of psoriatic arthritis (PsA).
Aim: To investigate the effects of apremilast on the production of cytokines by peripheral blood monocyte-derived macrophages, innate-like lymphocyte cells (ILCs), mucosal-associated invariant T (MAIT) cells, γδ T cells, natural killer (NK) cells, and NKT-like cells from patients with PsA manifesting different clinical responses to the treatment.
Methods: Peripheral blood samples were obtained from patients with PsA at baseline and after 1 and 4 months of apremilast therapy (n = 23) and 20 controls with osteoarthritis.
JTO Clin Res Rep
January 2025
Department of Internal Medicine (Division of Hematology-Oncology), University of Texas Southwestern Medical Center, Dallas, Texas.
Introduction: Racial and ethnic disparities in the presentation and outcomes of lung cancer are widely known. To evaluate potential factors contributing to these observations, we measured systemic immune parameters in Black and White patients with lung cancer.
Methods: Patients scheduled to receive cancer immunotherapy were enrolled in a multi-institutional prospective biospecimen collection registry.
Cancers (Basel)
November 2024
Department of Experimental Immunology, Medical University of Lublin, 4a Chodźki Street, 20-093 Lublin, Poland.
: The aim of this study was to determine the assessment of the percentage of NK and NKT-like cells expressing Toll-like receptors (TLR-2, TLR-3, TLR-4, and TLR-9) in patients with gastric cancer (GC) compared with healthy volunteers (HV) and to investigate differences according to cancer subtype. We also assessed TLR gene expression by RT-qPCR to assess whether TLRs could be diagnostic and prognostic biomarkers. : The study included 86 patients with histologically confirmed gastric cancer and 30 healthy volunteers.
View Article and Find Full Text PDFCytometry A
November 2024
Cytek Biosciences, Inc., Scientific Commercialization, Fremont, California, USA.
The need for more in-depth exploration of the human immune system has moved the flow cytometry field forward with advances in instrumentation, reagent development and availability, and user-friendly implementation of data analysis methods. We developed a high-quality human 45-color panel, for comprehensive characterization of major cell lineages present in circulation including T cells, γδ T cells, NKT-like cells, B cells, NK cells, monocytes, basophils, dendritic cells, and ILCs. Assay optimization steps are described in detail to ensure that each marker in the panel was optimally resolved.
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