Deep proteome profiling of mature and reticulated platelets in patients with chronic coronary syndrome using mass cytometry. (10th June 2022)

• Record Type: Journal Article
• Authors: Klug, M; Bernett, J; Manz, Q; Arend, L; Han, J; Kirmes, K; Lazareva, O; Rosenbaum, M; Ruland, J; Laugwitz, KL; List, M; Bernlochner, MI; Bongiovanni, D
• Is Part Of: Cardiovascular research. Volume 118(2022)Supplement 1
• Publication Date: 2022-06-10
• Subjects: Cardiovascular system -- Diseases -- Periodicals; Cardiovascular system -- Periodicals; 616.1
• DOI: 10.1093/cvr/cvac066.167
• Languages: English
• ISSNs: 0008-6363

Abstract

Abstract: Funding Acknowledgements: Type of funding sources: Public grant(s) – National budget only. Main funding source(s): This work was supported by the German Center for Cardiovascular Research (DZHK grant number Deutsches Zentrum für Herz- Kreislaufforschung 81 × 3600606 to D.B.). Abstract: Background/Introduction: Reticulated platelets (RPs) are prothrombotic RNA-rich platelets suggested to be detrimental in patients with chronic coronary syndrome (CCS) and high on treatment platelet reactivity. In addition, circulating RPs levels are independent predictor for adverse cardiovascular events in CCS patients and other pathological settings. However, RPs biology still need to be investigated. Purpose: We thought to investigate the RPs proteome on single-cell level at rest and after activation using time-of-flight mass cytometry (CyTOF). Method: Thrombocytes from peripheral blood of 11 CCS patients were isolated, prepared for CyTOF and stained with a custom-made CyTOF-antibody panel of 20 antibodies targeting important transmembrane proteins (anti-CD9, anti-CD29, anti-CD31, anti-CD36-, anti-CD40, anti-CD41, anti-CD42a, anti-CD42b-, anti-CD47, anti-CD61, anti-CD62P-, anti-CD63, anti-CD69, anti-CD107a, anti-CD154, anti-GPVI, anti-GPIIbIIa complex, anti-Par1, anti-PEAR-1 and the negative control anti-CD3 coupled with different metal isotopes). Two samples were prepared from each patient: one baseline sample (non-stimulated platelets) and one sample stimulated with 10 μM thrombin receptor-activating peptide (TRAP). According to previous experiences and common practice, we detected RPs and mature platelets (MPs) based on their RNA content. We analyzed the results with a custom bioinformatic pipeline comparing RPs to MPs expression. Earth mover's distance (EMD) was assed as a measure of differential expression. Results: While our bioinformatic analysis revealed that all transmembrane markers are significantly higher expressed in the larger RPs compared to MPs, not all markers differ to the same extend. Interestingly, the four markers with the highest calculated EMD (values in brackets) are all key regulators of platelet activation and aggregation: the collagen receptor GPVI (34.18), the collagen integrin receptor unit CD29 (ITGB1: 33.17), the adhesion protein CD9 (32.94) and the von Willebrand receptor unit CD42b (GPIbalpha) (30.08) (Figure 1A). Regarding the activation marker expression upon TRAP stimulation, RPs show higher median signal intensities of all four activation markers compared to MPs (Figure 1B and C). Especially, the markers CD107a (LAMP-1) and CD154 (CD40L) are expressed in MPs only to a very low extend, whereas there is a clear overexpression in RPs. Conclusion: This dataset provides the first high resolution analysis of RPs proteome at rest and upon activation. The pro-thrombotic profile of RPs explains their hyperactivity and could offer the first biomolecular explanation of the detrimental role of RPs in CCS patients. In addition, this dataset provide high resolution biomolecular information which could be useful to personalize antiplatelet therapy in patients with high RPs levels.