Identification of genes and analysis of prognostic values in nonsmoking females with non-small cell lung carcinoma by bioinformatics analyses
Authors Yang GD, Chen QY, Xiao JM, Zhang HL, Wang ZC, Lin XG
Received 17 May 2018
Accepted for publication 24 August 2018
Published 8 October 2018 Volume 2018:10 Pages 4287—4295
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Colin Mak
Peer reviewer comments 3
Editor who approved publication: Professor Nakshatri
Guangda Yang,1 Qianya Chen,1 Jieming Xiao,2 Hailiang Zhang,1 Zhichao Wang,1 Xiangan Lin3
1Department of Cancer Chemotherapy, Zengcheng District People’s Hospital of Guangzhou (BoJi-Affiliated Hospital of Sun Yat-Sen University), Guangzhou, China; 2Department of Emergency, Zengcheng District People’s Hospital of Guangzhou (BoJi-Affiliated Hospital of Sun Yat-Sen University), Guangzhou, China; 3Department of Cancer Chemotherapy, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China
Background: This study was performed to identify disease-related genes and analyze prognostic values in nonsmoking females with non-small cell lung carcinoma (NSCLC).
Materials and methods: Gene expression profile GSE19804 was downloaded from the Gene Expression Omnibus (GEO) database and analyzed by using GEO2R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used for the functional and pathway enrichment analysis. Then, the Search Tool for the Retrieval of Interacting Genes, Cytoscape, and Molecular Complex Detection were used to construct the protein–protein interaction (PPI) network and identify hub genes. Finally, the Kaplan–Meier plotter online tool was used for the overall survival analysis of hub genes.
Results: A cohort of 699 differentially expressed genes was screened, and they were mainly enriched in the terms of ECM–receptor interaction, focal adhesion, and cell adhesion molecules. A PPI network was constructed, and 15 hub genes were identified base on the subset of PPI network. Then, two significant modules were detected and several genes were found to be associated with the cell cycle pathway. Finally, nine hub genes’ (UBE2C, DLGAP5, TPX2, CCNB2, BIRC5, KIF20A, TOP2A, GNG11, and ANXA1) expressions were found to be associated with the prognosis of the patients.
Conclusion: Overall, we propose that the cell cycle pathway may play an important role in nonsmoking females with NSCLC and the nine hub genes may be further explored as potential targets for NSCLC diagnosis and treatment.
Keywords: non-small cell lung carcinoma, NSCLC, nonsmoking females, GEO2R, prognostic biomarkers, Kaplan–Meier plotter
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