Bioinformatics analysis of potential crucial genes in lung squamous cell cancer

Objective To explore the differentially expressed genes related to the occurrence and development of squamous cell lung cancer along with screening out potential drug targets. Methods The microarray data associated with squamous cell lung cancer were obtained from GEO database and identified differentially expressed genes (DEGs) based on Limma package of R statistical software.Gene ontology (GO) and KEGG enrichment analysis, protein-protein interaction (PPI) network analysis, and survival analysis for network hub genes were performed. Results A total of 628 DEGs (263 up-regulated and 365 down-regulated) were identified. Based on these DEGs, a number of bio-pathways appeared to be altered in squamous cell lung cancer, including cell cycle, p53 signaling pathway, ECM-receptor interaction, Mismatch repair, PPAR signaling pathway and Cell adhesion molecules (CAMs). The top 10 centrality hub genes MAD2L1, CCNB1, DLGAP5, CDC20, TOP2A, MELK, BUB1B, CCNA2, CDK1 and CCNB2 were identified from the PPI network and they were associated with prognosis of patients. Conclusion The present study identifies hub genes and signal pathways, which benefits us to get insight into the molecular mechanisms of carcinogenesis and development of the disease, and it may provide a theoretical basis for the study of clinical targeted therapy.