Atherosclerosis, a chronic inflammatory disease of the arterial wall, is driven by dysregulated immune responses. Dendritic cells (DCs), as central orchestrators of innate and adaptive immunity, accumulate in atherosclerotic lesions and critically influence disease progression through their roles in lipid metabolism, antigen presentation, and cytokine signaling. Recent advances in single-cell omics and genetic lineage tracing have unveiled the functional diversity of DC subsets, including conventional DCs (cDC1, cDC2), plasmacytoid DCs (pDCs), and monocyte-derived DCs (Mo-DCs), in shaping plaque inflammation, immune tolerance, and tissue repair. However, the mechanisms underlying DC heterogeneity, recruitment, and crosstalk with other immune and vascular cells remain incompletely understood. This review summarizes current knowledge on DC ontogeny, subset-specific functions, and their interplay with T cells, B cells, endothelial cells (ECs), and smooth muscle cells in Atherosclerosis. We also critically evaluate transgenic models for DC research and emerging DC-targeted therapies, including tolerogenic vaccines and nanoparticle-based strategies. Unresolved questions about spatial distribution, functional duality, and ontogenetic pathways are discussed to guide future investigations.
Oral squamous cell carcinoma (OSCC) is a malignant epithelial neoplasm characterized by high aggressiveness and limited options for early diagnosis. In recent years, extracellular vesicles (EVs) have gained attention as mediators of intercellular communication in cancer, contributing to tumor progression and remodeling of the microenvironment. O-GlcNAcylation, regulated by O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA), participates in multiple tumor processes; however, its association with EVs in OSCC has not yet been explored. In this study, EVs were isolated from SCC-152, SCC-25, and HaCaT cell lines using differential centrifugation, and their identity was confirmed by detection of CD63 and TSG101 markers and by transmission electron microscopy (TEM). Immunocytochemistry revealed the nuclear and cytoplasmic localization of OGT and OGA in all analyzed cell lines. Importantly, both enzymes were detected in EVs cargo by Western blot analysis, with significant differences between tumor and non-tumor lines as determined by densitometric and fluorescence intensity analyses. Quantitative analysis indicated a higher relative signal for OGA compared with OGT across all cell lines (with an approximate ~1.5–2.2-fold difference depending on the cell line, p < 0.05), and cell line-derived samples showed a higher relative signal than non-tumoral HaCaT (corresponding to an approximate ~1.2–1.3-fold increase under the experimental conditions evaluated). All experiments were performed using three independent biological replicates (n = 3), and statistical significance was assessed using one-way or two-way ANOVA followed by Tukey’s post hoc test. These findings suggest that OSCC-derived EVs carry enzymatic components of the O-GlcNAcylation machinery as vesicular protein cargo, potentially influencing tumor microenvironment regulation and cancer progression. Overall, these results should be considered hypothesis-generating, opening new perspectives for their use as vesicular biomarkers.
Extracellular vesicles (EVs) are molecularly very heterogeneous, and their characterization at the single-particle level is technically challenging. Existing approaches, such as nanoparticle tracking analysis, fluorescence microscopy, and nano-flow cytometry, provide important insights but often lack the flexibility to detect multiple molecular markers simultaneously. Here, we describe an optimized workflow for multiparametric EV phenotyping using a spectral flow cytometry instrument with enhanced small particle detection capacity. EVs were isolated from murine melanoma and melanocyte cell lines via size-exclusion chromatography and labeled with a fluorogenic membrane probe that enables robust, single EV detection. In this study, we systematically optimized staining conditions, EV concentrations, and fluorophore combinations for a 5-color antibody panel on single EVs. We show that single-particle flow cytometry can reliably detect and resolve multiple EV surface markers simultaneously. Data analysis by unsupervised clustering further enabled unbiased identification of distinct EV subsets, providing a practical approach for EV phenotyping in both research and clinical contexts.
Despite significant progress in immune checkpoint inhibitors (ICIs) and targeted therapies, non-small cell lung cancer (NSCLC) continues to be associated with high rates of primary and acquired resistance. Although PD-1/PD-L1 blockade has revolutionized treatment, its clinical development has largely followed a one-size-fits-all approach, relying on limited biomarkers such as PD-L1 expression or tumor mutational burden. It is now increasingly clear that immune escape in NSCLC is orchestrated by a multifaceted, multilayered network of both tumor-intrinsic alterations and TME (tumor microenvironment)–driven mechanisms. The challenge has been to understand and to therapeutically exploit these immune escape pathways and this knowledge is now needed so that rather than embark on empirical combinations we can advance to rational, immune-informed targeted therapies.
