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Using microRNAs as Novel Predictors of Urologic Cancer Survival: An Integrated Analysis

BACKGROUND: MicroRNAs(miRNAs) are involved in the formation, maintenance, and metastasis of urologic cancer. Here, we aim to gather and evaluate all of the evidence regarding the potential role of miRNAs as novel predictors of urologic cancer survival. METHODS: A systematic review was performed to i...

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Autores principales: Chen, Zhicong, Zhan, Yonghao, Chi, Jieshan, Guo, Shuyuan, Zhong, Xinliang, He, Anbang, Zheng, Jianrong, Gong, Yanqing, Li, Xuesong, Zhou, Liqun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6116416/
https://www.ncbi.nlm.nih.gov/pubmed/30037718
http://dx.doi.org/10.1016/j.ebiom.2018.07.014
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author Chen, Zhicong
Zhan, Yonghao
Chi, Jieshan
Guo, Shuyuan
Zhong, Xinliang
He, Anbang
Zheng, Jianrong
Gong, Yanqing
Li, Xuesong
Zhou, Liqun
author_facet Chen, Zhicong
Zhan, Yonghao
Chi, Jieshan
Guo, Shuyuan
Zhong, Xinliang
He, Anbang
Zheng, Jianrong
Gong, Yanqing
Li, Xuesong
Zhou, Liqun
author_sort Chen, Zhicong
collection PubMed
description BACKGROUND: MicroRNAs(miRNAs) are involved in the formation, maintenance, and metastasis of urologic cancer. Here, we aim to gather and evaluate all of the evidence regarding the potential role of miRNAs as novel predictors of urologic cancer survival. METHODS: A systematic review was performed to identify and score all of the published studies that evaluated the prognostic effects of miRNAs in kidney (KCa), bladder (BCa) or prostate cancer (PCa). Where appropriate, the summary effects of miRNAs on urologic cancer were meta-analysed. The reliability of those results was then further validated by an integrated analysis of the TCGA cohort and miRNA panel. RESULTS: Of 151 datasets, 80 miRNAs were enrolled in this systematic review. A meta-analysis of the prognostic qualities of each miRNA identified an objective association between miRNA and prognosis. miR-21 was identified as an unfavourable miRNA with the overall survival (HR:2.699, 1.76–4.14, P < 0.001) across various prognostic events. Our further meta-analyses, integrating a parallel TCGA analysis, confirmed these partial previous results and further revealed different summary effects, such as the moderate effect of miR-21 in BCa. The refined miRNA panel (KCa-6: miR-27b, −942, −497, −144, −141 and -27a) was more capable of predicting the overall survival than was any single miRNAs included in it (HR: 3.214, 1.971–5.240, P < 0.01). CONCLUSIONS: A miRNA panel may be able to determine the prognosis of urologic tumour more effectively and compensate for the unreliability of individual miRNA in estimating prognosis. More large-scale studies are therefore required to evaluate the unbiased prognostic value of miRNAs in urologic cancer effectively.
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spelling pubmed-61164162018-08-31 Using microRNAs as Novel Predictors of Urologic Cancer Survival: An Integrated Analysis Chen, Zhicong Zhan, Yonghao Chi, Jieshan Guo, Shuyuan Zhong, Xinliang He, Anbang Zheng, Jianrong Gong, Yanqing Li, Xuesong Zhou, Liqun EBioMedicine Research Paper BACKGROUND: MicroRNAs(miRNAs) are involved in the formation, maintenance, and metastasis of urologic cancer. Here, we aim to gather and evaluate all of the evidence regarding the potential role of miRNAs as novel predictors of urologic cancer survival. METHODS: A systematic review was performed to identify and score all of the published studies that evaluated the prognostic effects of miRNAs in kidney (KCa), bladder (BCa) or prostate cancer (PCa). Where appropriate, the summary effects of miRNAs on urologic cancer were meta-analysed. The reliability of those results was then further validated by an integrated analysis of the TCGA cohort and miRNA panel. RESULTS: Of 151 datasets, 80 miRNAs were enrolled in this systematic review. A meta-analysis of the prognostic qualities of each miRNA identified an objective association between miRNA and prognosis. miR-21 was identified as an unfavourable miRNA with the overall survival (HR:2.699, 1.76–4.14, P < 0.001) across various prognostic events. Our further meta-analyses, integrating a parallel TCGA analysis, confirmed these partial previous results and further revealed different summary effects, such as the moderate effect of miR-21 in BCa. The refined miRNA panel (KCa-6: miR-27b, −942, −497, −144, −141 and -27a) was more capable of predicting the overall survival than was any single miRNAs included in it (HR: 3.214, 1.971–5.240, P < 0.01). CONCLUSIONS: A miRNA panel may be able to determine the prognosis of urologic tumour more effectively and compensate for the unreliability of individual miRNA in estimating prognosis. More large-scale studies are therefore required to evaluate the unbiased prognostic value of miRNAs in urologic cancer effectively. Elsevier 2018-07-21 /pmc/articles/PMC6116416/ /pubmed/30037718 http://dx.doi.org/10.1016/j.ebiom.2018.07.014 Text en © 2018 Published by Elsevier B.V. http://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 Paper
Chen, Zhicong
Zhan, Yonghao
Chi, Jieshan
Guo, Shuyuan
Zhong, Xinliang
He, Anbang
Zheng, Jianrong
Gong, Yanqing
Li, Xuesong
Zhou, Liqun
Using microRNAs as Novel Predictors of Urologic Cancer Survival: An Integrated Analysis
title Using microRNAs as Novel Predictors of Urologic Cancer Survival: An Integrated Analysis
title_full Using microRNAs as Novel Predictors of Urologic Cancer Survival: An Integrated Analysis
title_fullStr Using microRNAs as Novel Predictors of Urologic Cancer Survival: An Integrated Analysis
title_full_unstemmed Using microRNAs as Novel Predictors of Urologic Cancer Survival: An Integrated Analysis
title_short Using microRNAs as Novel Predictors of Urologic Cancer Survival: An Integrated Analysis
title_sort using micrornas as novel predictors of urologic cancer survival: an integrated analysis
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6116416/
https://www.ncbi.nlm.nih.gov/pubmed/30037718
http://dx.doi.org/10.1016/j.ebiom.2018.07.014
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