Abstract
Although lung cancer is one of the greatest threats to human health, its signaling pathway and related genes are still unknown. This study integrates data from three groups of people to study potential key candidate genes and pathways related to lung cancer. Expression profiles (GSE18842, GSE19188 and GSE27262), including 162 tumor tissue and 135 adjacent normal lung tissue samples, were integrated and analyzed. Differentially expressed genes (DEGs) and candidate genes were identified, their expression pathways were analyzed, and the diethylene glycol-related protein–protein interaction (PPI) network was analyzed. We identified 232 shared DEGs (40 upregulated and 192 down-regulated) from the three GSE datasets. The DEGs were clustered according to function and signaling pathway for significant enrichment analysis. In total, 129 nodes/DEGs were identified from the DEG PPI network complex. An improved prognosis was associated with increased Helicase, Lymphoid-Specific (HELLS) and decreased Intercellular adhesion molecule 1 (ICAM1) mRNA expression in lung cancer patients. In conclusion, we used integrated bioinformatics analysis to identify candidate genes and pathways in lung cancer to show that HELLS and ICAM1 might be the key genes related to tumorigenesis or tumor progression in lung cancer. Additional studies are needed to further explore the involved functional mechanisms.
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