Shared Gene Expression Alterations in Nasal and Bronchial Epithelium for Lung Cancer Detection. (27th February 2017)

• Record Type: Journal Article
• Authors: Perez-Rogers, Joseph F.; Gerrein, Joseph; Anderlind, Christina; Liu, Gang; Zhang, Sherry; Alekseyev, Yuriy; Smith, Kate Porta; Whitney, Duncan; Evan Johnson, W.; Elashoff, David A.; Dubinett, Steven M.; Brody, Jerome; Spira, Avrum; Lenburg, Marc E.
• Is Part Of: Journal of the National Cancer Institute. Volume 109:Number 7(2017)
• Publication Date: 2017-02-27
• Subjects: Cancer -- Periodicals; Cancer -- Research -- Periodicals; 616.994
• DOI: 10.1093/jnci/djw327
• Languages: English
• ISSNs: 0027-8874

Abstract

Abstract: Background: We previously derived and validated a bronchial epithelial gene expression biomarker to detect lung cancer in current and former smokers. Given that bronchial and nasal epithelial gene expression are similarly altered by cigarette smoke exposure, we sought to determine if cancer-associated gene expression might also be detectable in the more readily accessible nasal epithelium. Methods: Nasal epithelial brushings were prospectively collected from current and former smokers undergoing diagnostic evaluation for pulmonary lesions suspicious for lung cancer in the AEGIS-1 (n = 375) and AEGIS-2 (n = 130) clinical trials and gene expression profiled using microarrays. All statistical tests were two-sided. Results: We identified 535 genes that were differentially expressed in the nasal epithelium of AEGIS-1 patients diagnosed with lung cancer vs those with benign disease after one year of follow-up ( P < .001). Using bronchial gene expression data from the AEGIS-1 patients, we found statistically significant concordant cancer-associated gene expression alterations between the two airway sites ( P < .001). Differentially expressed genes in the nose were enriched for genes associated with the regulation of apoptosis and immune system signaling. A nasal lung cancer classifier derived in the AEGIS-1 cohort that combined clinical factors (age, smoking status, time since quit, mass size) and nasal gene expression (30 genes) had statistically significantly higher area under the curve (0.81; 95% confidence interval [CI] = 0.74 to 0.89, P = .01) and sensitivity (0.91; 95% CI = 0.81 to 0.97, P = .03) than a clinical-factor only model in independent samples from the AEGIS-2 cohort. Conclusions: These results support that the airway epithelial field of lung cancer–associated injury in ever smokers extends to the nose and demonstrates the potential of using nasal gene expression as a noninvasive biomarker for lung cancer detection.