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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...

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Autores principales: Lin, Peng, He, Rong-Quan, Dang, Yi-Wu, Wen, Dong-Yue, Ma, Jie, He, Yun, Chen, Gang, Yang, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2018
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.
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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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