Extracellular vesicles (EVs) are nano- and micro-sized double-layered membrane entities derived from most cell types and released into biological fluids. Biological properties (cell-uptake, biocompatibility), and chemical (composition, structure) or physical (size, density) characteristics make EVs a good candidate for drug delivery systems (DDS). Recent advances in the field of EVs (e.g., scaling-up production, purification) and developments of new imaging methods (total-body positron emission tomography [PET]) revealed benefits of radiolabeled EVs in diagnostic and interventional medicine as a potential DDs in theranostics.

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Introduction Cargo carried by extracellular vesicles (EVs) is considered a promising diagnostic marker, especially proteins. EVs can be divided according to their size and way of biogenesis into exosomes (diameter < 200 nm) and ectosomes (diameter > 200 nm). Exosomes are considered to be of endocytic origin, and ectosomes are produced by budding and shedding from the plasma membrane [1]. Methods The first step of this study was a characterization of the exosome sample. Using Tunable Resistive Pulse Sensing (qNano) size distribution and concentration were measured. The mean size of exosomes was 120±9.17 nm. In the present study, a nano liquid chromatography coupled with tandem mass spectrometry (nanoLCMS/MS) was used to compare protein profiles of exosomes secreted by pancreatic beta cells (1.1B4) grown under normal glucose (NG, 5 mM D-glucose) and high glucose (HG, 25 mM D-glucose) conditions. The EV samples were lysed, and proteins were denatured, digested, and analyzed using a Q-Exactive mass spectrometer coupled with the UltiMate 3000 RSLC nano system. The nanoLC-MS/MS data were searched against the SwissProt Homo sapiens database using MaxQuant software and protein quantitation was done by the MaxLFQ algorithm. Statistical analysis was carried out with Perseus software. Further bioinformatic analysis was performed using the FunRich 3.1.4 software with the UniProt protein database and String [2]. Results As a result of the nanoLC-MS/MS analysis more than 1,000 proteins were identified and quantified in each sample. The average number of identified proteins in exosomes was 1,397. Label-free quantitative analysis showed that exosome composition differed significantly between those isolated under NG and HG conditions. Many pathways were down-regulated in HG, particularly the ubiquitin-proteasome pathway. In addition, a significant up-regulation of the Ras-proteins pathway was observed in HG. Conclusion Our description of exosomes protein content and its related functions provides the first insight into the EV interactome and its role in glucose intolerance development and diabetic complications. The results also indicate the applicability of EV proteins for further investigation regarding their potential as circulating in vivo biomarkers.

This review introduce extracellular vesicles (EVs) to a molecular imaging field. The idea of modern analyses based on the use of omics studies, using high-throughput methods to characterize the molecular content of a single biological system, vesicolomics seems to be the new approach to collect molecular data about EV content, to find novel biomarkers or therapeutic targets. The use of various imaging techniques, including those based on radionuclides as positron emission tomography (PET) or single photon emission computed tomography (SPECT), combining molecular data on EVs, opens up the new space for radiovesicolomics—a new approach to be used in theranostics.