Abstract 1162: MicroRNA expression profiles of tumors, normal lung tissues and plasma samples from spiral-computed tomography (CT) trial for early lung cancer detection

Abstract

Abstract The benefits of lung cancer screening by spiral CT are still controversial: in contrast with an up to three-fold increase in the number of lung cancer diagnoses, there is not apparent decrease in advanced cancers and no substantial reduction of mortality in smokers. Changes relating to the (early) invasive and aggressive phenotype acquired by some of the CT-detected lesions might represent the crucial players to define novel prognostic/predictive markers and, potentially, novel therapeutic targets. In this study we explored miRNA expression profile in tissues and plasma samples of 28 patients developing lung cancer, identified in a spiral-CT screening trial performed in our Institution on 1035 heavy smokers observed for 5 years. 5µg of total RNA from tissues samples were used for labeling and hybridization on miRNA microarray chip (Ohio State microRNA microarray version 2.0) containing 460 probes in quadruplicate. By class comparison and prediction analyses we identify significant miRNAs (P<0.001) that discriminate normal lung versus cancer tissues. This list included miRNAs previously identified (i.e. mir-21) and unidentified (i.e. miR-486) in symptomatic lung cancer patients. In both tumors and normal lung tissues possible association of microRNA expression profiles with clinical-pathological characteristics of the patients was then investigated. A set of miRNA significantly discriminated tumor histotype, growth rate and clinical outcome of the patients. Interestingly, miRNA expression profile of patients who developed tumors in the first two years of the trial was found to be different from the profile of those detected after the 2nd year. We also analyzed miRNAs expression profiles in plasma samples of the patients collected before and in presence of the disease and compared to those of disease-free heavy smokers controls enrolled in the screening trial. In this analysis 100 miRNAs were detectable by simple qReal Time PCR assay in plasma samples, with a number of miRNAs able to predict lung cancer development up to 2 years before its clinical appearance (P<0.05). These data have been validated in an independent cohort of 27 individuals developing lung cancer in a second CT-screening trial ongoing in our Institution, where the signatures identified in the training set showed a good sensitivity and an optimal specificity. In conclusion in tumor and normal lung tissues specific miRNA profiles characterize aggressive and lethal lung cancers. Moreover, mirRNAs can be easily detectable in plasma samples and are able to identify aggressive lung cancer before its clinical appearance indicating a potential role of miRNAs in plasma as molecular predictors of high risk disease. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 1162. doi:10.1158/1538-7445.AM2011-1162