Abstract 1954: microRNA expression in bronchial epithelium for lung cancer detection (2016)

Abstract Introduction We have previously shown that gene expression alterations in the cytologically-normal mainstem bronchus can be leveraged as a biomarker for lung cancer detection (Silvestri et al. NEJM 2015), a test that is now used clinically. Extending this approach, we hypothesized that bronchial microRNA (miRNA) expression is altered in patients with lung cancer and that incorporating miRNA expression into the mRNA classifier may improve its performance. Methods Using bronchial brushes collected prospectively from current and former smokers undergoing bronchoscopy for suspect lung cancer across 28 medical centers as part of the AEGIS 1 and 2 clinical trials, we profiled miRNA expression via small RNA sequencing of 341 patients for which gene expression data was also available on the same bronchial brush sample. Patients were followed for up to one year post-bronchoscopy until a final diagnosis was established. 138 patients from AEGIS 1 (88 cancer-positive and 50 cancer-free) served as a discovery set, while other 203 patients from AEGIS 1 and 2 (103 cancer-positive and 100 cancer-free) were used as an independent test set. First, we identified miRNAs whose expression is associated with cancer by linear modeling in the discovery set. We next explored the relationships between the expression of these miRNAs and their predicted mRNA targets. Lastly, using logistic regression, we incorporated a cancer miRNA feature into our bronchial gene-expression classifier (Silvestri et al., NEJM 2015) and validated its performance in the test set. Results We found that expression profiles of 42 miRNAs were associated with cancer status in the discovery set (p&lt;0.05, 23 miRNAs expected by chance). The top four differentially expressed miRNAs (q&lt;0.2) were all decreased in the bronchial epithelium of cancer patients. The expression values of these miRNAs were significantly negatively correlated with the expression of their predicted mRNA targets (p&lt;0.05). The predicted gene targets of the top miRNAs were significantly enriched (p&lt;0.05) for cancer-related processes including the PDGF signaling pathway, insulin/IGF pathway-mitogen and activated protein kinase/MAP kinase cascade. Moreover, we found that the addition of one of the top differentially expressed miRNAs in the discovery set to the existing gene expression biomarker significantly improved the classifier's performance (ROC AUC) in the test set (p = 0.025). Conclusions We have established that there are alterations in miRNA expression in the cytologically normal mainstem bronchus of smokers with lung cancer. Importantly, we demonstrated the potential of these miRNA alterations to improve the performance of an existing bronchial gene expression biomarker for lung cancer detection. Citation Format: Ana Brandusa Pavel, Joshua Campbell, Gang Liu, Sherry Zhang, Hanqiao Liu, Ji Xiao, Kate Porta, Duncan Whitney, Steven Dubinett, David Elashoff, Marc Lenburg, Avrum Spira. microRNA expression in bronchial epithelium for lung cancer detection. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1954.