Positive and Negative Selection of Extracellular Vesicle-Based Biomarkers: Insights from L1CAM Immunocapture and Emerging Immunodepletion Strategies

Extracellular vesicles (EVs) reflect their spatiotemporal cellular origins and, when released into the peripheral bloodstream, represent sources of biomarkers for processes occurring in inaccessible tissues, such as the brain. Positive selection by immunoaffinity isolation targeting a specific EV surface marker can be used to preferentially enrich for EVs from a particular cell type over other EVs in circulation. However, the case of L1CAM immunocapture for enrichment of brain-derived neuronal EVs has exemplified the biological and technical influences affecting the outcomes of positive selection, which are discussed here. These include findings from the wider (non-EV) literature showing that soluble L1CAM is a binding partner of the common EV marker CD9. Additional studies show that CD9 is not expressed by the vast majority of neurons in the brain, but it is highly expressed by neurons of the peripheral nervous system, which could affect the interpretation of studies demonstrating the co-localisation of L1CAM and CD9 on EVs to assert isolation of EVs derived from neurons in the brain. Next, emerging negative selection strategies are discussed which, when combined with positive selection, could overcome some of the challenges associated with enriching for EV-based biomarkers. These strategies include depleting EVs on a cell-by-cell type basis, as well as targeting common EV markers to simultaneously deplete diverse, undesired EV populations whilst selecting for the EVs of interest. An example is given of how CD9 depletion could enrich and select for brain-derived neuronal EVs. Additionally, studies that have used negative selection alone to select for EVs, and the advantages of this approach for biomarker detection, are highlighted. Finally, based on these insights, considerations for the choice of future positive and negative selection targets are discussed, including how understanding the nuances of EV heterogeneity could facilitate the process of EV-based biomarker discovery and their translation to the clinic.