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A six‐microRNA signature to predict outcomes of patients with gastric cancer

Gastric cancer (GC) is a common gastrointestinal tumor with poor prognosis. However, conventional prognostic factors cannot accurately predict the outcomes of GC patients. Therefore, there remains a need to identify novel predictive markers to improve prognosis. In this study, we obtained microRNA e...

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Autores principales: Chen, Jian, Hu, Bing, Wang, Wei, Qian, Xiao‐jun, Shan, Ben‐jie, He, Yi‐fu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6396146/
https://www.ncbi.nlm.nih.gov/pubmed/30868062
http://dx.doi.org/10.1002/2211-5463.12593
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author Chen, Jian
Hu, Bing
Wang, Wei
Qian, Xiao‐jun
Shan, Ben‐jie
He, Yi‐fu
author_facet Chen, Jian
Hu, Bing
Wang, Wei
Qian, Xiao‐jun
Shan, Ben‐jie
He, Yi‐fu
author_sort Chen, Jian
collection PubMed
description Gastric cancer (GC) is a common gastrointestinal tumor with poor prognosis. However, conventional prognostic factors cannot accurately predict the outcomes of GC patients. Therefore, there remains a need to identify novel predictive markers to improve prognosis. In this study, we obtained microRNA expression profiles of 385 GC patients from The Cancer Genome Atlas. We performed Cox regression analysis to identify overall survival‐related microRNA and then constructed a microRNA signature‐based prognostic model. The accuracy of the model was evaluated and validated through Kaplan–Meier survival analysis and time‐dependent receiver operating characteristic (ROC) curve analysis. The independent prognostic value of the model was assessed by multivariate Cox regression analysis. Enrichment analysis was performed to explore potential functions of the prognostic microRNA. Finally, a prognostic model based on a six‐microRNA (miRNA‐100, miRNA‐374a, miRNA‐509‐3, miRNA‐668, miRNA‐549, and miRNA‐653) signature was developed. Further analysis in the training, test, and complete The Cancer Genome Atlas set showed the model can distinguish between high‐risk and low‐risk patients and predict 3‐year and 5‐year survival. The six‐microRNA signature was also an independent prognostic marker, and enrichment analysis suggested that the microRNA may be involved in cell cycle and mitosis. These results demonstrated that the model based on the six‐microRNA signature can be used to accurately predict the prognosis of GC patients.
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spelling pubmed-63961462019-03-13 A six‐microRNA signature to predict outcomes of patients with gastric cancer Chen, Jian Hu, Bing Wang, Wei Qian, Xiao‐jun Shan, Ben‐jie He, Yi‐fu FEBS Open Bio Research Articles Gastric cancer (GC) is a common gastrointestinal tumor with poor prognosis. However, conventional prognostic factors cannot accurately predict the outcomes of GC patients. Therefore, there remains a need to identify novel predictive markers to improve prognosis. In this study, we obtained microRNA expression profiles of 385 GC patients from The Cancer Genome Atlas. We performed Cox regression analysis to identify overall survival‐related microRNA and then constructed a microRNA signature‐based prognostic model. The accuracy of the model was evaluated and validated through Kaplan–Meier survival analysis and time‐dependent receiver operating characteristic (ROC) curve analysis. The independent prognostic value of the model was assessed by multivariate Cox regression analysis. Enrichment analysis was performed to explore potential functions of the prognostic microRNA. Finally, a prognostic model based on a six‐microRNA (miRNA‐100, miRNA‐374a, miRNA‐509‐3, miRNA‐668, miRNA‐549, and miRNA‐653) signature was developed. Further analysis in the training, test, and complete The Cancer Genome Atlas set showed the model can distinguish between high‐risk and low‐risk patients and predict 3‐year and 5‐year survival. The six‐microRNA signature was also an independent prognostic marker, and enrichment analysis suggested that the microRNA may be involved in cell cycle and mitosis. These results demonstrated that the model based on the six‐microRNA signature can be used to accurately predict the prognosis of GC patients. John Wiley and Sons Inc. 2019-01-31 /pmc/articles/PMC6396146/ /pubmed/30868062 http://dx.doi.org/10.1002/2211-5463.12593 Text en © 2019 The Authors. Published by FEBS Press and John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Chen, Jian
Hu, Bing
Wang, Wei
Qian, Xiao‐jun
Shan, Ben‐jie
He, Yi‐fu
A six‐microRNA signature to predict outcomes of patients with gastric cancer
title A six‐microRNA signature to predict outcomes of patients with gastric cancer
title_full A six‐microRNA signature to predict outcomes of patients with gastric cancer
title_fullStr A six‐microRNA signature to predict outcomes of patients with gastric cancer
title_full_unstemmed A six‐microRNA signature to predict outcomes of patients with gastric cancer
title_short A six‐microRNA signature to predict outcomes of patients with gastric cancer
title_sort six‐microrna signature to predict outcomes of patients with gastric cancer
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6396146/
https://www.ncbi.nlm.nih.gov/pubmed/30868062
http://dx.doi.org/10.1002/2211-5463.12593
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