Cargando…

Secreted MicroRNA to Predict Embryo Implantation Outcome: From Research to Clinical Diagnostic Application

Embryo implantation failure is considered a leading cause of infertility and a significant bottleneck for in vitro fertilization (IVF) treatment. Confirmed factors that lead to implantation failure involve unhealthy embryos, unreceptive endometrium, and asynchronous development and communication bet...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhou, Wei, Dimitriadis, Evdokia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7537741/
https://www.ncbi.nlm.nih.gov/pubmed/33072767
http://dx.doi.org/10.3389/fcell.2020.586510
_version_ 1783590725436309504
author Zhou, Wei
Dimitriadis, Evdokia
author_facet Zhou, Wei
Dimitriadis, Evdokia
author_sort Zhou, Wei
collection PubMed
description Embryo implantation failure is considered a leading cause of infertility and a significant bottleneck for in vitro fertilization (IVF) treatment. Confirmed factors that lead to implantation failure involve unhealthy embryos, unreceptive endometrium, and asynchronous development and communication between the two. The quality of embryos is further dependent on sperm parameters, oocyte quality, and early embryo development after fertilization. The extensive involvement of such different factors contributes to the variability of implantation potential across different menstrual cycles. An ideal approach to predict the implantation outcome should not compromise embryo implantation. The use of clinical material, including follicular fluid, cumulus cells, sperm, seminal exosomes, spent blastocyst culture medium, blood, and uterine fluid, that can be collected relatively non-invasively without compromising embryo implantation in a transfer cycle opens new perspectives for the diagnosis of embryo implantation potential. Compositional comparison of these samples between fertile women and women or couples with implantation failure has identified both quantitative and qualitative differences in the expression of microRNAs (miRs) that hold diagnostic potential for implantation failure. Here, we review current findings of secreted miRs that have been identified to potentially be useful in predicting implantation outcome using material that can be collected relatively non-invasively. Developing non-invasive biomarkers of implantation potential would have a major impact on implantation failure and infertility.
format Online
Article
Text
id pubmed-7537741
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-75377412020-10-16 Secreted MicroRNA to Predict Embryo Implantation Outcome: From Research to Clinical Diagnostic Application Zhou, Wei Dimitriadis, Evdokia Front Cell Dev Biol Cell and Developmental Biology Embryo implantation failure is considered a leading cause of infertility and a significant bottleneck for in vitro fertilization (IVF) treatment. Confirmed factors that lead to implantation failure involve unhealthy embryos, unreceptive endometrium, and asynchronous development and communication between the two. The quality of embryos is further dependent on sperm parameters, oocyte quality, and early embryo development after fertilization. The extensive involvement of such different factors contributes to the variability of implantation potential across different menstrual cycles. An ideal approach to predict the implantation outcome should not compromise embryo implantation. The use of clinical material, including follicular fluid, cumulus cells, sperm, seminal exosomes, spent blastocyst culture medium, blood, and uterine fluid, that can be collected relatively non-invasively without compromising embryo implantation in a transfer cycle opens new perspectives for the diagnosis of embryo implantation potential. Compositional comparison of these samples between fertile women and women or couples with implantation failure has identified both quantitative and qualitative differences in the expression of microRNAs (miRs) that hold diagnostic potential for implantation failure. Here, we review current findings of secreted miRs that have been identified to potentially be useful in predicting implantation outcome using material that can be collected relatively non-invasively. Developing non-invasive biomarkers of implantation potential would have a major impact on implantation failure and infertility. Frontiers Media S.A. 2020-09-22 /pmc/articles/PMC7537741/ /pubmed/33072767 http://dx.doi.org/10.3389/fcell.2020.586510 Text en Copyright © 2020 Zhou and Dimitriadis. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cell and Developmental Biology
Zhou, Wei
Dimitriadis, Evdokia
Secreted MicroRNA to Predict Embryo Implantation Outcome: From Research to Clinical Diagnostic Application
title Secreted MicroRNA to Predict Embryo Implantation Outcome: From Research to Clinical Diagnostic Application
title_full Secreted MicroRNA to Predict Embryo Implantation Outcome: From Research to Clinical Diagnostic Application
title_fullStr Secreted MicroRNA to Predict Embryo Implantation Outcome: From Research to Clinical Diagnostic Application
title_full_unstemmed Secreted MicroRNA to Predict Embryo Implantation Outcome: From Research to Clinical Diagnostic Application
title_short Secreted MicroRNA to Predict Embryo Implantation Outcome: From Research to Clinical Diagnostic Application
title_sort secreted microrna to predict embryo implantation outcome: from research to clinical diagnostic application
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7537741/
https://www.ncbi.nlm.nih.gov/pubmed/33072767
http://dx.doi.org/10.3389/fcell.2020.586510
work_keys_str_mv AT zhouwei secretedmicrornatopredictembryoimplantationoutcomefromresearchtoclinicaldiagnosticapplication
AT dimitriadisevdokia secretedmicrornatopredictembryoimplantationoutcomefromresearchtoclinicaldiagnosticapplication