Cargando…
Prognostic value of meta-signature miRNAs in renal cell carcinoma: an integrated miRNA expression profiling analysis
To identify a robust panel of microRNA (miRNA) signatures that can distinguish renal cell carcinoma (RCC) from normal kidney using miRNA expression levels. We performed a comprehensive meta-analysis of 29 published studies that compared the miRNA expression profiles of RCC tissues and adjacent norma...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4431463/ https://www.ncbi.nlm.nih.gov/pubmed/25974855 http://dx.doi.org/10.1038/srep10272 |
_version_ | 1782371356290056192 |
---|---|
author | Tang, Kun Xu, Hua |
author_facet | Tang, Kun Xu, Hua |
author_sort | Tang, Kun |
collection | PubMed |
description | To identify a robust panel of microRNA (miRNA) signatures that can distinguish renal cell carcinoma (RCC) from normal kidney using miRNA expression levels. We performed a comprehensive meta-analysis of 29 published studies that compared the miRNA expression profiles of RCC tissues and adjacent normal tissues (NT) to determine candidate miRNAs as prognostic biomarkers for RCC. Using vote-counting strategy and robust rank aggregation method, we identified a statistically significant miRNA meta-signature of two upregulated (miR-21, miR-210) and three downregulated (miR-141, miR-200c and miR-429) miRNAs. X-tile plot was used to generate the optimum cut-off point for the 15 different deregulated miRNAs and Kaplan-Meier method was used to calculate CSS. In a cohort of 45 patients, the high expression of miR-21 (HR: 5.46, 95%CI: 2.02-53.39) and miR-210 (HR: 6.85, 95%CI: 2.13-43.36), the low expression of miR-141 (HR: 0.16, 95%CI: 0.004-0.18), miR-200c (HR: 0.08, 95%CI: 0.01-0.43) and miR-429 (HR: 0.18, 95%CI: 0.02-0.50) were associated with poor cancer-specific survival (CSS) following RCC resection. We also constructed a five-miRNAs-based classifier as a reliable prognostic and predictive tool for CSS in patients with RCC, especially in clear cell RCC (ccRCC) (HR: 5.46, 95% CI: 1.51-19.66). This method might facilitate patient counselling and individualise management of RCC. |
format | Online Article Text |
id | pubmed-4431463 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-44314632015-05-22 Prognostic value of meta-signature miRNAs in renal cell carcinoma: an integrated miRNA expression profiling analysis Tang, Kun Xu, Hua Sci Rep Article To identify a robust panel of microRNA (miRNA) signatures that can distinguish renal cell carcinoma (RCC) from normal kidney using miRNA expression levels. We performed a comprehensive meta-analysis of 29 published studies that compared the miRNA expression profiles of RCC tissues and adjacent normal tissues (NT) to determine candidate miRNAs as prognostic biomarkers for RCC. Using vote-counting strategy and robust rank aggregation method, we identified a statistically significant miRNA meta-signature of two upregulated (miR-21, miR-210) and three downregulated (miR-141, miR-200c and miR-429) miRNAs. X-tile plot was used to generate the optimum cut-off point for the 15 different deregulated miRNAs and Kaplan-Meier method was used to calculate CSS. In a cohort of 45 patients, the high expression of miR-21 (HR: 5.46, 95%CI: 2.02-53.39) and miR-210 (HR: 6.85, 95%CI: 2.13-43.36), the low expression of miR-141 (HR: 0.16, 95%CI: 0.004-0.18), miR-200c (HR: 0.08, 95%CI: 0.01-0.43) and miR-429 (HR: 0.18, 95%CI: 0.02-0.50) were associated with poor cancer-specific survival (CSS) following RCC resection. We also constructed a five-miRNAs-based classifier as a reliable prognostic and predictive tool for CSS in patients with RCC, especially in clear cell RCC (ccRCC) (HR: 5.46, 95% CI: 1.51-19.66). This method might facilitate patient counselling and individualise management of RCC. Nature Publishing Group 2015-05-14 /pmc/articles/PMC4431463/ /pubmed/25974855 http://dx.doi.org/10.1038/srep10272 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Tang, Kun Xu, Hua Prognostic value of meta-signature miRNAs in renal cell carcinoma: an integrated miRNA expression profiling analysis |
title | Prognostic value of meta-signature miRNAs in renal cell carcinoma: an integrated miRNA expression profiling analysis |
title_full | Prognostic value of meta-signature miRNAs in renal cell carcinoma: an integrated miRNA expression profiling analysis |
title_fullStr | Prognostic value of meta-signature miRNAs in renal cell carcinoma: an integrated miRNA expression profiling analysis |
title_full_unstemmed | Prognostic value of meta-signature miRNAs in renal cell carcinoma: an integrated miRNA expression profiling analysis |
title_short | Prognostic value of meta-signature miRNAs in renal cell carcinoma: an integrated miRNA expression profiling analysis |
title_sort | prognostic value of meta-signature mirnas in renal cell carcinoma: an integrated mirna expression profiling analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4431463/ https://www.ncbi.nlm.nih.gov/pubmed/25974855 http://dx.doi.org/10.1038/srep10272 |
work_keys_str_mv | AT tangkun prognosticvalueofmetasignaturemirnasinrenalcellcarcinomaanintegratedmirnaexpressionprofilinganalysis AT xuhua prognosticvalueofmetasignaturemirnasinrenalcellcarcinomaanintegratedmirnaexpressionprofilinganalysis |