The heterogeneity of exosomal populations has hindered our understanding of their biogenesis, molecular composition, biodistribution and functions. By employing asymmetric flow field-flow fractionation (AF4), we identified two exosome subpopulations (large exosome vesicles, Exo-L, 90–120 nm; small exosome vesicles, Exo-S, 60–80 nm) and discovered an abundant population of non-membranous nanoparticles termed ‘exomeres’ (~35 nm). Exomere proteomic profiling revealed an enrichment in metabolic enzymes and hypoxia, microtubule and coagulation proteins as well as specific pathways, such as glycolysis and mTOR signalling. Exo-S and Exo-L contained proteins involved in endosomal function and secretion pathways, and mitotic spindle and IL-2/STAT5 signalling pathways, respectively. Exo-S, Exo-L and exomeres each had unique N-glycosylation, protein, lipid, DNA and RNA profiles and biophysical properties. These three nanoparticle subsets demonstrated diverse organ biodistribution patterns, suggesting distinct biological functions. This study demonstrates that AF4 can serve as an improved analytical tool for isolating extracellular vesicles and addressing the complexities of heterogeneous nanoparticle subpopulations.

Glycans are major constituents of extracellular vesicles (EVs). Alterations in the glycosylation pathway are a common feature of cancer cells, which gives rise to de novo or increased synthesis of particular glycans. Therefore, glycans and glycoproteins have been widely used in the clinic as both stratification and prognosis cancer biomarkers. Interestingly, several of the known tumor-associated glycans have already been identified in cancer EVs, highlighting EV glycosylation as a potential source of circulating cancer biomarkers. These particles are crucial vehicles of cell–cell communication, being able to transfer molecular information and to modulate the recipient cell behavior. The presence of particular glycoconjugates has been described to be important for EV protein sorting, uptake and organ-tropism. Furthermore, specific EV glycans or glycoproteins have been described to be able to distinguish tumor EVs from benign EVs. In this review, the application of EV glycosylation in the development of novel EV detection and capture methodologies is discussed. In addition, we highlight the potential of EV glycosylation in the clinical setting for both cancer biomarker discovery and EV therapeutic delivery strategies.

Extracellular vesicles (EVs) are a heterogeneous group of small secreted particles involved in intercellular communication and mediating a broad spectrum of biological functions. EVs cargo is composed of a large repertoire of molecules, including glycoconjugates. Herein, we report the first study on the impact of the isolation strategy on the EV populations' glycosylation profile. The use of different state‐of‐the‐art protocols, namely differential ultracentrifugation (UC), total exosome isolation (TEI), OptiPrep^TM density gradient (ODG) and size exclusion chromatography (SEC) resulted in EV populations displaying different sets of glycoconjugates. The EV populations obtained by UC, ODG and SEC methods displayed similar protein and glycan profiles, whereas TEI methodology isolated the most distinct EV population. In addition, ODG and SEC isolation protocols provided an enhanced EV glycoproteins detection. Remarkably, proteins displaying the tumour‐associated glycan sialyl‐Tn (STn) were identified as packaged cargo into EVs independently of the isolation methodology. STn carrying EV samples isolated by UC, ODG and SEC presented a considerable set of cancer‐related proteins that were not detected in EVs isolated by TEI. Our work demonstrates the impact of using different isolation methodologies in the populations of EVs that are obtained, with consequences in the glycosylation profile of the isolated population. Furthermore, our results highlight the importance of selecting adequate EV isolation protocols and cell culture conditions to determine the structural and functional complexity of the EV glycoconjugates.

Circulating O-glycoproteins shed from cancer cells represent important serum biomarkers for diagnostic and prognostic purposes. We have recently shown that selective detection of cancer-associated aberrant glycoforms of circulating O-glycoprotein biomarkers can increase specificity of cancer biomarker assays. However, the current knowledge of secreted and circulating O-glycoproteins is limited. Here, we used the COSMC KO “SimpleCell” (SC) strategy to characterize the O-glycoproteome of two gastric cancer SimpleCell lines (AGS, MKN45) as well as a gastric cell line (KATO III) which naturally expresses at least partially truncated O-glycans. Overall, we identified 499 O-glycoproteins and 1236 O-glycosites in gastric cancer SimpleCells, and a total 47 O-glycoproteins and 73 O-glycosites in the KATO III cell line. We next modified the glycoproteomic strategy to apply it to pools of sera from gastric cancer and healthy individuals to identify circulating O-glycoproteins with the STn glycoform. We identified 37 O-glycoproteins in the pool of cancer sera, and only nine of these were also found in sera from healthy individuals. Two identified candidate O-glycoprotein biomarkers (CD44 and GalNAc-T5) circulating with the STn glycoform were further validated as being expressed in gastric cancer tissue. A proximity ligation assay was used to show that CD44 was expressed with the STn glycoform in gastric cancer tissues. The study provides a discovery strategy for aberrantly glycosylated O-glycoproteins and a set of O-glycoprotein candidates with biomarker potential in gastric cancer.