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Several microRNAs could predict survival in patients with hepatitis B-related liver cancer
MicroRNAs as biomarkers play an important role in the tumorigenesis process, including hepatocellular carcinomas (HCCs). In this paper, we used The Cancer Genome Atlas (TCGA) database to mine hepatitis B-related liver cancer microRNAs that could predict survival in patients with hepatitis B-related...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5359660/ https://www.ncbi.nlm.nih.gov/pubmed/28322348 http://dx.doi.org/10.1038/srep45195 |
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author | Zhen, Ye Xinghui, Zhao Chao, Wu Yi, Zhao Jinwen, Chen Ruifang, Gao Chao, Zhang Min, Zhao Chunlei, Guo Yan, Fang Lingfang, Du Long, Shen Wenzhi, Shen Xiaohe, Luo Rong, Xiang |
author_facet | Zhen, Ye Xinghui, Zhao Chao, Wu Yi, Zhao Jinwen, Chen Ruifang, Gao Chao, Zhang Min, Zhao Chunlei, Guo Yan, Fang Lingfang, Du Long, Shen Wenzhi, Shen Xiaohe, Luo Rong, Xiang |
author_sort | Zhen, Ye |
collection | PubMed |
description | MicroRNAs as biomarkers play an important role in the tumorigenesis process, including hepatocellular carcinomas (HCCs). In this paper, we used The Cancer Genome Atlas (TCGA) database to mine hepatitis B-related liver cancer microRNAs that could predict survival in patients with hepatitis B-related liver cancer. There were 93 cases of HBV-HCC and 49 cases of adjacent normal controls included in the study. Kaplan–Meier survival analysis of a liver cancer group versus a normal control group of differentially expressed genes identified eight genes with statistical significance. Compared with the normal liver cell line, hepatocellular carcinoma cell lines had high expression of 8 microRNAs, albeit at different levels. A Cox proportional hazards regression model for multivariate analysis showed that four genes had a significant difference. We established classification models to distinguish short survival time and long survival time of liver cancers. Eight genes (mir9-3, mir10b, mir31, mir519c, mir522, mir3660, mir4784, and mir6883) were identified could predict survival in patients with HBV-HCC. There was a significant correlation between mir10b and mir31 and clinical stages (p < 0.05). A random forests model effectively estimated patient survival times. |
format | Online Article Text |
id | pubmed-5359660 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53596602017-03-22 Several microRNAs could predict survival in patients with hepatitis B-related liver cancer Zhen, Ye Xinghui, Zhao Chao, Wu Yi, Zhao Jinwen, Chen Ruifang, Gao Chao, Zhang Min, Zhao Chunlei, Guo Yan, Fang Lingfang, Du Long, Shen Wenzhi, Shen Xiaohe, Luo Rong, Xiang Sci Rep Article MicroRNAs as biomarkers play an important role in the tumorigenesis process, including hepatocellular carcinomas (HCCs). In this paper, we used The Cancer Genome Atlas (TCGA) database to mine hepatitis B-related liver cancer microRNAs that could predict survival in patients with hepatitis B-related liver cancer. There were 93 cases of HBV-HCC and 49 cases of adjacent normal controls included in the study. Kaplan–Meier survival analysis of a liver cancer group versus a normal control group of differentially expressed genes identified eight genes with statistical significance. Compared with the normal liver cell line, hepatocellular carcinoma cell lines had high expression of 8 microRNAs, albeit at different levels. A Cox proportional hazards regression model for multivariate analysis showed that four genes had a significant difference. We established classification models to distinguish short survival time and long survival time of liver cancers. Eight genes (mir9-3, mir10b, mir31, mir519c, mir522, mir3660, mir4784, and mir6883) were identified could predict survival in patients with HBV-HCC. There was a significant correlation between mir10b and mir31 and clinical stages (p < 0.05). A random forests model effectively estimated patient survival times. Nature Publishing Group 2017-03-21 /pmc/articles/PMC5359660/ /pubmed/28322348 http://dx.doi.org/10.1038/srep45195 Text en Copyright © 2017, The Author(s) 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 Zhen, Ye Xinghui, Zhao Chao, Wu Yi, Zhao Jinwen, Chen Ruifang, Gao Chao, Zhang Min, Zhao Chunlei, Guo Yan, Fang Lingfang, Du Long, Shen Wenzhi, Shen Xiaohe, Luo Rong, Xiang Several microRNAs could predict survival in patients with hepatitis B-related liver cancer |
title | Several microRNAs could predict survival in patients with hepatitis B-related liver cancer |
title_full | Several microRNAs could predict survival in patients with hepatitis B-related liver cancer |
title_fullStr | Several microRNAs could predict survival in patients with hepatitis B-related liver cancer |
title_full_unstemmed | Several microRNAs could predict survival in patients with hepatitis B-related liver cancer |
title_short | Several microRNAs could predict survival in patients with hepatitis B-related liver cancer |
title_sort | several micrornas could predict survival in patients with hepatitis b-related liver cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5359660/ https://www.ncbi.nlm.nih.gov/pubmed/28322348 http://dx.doi.org/10.1038/srep45195 |
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