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Background  Lung cancer is one of the most common carcinomas in the world, and lung adenocarcinoma (LUAD) is the most lethal and most common subtype of lung cancer. Cigarette smoking is the most leading risk factor of lung cancer, but it is still unclear how normal lung cells become cancerous in cigarette smokers. This study aims to identify potential smoking-related biomarkers associated with the progression and prognosis of LUAD, as well as their regulation mechanism using an in vitro carcinogenesis model and bioinformatics analysis.    Results  Based on the integration analysis of four Gene Expression Omnibus (GEO) datasets and our mRNA sequencing analysis, 2 up-regulated and 11 down-regulated genes were identified in both S30 cells and LUAD. By analyzing the LUAD dataset in The Cancer Gene Analysis (TCGA) database, 3 of the 13 genes, viz., glycophorin C ( GYPC ), NME/NM23 nucleoside diphosphate kinase 1 ( NME1 ) and slit guidance ligand 2 ( SLIT2 ), were found to be significantly correlated with LUAD patients’ smoking history. The expression levels of  GYPC ,  NME1  and  SLIT2  in S30 cells and lung cancer cell lines were validated by quantitative PCR, immunofluorescence, and western blot assays. Besides, these three genes are associated with tumor invasion depth, and elevated expression of  NME1  was correlated with lymph node metastasis. The enrichment analysis suggested that these genes were highly correlated to tumorigenesis and metastasis-related biological processes and pathways. Moreover, the increased expression levels of  GYPC  and  SLIT2 , as well as decreased expression of  NME1  were associated with a favorable prognosis in LUAD patients. Furthermore, based on the multi-omics data in the TCGA database, these genes were found to be regulated by DNA methylation.    Conclusion  In conclusion, our observations indicated that the differential expression of  GYPC ,  NME1  and  SLIT2  may be regulated by DNA methylation, and they are associated with cigarette smoke-induced LUAD, as well as serve as prognostic factors in LUAD patients.

Identification and validation of smoking-related genes in lung adenocarcinoma using an in vitro carcinogenesis model and bioinformatics analysis