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A two-gene-based prognostic signature for pancreatic cancer

The purpose of this study was to identify a vital gene signature that has prognostic value for pancreatic cancer based on gene expression datasets from the Cancer Genome Atlas and Gene Expression Omnibus. A total of 34 genes were obtained by the univariate analysis, which were significantly associat...

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Autores principales: Zhou, Shuyi, Yan, Yuanliang, Chen, Xi, Zeng, Shuangshuang, Wei, Jie, Wang, Xiang, Gong, Zhicheng, Xu, Zhijie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7585105/
https://www.ncbi.nlm.nih.gov/pubmed/32966237
http://dx.doi.org/10.18632/aging.103698
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author Zhou, Shuyi
Yan, Yuanliang
Chen, Xi
Zeng, Shuangshuang
Wei, Jie
Wang, Xiang
Gong, Zhicheng
Xu, Zhijie
author_facet Zhou, Shuyi
Yan, Yuanliang
Chen, Xi
Zeng, Shuangshuang
Wei, Jie
Wang, Xiang
Gong, Zhicheng
Xu, Zhijie
author_sort Zhou, Shuyi
collection PubMed
description The purpose of this study was to identify a vital gene signature that has prognostic value for pancreatic cancer based on gene expression datasets from the Cancer Genome Atlas and Gene Expression Omnibus. A total of 34 genes were obtained by the univariate analysis, which were significantly associated with the overall survival of PC patients. After further analysis, Anillin (ANLN) and Histone H1c (HIST1H1C) were identified and considered to be the most significant prognostic genes among the 34 genes. A prognostic model based on these two genes was constructed, and successfully distinguished pancreatic cancer survival into high-risk and low-risk groups in the training set and testing set. Subsequently, independent predictive factors, including the age, margin condition and risk score, were then employed to construct the nomogram model. The area under curve for the nomogram model was 0.826 at 0.5 years and 0.726 at 1 year, and the C-index of the nomogram model was 0.664 higher than the others variables alone. These findings have indicated that high expression of ANLN and HIST1H1C predicted poor outcomes for patients with pancreatic cancer. The nomogram model based on the expression of two genes could be valuable for the guidance of clinical treatment.
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spelling pubmed-75851052020-11-03 A two-gene-based prognostic signature for pancreatic cancer Zhou, Shuyi Yan, Yuanliang Chen, Xi Zeng, Shuangshuang Wei, Jie Wang, Xiang Gong, Zhicheng Xu, Zhijie Aging (Albany NY) Research Paper The purpose of this study was to identify a vital gene signature that has prognostic value for pancreatic cancer based on gene expression datasets from the Cancer Genome Atlas and Gene Expression Omnibus. A total of 34 genes were obtained by the univariate analysis, which were significantly associated with the overall survival of PC patients. After further analysis, Anillin (ANLN) and Histone H1c (HIST1H1C) were identified and considered to be the most significant prognostic genes among the 34 genes. A prognostic model based on these two genes was constructed, and successfully distinguished pancreatic cancer survival into high-risk and low-risk groups in the training set and testing set. Subsequently, independent predictive factors, including the age, margin condition and risk score, were then employed to construct the nomogram model. The area under curve for the nomogram model was 0.826 at 0.5 years and 0.726 at 1 year, and the C-index of the nomogram model was 0.664 higher than the others variables alone. These findings have indicated that high expression of ANLN and HIST1H1C predicted poor outcomes for patients with pancreatic cancer. The nomogram model based on the expression of two genes could be valuable for the guidance of clinical treatment. Impact Journals 2020-09-23 /pmc/articles/PMC7585105/ /pubmed/32966237 http://dx.doi.org/10.18632/aging.103698 Text en Copyright: © 2020 Zhou et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Zhou, Shuyi
Yan, Yuanliang
Chen, Xi
Zeng, Shuangshuang
Wei, Jie
Wang, Xiang
Gong, Zhicheng
Xu, Zhijie
A two-gene-based prognostic signature for pancreatic cancer
title A two-gene-based prognostic signature for pancreatic cancer
title_full A two-gene-based prognostic signature for pancreatic cancer
title_fullStr A two-gene-based prognostic signature for pancreatic cancer
title_full_unstemmed A two-gene-based prognostic signature for pancreatic cancer
title_short A two-gene-based prognostic signature for pancreatic cancer
title_sort two-gene-based prognostic signature for pancreatic cancer
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7585105/
https://www.ncbi.nlm.nih.gov/pubmed/32966237
http://dx.doi.org/10.18632/aging.103698
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