4.6 Article

Extracellular vesicles as source for the identification of minimally invasive molecular signatures in glioblastoma

Journal

SEMINARS IN CANCER BIOLOGY
Volume 87, Issue -, Pages 148-159

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.semcancer.2022.11.004

Keywords

Extracellular vesicle; Exosome; Biomarker; Liquid biopsy; Glioblastoma

Categories

Funding

  1. EV-Glio ERAPerMed EU project [AECC- PER- ME20733FALC, ISCIII-AC20/00024]
  2. Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) [471840646]
  3. Alzheimer's Association Grant [AARG-NTF-22-968911]
  4. Spanish Ministry of Science and Innovation [RTI2018-094969-B-I00, PID2021-125104OB-I00]

Ask authors/readers for more resources

The analysis of extracellular vesicles (EVs) as a source of cancer biomarkers is a promising field, providing low-invasive biomarkers. EVs, present in most body fluids and released by all cell types, including cancer cells, can serve as a potential source of reliable biomarkers for cancer. EV biomarkers in liquid biopsy can complement current medical technologies for cancer diagnosis, prognosis, and therapy monitoring, particularly for glioblastoma.
The analysis of extracellular vesicles (EVs) as a source of cancer biomarkers is an emerging field since low -invasive biomarkers are highly demanded. EVs constitute a heterogeneous population of small membrane -contained vesicles that are present in most of body fluids. They are released by all cell types, including cancer cells and their cargo consists of nucleic acids, proteins and metabolites and varies depending on the biological -pathological state of the secretory cell. Therefore, EVs are considered as a potential source of reliable biomarkers for cancer. EV biomarkers in liquid biopsy can be a valuable tool to complement current medical technologies for cancer diagnosis, as their sampling is minimally invasive and can be repeated over time to monitor disease progression. In this review, we highlight the advances in EV biomarker research for cancer diagnosis, prognosis, and therapy monitoring. We especially focus on EV derived biomarkers for glioblastoma. The diagnosis and monitoring of glioblastoma still relies on imaging techniques, which are not sufficient to reflect the highly heterogenous and invasive nature of glioblastoma. Therefore, we discuss how the use of EV biomarkers could overcome the challenges faced in diagnosis and monitoring of glioblastoma.

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