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  5. Microfluidics for detection of exosomes and microRNAs in cancer: State of the art

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Article
en
2022

Microfluidics for detection of exosomes and microRNAs in cancer: State of the art

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en
2022
Vol 28
Vol. 28
DOI: 10.1016/j.omtn.2022.04.011

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Michael R Hamblin
Michael R Hamblin

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Seyed Mojtaba Mousavi
Seyed Mohammad Amin Mahdian
Mohammad Saeid Ebrahimi
+11 more

Abstract

Exosomes are small extracellular vesicles with sizes ranging from 30-150 nanometers that contain proteins, lipids, mRNAs, microRNAs, and double-stranded DNA derived from the cells of origin. Exosomes can be taken up by target cells, acting as a means of cell-to-cell communication. The discovery of these vesicles in body fluids and their participation in cell communication has led to major breakthroughs in diagnosis, prognosis, and treatment of several conditions (e.g., cancer). However, conventional isolation and evaluation of exosomes and their microRNA content suffers from high cost, lengthy processes, difficult standardization, low purity, and poor yield. The emergence of microfluidics devices with increased efficiency in sieving, trapping, and immunological separation of small volumes could provide improved detection and monitoring of exosomes involved in cancer. Microfluidics techniques hold promise for advances in development of diagnostic and prognostic devices. This review covers ongoing research on microfluidics devices for detection of microRNAs and exosomes as biomarkers and their translation to point-of-care and clinical applications.

How to cite this publication

Seyed Mojtaba Mousavi, Seyed Mohammad Amin Mahdian, Mohammad Saeid Ebrahimi, Mohammad Taghizadieh, Massoud Vosough, Javid Sadri Nahand, Saereh Hosseindoost, Nasim Vousooghi, Hamid Akbari Javar, Bagher Larijani, Mahmoudreza Hadjighassem, Neda Rahimian, Michael R Hamblin, Hamed Mirzaei (2022). Microfluidics for detection of exosomes and microRNAs in cancer: State of the art. , 28, DOI: https://doi.org/10.1016/j.omtn.2022.04.011.

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Publication Details

Type

Article

Year

2022

Authors

14

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1016/j.omtn.2022.04.011

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