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Validation of miRNA prognostic power in hepatocellular carcinoma using expression data of independent datasets
Multiple studies suggested using different miRNAs as biomarkers for prognosis of hepatocellular carcinoma (HCC). We aimed to assemble a miRNA expression database from independent datasets to enable an independent validation of previously published prognostic biomarkers of HCC. A miRNA expression dat...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6003936/ https://www.ncbi.nlm.nih.gov/pubmed/29907753 http://dx.doi.org/10.1038/s41598-018-27521-y |
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author | Nagy, Ádám Lánczky, András Menyhárt, Otília Győrffy, Balázs |
author_facet | Nagy, Ádám Lánczky, András Menyhárt, Otília Győrffy, Balázs |
author_sort | Nagy, Ádám |
collection | PubMed |
description | Multiple studies suggested using different miRNAs as biomarkers for prognosis of hepatocellular carcinoma (HCC). We aimed to assemble a miRNA expression database from independent datasets to enable an independent validation of previously published prognostic biomarkers of HCC. A miRNA expression database was established by searching the TCGA (RNA-seq) and GEO (microarray) repositories to identify miRNA datasets with available expression and clinical data. A PubMed search was performed to identify prognostic miRNAs for HCC. We performed a uni- and multivariate Cox regression analysis to validate the prognostic significance of these miRNAs. The Limma R package was applied to compare the expression of miRNAs between tumor and normal tissues. We uncovered 214 publications containing 223 miRNAs identified as potential prognostic biomarkers for HCC. In the survival analysis, the expression levels of 55 and 84 miRNAs were significantly correlated with overall survival in RNA-seq and gene chip datasets, respectively. The most significant miRNAs were hsa-miR-149, hsa-miR-139, and hsa-miR-3677 in the RNA-seq and hsa-miR-146b-3p, hsa-miR-584, and hsa-miR-31 in the microarray dataset. Of the 223 miRNAs studied, the expression was significantly altered in 102 miRNAs in tumors compared to normal liver tissues. In summary, we set up an integrated miRNA expression database and validated prognostic miRNAs in HCC. |
format | Online Article Text |
id | pubmed-6003936 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-60039362018-06-26 Validation of miRNA prognostic power in hepatocellular carcinoma using expression data of independent datasets Nagy, Ádám Lánczky, András Menyhárt, Otília Győrffy, Balázs Sci Rep Article Multiple studies suggested using different miRNAs as biomarkers for prognosis of hepatocellular carcinoma (HCC). We aimed to assemble a miRNA expression database from independent datasets to enable an independent validation of previously published prognostic biomarkers of HCC. A miRNA expression database was established by searching the TCGA (RNA-seq) and GEO (microarray) repositories to identify miRNA datasets with available expression and clinical data. A PubMed search was performed to identify prognostic miRNAs for HCC. We performed a uni- and multivariate Cox regression analysis to validate the prognostic significance of these miRNAs. The Limma R package was applied to compare the expression of miRNAs between tumor and normal tissues. We uncovered 214 publications containing 223 miRNAs identified as potential prognostic biomarkers for HCC. In the survival analysis, the expression levels of 55 and 84 miRNAs were significantly correlated with overall survival in RNA-seq and gene chip datasets, respectively. The most significant miRNAs were hsa-miR-149, hsa-miR-139, and hsa-miR-3677 in the RNA-seq and hsa-miR-146b-3p, hsa-miR-584, and hsa-miR-31 in the microarray dataset. Of the 223 miRNAs studied, the expression was significantly altered in 102 miRNAs in tumors compared to normal liver tissues. In summary, we set up an integrated miRNA expression database and validated prognostic miRNAs in HCC. Nature Publishing Group UK 2018-06-15 /pmc/articles/PMC6003936/ /pubmed/29907753 http://dx.doi.org/10.1038/s41598-018-27521-y Text en © The Author(s) 2018 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Nagy, Ádám Lánczky, András Menyhárt, Otília Győrffy, Balázs Validation of miRNA prognostic power in hepatocellular carcinoma using expression data of independent datasets |
title | Validation of miRNA prognostic power in hepatocellular carcinoma using expression data of independent datasets |
title_full | Validation of miRNA prognostic power in hepatocellular carcinoma using expression data of independent datasets |
title_fullStr | Validation of miRNA prognostic power in hepatocellular carcinoma using expression data of independent datasets |
title_full_unstemmed | Validation of miRNA prognostic power in hepatocellular carcinoma using expression data of independent datasets |
title_short | Validation of miRNA prognostic power in hepatocellular carcinoma using expression data of independent datasets |
title_sort | validation of mirna prognostic power in hepatocellular carcinoma using expression data of independent datasets |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6003936/ https://www.ncbi.nlm.nih.gov/pubmed/29907753 http://dx.doi.org/10.1038/s41598-018-27521-y |
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