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Key genes involved with prognosis were identified in lung adenocarcinoma by integrated bioinformatics analysis

OBJECTIVE: By screening the core genes in lung adenocarcinoma (LUAD) with bioinformatics, our study evaluated its prognosis value and role in infiltration process of immune cells. METHODS: Using GEO database, we screened 5 gene chips, including GSE11072, GSE32863, GSE43458, GSE115002, and GSE116959....

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Autores principales: Song, Hao, Wu, Junfeng, Liu, Wang, Cai, Kaier, Xie, Zhilong, Liu, Yingao, Huang, Jiandi, Gan, Siyuan, Xiong, Yinghuan, Sun, Yanqin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10258416/
https://www.ncbi.nlm.nih.gov/pubmed/37313154
http://dx.doi.org/10.1016/j.heliyon.2023.e16789
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author Song, Hao
Wu, Junfeng
Liu, Wang
Cai, Kaier
Xie, Zhilong
Liu, Yingao
Huang, Jiandi
Gan, Siyuan
Xiong, Yinghuan
Sun, Yanqin
author_facet Song, Hao
Wu, Junfeng
Liu, Wang
Cai, Kaier
Xie, Zhilong
Liu, Yingao
Huang, Jiandi
Gan, Siyuan
Xiong, Yinghuan
Sun, Yanqin
author_sort Song, Hao
collection PubMed
description OBJECTIVE: By screening the core genes in lung adenocarcinoma (LUAD) with bioinformatics, our study evaluated its prognosis value and role in infiltration process of immune cells. METHODS: Using GEO database, we screened 5 gene chips, including GSE11072, GSE32863, GSE43458, GSE115002, and GSE116959. Then, we obtained the corresponding differentially expressed genes by analyzed 5 gene chips online by GEO2R (P < 0.05, |logFC| > 1). Then, through DAVID online platform, Cytoscape 3.6.1 software and PPI network analysis, the network was visualized and obtain the final core genes. Next, we plan to use the GEPIA, UALCAN, Kaplan–Meier plotter and Time 2.0 database for corresponding analysis. The GEPIA database was used to verify the expression of core genes in LUAD and normal lung tissues, and survival analysis was used to evaluate the value of core genes in the prognosis of LUAD patients. UALCAN was used to verify the expression of the LUAD core gene and promoter methylation status, and the predictive value of core genes was evaluated in LUAD patients by the Kaplan–Meier plotter online tool. Then, we used the Time 2.0 database to identify the relationship to immune infiltration in LUAD. Finally, we used the human protein atlas (HPA) database for online immunohistochemical analysis of the expressed proteins. RESULTS: The expression of CCNB2 and CDC20 in LUAD were higher than those in normal lung tissues, their increased expression was negatively correlated with the overall survival rate of LUAD, and they were involved in cell cycle signal transduction, oocyte meiosis signal transduction as well as the infiltration process of immune cells in LUAD. The expression proteins of CCNB2 and CDC20 were also different in lung cancer tissue and normal lung tissue. Therefore, CCNB2 and CDC20 were identified as the vital core genes. CONCLUSION: CCNB2 and CDC20 are essential genes that may constitute prognostic biomarkers in LUAD, they also participate the immune infiltration process and protein expression process of LUAD, and might provides basis for clinical anti-tumor drug research.
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spelling pubmed-102584162023-06-13 Key genes involved with prognosis were identified in lung adenocarcinoma by integrated bioinformatics analysis Song, Hao Wu, Junfeng Liu, Wang Cai, Kaier Xie, Zhilong Liu, Yingao Huang, Jiandi Gan, Siyuan Xiong, Yinghuan Sun, Yanqin Heliyon Research Article OBJECTIVE: By screening the core genes in lung adenocarcinoma (LUAD) with bioinformatics, our study evaluated its prognosis value and role in infiltration process of immune cells. METHODS: Using GEO database, we screened 5 gene chips, including GSE11072, GSE32863, GSE43458, GSE115002, and GSE116959. Then, we obtained the corresponding differentially expressed genes by analyzed 5 gene chips online by GEO2R (P < 0.05, |logFC| > 1). Then, through DAVID online platform, Cytoscape 3.6.1 software and PPI network analysis, the network was visualized and obtain the final core genes. Next, we plan to use the GEPIA, UALCAN, Kaplan–Meier plotter and Time 2.0 database for corresponding analysis. The GEPIA database was used to verify the expression of core genes in LUAD and normal lung tissues, and survival analysis was used to evaluate the value of core genes in the prognosis of LUAD patients. UALCAN was used to verify the expression of the LUAD core gene and promoter methylation status, and the predictive value of core genes was evaluated in LUAD patients by the Kaplan–Meier plotter online tool. Then, we used the Time 2.0 database to identify the relationship to immune infiltration in LUAD. Finally, we used the human protein atlas (HPA) database for online immunohistochemical analysis of the expressed proteins. RESULTS: The expression of CCNB2 and CDC20 in LUAD were higher than those in normal lung tissues, their increased expression was negatively correlated with the overall survival rate of LUAD, and they were involved in cell cycle signal transduction, oocyte meiosis signal transduction as well as the infiltration process of immune cells in LUAD. The expression proteins of CCNB2 and CDC20 were also different in lung cancer tissue and normal lung tissue. Therefore, CCNB2 and CDC20 were identified as the vital core genes. CONCLUSION: CCNB2 and CDC20 are essential genes that may constitute prognostic biomarkers in LUAD, they also participate the immune infiltration process and protein expression process of LUAD, and might provides basis for clinical anti-tumor drug research. Elsevier 2023-05-29 /pmc/articles/PMC10258416/ /pubmed/37313154 http://dx.doi.org/10.1016/j.heliyon.2023.e16789 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Song, Hao
Wu, Junfeng
Liu, Wang
Cai, Kaier
Xie, Zhilong
Liu, Yingao
Huang, Jiandi
Gan, Siyuan
Xiong, Yinghuan
Sun, Yanqin
Key genes involved with prognosis were identified in lung adenocarcinoma by integrated bioinformatics analysis
title Key genes involved with prognosis were identified in lung adenocarcinoma by integrated bioinformatics analysis
title_full Key genes involved with prognosis were identified in lung adenocarcinoma by integrated bioinformatics analysis
title_fullStr Key genes involved with prognosis were identified in lung adenocarcinoma by integrated bioinformatics analysis
title_full_unstemmed Key genes involved with prognosis were identified in lung adenocarcinoma by integrated bioinformatics analysis
title_short Key genes involved with prognosis were identified in lung adenocarcinoma by integrated bioinformatics analysis
title_sort key genes involved with prognosis were identified in lung adenocarcinoma by integrated bioinformatics analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10258416/
https://www.ncbi.nlm.nih.gov/pubmed/37313154
http://dx.doi.org/10.1016/j.heliyon.2023.e16789
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