Single extracellular vesicle analysis for early cancer detection

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. 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. 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. small EVs (50–150 nm) released by cells through the fusion of MVBs and containing parental cell contents. Production is derived by the ESCRT pathway [5.Colombo M. et al.Biogenesis, secretion, and intercellular interactions of exosomes and other extracellular vesicles.Annu. Rev. Cell Dev. Biol. 2014; 30: 255-289Crossref PubMed Scopus (3398) Google Scholar]. of any origin (tumor-cell or host-cell derived). This includes exosomes, microvesicles, and others. Vesicles are shed into the tumor interstitium with uptake by lymphatics [84.Pucci F. et al.SCS macrophages suppress melanoma by restricting tumor-derived vesicle–B cell interactions.Science. 2016; 352: 242-246Crossref PubMed Scopus (200) Google Scholar] and capillaries. a cystic lesion in the pancreas often detected incidentally by imaging and which can give rise to PDAC in 10% of cases [57.Yang K.S. et al.Extracellular vesicle analysis allows for identification of invasive IPMN.Gastroenterology. 2020; 160: 1345-1358Abstract Full Text Full Text PDF PubMed Scopus (27) Google Scholar]. larger (100–1000 nm) vesicles shed by outward blebbing of the plasma membrane [5.Colombo M. et al.Biogenesis, secretion, and intercellular interactions of exosomes and other extracellular vesicles.Annu. Rev. Cell Dev. Biol. 2014; 30: 255-289Crossref PubMed Scopus (3398) Google Scholar]. an emerging highly multiplexed cycling technique. originating from pancreatic intraepithelial neoplasia (PanIN) (90%) or IPMN (10%). based on solution-phase staining and subsequent microscopic analysis [36.Ferguson S. et al.Single-EV analysis (sEVA) of mutated proteins allows detection of stage 1 pancreatic cancer.Sci. Adv. 2022; 8eabm3453Crossref Scopus (5) Google Scholar]. the first clinically viable technique now abandoned for sEVA [39.Lee K. et al.Multiplexed profiling of single extracellular vesicles.ACS Nano. 2017; 12: 494-503Crossref Scopus (175) Google Scholar].