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General Physiology and Biophysics Vol.40, No.1, p.31–48, 2021 |
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Title: Identification of differentially expressed genes associated with lung adenocarcinoma via bioinformatics analysis | ||
Author: Xinmeng Yang, Qingchuan Feng, Jianan Jing, Jiahui Yan, Zhaoshu Zeng, Hao Zheng, Xiaoli Cheng | ||
Abstract: Lung adenocarcinoma (LUAD) with extremely high morbidity as well as mortality is still in the exploration stage of pathogenesis and treatment. This study aimed to screen and identify differentially expressed genes (DEGs) associated with LUAD via bioinformatics analysis. Three LUAD microarray datasets, GSE116959, GSE68571 and GSE40791, were selected from the Gene Expression Omnibus (GEO) database to analyze the DEGs. 128 DEGs were identified in all, incorporating 36 upregulated and 92 downregulated. Function and pathway enrichment analyses showed that metabolic pathways were their main signaling pathways. After that, seven hub genes including VWF, SPP1, PECAM1, TOP2A, CDK1, UBE2C and KIF23 were mined by the protein-protein interaction (PPI) network. Gene expression analysis, TNM and survival analysis of these hub genes were performed via Gene Expression Profiling Interactive Analysis (GEPIA) online database. Further analysis indicated that TOP2A, CDK1, UBE2C and KIF23 were related to the stage of LUAD patients and overall survival. Then, we verified the relative expression levels of TOP2A, CDK1, UBE2C and KIF23 in LUAD cell lines by qRT-PCR. In conclusion, this study indicated that the four hub genes screened out by bioinformatics analysis were differentially expressed in LUAD compared to normal sample and might be prognostic markers of LUAD. |
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Keywords: Lung adenocarcinoma, Differentially expressed genes, Microarray datasets, Bioinformatics analysis, Hub genes | ||
Published online: 09-Feb-2021 | ||
Year: 2021, Volume: 40, Issue: 1 | Page From: 31, Page To: 48 | |
doi:10.4149/gpb_2020037 |
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