4.7 Review

Implications and pitfalls for cancer diagnostics exploiting extracellular vesicles

Journal

ADVANCED DRUG DELIVERY REVIEWS
Volume 175, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.addr.2021.05.029

Keywords

Tumor marker; Biomarker; Exosomes; Oncology; Preventive screening; Therapy monitoring; miRNA

Funding

  1. European Union's Horizon 2020 research and innovation programme (Marie Sklodowska-Curie project) [860303]
  2. Austrian Science Fund FWF [P 34137-B]

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Early detection of cancer remains a challenge in clinical diagnostics, but the combination of extracellular vesicle analysis with liquid biopsy has opened up new possibilities for tumor detection. This review summarizes the diversity of known EV species and their cargo molecules, discusses challenges and future directions in the application of liquid biopsy-based EV analytics in oncology.
Early detection of cancer in order to facilitate timely therapeutic interventions is an unsolved problem in today's clinical diagnostics. Tumors are detected so far mostly after pathological symptoms have emerged (usually already in progressed disease states), within preventive screenings, or occasionally as incidental finding. The emergence of extracellular vesicle (EV) analytics in combination with liquid biopsy sampling opened a plethora of new possibilities for the detection of tumors (and other diseases). This review gives an overview of the diversity of currently known EV species and the relevant cargo molecules representing potential biomarkers to detect, identify and characterize tumor cells. A number of molecules reported in recent years to be valuable targets for different aspects of cancer diagnostics, are presented. Furthermore, we discuss (technical) challenges and pitfalls related to the various potential applications (screening, diagnosis, prognosis, monitoring) of liquid biopsy based EV analytics, and give an outlook to possible future directions of this emerging field in oncology. (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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