Customised extracellular vesicle therapeutics for neurological conditions
摘要
Cell-based therapies for neurological conditions have been developed on the premise of the regenerative, anti-inflammatory and homing properties of mesenchymal stromal cells (MSCs) and neural stem cells. These properties are often attributed to their cellular secretome, which comprises proteins such as growth factors and cytokines, as well as extracellular vesicles (EVs) containing bioactive cargo. Therefore, EVs have been proposed as a therapeutic modality for the treatment of neurological diseases. EVs are nanoparticles produced by all cell types and contain cargo such as proteins and nucleic acids delimited by a lipid bilayer. Recent studies have focused on the use of MSC- and stem cell-derived EVs for the treatment of neurological conditions due to their regenerative properties, their proposed ability to cross the blood brain barrier (BBB), and their safety in vivo. In these studies, naturally generated (native) EVs produced by unmodified cells have been shown to possess therapeutic and regenerative properties in both in vitro and in vivo models of neurological disease and injury. To further enhance the therapeutic ability of EVs, they can be customised by modifying the EV surface and/or supplementing the EV cargo. The methods used to modify the cargo composition of EVs are still being developed. In this review, we discuss the functions of native EVs and the role of EVs in neurobiology, current EV customisation methods, and delivery methods for EVs. The methods for EV customisation include loading of therapeutic proteins, nucleic acids, and small molecule drugs into EVs, as well as surface modifications to enhance EV targeting to the central nervous system (CNS). Several methods for both luminal and surface EV customisation can be applied to purified EVs. We also describe methods for the modification of EV-producing cells, also known as endogenous loading, resulting in the production of customised EVs, and the current techniques for analysis of EV loading and cargo retention.
Graphical Abstract