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Prognostic implications of autophagy-associated gene signatures in non-small cell lung cancer

Autophagy, a highly conserved cellular proteolysis process, has been involved in non-small cell lung cancer (NSCLC). We tried to develop a prognostic prediction model for NSCLC patients based on the expression profiles of autophagy-associated genes. Univariate Cox regression analysis was used to det...

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Autores principales: Liu, Yang, Wu, Ligao, Ao, Haijiao, Zhao, Meng, Leng, Xue, Liu, Mingdong, Ma, Jianqun, Zhu, Jinhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6932887/
https://www.ncbi.nlm.nih.gov/pubmed/31811814
http://dx.doi.org/10.18632/aging.102544
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author Liu, Yang
Wu, Ligao
Ao, Haijiao
Zhao, Meng
Leng, Xue
Liu, Mingdong
Ma, Jianqun
Zhu, Jinhong
author_facet Liu, Yang
Wu, Ligao
Ao, Haijiao
Zhao, Meng
Leng, Xue
Liu, Mingdong
Ma, Jianqun
Zhu, Jinhong
author_sort Liu, Yang
collection PubMed
description Autophagy, a highly conserved cellular proteolysis process, has been involved in non-small cell lung cancer (NSCLC). We tried to develop a prognostic prediction model for NSCLC patients based on the expression profiles of autophagy-associated genes. Univariate Cox regression analysis was used to determine autophagy-associated genes significantly correlated with overall survival (OS) of the TCGA lung cancer cohort. LASSO regression was performed to build multiple-gene prognostic signatures. We found that the 22-gene and 11-gene signatures could dichotomize patients with significantly different OS and independently predict the OS in TCGA lung adenocarcinoma (HR=2.801, 95% CI=2.252-3.486, P<0.001) and squamous cell carcinoma (HR=1.105, 95% CI=1.067-1.145, P<0.001), respectively. The prognostic performance of the 22-gene signature was validated in four GEO lung cancer cohorts. Moreover, GO, KEGG, and GSEA analyses unveiled several fundamental signaling pathways and cellular processes associated with the 22-gene signature in lung adenocarcinoma. We also constructed a clinical nomogram with a concordance index of 0.71 to predict the survival possibility of NSCLC patients by integrating clinical characteristics and the autophagy gene signature. The calibration curves substantiated fine concordance between nomogram prediction and actual observation. Overall, we constructed and verified a novel autophagy-associated gene signature that could improve the individualized outcome prediction in NSCLC.
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spelling pubmed-69328872020-01-03 Prognostic implications of autophagy-associated gene signatures in non-small cell lung cancer Liu, Yang Wu, Ligao Ao, Haijiao Zhao, Meng Leng, Xue Liu, Mingdong Ma, Jianqun Zhu, Jinhong Aging (Albany NY) Research Paper Autophagy, a highly conserved cellular proteolysis process, has been involved in non-small cell lung cancer (NSCLC). We tried to develop a prognostic prediction model for NSCLC patients based on the expression profiles of autophagy-associated genes. Univariate Cox regression analysis was used to determine autophagy-associated genes significantly correlated with overall survival (OS) of the TCGA lung cancer cohort. LASSO regression was performed to build multiple-gene prognostic signatures. We found that the 22-gene and 11-gene signatures could dichotomize patients with significantly different OS and independently predict the OS in TCGA lung adenocarcinoma (HR=2.801, 95% CI=2.252-3.486, P<0.001) and squamous cell carcinoma (HR=1.105, 95% CI=1.067-1.145, P<0.001), respectively. The prognostic performance of the 22-gene signature was validated in four GEO lung cancer cohorts. Moreover, GO, KEGG, and GSEA analyses unveiled several fundamental signaling pathways and cellular processes associated with the 22-gene signature in lung adenocarcinoma. We also constructed a clinical nomogram with a concordance index of 0.71 to predict the survival possibility of NSCLC patients by integrating clinical characteristics and the autophagy gene signature. The calibration curves substantiated fine concordance between nomogram prediction and actual observation. Overall, we constructed and verified a novel autophagy-associated gene signature that could improve the individualized outcome prediction in NSCLC. Impact Journals 2019-12-07 /pmc/articles/PMC6932887/ /pubmed/31811814 http://dx.doi.org/10.18632/aging.102544 Text en Copyright © 2019 Liu 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 (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
Liu, Yang
Wu, Ligao
Ao, Haijiao
Zhao, Meng
Leng, Xue
Liu, Mingdong
Ma, Jianqun
Zhu, Jinhong
Prognostic implications of autophagy-associated gene signatures in non-small cell lung cancer
title Prognostic implications of autophagy-associated gene signatures in non-small cell lung cancer
title_full Prognostic implications of autophagy-associated gene signatures in non-small cell lung cancer
title_fullStr Prognostic implications of autophagy-associated gene signatures in non-small cell lung cancer
title_full_unstemmed Prognostic implications of autophagy-associated gene signatures in non-small cell lung cancer
title_short Prognostic implications of autophagy-associated gene signatures in non-small cell lung cancer
title_sort prognostic implications of autophagy-associated gene signatures in non-small cell lung cancer
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6932887/
https://www.ncbi.nlm.nih.gov/pubmed/31811814
http://dx.doi.org/10.18632/aging.102544
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