The surface protein composition of extracellular vesicles (EVs) is related to the originating cell and may play a role in vesicle function. Knowledge of the protein content of individual EVs is still limited because of the technical challenges to analyse small vesicles. Here, we introduce a novel multiplex bead-based platform to investigate up to 39 different surface markers in one sample. The combination of capture antibody beads with fluorescently labelled detection antibodies allows the analysis of EVs that carry surface markers recognized by both antibodies. This new method enables an easy screening of surface markers on populations of EVs. By combining different capture and detection antibodies, additional information on relative expression levels and potential vesicle subpopulations is gained. We also established a protocol to visualize individual EVs by stimulated emission depletion (STED) microscopy. Thereby, markers on single EVs can be detected by fluorophore-conjugated antibodies. We used the multiplex platform and STED microscopy to show for the first time that NK cell–derived EVs and platelet-derived EVs are devoid of CD9 or CD81, respectively, and that EVs isolated from activated B cells comprise different EV subpopulations. We speculate that, according to our STED data, tetraspanins might not be homogenously distributed but may mostly appear as clusters on EV subpopulations. Finally, we demonstrate that EV mixtures can be separated by magnetic beads and analysed subsequently with the multiplex platform. Both the multiplex bead-based platform and STED microscopy revealed subpopulations of EVs that have been indistinguishable by most analysis tools used so far. We expect that an in-depth view on EV heterogeneity will contribute to our understanding of different EVs and functions.
Extracellular vesicles (EVs) are specifically loaded with nucleic acids, lipids, and proteins from their parental cell. Therefore, the constitution of EVs reflects the type and status of the originating cell and EVs in melanoma patient’s plasma could be indicative for the tumor. Likewise, EVs might influence tumor progression by regulating immune responses. We performed a broad protein characterization of EVs from plasma of melanoma patients and healthy donors as well as from T cells, B cells, natural killer (NK) cells, monocytes, monocyte-derived dendritic cells (moDCs), and platelets using a multiplex bead-based platform. Using this method, we succeeded in analyzing 58 proteins that were differentially displayed on EVs. Hierarchical clustering of protein intensity patterns grouped EVs according to their originating cell type. The analysis of EVs from stimulated B cells and moDCs revealed the transfer of surface proteins to vesicles depending on the cell status. The protein profiles of plasma vesicles resembled the protein profiles of EVs from platelets, antigen-presenting cells and NK cells as shown by platelet markers, co-stimulatory proteins, and a NK cell subpopulation marker. In comparison to healthy plasma vesicles, melanoma plasma vesicles showed altered signals for platelet markers, indicating a changed vesicle secretion or protein loading of EVs by platelets and a lower CD8 signal that might be associated with a diminished activity of NK cells or T cells. As we hardly detected melanoma-derived vesicles in patient’s plasma, we concluded that blood cells induced the observed differences. In summary, our results question a direct effect of melanoma cells on the composition of EVs in melanoma plasma, but rather argue for an indirect influence of melanoma cells on the vesicle secretion or vesicle protein loading by blood cells.
Fibroblasts are thought to be key players in the tumor microenvironment. Means to identify and isolate fibroblasts as well as an understanding of their cancer-specific features are essential to dissect their role in tumor biology. To date, the identification of cancer-associated fibroblasts is widely based on generic markers for activated fibroblasts in combination with their origin in tumor tissue. This study was focused on a deep characterization of the cell surface marker profile of cancer-associated fibroblasts in widely used mouse tumor models and defining aberrant expression profiles by comparing them to their healthy counterparts. We established a generic workflow to isolate healthy and cancer-associated fibroblasts from solid tissues, thereby reducing bias, and background noise introduced by non-target cells. We identified CD87, CD44, CD49b, CD95, and Ly-6C as cancer-associated fibroblast cell surface markers, while CD39 was identified to mark normal fibroblasts from healthy tissues. In addition, we found a functional association of most cancer-related fibroblast markers to proliferation and a systemic upregulation of CD87, and CD49b in tumor-bearing mice, even in non-affected tissues. These novel markers will facilitate the characterization of fibroblasts and shed further light in their functions and implication in cancer progression.
Natural killer (NK) cells belong to a subgroup of lymphocytes (CD3-CD56+) which play an important role in the cellular immune response against virus-infected cells and tumors. The activity of NK cells is regulated by a balance of triggering and inhibitory receptors, including Killer Ig-like Receptor (KIR) molecules which interact with specific HLA class I molecules, predominantly HLA-C, on target cells. The 17 known KIR genes are divided into two classes: activating KIRs and inhibitory KIRs. There is strong evidence that inhibitory KIR mismatch between donor and recipient improves the outcome of haploidentical hematopoietic stem cell transplantation (HSTC) in leukemia patients (Ruggeri et al. 2002). In addition, the KIR-HLA constellation is assumed to have an influence on the severity of graft versus host disease (GvHD). Whether these activities of NK cells are clinically important and to what extent these processes are mediated only by KIR-HLA class I interactions remains to be determined. In human populations, KIR gene haplotypes vary in the number and type of KIR genes they contain. Further diversification is observed by expanded allelic polymorphism at the individual genes. In general, KIR haplotypes contain 7–12 genes plus 2 pseudogenes. Extra KIR heterogeneity is provided at the expression level: different subsets of NK cells within an individual express different KIRs. Recently, it was shown that KIR genotyping alone does not seem to be sufficient for donor KIR assessment because of the lack of gene expression in approximately one-fourth of the individuals for one of the inhibitory KIRs that recognize the three major groups of MHC class I ligands (Leung et al. 2005). KIR phenotyping by flow cytometry using monoclonal antibodies is insufficient due to the lack of specific monoclonal antibodies. For trustworthy analysis, one has to combine KIR genotyping with mRNA expression profiling and flow cytometry. Therefore, we developed a new set of sequence-specific primers (SSP). This primer set can be applied to perform either KIR genotyping or mRNA expression profiling despite the high degree of identity of the genes (80–90%, sometimes more than 95%). The primers of each KIR gene (15 genes and 2 pseudogenes) cover all allelic variants annotated by the IPD KIR Sequence Data Base (status quo July 05). Using this primer set, we genotyped 25 individuals, and compared the results with other sets of KIR primers published elsewhere. Additionally, we show the mRNA expression profile employing the same set of new primers. We confirmed these results on the protein level by flow cytometry.
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