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Gene-Environment Interaction Signatures by Quantitative mRNA Profiling in Exfoliated Buccal Mucosal Cells

¹ Laboratory of Human Toxicology and Molecular Epidemiology, ² Organic Analytic Chemistry Laboratory, ³ SUNY School of Public Health, Environmental Health and Toxicology, Wadsworth Center, New York State Department of Health; and ⁴ Albany Medical College, Pulmonary and Critical Care Medicine, Albany, New York

Exfoliated cytologic specimens from mouth (buccal) epithelium may contain viable cells, permitting assay of gene expression for direct and noninvasive measurement of gene-environment interactions, such as for inhalation (e.g., tobacco smoke) exposures. We determined specific mRNA levels in exfoliated buccal cells collected by cytologic brush, using a recently developed RNA-specific real-time quantitative reverse transcription-PCR strategy. In a pilot study, metabolic activity of exfoliated buccal cells was verified by 3-[4,5-dimethylthiazol-2-yl]-2,5- diphenyltetrazolium assay in vitro. Transcriptional activity was observed, after timed in vivo exposure to mainstream tobacco smoke resulted in induction of CYP1B1 in serially collected buccal samples from the one subject examined. For a set of 11 subjects, mRNA expression of nine genes encoding carcinogen- and oxidant-metabolizing enzymes qualitatively detected in buccal cells was then shown to correlate with that in laser-microdissected lung from the same individuals (² = 52.91, P < 0.001). Finally, quantitative real-time reverse transcription-PCR assays for seven target gene (AhR, CYP1A1, CYP1B1, GSTM1, GSTM3, GSTP1, and GSTT1) and three reference gene [glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ß-actin, and 36B4] transcripts were performed on buccal specimens from 42 subjects. In multivariate analyses, gender, tobacco smoke exposure, and other factors were associated with the level of expression of CYP1B1, GSTP1, and other transcripts on a gene-specific basis, but substantial interindividual variability in mRNA expression remained unexplained. Within the power limits of this pilot study, gene expression signature was not clearly predictive of lung cancer case or control status. This noninvasive and quantitative method may be incorporated into high-throughput human applications for probing gene-environment interactions associated with cancer.

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