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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Future Medicine Ltd
2020
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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. |
format | Online Article Text |
id | pubmed-7186853 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Future Medicine Ltd |
record_format | MEDLINE/PubMed |
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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