Single extracellular vesicle analysis for early cancer detection. Issue 8 (August 2022)

• Record Type: Journal Article
• Authors: Ferguson, Scott; Yang, Katherine S.; Weissleder, Ralph
• Is Part Of: Trends in molecular medicine. Volume 28:Issue 8(2022)
• Page Start: 681
• Page End: 692
• Publication Date: 2022-08
• Subjects: early detection -- cancer -- exosome -- extracellular vesicle; Molecular biology -- Periodicals; Pathology, Molecular -- Periodicals; Physiology, Pathological -- Periodicals; 572.8
• DOI: 10.1016/j.molmed.2022.05.003
• Languages: English
• ISSNs: 1471-4914

Abstract

Abstract : Extracellular vesicles (EVs) are actively shed into the circulation from both cancer and host cells. EVs are emerging as one of the diagnostic frontrunners for early cancer detection, disease monitoring, and treatment evaluation. The advantages of EVs rely on the fact that vesicles are being shed by dividing tumor cells, with indications that human and viral oncogenes, cellular metabolic rate, and tumor characteristics such as pH and hypoxia contribute to the high shed rates in cancer. In this review, we provide an overview of EVs and the rationale for using them for early cancer detection. We examine emerging technologies for single EV analysis (sEVA) and why these technologies will be necessary for early cancer detection. Highlights: After years of research, single extracellular vesicle (EV) analysis (sEVA) has become technically feasible in a clinical environment and is diagnostically promising. Unbiased single-EV assays have now been successfully employed in several cancer types. Including colorectal, prostate, breast, cervical, melanoma, and pancreatic ductal adenocarcinoma (PDAC). Most technical challenges in the analysis have been overcome, but some important ones remain. These include the need for deeper multiplexing to: (i) differentiate benign from malignant EVs; (ii) determine the organ of origin of circulating tumor-derived EVs (ctEVs); (iii) better understand the heterogeneity of EVs in different human cancers; and (iv) discover new promising EV biomarkers. A significant challenge has been the lack of rigorous, well-controlled clinical studies. There is a need to scale up and implement easy-to-use sEVA systems in clinical laboratories to enable broader use in early cancer detection. Clinically, there is a need to perform prospective, well-controlled clinical studies to validate existing biomarkers across different high-risk populations.