Potential Biomarkers and Therapeutic Targets of Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) is the most common lung cancer that has shown resistance to multiple treatments. This article aims to screen out reliable core genes and explore their underlying mechanisms in limited-stage NSCLC.

Three datasets (GSE19188, GSE27262, and GSE33532) were selected from the gene expression omnibus (GEO). Venn diagram software, omicshare tools, and gene ontology (GO) were used to screen identified differentially expressed genes (DEGs) and potential pathways. A protein-protein interaction (PPI) network was drawn using Search Tool for the Retrieval of Interacting Genes (STING), and Cytoscape was applied for module analysis. Prognostic information in NSCLC clinical samples was also reconfirmed by Gene Expression Profiling Interactive Analysis (GEPIA) and the Kaplan Meier-plotter program. The filtered core genes were analyzed through the Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment.

235 common DEGs (Differentially Expressed Genes) were obtained. 32 genes were screened out through the PPI network and MCODE. 9 core genes (CCNB1, CCNB2, MAD2L1, BUB1, TTK, CDC20, AURKA, RRM2, GTSE1) were obtained through the KEGG pathway enrichment, which mainly enriched in 4 pathways, namely, Cell cycle, Oocyte meiosis, p53 signaling pathway, and Progesterone-mediated oocyte maturation, respectively.

Nine critical dependable DEGs were identified in limited-stage NSCLC using integrated bioinformatical approaches, and these core genes show great potential as prospective biomarkers and therapeutic targets in the progression of limited-stage NSCLC.

non-small cell lung cancer, biomarkers, therapeutic targets, p53 signaling pathway, bioinformatics analysis.