Current Search through Liquid Biopsy of Effective Biomarkers for Early Cancer Diagnosis into the Rich Cargoes of Extracellular Vesicles

There exist many different human cancers, but regardless of the cancer type, an early diagnosis is a necessary condition for further optimal outcomes from the disease. Therefore, efficient specific and sensitive cancer biomarkers are urgently needed. This is especially true for the cancers depicting...

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Main Author: Irène Tatischeff
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:International Journal of Molecular Sciences
Subjects:
Online Access:https://www.mdpi.com/1422-0067/22/11/5674
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spelling doaj-fcb31dd7844c4754bbaa2e450503b9572021-06-01T01:13:37ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672021-05-01225674567410.3390/ijms22115674Current Search through Liquid Biopsy of Effective Biomarkers for Early Cancer Diagnosis into the Rich Cargoes of Extracellular VesiclesIrène Tatischeff0Honorary CNRS and UPMC Research Director, Founder of RevInterCell, a Scientific Consulting Service, 91400 Orsay, FranceThere exist many different human cancers, but regardless of the cancer type, an early diagnosis is a necessary condition for further optimal outcomes from the disease. Therefore, efficient specific and sensitive cancer biomarkers are urgently needed. This is especially true for the cancers depicting a silent progression, and those only diagnosed in an already metastatic state with a poor survival prognostic. After a rapid overview of the previous methods for cancer diagnosis, the outstanding characteristics of extracellular vesicles (EVs) will be presented, as new interesting candidates for early cancer diagnosis in human biofluid non-invasive liquid biopsy. The present review aims to give the state-of-the-art of the numerous searches of efficient EV-mediated cancer diagnosis. The corresponding literature quest was performed by means of an original approach, using a powerful Expernova Questel <i>big data</i> platform, which was specifically adapted for a literature search on EVs. The chosen collected scientific papers are presented in two parts, the first one drawing up a picture of the current general status of EV-mediated cancer diagnosis and the second one showing recent applications of such EV-mediated diagnosis for six important human-specific cancers, i.e., lung, breast, prostate, colorectal, ovary and pancreatic cancers. However, the promising perspective of finally succeeding in the worldwide quest for the much-needed early cancer diagnosis has to be moderated by the many remaining challenges left to solve before achieving the efficient clinical translation of the constantly increasing scientific knowledge.https://www.mdpi.com/1422-0067/22/11/5674extracellular vesicles (exosomesmicrovesiclesoncosomesapoptotic bodies)specific human cancers (lungbreast
collection DOAJ
language English
format Article
sources DOAJ
author Irène Tatischeff
spellingShingle Irène Tatischeff
Current Search through Liquid Biopsy of Effective Biomarkers for Early Cancer Diagnosis into the Rich Cargoes of Extracellular Vesicles
International Journal of Molecular Sciences
extracellular vesicles (exosomes
microvesicles
oncosomes
apoptotic bodies)
specific human cancers (lung
breast
author_facet Irène Tatischeff
author_sort Irène Tatischeff
title Current Search through Liquid Biopsy of Effective Biomarkers for Early Cancer Diagnosis into the Rich Cargoes of Extracellular Vesicles
title_short Current Search through Liquid Biopsy of Effective Biomarkers for Early Cancer Diagnosis into the Rich Cargoes of Extracellular Vesicles
title_full Current Search through Liquid Biopsy of Effective Biomarkers for Early Cancer Diagnosis into the Rich Cargoes of Extracellular Vesicles
title_fullStr Current Search through Liquid Biopsy of Effective Biomarkers for Early Cancer Diagnosis into the Rich Cargoes of Extracellular Vesicles
title_full_unstemmed Current Search through Liquid Biopsy of Effective Biomarkers for Early Cancer Diagnosis into the Rich Cargoes of Extracellular Vesicles
title_sort current search through liquid biopsy of effective biomarkers for early cancer diagnosis into the rich cargoes of extracellular vesicles
publisher MDPI AG
series International Journal of Molecular Sciences
issn 1661-6596
1422-0067
publishDate 2021-05-01
description There exist many different human cancers, but regardless of the cancer type, an early diagnosis is a necessary condition for further optimal outcomes from the disease. Therefore, efficient specific and sensitive cancer biomarkers are urgently needed. This is especially true for the cancers depicting a silent progression, and those only diagnosed in an already metastatic state with a poor survival prognostic. After a rapid overview of the previous methods for cancer diagnosis, the outstanding characteristics of extracellular vesicles (EVs) will be presented, as new interesting candidates for early cancer diagnosis in human biofluid non-invasive liquid biopsy. The present review aims to give the state-of-the-art of the numerous searches of efficient EV-mediated cancer diagnosis. The corresponding literature quest was performed by means of an original approach, using a powerful Expernova Questel <i>big data</i> platform, which was specifically adapted for a literature search on EVs. The chosen collected scientific papers are presented in two parts, the first one drawing up a picture of the current general status of EV-mediated cancer diagnosis and the second one showing recent applications of such EV-mediated diagnosis for six important human-specific cancers, i.e., lung, breast, prostate, colorectal, ovary and pancreatic cancers. However, the promising perspective of finally succeeding in the worldwide quest for the much-needed early cancer diagnosis has to be moderated by the many remaining challenges left to solve before achieving the efficient clinical translation of the constantly increasing scientific knowledge.
topic extracellular vesicles (exosomes
microvesicles
oncosomes
apoptotic bodies)
specific human cancers (lung
breast
url https://www.mdpi.com/1422-0067/22/11/5674
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