Identification and validation of key genes associated with smoking-induced lung adenocarcinoma development through bioinformatics analysis and predictions of small-molecule drugs
Abstract
Although smoking is known to be the leading risk factor for lung cancer, it is still unclear how normal cells turn cancerous in cigarette smokers. This study aimed to identify key molecular drivers that contributed to the progression and prognosis of lung adenocarcinoma (LUAD) in cigarette smokers, as well as screen, correlated small molecule therapeutic drugs by bioinformatics analysis. Gene expression profile was obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between current smokers without cancer and never smokers were identified and were analyzed to identify gene ontologies, pathways, protein‑protein interaction (PPI) networks, hub genes, and prognostic potentials. Finally, effective small-molecule compounds were screened by the Connectivity Map (CMap) database. A total of nine genes were screened out as the critical among the DEGs from the PPI network. Overall survival analysis revealed that high mRNA expression of ACTR2 and ANAPC10 were significantly associated with the LUAD. Furthermore, three candidate small-molecule drugs for manipulating LUAD progression were predicted. Identification of critical genes involved in disease development and candidate drugs to combat it can lead us to better diagnosis and targeted therapy strategies. The results of the present study may provide insight into the mechanisms underlying LUAD pathogenesis development risk in cigarette smokers and may provide potential targets for prevention.
Keywords
Bioinformatics analysis, Differentially expressed genes, Lung adenocarcinoma, Overall survival, Smoking.
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