Current methods for characterisation of extracellular vesicles (EVs) need further standardisation in order to obtain an acceptable level of data comparability. Size and concentration of EVs can be determined by nanoparticle tracking analysis (NTA). However, both the heterogeneity of EVs and the choice of instrument settings may cause an appreciable analytical variation. Intra-assay (within-day, n = 6) and inter-assay (day-to-day, n = 6) variations (coefficient of variation, % CV) of different preparations of EVs and artificial vesicles or beads were determined using two NanoSight NS500 instruments, located at different laboratories. All analyses were performed by the same operator. The effect of applying identical software settings or instrument-optimised settings for each sample type and instrument was also evaluated. Finally, the impact of different operators and the use of two different software versions were investigated. The intra-assay CVs were 1–12% for both EVs and artificial samples, measured on the same instrument. The overall day-to-day variation was similar for both instruments, ranging from 2% to 25%. However, significantly different results were observed between the two instruments using identical software settings. The effect of applying instrument-optimised settings reduced the mismatch between the instruments, resulting in little to no significant divergences. The impact of using different operators and software versions when analysing silica microspheres and microvesicles from monocytes using instrument-optimised settings on the same instrument did not contribute to significant variation compared to the overall day-to-day variation of one operator. Performance differences between two similar NTA instruments may display significant divergences in size and concentration measurements when analysing EVs, depending on applied instrument settings and technical conditions. The importance of developing a streamlined and standardised execution of analysis, as well as monitoring longitudinal variation parameters on both biological and synthetic samples, should be highlighted.

Sixteen research groups participated in the ISOBM TD-4 Workshop in which the reactivity and specificity of 56 monoclonal antibodies against the MUC1 mucin was investigated using a diverse panel of target antigens and MUC1 mucin- related synthetic peptides and glycopeptides. The majority of antibodies (34/56) defined epitopes located within the 20-amino acid tandem repeat sequence of the MUC1 mucin protein core. Of the remaining 22 antibodies, there was evidence for the involvement of carbohydrate residues in the epitopes for 16 antibodies. There was no obvious relationship between the type of immunogen and the specificity of each antibody. Synthetic peptides and glycopeptides were analyzed for their reactivity with each antibody either by assay of direct binding (e.g. by ELISA or BiaCore) or by determining the capacity of synthetic ligands to inhibit antibody binding interactions. There was good concordance between the research groups in identifying antibodies reactive with peptide epitopes within the MUC1 protein core. Epitope mapping tests were performed using the Pepscan analysis for antibody reactivity against overlapping synthetic peptides, and results were largely consistent between research groups. The dominant feature of epitopes within the MUC1 protein core was the presence, in full or part, of the hydrophilic sequence of PDTRPAP. Carbohydrate epitopes were less easily characterized and the most useful reagents in this respect were defined oligosaccharides, rather than purified mucin preparations enriched in particular carbohydrate moieties. It was evident that carbohydrate residues were involved in many epitopes, by regulating epitope accessibility or masking determinants, or by stabilizing preferred conformations of peptide epitopes within the MUC1 protein core. Overall, the studies highlight concordance between groups rather than exposing inconsistencies which gives added confidence to the results of analyses of the specificity of anti-mucin monoclonal antibodies.

Distribution of exosomes that contain CD19, CD20, CD24, CD37, and HLA-DR may intercept immunotherapy directed against these antigens, which is important to be aware of for optimal treatment. The use of an immunomagnetic separation platform enables easy isolation and characterization of exosome subpopulations for further studies of the exosome biology to understand the potential for therapeutic and diagnostic use.

This chapter covers magnetic bead-based isolation and analysis of the smallest members of extracellular vesicles (EVs), the exosomes (30-150 nm), generally regarded to originate from the multivesicular bodies (MVBs). Also included, are descriptions of how to prepare samples prior to isolations. The magnetic bead-based isolation workflow is dramatically shortened both by omitting the pre-enrichment step and providing an option for a very short capture time. Three direct exosome isolation strategies are described: (1) "Specific and Direct," (2) "Semi Generic and Direct" and (3) "Generic and Direct" as well as exosome release from the magnetic beads. Detailed description of downstream exosome analysis is included covering flow cytometry, Western blot and electron microscopy. Finally, a description of exosome isolation from more complex starting material including urine and serum/plasma is discussed.