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An autophagy-related gene expression signature for survival prediction in multiple cohorts of hepatocellular carcinoma patients
Prognostic signatures have been proposed as clinical tools to estimate prognosis in hepatocellular carcinoma (HCC), which is the second most common contributor to cancer-related death at present globally. Autophagy-related genes play a dynamic and fundamental role in HCC, but knowledge of their util...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5915122/ https://www.ncbi.nlm.nih.gov/pubmed/29707114 http://dx.doi.org/10.18632/oncotarget.24089 |
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author | Lin, Peng He, Rong-Quan Dang, Yi-Wu Wen, Dong-Yue Ma, Jie He, Yun Chen, Gang Yang, Hong |
author_facet | Lin, Peng He, Rong-Quan Dang, Yi-Wu Wen, Dong-Yue Ma, Jie He, Yun Chen, Gang Yang, Hong |
author_sort | Lin, Peng |
collection | PubMed |
description | Prognostic signatures have been proposed as clinical tools to estimate prognosis in hepatocellular carcinoma (HCC), which is the second most common contributor to cancer-related death at present globally. Autophagy-related genes play a dynamic and fundamental role in HCC, but knowledge of their utility as prognostic markers is limited. Here, we facilitated univariate and multivariate Cox proportional hazards regression analyses to reveal that 3 autophagy-related genes (BIRC5, FOXO1 and SQSTM1) were closely related to the survival of HCC. Then, we generated a prognosis index (PI) for predicting overall survival (OS) based on the three genes, which was an independent prognostic indicator for the OS of HCC (HR = 1.930, 95% CI: 1.200–3.104, P = 0.007). The PI showed moderate performance for predicting the survival of HCC patients and its efficacy was validated by data from three microarrays (GSE10143, GSE10186 and GSE17856). Furthermore, we deeply mined the integrated large-scale datasets from public microarrays and immunohistochemistry to validate the overexpression of BIRC5 and SQSTM1 while down-regulated FOXO1 expression in HCC. Bioinformatic analysis offered the hypothesis that proliferative signals in high-risk HCC patients were disturbing and thereby facilitated inferior clinical outcomes. Collectively, the prognostic signature we proposed is a promising biomarker for monitoring outcome of HCC. Nevertheless, prospective experimental studies are needed to validate the clinical utility. |
format | Online Article Text |
id | pubmed-5915122 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-59151222018-04-27 An autophagy-related gene expression signature for survival prediction in multiple cohorts of hepatocellular carcinoma patients Lin, Peng He, Rong-Quan Dang, Yi-Wu Wen, Dong-Yue Ma, Jie He, Yun Chen, Gang Yang, Hong Oncotarget Research Paper Prognostic signatures have been proposed as clinical tools to estimate prognosis in hepatocellular carcinoma (HCC), which is the second most common contributor to cancer-related death at present globally. Autophagy-related genes play a dynamic and fundamental role in HCC, but knowledge of their utility as prognostic markers is limited. Here, we facilitated univariate and multivariate Cox proportional hazards regression analyses to reveal that 3 autophagy-related genes (BIRC5, FOXO1 and SQSTM1) were closely related to the survival of HCC. Then, we generated a prognosis index (PI) for predicting overall survival (OS) based on the three genes, which was an independent prognostic indicator for the OS of HCC (HR = 1.930, 95% CI: 1.200–3.104, P = 0.007). The PI showed moderate performance for predicting the survival of HCC patients and its efficacy was validated by data from three microarrays (GSE10143, GSE10186 and GSE17856). Furthermore, we deeply mined the integrated large-scale datasets from public microarrays and immunohistochemistry to validate the overexpression of BIRC5 and SQSTM1 while down-regulated FOXO1 expression in HCC. Bioinformatic analysis offered the hypothesis that proliferative signals in high-risk HCC patients were disturbing and thereby facilitated inferior clinical outcomes. Collectively, the prognostic signature we proposed is a promising biomarker for monitoring outcome of HCC. Nevertheless, prospective experimental studies are needed to validate the clinical utility. Impact Journals LLC 2018-01-09 /pmc/articles/PMC5915122/ /pubmed/29707114 http://dx.doi.org/10.18632/oncotarget.24089 Text en Copyright: © 2018 Lin et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.t |
spellingShingle | Research Paper Lin, Peng He, Rong-Quan Dang, Yi-Wu Wen, Dong-Yue Ma, Jie He, Yun Chen, Gang Yang, Hong An autophagy-related gene expression signature for survival prediction in multiple cohorts of hepatocellular carcinoma patients |
title | An autophagy-related gene expression signature for survival prediction in multiple cohorts of hepatocellular carcinoma patients |
title_full | An autophagy-related gene expression signature for survival prediction in multiple cohorts of hepatocellular carcinoma patients |
title_fullStr | An autophagy-related gene expression signature for survival prediction in multiple cohorts of hepatocellular carcinoma patients |
title_full_unstemmed | An autophagy-related gene expression signature for survival prediction in multiple cohorts of hepatocellular carcinoma patients |
title_short | An autophagy-related gene expression signature for survival prediction in multiple cohorts of hepatocellular carcinoma patients |
title_sort | autophagy-related gene expression signature for survival prediction in multiple cohorts of hepatocellular carcinoma patients |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5915122/ https://www.ncbi.nlm.nih.gov/pubmed/29707114 http://dx.doi.org/10.18632/oncotarget.24089 |
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