Integrated analysis reveals key genes with prognostic value in lung adenocarcinoma

• Published in: Cancer management and research Vol. 10; pp. 6097 - 6108
• Main Authors: Song, Ying-Jian, Tan, Juan, Gao, Xin-Huai, Wang, Li-Xin
• Format: Journal Article
• Language: English
• Published: New Zealand Dove Medical Press Limited 01.01.2018; Taylor & Francis Ltd; Dove Medical Press
• Subjects: Adenocarcinoma; Analysis; Biochemistry; Bioinformatics; bioinformatics analysis; Biological markers; Biomarkers; Breast cancer; Cancer genetics; Cancer research; Cancer therapies; Cancer treatment; Cell cycle; Computational biology; Datasets; differentially expressed; Gastric cancer; Gene expression; gene expression profiling; Gene mutation; Gene therapy; Genes; Genetic aspects; Genomes; Genomics; Kinases; lung adenocarcinoma; Lung cancer; Medical prognosis; Motility; Mutation; Non-small cell lung cancer; Original Research; Patient outcomes; Phenols (Class of compounds); Prognosis; Prostate cancer; Protein-protein interactions; Proteins; Respiratory system agents; Studies; Survival analysis; Tumor proteins; Tumors; Tyrosine; Women's health; United States; China; differentially expressed; gene expression profiling; bioinformatics analysis; prognosis; lung adenocarcinoma
• ISSN: 1179-1322; 1179-1322
• DOI: 10.2147/CMAR.S168636

Lung cancer is one of the most common malignant tumors. Despite advances in lung cancer therapies, prognosis of non-small-cell lung cancer is still unfavorable. The aim of this study was to identify the prognostic value of key genes in lung tumorigenesis. Differentially expressed genes (DEGs) were screened out by GEO2R from three Gene Expression Omnibus cohorts. Common DEGs were selected for Kyoto Encyclopedia of Genes and Genomes pathway analysis and Gene Ontology enrichment analysis. Protein- protein interaction networks were constructed by the STRING database and visualized by Cytoscape software. Hub genes, filtered from the CytoHubba, were validated using the Gene Expression Profiling Interactive Analysis database, and their genomic alterations were identified by performing the cBioportal. Finally, overall survival analysis of hub genes was performed using Kaplan-Meier Plotter. From three datasets, 169 DEGs (70 upregulated and 99 downregulated) were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that upregulated DEGs were significantly enriched in cell cycle, p53 pathway, and extracellular matrix-receptor interactions; the downregulated DEGs were significantly enriched in PPAR pathway and tyrosine metabolism. The protein-protein interaction network consisted of 71 nodes and 305 edges, including 49 upregulated and 22 downregulated genes. The hub genes, including , , , , and , were overexpressed compared with the normal group by Gene Expression Profiling Interactive Analysis analysis, and associated with reduced overall survival in lung cancer patients. In the genomic alterations analysis, two hotspot mutations (S2021C/F and E314K/V) were identified in Pfam protein domains. DEGs, including , , , , and might be potential biomarkers for the prognosis and treatment of lung adenocarcinoma.