Bioinformatics Analysis of the Effects of Tobacco Smoke on Gene Expression.

• Main Authors: Chunhua Cao, Jianhua Chen, Chengqi Lyu, Jia Yu, Wei Zhao, Yi Wang, Derong Zou
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2015-01-01
• Series: PLoS ONE
• Online Access: http://europepmc.org/articles/PMC4667894?pdf=render

This study was designed to explore the effects of tobacco smoke on gene expression through bioinformatics analyses. Gene expression profile GSE17913 was downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) in buccal mucosa tissues between 39 active smokers and 40 never smokers were identified. Gene Ontology Specifically, the DEG distribution in the pathway of Metabolism of xenobiotics by cytochrome P450 was shown in Fig 2[corrected] were performed, followed by protein-protein interaction (PPI) network, transcriptional regulatory network as well as miRNA-target regulatory network construction. In total, 88 up-regulated DEGs and 106 down-regulated DEGs were identified. Among these DEGs, cytochrome P450, family 1, subfamily A, polypeptide 1 (CYP1A1) and CYP1B1 were enriched in the Metabolism of xenobiotics by cytochrome P450 pathway. In the PPI network, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta (YWHAZ), and CYP1A1 were hub genes. In the transcriptional regulatory network, transcription factors of MYC associated factor X (MAX) and upstream transcription factor 1 (USF1) regulated many overlapped DEGs. In addition, protein tyrosine phosphatase, receptor type, D (PTPRD) was regulated by multiple miRNAs in the miRNA-DEG regulatory network. CYP1A1, CYP1B1, YWHAZ and PTPRD, and TF of MAX and USF1 may have the potential to be used as biomarkers and therapeutic targets in tobacco smoke-related pathological changes.