Extracellular vesicles: A dive into their role in the tumor microenvironment and cancer progression

Extracellular vesicles (EVs) encompass a diverse set of membrane-derived particles released from cells and are found in numerous biological matrices and the extracellular space. Specific classes of EVs include apoptotic bodies, exosomes, and microvesicles, which vary in their size, origin, membrane protein expression, and interior cargo. EVs provide a mechanism for shuttling cargo between cells, which can influence cell physiology by transporting proteins, DNA, and RNA. EVs are an abundant component of the tumor microenvironment (TME) and are proposed to drive tumor growth and progression by communicating between fibroblasts, macrophages, and tumor cells in the TME. The cargo, source, and type of EV influences the pro- or anti-tumoral role of these molecules. Therefore, robust EV isolation and characterization techniques are required to ensure accurate elucidation of their association with disease. Here, we summarize different EV subclasses, methods for EV isolation and characterization, and a selection of current clinical trials studying EVs. We also review key studies exploring the role and impact of EVs in the TME, including how EVs mediate intercellular communication, drive cancer progression, and remodel the TME.

Automated summary

Extracellular vesicles (EVs) are versatile membrane-derived particles released from cells and found in various biological matrices and the extracellular space. Different types of EVs, including apoptotic bodies, exosomes, and microvesicles, differ in their size, origin, membrane protein expression, and cargo contents. EVs act as shuttles for proteins, DNA, RNA, and other molecules between cells, influencing cell physiology. In the tumor microenvironment (TME), EVs play a crucial role in tumor growth and progression by facilitating communication among fibroblasts, macrophages, and tumor cells. Therefore, it is important to develop robust techniques for EV isolation and characterization to understand their association with diseases accurately.