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Development and validation of a four-microRNA signature for placenta accreta spectrum: an integrated competing endogenous RNA network analysis

BACKGROUND: Placenta accreta spectrum (PAS) is a major cause of maternal morbidity and mortality in modern obstetrics, however, few studies have explored the underlying molecular mechanisms and biomarkers. In this study, we aimed to elucidate the regulatory RNA network contributing to PAS, comprisin...

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Autores principales: Yang, Tian, Li, Na, Hou, Rui, Qiao, Chong, Liu, Caixia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7475428/
https://www.ncbi.nlm.nih.gov/pubmed/32953719
http://dx.doi.org/10.21037/atm-20-1150
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author Yang, Tian
Li, Na
Hou, Rui
Qiao, Chong
Liu, Caixia
author_facet Yang, Tian
Li, Na
Hou, Rui
Qiao, Chong
Liu, Caixia
author_sort Yang, Tian
collection PubMed
description BACKGROUND: Placenta accreta spectrum (PAS) is a major cause of maternal morbidity and mortality in modern obstetrics, however, few studies have explored the underlying molecular mechanisms and biomarkers. In this study, we aimed to elucidate the regulatory RNA network contributing to PAS, comprising long non-coding (lnc), micro (mi), and messenger (m) RNAs, and identify biomarkers for the prediction of intraoperative blood volume loss. METHODS: Using RNA sequencing, we compared mRNA, lncRNA, and miRNA expression profiles between five PAS and five normal placental tissues. Furthermore, the miRNA expression profiles in maternal plasma samples from ten PAS and ten control participants were assessed. The data and clinical information were analyzed using R language and GraphPad Prism 7 software. RESULTS: Upon comparing PAS and control placentas, we identified 8,806 lncRNAs, 128 miRNAs, and 1,788 mRNAs that were differentially expressed. Based on a lasso regression analysis and correlation predictions, we developed a competing endogenous (ce) RNA network comprising 20 lncRNAs, 4 miRNAs, and 19 mRNAs. This network implicated a reduced angiogenesis pathway in PAS, and correlation analyses indicated that two miRNAs (hsa-miR‐490-3p and hsa-miR-133a-3p) were positively correlated to operation-related blood volume loss. CONCLUSIONS: We identified a ceRNA regulatory mechanism in PAS, and two miRNAs that may potentially serve as biomarkers of PAS prognosis.
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spelling pubmed-74754282020-09-17 Development and validation of a four-microRNA signature for placenta accreta spectrum: an integrated competing endogenous RNA network analysis Yang, Tian Li, Na Hou, Rui Qiao, Chong Liu, Caixia Ann Transl Med Original Article BACKGROUND: Placenta accreta spectrum (PAS) is a major cause of maternal morbidity and mortality in modern obstetrics, however, few studies have explored the underlying molecular mechanisms and biomarkers. In this study, we aimed to elucidate the regulatory RNA network contributing to PAS, comprising long non-coding (lnc), micro (mi), and messenger (m) RNAs, and identify biomarkers for the prediction of intraoperative blood volume loss. METHODS: Using RNA sequencing, we compared mRNA, lncRNA, and miRNA expression profiles between five PAS and five normal placental tissues. Furthermore, the miRNA expression profiles in maternal plasma samples from ten PAS and ten control participants were assessed. The data and clinical information were analyzed using R language and GraphPad Prism 7 software. RESULTS: Upon comparing PAS and control placentas, we identified 8,806 lncRNAs, 128 miRNAs, and 1,788 mRNAs that were differentially expressed. Based on a lasso regression analysis and correlation predictions, we developed a competing endogenous (ce) RNA network comprising 20 lncRNAs, 4 miRNAs, and 19 mRNAs. This network implicated a reduced angiogenesis pathway in PAS, and correlation analyses indicated that two miRNAs (hsa-miR‐490-3p and hsa-miR-133a-3p) were positively correlated to operation-related blood volume loss. CONCLUSIONS: We identified a ceRNA regulatory mechanism in PAS, and two miRNAs that may potentially serve as biomarkers of PAS prognosis. AME Publishing Company 2020-08 /pmc/articles/PMC7475428/ /pubmed/32953719 http://dx.doi.org/10.21037/atm-20-1150 Text en 2020 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Yang, Tian
Li, Na
Hou, Rui
Qiao, Chong
Liu, Caixia
Development and validation of a four-microRNA signature for placenta accreta spectrum: an integrated competing endogenous RNA network analysis
title Development and validation of a four-microRNA signature for placenta accreta spectrum: an integrated competing endogenous RNA network analysis
title_full Development and validation of a four-microRNA signature for placenta accreta spectrum: an integrated competing endogenous RNA network analysis
title_fullStr Development and validation of a four-microRNA signature for placenta accreta spectrum: an integrated competing endogenous RNA network analysis
title_full_unstemmed Development and validation of a four-microRNA signature for placenta accreta spectrum: an integrated competing endogenous RNA network analysis
title_short Development and validation of a four-microRNA signature for placenta accreta spectrum: an integrated competing endogenous RNA network analysis
title_sort development and validation of a four-microrna signature for placenta accreta spectrum: an integrated competing endogenous rna network analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7475428/
https://www.ncbi.nlm.nih.gov/pubmed/32953719
http://dx.doi.org/10.21037/atm-20-1150
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