Screening of key genes and prediction of therapeutic agents in Arsenic-induced lung carcinoma

BACKGROUND: Evidence indicates that inorganic arsenic (iAs) can directly damage cells and result in malignant transformation with unclear complicated mechanisms. In the present study, we aimed to explore the possible molecules, pathways and therapeutic agents by using bioinformatics methods. METHODS: Microarray-based data were retrieved and analyzed to screen the differentially expressed genes (DEGs) between iAs-treated lung cells and controls. Then, the functions of DEGs were annotated and the hub genes were filtrated. The key genes were selected from the hub genes through validation in The Cancer Genome Atlas (TCGA) cohorts. Possible drugs were predicted by using CMAP tool. RESULTS: Two datasets (GSE33520 and GSE36684) were retrieved, and 61 up-regulated and 228 down-regulated DEGs were screened out, which were enriched in various pathways, particularly metabolism-related pathways. Among the DEGs, four hub genes including MTIF2, ACOX1, CAV1, and MRPL17, which might affect lung cancer prognosis, were selected as the key genes. Interestingly, Quinostatin was predicted to be a potential agent reversing iAs-induced lung cell malignant transformation. CONCLUSION: The present study sheds novel insights into the mechanisms of iAs-induced lung cell malignant transformation and identified several potential small agents for iAs toxicity prevention and therapy.