Comprehensive analysis of non-small-cell lung cancer microarray datasets identifies several prognostic biomarkers

Abstract

Aim: To find accurate and effective biomarkers for diagnosis of non-small-cell lung cancer (NSCLC) patients. Materials & methods: We downloaded microarray datasets GSE19188, GSE33532, GSE101929 and GSE102286 from the database of Gene Expression Omnibus. We screened out differentially expressed genes (DEGs) and miRNAs (DEMs) with GEO2R. We also performed analyses for the enrichment of DEGs’ and DEMs’ function and pathway by several tools including database for annotation, visualization and integrated discovery, protein–protein interaction and Kaplan–Meier-plotter. Results: Total 913 DEGs were screened out, among which ten hub genes were discovered. All the hub genes were linked to the worsening overall survival of the NSCLC patients. Besides, 98 DEMs were screened out. MiR-9 and miR-520e were the most significantly regulated miRNAs. Conclusion: Our results could provide potential targets for the diagnosis and treatment of NSCLC.