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 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.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2019 |
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Erschienen: |
2019 |
Enthalten in: |
Zur Gesamtaufnahme - volume:11 |
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Enthalten in: |
Aging - 11(2019), 23 vom: 07. Dez., Seite 11440-11462 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Liu, Yang [VerfasserIn] |
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Links: |
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Themen: |
63231-63-0 |
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Anmerkungen: |
Date Completed 23.10.2020 Date Revised 23.10.2020 published: Print-Electronic Citation Status MEDLINE |
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doi: |
10.18632/aging.102544 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM304133795 |
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520 | |a 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 | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a Research Support, Non-U.S. Gov't | |
650 | 4 | |a NSCLC | |
650 | 4 | |a autophagy | |
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650 | 4 | |a nomogram | |
650 | 4 | |a prognosis | |
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700 | 1 | |a Wu, Ligao |e verfasserin |4 aut | |
700 | 1 | |a Ao, Haijiao |e verfasserin |4 aut | |
700 | 1 | |a Zhao, Meng |e verfasserin |4 aut | |
700 | 1 | |a Leng, Xue |e verfasserin |4 aut | |
700 | 1 | |a Liu, Mingdong |e verfasserin |4 aut | |
700 | 1 | |a Ma, Jianqun |e verfasserin |4 aut | |
700 | 1 | |a Zhu, Jinhong |e verfasserin |4 aut | |
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