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Using bioinformatics approaches to identify survival-related oncomiRs as potential targets of miRNA-based treatments for lung adenocarcinoma

Lung cancer is a major cause of cancer-associated deaths worldwide, and lung adenocarcinoma (LUAD) is the most common lung cancer subtype. Micro RNAs (miRNAs) regulate the pattern of gene expression in multiple cancer types and have been explored as potential drug development targets. To develop an...

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Autores principales: Liu, Chia-Hsin, Liu, Shu-Hsuan, Lai, Yo-Liang, Cho, Yi-Chun, Chen, Fang-Hsin, Lin, Li-Jie, Peng, Pei-Hua, Li, Chia-Yang, Wang, Shu-Chi, Chen, Ji-Lin, Wu, Heng-Hsiung, Wu, Min-Zu, Sher, Yuh-Pyng, Cheng, Wei-Chung, Hsu, Kai-Wen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9449502/
https://www.ncbi.nlm.nih.gov/pubmed/36090818
http://dx.doi.org/10.1016/j.csbj.2022.08.042
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author Liu, Chia-Hsin
Liu, Shu-Hsuan
Lai, Yo-Liang
Cho, Yi-Chun
Chen, Fang-Hsin
Lin, Li-Jie
Peng, Pei-Hua
Li, Chia-Yang
Wang, Shu-Chi
Chen, Ji-Lin
Wu, Heng-Hsiung
Wu, Min-Zu
Sher, Yuh-Pyng
Cheng, Wei-Chung
Hsu, Kai-Wen
author_facet Liu, Chia-Hsin
Liu, Shu-Hsuan
Lai, Yo-Liang
Cho, Yi-Chun
Chen, Fang-Hsin
Lin, Li-Jie
Peng, Pei-Hua
Li, Chia-Yang
Wang, Shu-Chi
Chen, Ji-Lin
Wu, Heng-Hsiung
Wu, Min-Zu
Sher, Yuh-Pyng
Cheng, Wei-Chung
Hsu, Kai-Wen
author_sort Liu, Chia-Hsin
collection PubMed
description Lung cancer is a major cause of cancer-associated deaths worldwide, and lung adenocarcinoma (LUAD) is the most common lung cancer subtype. Micro RNAs (miRNAs) regulate the pattern of gene expression in multiple cancer types and have been explored as potential drug development targets. To develop an oncomiR-based panel, we identified miRNA candidates that show differential expression patterns and are relevant to the worse 5-year overall survival outcomes in LUAD patient samples. We further evaluated various combinations of miRNA candidates for association with 5-year overall survival and identified a four-miRNA panel: miR-9-5p, miR-1246, miR-31-3p, and miR-3136-5p. The combination of these four miRNAs outperformed any single miRNA for predicting 5-year overall survival (hazard ratio [HR]: 3.47, log-rank p-value = 0.000271). Experiments were performed on lung cancer cell lines and animal models to validate the effects of these miRNAs. The results showed that singly transfected antagomiRs largely inhibited cell growth, migration, and invasion, and the combination of all four antagomiRs considerably reduced cell numbers, which is twice as effective as any single miRNA-targeted transfected. The in vivo studies revealed that antagomiR-mediated knockdown of all four miRNAs significantly reduced tumor growth and metastatic ability of lung cancer cells compared to the negative control group. The success of these in vivo and in vitro experiments suggested that these four identified oncomiRs may have therapeutic potential.
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spelling pubmed-94495022022-09-09 Using bioinformatics approaches to identify survival-related oncomiRs as potential targets of miRNA-based treatments for lung adenocarcinoma Liu, Chia-Hsin Liu, Shu-Hsuan Lai, Yo-Liang Cho, Yi-Chun Chen, Fang-Hsin Lin, Li-Jie Peng, Pei-Hua Li, Chia-Yang Wang, Shu-Chi Chen, Ji-Lin Wu, Heng-Hsiung Wu, Min-Zu Sher, Yuh-Pyng Cheng, Wei-Chung Hsu, Kai-Wen Comput Struct Biotechnol J Research Article Lung cancer is a major cause of cancer-associated deaths worldwide, and lung adenocarcinoma (LUAD) is the most common lung cancer subtype. Micro RNAs (miRNAs) regulate the pattern of gene expression in multiple cancer types and have been explored as potential drug development targets. To develop an oncomiR-based panel, we identified miRNA candidates that show differential expression patterns and are relevant to the worse 5-year overall survival outcomes in LUAD patient samples. We further evaluated various combinations of miRNA candidates for association with 5-year overall survival and identified a four-miRNA panel: miR-9-5p, miR-1246, miR-31-3p, and miR-3136-5p. The combination of these four miRNAs outperformed any single miRNA for predicting 5-year overall survival (hazard ratio [HR]: 3.47, log-rank p-value = 0.000271). Experiments were performed on lung cancer cell lines and animal models to validate the effects of these miRNAs. The results showed that singly transfected antagomiRs largely inhibited cell growth, migration, and invasion, and the combination of all four antagomiRs considerably reduced cell numbers, which is twice as effective as any single miRNA-targeted transfected. The in vivo studies revealed that antagomiR-mediated knockdown of all four miRNAs significantly reduced tumor growth and metastatic ability of lung cancer cells compared to the negative control group. The success of these in vivo and in vitro experiments suggested that these four identified oncomiRs may have therapeutic potential. Research Network of Computational and Structural Biotechnology 2022-08-22 /pmc/articles/PMC9449502/ /pubmed/36090818 http://dx.doi.org/10.1016/j.csbj.2022.08.042 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Liu, Chia-Hsin
Liu, Shu-Hsuan
Lai, Yo-Liang
Cho, Yi-Chun
Chen, Fang-Hsin
Lin, Li-Jie
Peng, Pei-Hua
Li, Chia-Yang
Wang, Shu-Chi
Chen, Ji-Lin
Wu, Heng-Hsiung
Wu, Min-Zu
Sher, Yuh-Pyng
Cheng, Wei-Chung
Hsu, Kai-Wen
Using bioinformatics approaches to identify survival-related oncomiRs as potential targets of miRNA-based treatments for lung adenocarcinoma
title Using bioinformatics approaches to identify survival-related oncomiRs as potential targets of miRNA-based treatments for lung adenocarcinoma
title_full Using bioinformatics approaches to identify survival-related oncomiRs as potential targets of miRNA-based treatments for lung adenocarcinoma
title_fullStr Using bioinformatics approaches to identify survival-related oncomiRs as potential targets of miRNA-based treatments for lung adenocarcinoma
title_full_unstemmed Using bioinformatics approaches to identify survival-related oncomiRs as potential targets of miRNA-based treatments for lung adenocarcinoma
title_short Using bioinformatics approaches to identify survival-related oncomiRs as potential targets of miRNA-based treatments for lung adenocarcinoma
title_sort using bioinformatics approaches to identify survival-related oncomirs as potential targets of mirna-based treatments for lung adenocarcinoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9449502/
https://www.ncbi.nlm.nih.gov/pubmed/36090818
http://dx.doi.org/10.1016/j.csbj.2022.08.042
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