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Identification of 5 microRNA biomarkers associated with the prognosis of uveal melanoma
To uncover the role of microRNAs in the occurrence and development of uveal melanoma (UM), we used R language packages in this study to analyze the correlations between the expression of microRNA isoforms, their target genes, and the clinical data for UM patients retrieved from The Cancer Genome Atl...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9439784/ https://www.ncbi.nlm.nih.gov/pubmed/36107591 http://dx.doi.org/10.1097/MD.0000000000030366 |
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author | Sun, Yabin Zhang, Xinmin Cong, Zhongyi Teng, Siying |
author_facet | Sun, Yabin Zhang, Xinmin Cong, Zhongyi Teng, Siying |
author_sort | Sun, Yabin |
collection | PubMed |
description | To uncover the role of microRNAs in the occurrence and development of uveal melanoma (UM), we used R language packages in this study to analyze the correlations between the expression of microRNA isoforms, their target genes, and the clinical data for UM patients retrieved from The Cancer Genome Atlas (TCGA). We used Weighted Correlation Network Analysis (WGCNA) to divide the expression profiles of different microRNAs into 10 modules, among which blue and yellow modules were associated with UM survival. Hsa-miR-513a-5p, miR-506-3p, miR-508-3p, miR-140-3p, and miR-103a-2-5p were further identified as the top 5 node microRNAs based on the risk scores in both modules using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. After combining these 5 microRNAs into an integrated risk signature, the prognostic performance of the risk signature was evaluated by area under the receiver operating characteristic (AUROC) curve, and their association with UM clinical characteristics was further analyzed using multiple Cox regression. Our results showed that this risk signature was sensitivity and specificity, and could serve as an independent prognostic factor. In addition, Spearman correlation analysis showed that expression of almost all target mRNAs were significantly positively or negatively correlated with the associated microRNAs. The gene ontology (GO), pathways, and disease enrichment analyses also showed that these 5 microRNAs were closely related to the incidence and progression of tumor, indicating their potential for predicting the outcome of UM. |
format | Online Article Text |
id | pubmed-9439784 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-94397842022-09-06 Identification of 5 microRNA biomarkers associated with the prognosis of uveal melanoma Sun, Yabin Zhang, Xinmin Cong, Zhongyi Teng, Siying Medicine (Baltimore) Research Article To uncover the role of microRNAs in the occurrence and development of uveal melanoma (UM), we used R language packages in this study to analyze the correlations between the expression of microRNA isoforms, their target genes, and the clinical data for UM patients retrieved from The Cancer Genome Atlas (TCGA). We used Weighted Correlation Network Analysis (WGCNA) to divide the expression profiles of different microRNAs into 10 modules, among which blue and yellow modules were associated with UM survival. Hsa-miR-513a-5p, miR-506-3p, miR-508-3p, miR-140-3p, and miR-103a-2-5p were further identified as the top 5 node microRNAs based on the risk scores in both modules using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. After combining these 5 microRNAs into an integrated risk signature, the prognostic performance of the risk signature was evaluated by area under the receiver operating characteristic (AUROC) curve, and their association with UM clinical characteristics was further analyzed using multiple Cox regression. Our results showed that this risk signature was sensitivity and specificity, and could serve as an independent prognostic factor. In addition, Spearman correlation analysis showed that expression of almost all target mRNAs were significantly positively or negatively correlated with the associated microRNAs. The gene ontology (GO), pathways, and disease enrichment analyses also showed that these 5 microRNAs were closely related to the incidence and progression of tumor, indicating their potential for predicting the outcome of UM. Lippincott Williams & Wilkins 2022-09-02 /pmc/articles/PMC9439784/ /pubmed/36107591 http://dx.doi.org/10.1097/MD.0000000000030366 Text en Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC) (https://creativecommons.org/licenses/by-nc/4.0/) , where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. |
spellingShingle | Research Article Sun, Yabin Zhang, Xinmin Cong, Zhongyi Teng, Siying Identification of 5 microRNA biomarkers associated with the prognosis of uveal melanoma |
title | Identification of 5 microRNA biomarkers associated with the prognosis of uveal melanoma |
title_full | Identification of 5 microRNA biomarkers associated with the prognosis of uveal melanoma |
title_fullStr | Identification of 5 microRNA biomarkers associated with the prognosis of uveal melanoma |
title_full_unstemmed | Identification of 5 microRNA biomarkers associated with the prognosis of uveal melanoma |
title_short | Identification of 5 microRNA biomarkers associated with the prognosis of uveal melanoma |
title_sort | identification of 5 microrna biomarkers associated with the prognosis of uveal melanoma |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9439784/ https://www.ncbi.nlm.nih.gov/pubmed/36107591 http://dx.doi.org/10.1097/MD.0000000000030366 |
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