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Identification of Potential microRNA Panels for Male Non-Small Cell Lung Cancer Identification Using Microarray Datasets and Bioinformatics Methods

Background: Non-small cell lung cancer (NSCLC) is still one of the types of cancer with the highest death rates. MicroRNAs (miRNAs) play essential roles in NSCLC development. This study evaluates miRNA expression patterns and specific mechanisms in male patients with NSCLC. Methods: We report an int...

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Autores principales: Haranguș, Antonia, Lajos, Raduly, Budisan, Livia, Zanoaga, Oana, Ciocan, Cristina, Bica, Cecilia, Pirlog, Radu, Simon, Ioan, Simon, Marioara, Braicu, Cornelia, Berindan-Neagoe, Ioana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9780989/
https://www.ncbi.nlm.nih.gov/pubmed/36556276
http://dx.doi.org/10.3390/jpm12122056
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author Haranguș, Antonia
Lajos, Raduly
Budisan, Livia
Zanoaga, Oana
Ciocan, Cristina
Bica, Cecilia
Pirlog, Radu
Simon, Ioan
Simon, Marioara
Braicu, Cornelia
Berindan-Neagoe, Ioana
author_facet Haranguș, Antonia
Lajos, Raduly
Budisan, Livia
Zanoaga, Oana
Ciocan, Cristina
Bica, Cecilia
Pirlog, Radu
Simon, Ioan
Simon, Marioara
Braicu, Cornelia
Berindan-Neagoe, Ioana
author_sort Haranguș, Antonia
collection PubMed
description Background: Non-small cell lung cancer (NSCLC) is still one of the types of cancer with the highest death rates. MicroRNAs (miRNAs) play essential roles in NSCLC development. This study evaluates miRNA expression patterns and specific mechanisms in male patients with NSCLC. Methods: We report an integrated microarray analysis of miRNAs for eight matched samples of males with NSCLC compared to the study of public datasets of males with NSCLC from TCGA, followed by qRT-PCR validation. Results: For the TCGA dataset, we identified 385 overexpressed and 75 underexpressed miRNAs. Our cohort identified 54 overexpressed and 77 underexpressed miRNAs, considering a fold-change (FC) of ±1.5 and p < 0.05 as the cutoff value. The common miRNA signature consisted of eight overexpressed and nine underexpressed miRNAs. Validation was performed using qRT-PCR on the tissue samples for miR-183-3p and miR-34c-5p and on plasma samples for miR-34c-5p. We also created mRNA-miRNA regulatory networks to identify critical molecules, revealing NSCLC signaling pathways related to underexpressed and overexpressed transcripts. The genes targeted by these transcripts were correlated with overall survival. Conclusions: miRNAs and some of their target genes could play essential roles in investigating the mechanisms involved in NSCLC evolution and provide opportunities to identify potential therapeutic targets.
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spelling pubmed-97809892022-12-24 Identification of Potential microRNA Panels for Male Non-Small Cell Lung Cancer Identification Using Microarray Datasets and Bioinformatics Methods Haranguș, Antonia Lajos, Raduly Budisan, Livia Zanoaga, Oana Ciocan, Cristina Bica, Cecilia Pirlog, Radu Simon, Ioan Simon, Marioara Braicu, Cornelia Berindan-Neagoe, Ioana J Pers Med Article Background: Non-small cell lung cancer (NSCLC) is still one of the types of cancer with the highest death rates. MicroRNAs (miRNAs) play essential roles in NSCLC development. This study evaluates miRNA expression patterns and specific mechanisms in male patients with NSCLC. Methods: We report an integrated microarray analysis of miRNAs for eight matched samples of males with NSCLC compared to the study of public datasets of males with NSCLC from TCGA, followed by qRT-PCR validation. Results: For the TCGA dataset, we identified 385 overexpressed and 75 underexpressed miRNAs. Our cohort identified 54 overexpressed and 77 underexpressed miRNAs, considering a fold-change (FC) of ±1.5 and p < 0.05 as the cutoff value. The common miRNA signature consisted of eight overexpressed and nine underexpressed miRNAs. Validation was performed using qRT-PCR on the tissue samples for miR-183-3p and miR-34c-5p and on plasma samples for miR-34c-5p. We also created mRNA-miRNA regulatory networks to identify critical molecules, revealing NSCLC signaling pathways related to underexpressed and overexpressed transcripts. The genes targeted by these transcripts were correlated with overall survival. Conclusions: miRNAs and some of their target genes could play essential roles in investigating the mechanisms involved in NSCLC evolution and provide opportunities to identify potential therapeutic targets. MDPI 2022-12-13 /pmc/articles/PMC9780989/ /pubmed/36556276 http://dx.doi.org/10.3390/jpm12122056 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Haranguș, Antonia
Lajos, Raduly
Budisan, Livia
Zanoaga, Oana
Ciocan, Cristina
Bica, Cecilia
Pirlog, Radu
Simon, Ioan
Simon, Marioara
Braicu, Cornelia
Berindan-Neagoe, Ioana
Identification of Potential microRNA Panels for Male Non-Small Cell Lung Cancer Identification Using Microarray Datasets and Bioinformatics Methods
title Identification of Potential microRNA Panels for Male Non-Small Cell Lung Cancer Identification Using Microarray Datasets and Bioinformatics Methods
title_full Identification of Potential microRNA Panels for Male Non-Small Cell Lung Cancer Identification Using Microarray Datasets and Bioinformatics Methods
title_fullStr Identification of Potential microRNA Panels for Male Non-Small Cell Lung Cancer Identification Using Microarray Datasets and Bioinformatics Methods
title_full_unstemmed Identification of Potential microRNA Panels for Male Non-Small Cell Lung Cancer Identification Using Microarray Datasets and Bioinformatics Methods
title_short Identification of Potential microRNA Panels for Male Non-Small Cell Lung Cancer Identification Using Microarray Datasets and Bioinformatics Methods
title_sort identification of potential microrna panels for male non-small cell lung cancer identification using microarray datasets and bioinformatics methods
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9780989/
https://www.ncbi.nlm.nih.gov/pubmed/36556276
http://dx.doi.org/10.3390/jpm12122056
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