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Construction of miRNA–mRNA networks for the identification of lung cancer biomarkers in liquid biopsies

Lung cancer (LC) is the most common cause of cancer death worldwide mostly due to the low survival rate: 75% of cases are identified in advanced stages. In this study, the list of useful biomarkers to make an early diagnosis using liquid biopsies was expanded. A total of 30 samples of LC were analyz...

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Autores principales: Espinosa Garcia, Elena, Arroyo Varela, Macarena, Larrosa Jimenez, Rafael, Gomez-Maldonado, Josefa, Cobo Dols, Manuel Angel, Claros, M. Gonzalo, Bautista Moreno, Rocio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941226/
https://www.ncbi.nlm.nih.gov/pubmed/36229739
http://dx.doi.org/10.1007/s12094-022-02969-7
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author Espinosa Garcia, Elena
Arroyo Varela, Macarena
Larrosa Jimenez, Rafael
Gomez-Maldonado, Josefa
Cobo Dols, Manuel Angel
Claros, M. Gonzalo
Bautista Moreno, Rocio
author_facet Espinosa Garcia, Elena
Arroyo Varela, Macarena
Larrosa Jimenez, Rafael
Gomez-Maldonado, Josefa
Cobo Dols, Manuel Angel
Claros, M. Gonzalo
Bautista Moreno, Rocio
author_sort Espinosa Garcia, Elena
collection PubMed
description Lung cancer (LC) is the most common cause of cancer death worldwide mostly due to the low survival rate: 75% of cases are identified in advanced stages. In this study, the list of useful biomarkers to make an early diagnosis using liquid biopsies was expanded. A total of 30 samples of LC were analyzed to define potential miRNA biomarkers in liquid biopsies for LC. The biomarkers have been identified in interaction networks miRNA–mRNA. The potential biomarkers have been then validated in large cohorts. A total of 15 candidate miRNAs, that regulate the repression of 30 mRNAs, have been identified as a specific functional interaction network for squamous carcinoma, while the specific functional interaction network of adenocarcinoma consists of four candidate miRNAs that seem to handle the repression of five mRNA. Inspection of expression levels in larger cohorts validates the usefulness of the 11 candidates as biomarkers in liquid biopsies. The 11 candidate miRNAs found could be utilized to form diagnostic predictive biomarkers for LC in liquid biopsies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12094-022-02969-7.
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spelling pubmed-99412262023-02-22 Construction of miRNA–mRNA networks for the identification of lung cancer biomarkers in liquid biopsies Espinosa Garcia, Elena Arroyo Varela, Macarena Larrosa Jimenez, Rafael Gomez-Maldonado, Josefa Cobo Dols, Manuel Angel Claros, M. Gonzalo Bautista Moreno, Rocio Clin Transl Oncol Research Article Lung cancer (LC) is the most common cause of cancer death worldwide mostly due to the low survival rate: 75% of cases are identified in advanced stages. In this study, the list of useful biomarkers to make an early diagnosis using liquid biopsies was expanded. A total of 30 samples of LC were analyzed to define potential miRNA biomarkers in liquid biopsies for LC. The biomarkers have been identified in interaction networks miRNA–mRNA. The potential biomarkers have been then validated in large cohorts. A total of 15 candidate miRNAs, that regulate the repression of 30 mRNAs, have been identified as a specific functional interaction network for squamous carcinoma, while the specific functional interaction network of adenocarcinoma consists of four candidate miRNAs that seem to handle the repression of five mRNA. Inspection of expression levels in larger cohorts validates the usefulness of the 11 candidates as biomarkers in liquid biopsies. The 11 candidate miRNAs found could be utilized to form diagnostic predictive biomarkers for LC in liquid biopsies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12094-022-02969-7. Springer International Publishing 2022-10-13 2023 /pmc/articles/PMC9941226/ /pubmed/36229739 http://dx.doi.org/10.1007/s12094-022-02969-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Espinosa Garcia, Elena
Arroyo Varela, Macarena
Larrosa Jimenez, Rafael
Gomez-Maldonado, Josefa
Cobo Dols, Manuel Angel
Claros, M. Gonzalo
Bautista Moreno, Rocio
Construction of miRNA–mRNA networks for the identification of lung cancer biomarkers in liquid biopsies
title Construction of miRNA–mRNA networks for the identification of lung cancer biomarkers in liquid biopsies
title_full Construction of miRNA–mRNA networks for the identification of lung cancer biomarkers in liquid biopsies
title_fullStr Construction of miRNA–mRNA networks for the identification of lung cancer biomarkers in liquid biopsies
title_full_unstemmed Construction of miRNA–mRNA networks for the identification of lung cancer biomarkers in liquid biopsies
title_short Construction of miRNA–mRNA networks for the identification of lung cancer biomarkers in liquid biopsies
title_sort construction of mirna–mrna networks for the identification of lung cancer biomarkers in liquid biopsies
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941226/
https://www.ncbi.nlm.nih.gov/pubmed/36229739
http://dx.doi.org/10.1007/s12094-022-02969-7
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