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Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma

AIM: To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD). MATERIALS & METHODS: We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially e...

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Detalles Bibliográficos
Autores principales: Ren, Chuanli, Sun, Weixiu, Lian, Xu, Han, Chongxu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Future Medicine Ltd 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7186853/
https://www.ncbi.nlm.nih.gov/pubmed/32346404
http://dx.doi.org/10.2217/lmt-2020-0009
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author Ren, Chuanli
Sun, Weixiu
Lian, Xu
Han, Chongxu
author_facet Ren, Chuanli
Sun, Weixiu
Lian, Xu
Han, Chongxu
author_sort Ren, Chuanli
collection PubMed
description AIM: To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD). MATERIALS & METHODS: We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially expressed genes was constructed by STRING and Cytoscape. Finally, core genes were screened. The overall survival time of patients with the core genes was analyzed by Kaplan–Meier method. Gene ontology and Kyoto encyclopedia of genes and genomes bioaccumulation was calculated by DAVID. RESULTS: Functional enrichment analysis indicated that nine key genes were actively involved in the biological process of smoking-related LUAD. CONCLUSION: 23 core genes and nine key genes among them were correlated with adverse prognosis of LUAD induced by smoking.
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spelling pubmed-71868532020-04-28 Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma Ren, Chuanli Sun, Weixiu Lian, Xu Han, Chongxu Lung Cancer Manag Short Communication AIM: To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD). MATERIALS & METHODS: We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially expressed genes was constructed by STRING and Cytoscape. Finally, core genes were screened. The overall survival time of patients with the core genes was analyzed by Kaplan–Meier method. Gene ontology and Kyoto encyclopedia of genes and genomes bioaccumulation was calculated by DAVID. RESULTS: Functional enrichment analysis indicated that nine key genes were actively involved in the biological process of smoking-related LUAD. CONCLUSION: 23 core genes and nine key genes among them were correlated with adverse prognosis of LUAD induced by smoking. Future Medicine Ltd 2020-04-27 /pmc/articles/PMC7186853/ /pubmed/32346404 http://dx.doi.org/10.2217/lmt-2020-0009 Text en © 2020 Chuanli Ren This work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License (http://creativecommons.org/licenses/by-nc-nd/4.0/)
spellingShingle Short Communication
Ren, Chuanli
Sun, Weixiu
Lian, Xu
Han, Chongxu
Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma
title Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma
title_full Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma
title_fullStr Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma
title_full_unstemmed Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma
title_short Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma
title_sort identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma
topic Short Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7186853/
https://www.ncbi.nlm.nih.gov/pubmed/32346404
http://dx.doi.org/10.2217/lmt-2020-0009
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