Description and optimization of a multiplex bead-based flow cytometry method (MBFCM) to characterize extracellular vesicles in serum samples from patients with hematological malignancies

Extracellular Vesicle Preparation and Analysis: A State-of-the-Art Review

In recent decades, research on Extracellular Vesicles (EVs) has gained prominence in the life sciences due to their critical roles in both health and disease states, offering promising applications in disease diagnosis, drug delivery, and therapy. However, their inherent heterogeneity and complex origins pose significant challenges to their preparation, analysis, and subsequent clinical application. This review is structured to provide an overview of the biogenesis, composition, and various sources of EVs, thereby laying the groundwork for a detailed discussion of contemporary techniques for their preparation and analysis. Particular focus is given to state-of-the-art technologies that employ both microfluidic and non-microfluidic platforms for EV processing. Furthermore, this discourse extends into innovative approaches that incorporate artificial intelligence and cutting-edge electrochemical sensors, with a particular emphasis on single EV analysis. This review proposes current challenges and outlines prospective avenues for future research. The objective is to motivate researchers to innovate and expand methods for the preparation and analysis of EVs, fully unlocking their biomedical potential.

Inter-laboratory multiplex bead-based surface protein profiling of MSC-derived EV preparations identifies MSC-EV surface marker signatures

Mesenchymal stromal cells (MSCs) are promising regenerative therapeutics that primarily exert their effects through secreted extracellular vesicles (EVs). These EVs - being small and non-living - are easier to handle and possess advantages over cellular products. Consequently, the therapeutic potential of MSC-EVs is increasingly investigated. However, due to variations in MSC-EV manufacturing strategies, MSC-EV products should be considered as highly diverse. Moreover, the diverse array of EV characterisation technologies used for MSC-EV characterisation further complicates reliable interlaboratory comparisons of published data. Consequently, this study aimed to establish a common method that can easily be used by various MSC-EV researchers to characterise MSC-EV preparations to facilitate interlaboratory comparisons. To this end, we conducted a comprehensive inter-laboratory assessment using a novel multiplex bead-based EV flow cytometry assay panel. This assessment involved 11 different MSC-EV products from five laboratories with varying MSC sources, culture conditions, and EV preparation methods. Through this assay panel covering a range of mostly MSC-related markers, we identified a set of cell surface markers consistently positive (CD44, CD73 and CD105) or negative (CD11b, CD45 and CD197) on EVs of all explored MSC-EV preparations. Hierarchical clustering analysis revealed distinct surface marker profiles associated with specific preparation processes and laboratory conditions. We propose CD73, CD105 and CD44 as robust positive markers for minimally identifying MSC-derived EVs and CD11b, CD14, CD19, CD45 and CD79 as reliable negative markers. Additionally, we highlight the influence of culture medium components, particularly human platelet lysate, on EV surface marker profiles, underscoring the influence of culture conditions on resulting EV products. This standardisable approach for MSC-EV surface marker profiling offers a tool for routine characterisation of manufactured EV products in pre-clinical and clinical research, enhances the quality control of MSC-EV preparations, and hopefully paves the way for higher consistency and reproducibility in the emerging therapeutic MSC-EV field.

Volatile Phases Derived from Serum, DC, or MLC Culture Supernatants to Deduce a VOC-Based Diagnostic Profiling Strategy for Leukemic Diseases

Volatile organic compounds (VOCs) reflect the metabolism in healthy and pathological conditions, and can be collected easily in a noninvasive manner. They are directly measured using electronical nose (eNose), and may qualify as a systemic tool to monitor biomarkers related to disease. Myeloid leukemic blasts can be transformed into leukemia-derived dendritic cells (DC_leu) able to improve (anti-leukemic) immune responses. To profile immunological changes in healthy and acute myeloid leukemic (AML) patients' ex vivo cell cultures, we correlated the cell biological data with the profiles of cell culture supernatant-derived VOCs. DC/DC_leu from leukemic or healthy whole blood (WB) were generated without (Control) or with immunomodulatory Kit M (Granulocyte macrophage-colony-stimulating-factor (GM-CSF) + prostaglandin E₁ (PGE₁)) in dendritic cell cultures (DC culture). Kit-pretreated/not pretreated WB was used to stimulate T cell-enriched immunoreactive cells in mixed lymphocyte cultures (MLC culture). Leukemia-specific adaptive and innate immune cells were detected with a degranulation assay (Deg) and an intracellular cytokine assay (InCyt). Anti-leukemic cytotoxicity was explored with a cytotoxicity fluorolysis assay (CTX). VOCs collected from serum or DC- and MLC culture supernatants (with vs. without Kit M pretreatment and before vs. after culture) were measured using eNose. Compared to the Control (without treatment), Kit M-pretreated leukemic and healthy WB gave rise to higher frequencies of mature (leukemia-derived) DC subtypes of activated and (memory) T cells after MLC. Moreover, antigen (leukemia)-specific cells of several lines (innate and adaptive immunity cells) were induced, giving rise to blast-lysing cells. The eNose could significantly distinguish between healthy and leukemic patients' serum, DC and MLC culture supernatant-derived volatile phases and could significantly separate several supernatant (with vs. without Kit M treatment, cultured vs. uncultured)-derived VOCs within subgroups (healthy DC or leukemic DC, or healthy MLC or leukemic MLC supernatants). Interestingly, the eNose could indicate a Kit M- and culture-associated effect. The eNose may be a prospective option for the deduction of a VOC-based profiling strategy using serum or cell culture supernatants and could be a useful diagnostic tool to recognize or qualify AML disease.

The potential role of serum extracellular vesicle derived small RNAs in AML research as non-invasive biomarker

BACKGROUND

Extracellular vesicles (EV) are cell-derived vesicles released by all cells in health and disease. Accordingly, EVs are also released by cells in acute myeloid leukemia (AML), a hematologic malignancy characterized by uncontrolled growth of immature myeloid cells, and these EVs likely carry markers and molecular cargo reflecting the malignant transformation occurring in diseased cells. Monitoring antileukemic or proleukemic processes during disease development and treatment is essential. Therefore, EVs and EV-derived microRNA (miRNA) from AML samples were explored as biomarkers to distinguish disease-related patterns ex vivo or in vivo.

METHODOLOGY

EVs were purified from serum of healthy (H) volunteers and AML patients by immunoaffinity. EV surface protein profiles were analyzed by multiplex bead-based flow cytometry (MBFCM) and total RNA was isolated from EVs prior to miRNA profiling via small RNA sequencing.

RESULTS

MBFCM revealed different surface protein patterns in H versus AML EVs. miRNA analysis showed individual as well as highly dysregulated patterns in H and AML samples.

CONCLUSIONS

In this study, we provide a proof-of-concept for the discriminative potential of EV derived miRNA profiles as biomarkers in H versus AML samples.

Nanostructured-Based Optical Readouts Interfaced with Machine Learning for Identification of Extracellular Vesicles

Extracellular vesicles (EVs) are shed from cancer cells into body fluids, enclosing molecular information about the underlying disease with the potential for being the target cancer biomarker in emerging diagnosis approaches such as liquid biopsy. Still, the study of EVs presents major challenges due to their heterogeneity, complexity, and scarcity. Recently, liquid biopsy platforms have allowed the study of tumor-derived materials, holding great promise for early-stage diagnosis and monitoring of cancer when interfaced with novel adaptations of optical readouts and advanced machine learning analysis. Here, recent advances in labeled and label-free optical techniques such as fluorescence, plasmonic, and chromogenic-based systems interfaced with nanostructured sensors like nanoparticles, nanoholes, and nanowires, and diverse machine learning analyses are reviewed. The adaptability of the different optical methods discussed is compared and insights are provided into prospective avenues for the translation of the technological approaches for cancer diagnosis. It is discussed that the inherent augmented properties of nanostructures enhance the sensitivity of the detection of EVs. It is concluded by reviewing recent integrations of nanostructured-based optical readouts with diverse machine learning models as novel analysis ventures that can potentially increase the capability of the methods to the point of translation into diagnostic applications.

EVAnalyzer: High content imaging for rigorous characterisation of single extracellular vesicles using standard laboratory equipment and a new open-source ImageJ/Fiji plugin

Extracellular vesicle (EV) research increasingly demands for quantitative characterisation at the single vesicle level to address heterogeneity and complexity of EV subpopulations. Emerging, commercialised technologies for single EV analysis based on, for example, imaging flow cytometry or imaging after capture on chips generally require dedicated instrumentation and proprietary software not readily accessible to every lab. This limits their implementation for routine EV characterisation in the rapidly growing EV field. We and others have shown that single vesicles can be detected as light diffraction limited fluorescent spots using standard confocal and widefield fluorescence microscopes. Advancing this simple strategy into a process for routine EV quantitation, we developed 'EVAnalyzer', an ImageJ/Fiji (Fiji is just ImageJ) plugin for automated, quantitative single vesicle analysis from imaging data. Using EVAnalyzer, we established a robust protocol for capture, (immuno-)labelling and fluorescent imaging of EVs. To exemplify the application scope, the process was optimised and systematically tested for (i) quantification of EV subpopulations, (ii) validation of EV labelling reagents, (iii) in situ determination of antibody specificity, sensitivity and species cross-reactivity for EV markers and (iv) optimisation of genetic EV engineering. Additionally, we show that the process can be applied to synthetic nanoparticles, allowing to determine siRNA encapsulation efficiencies of lipid-based nanoparticles (LNPs) and protein loading of SiO2 nanoparticles. EVAnalyzer further provides a pipeline for automated quantification of cell uptake at the single cell-single vesicle level, thereby enabling high content EV cell uptake assays and plate-based screens. Notably, the entire procedure from sample preparation to the final data output is entirely based on standard reagents, materials, laboratory equipment and open access software. In summary, we show that EVAnalyzer enables rigorous characterisation of EVs with generally accessible tools. Since we further provide the plugin as open-source code, we expect EVAnalyzer to not only be a resource of immediate impact, but an open innovation platform for the EV and nanoparticle research communities.