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Smoking modulates different secretory subpopulations expressing SARS-CoV-2 entry genes in the nasal and bronchial airways (AEGIS nasal brushings)

ABSTRACT: Nasal epithelial brushings were prospectively collected from current and former smokers with 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE210271 | GEO | 2022/10/25

REPOSITORIES: GEO

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Smoking modulates different secretory subpopulations expressing SARS-CoV-2 entry genes in the nasal and bronchial airways (BCLHS bronchial brushings)

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Smoking modulates different secretory subpopulations expressing SARS-CoV-2 entry genes in the nasal and bronchial airways (SU2C nasal brushings)

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Smoking modulates different secretory subpopulations expressing SARS-CoV-2 entry genes in the nasal and bronchial airways (AEGIS nasal brushings)

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Project description: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 epithelium gene expression is similarly altered by cigarette smoke exposure, we sought to determine if cancer-associated gene expression might also be detectable in more readily accessible nasal epithelium. Nasal epithelial brushings were prospectively collected from current and former smokers with 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. Using the 375 AEGIS 1 samples, we identified 535 genes that were differentially expressed in the nasal epithelium of patients who were ultimately diagnosed with lung cancer vs. those with benign disease after one year of follow-up (p<0.001). Using bronchial gene expression data from 299 AEGIS-1 patients (including 157 patients with matched nasal and bronchial expression data), we found significantly concordant cancer-associated gene expression differences between the two airway sites (p<0.001). Differentially expressed genes were enriched for genes associated with the regulation of apoptosis, mitotic cell cycle, and immune system signaling. A nasal lung cancer classifier derived in the AEGIS-1 cohort that combined clinical factors and nasal gene expression had significantly higher AUC (0.80) and sensitivity (0.94) over a clinical-factor only model (p<0.05) in independent samples from the AEGIS-2 cohort (n=130). These results suggest that the airway epithelial field of lung cancer-associated injury in current and former smokers extends to the nose and demonstrates the potential of using nasal gene expression as a non-invasive biomarker for the detection of lung cancer.

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