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Identification of three miRNAs signature as a prognostic biomarker in breast cancer using bioinformatics analysis

BACKGROUND: Accumulating evidences indicated that some miRNAs are dysregulated in breast cancer and involved in cell growth, migration and invasion, differentiation, cell cycle arrest, apoptosis, and autophagy. Our study aims to identify a novel set of biomarkers for predicting the prognosis of brea...

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Autores principales: Sang, Meijie, Li, Aiying, Wang, Xu, Chen, Can, Liu, Kun, Bai, Lin, Wu, Ming, Liu, Fei, Sang, Meixiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798573/
https://www.ncbi.nlm.nih.gov/pubmed/35117535
http://dx.doi.org/10.21037/tcr.2020.02.21
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author Sang, Meijie
Li, Aiying
Wang, Xu
Chen, Can
Liu, Kun
Bai, Lin
Wu, Ming
Liu, Fei
Sang, Meixiang
author_facet Sang, Meijie
Li, Aiying
Wang, Xu
Chen, Can
Liu, Kun
Bai, Lin
Wu, Ming
Liu, Fei
Sang, Meixiang
author_sort Sang, Meijie
collection PubMed
description BACKGROUND: Accumulating evidences indicated that some miRNAs are dysregulated in breast cancer and involved in cell growth, migration and invasion, differentiation, cell cycle arrest, apoptosis, and autophagy. Our study aims to identify a novel set of biomarkers for predicting the prognosis of breast cancer patients. METHODS: We downloaded clinical information and raw sequencing data from The Cancer Genome Atlas (TCGA) database. We selected samples with miRNA sequencing data and relevant clinical prognostic data for subsequent analysis. The association between miRNA and prognosis function was analyzed by Cox regression analysis. The potential biofunctions of target miRNAs were investigated through bioinformatic analysis. RESULTS: We identified 84 differentially expressed miRNAs (DEmiRNAs), among them, 17 were downregulated and 67 were upregulated. We used Kaplan-Meier survival analysis to evaluate the prognostic value of three miRNAs (mir-105-1, mir-301b and mir-1258). We also found that the three-miRNA signature is independent prognostic factors for breast cancer by using Cox regression analysis. It might be participated in different signaling pathways associated with cancer by using functional enrichment analysis, including adherens junction, autophagy, and TGF-beta signaling pathway, ErbB signaling pathway, FoxO signaling pathway. CONCLUSIONS: Taken together, three-miRNA signature might be used as a potential predicting prognostic biomarker in breast cancer.
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spelling pubmed-87985732022-02-02 Identification of three miRNAs signature as a prognostic biomarker in breast cancer using bioinformatics analysis Sang, Meijie Li, Aiying Wang, Xu Chen, Can Liu, Kun Bai, Lin Wu, Ming Liu, Fei Sang, Meixiang Transl Cancer Res Original Article BACKGROUND: Accumulating evidences indicated that some miRNAs are dysregulated in breast cancer and involved in cell growth, migration and invasion, differentiation, cell cycle arrest, apoptosis, and autophagy. Our study aims to identify a novel set of biomarkers for predicting the prognosis of breast cancer patients. METHODS: We downloaded clinical information and raw sequencing data from The Cancer Genome Atlas (TCGA) database. We selected samples with miRNA sequencing data and relevant clinical prognostic data for subsequent analysis. The association between miRNA and prognosis function was analyzed by Cox regression analysis. The potential biofunctions of target miRNAs were investigated through bioinformatic analysis. RESULTS: We identified 84 differentially expressed miRNAs (DEmiRNAs), among them, 17 were downregulated and 67 were upregulated. We used Kaplan-Meier survival analysis to evaluate the prognostic value of three miRNAs (mir-105-1, mir-301b and mir-1258). We also found that the three-miRNA signature is independent prognostic factors for breast cancer by using Cox regression analysis. It might be participated in different signaling pathways associated with cancer by using functional enrichment analysis, including adherens junction, autophagy, and TGF-beta signaling pathway, ErbB signaling pathway, FoxO signaling pathway. CONCLUSIONS: Taken together, three-miRNA signature might be used as a potential predicting prognostic biomarker in breast cancer. AME Publishing Company 2020-03 /pmc/articles/PMC8798573/ /pubmed/35117535 http://dx.doi.org/10.21037/tcr.2020.02.21 Text en 2020 Translational Cancer Research. 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/.
spellingShingle Original Article
Sang, Meijie
Li, Aiying
Wang, Xu
Chen, Can
Liu, Kun
Bai, Lin
Wu, Ming
Liu, Fei
Sang, Meixiang
Identification of three miRNAs signature as a prognostic biomarker in breast cancer using bioinformatics analysis
title Identification of three miRNAs signature as a prognostic biomarker in breast cancer using bioinformatics analysis
title_full Identification of three miRNAs signature as a prognostic biomarker in breast cancer using bioinformatics analysis
title_fullStr Identification of three miRNAs signature as a prognostic biomarker in breast cancer using bioinformatics analysis
title_full_unstemmed Identification of three miRNAs signature as a prognostic biomarker in breast cancer using bioinformatics analysis
title_short Identification of three miRNAs signature as a prognostic biomarker in breast cancer using bioinformatics analysis
title_sort identification of three mirnas signature as a prognostic biomarker in breast cancer using bioinformatics analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798573/
https://www.ncbi.nlm.nih.gov/pubmed/35117535
http://dx.doi.org/10.21037/tcr.2020.02.21
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