Effects of cigarette smoke on the human oral mucosal transcriptome.

Effects of cigarette smoke on the human oral mucosal transcriptome.
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DOI:
10.1158/1940-6207.capr-09-0192
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发表时间:
2010-03
期刊:
Cancer prevention research (Philadelphia, Pa.)
影响因子:
--
通讯作者:
Dannenberg AJ
Dannenberg AJ
中科院分区:
其他
文献类型:
--
作者:
Boyle JO;Gümüs ZH;Kacker A;Choksi VL;Bocker JM;Zhou XK;Yantiss RK;Hughes DB;Du B;Judson BL;Subbaramaiah K;Dannenberg AJ

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Use of tobacco is responsible for approximately 30% of all cancer-related deaths in the United States including cancers of the upper aerodigestive tract. In the current study, 40 current and 40 age- and gender-matched never smokers underwent buccal biopsies to evaluate the effects of smoking on the transcriptome. Microarray analyses were carried out using Affymetrix HGU 133 Plus2 arrays. Smoking altered the expression of numerous genes: 32 genes showed increased expression and 9 genes showed reduced expression in the oral mucosa of smokers vs. never smokers. Increases were found in genes involved in xenobiotic metabolism, oxidant stress, eicosanoid synthesis, nicotine signaling and cell adhesion. Increased numbers of Langerhans cells were found in the oral mucosa of smokers. Interestingly, smoking caused greater induction of aldo-keto reductases, enzymes linked to polycyclic aromatic hydrocarbon induced genotoxicity, in the oral mucosa of women than men. Striking similarities in expression changes were found in oral compared to the bronchial mucosa. The observed changes in gene expression were compared to known chemical signatures using the Connectivity Map database, and suggested that geldanamycin, an Hsp90 inhibitor, might be an anti-mimetic of tobacco smoke. Consistent with this prediction, geldanamycin caused dose-dependent suppression of tobacco smoke extract-mediated induction of CYP1A1 and CYP1B1 in vitro. Collectively, these results provide new insights into the carcinogenic effects of tobacco smoke, support the potential use of oral epithelium as a surrogate tissue in future lung cancer chemoprevention trials and illustrate the potential of computational biology to identify chemopreventive agents.