Abstract 4133: MicroRNAs for early detection of lung cancer

Introduction: Early detection of lung cancer by screening of high risk populations (identified by epidemiological and life-style factors) has the potential to save many lives. However, effective screening is reliant on minimally invasive techniques, such as CT screening, bronchioalveolar lavage (BAL) and blood tests, and the identification of suitable biomarkers. CT screening is effective in reducing mortality, but generates a large proportion of indeterminate nodules that must be further characterised. MicroRNAs (miRNA) have great potential as biomarkers due to their tissue-specific and cancer-specific expression patterns. We have identified tumour-specific miRNAs for non-small cell lung cancer (NSCLC), using a combination of screening on TaqMan microRNA TLDA cards and validation with qRTPCR assays, with the aim of utilising these as biomarkers in the early detection setting. Methods: Our sample group consisted of 31 frozen samples from 20 Liverpool Lung Project (LLP) NSCLC patients, including 10 adenocarcinomas (Ad), 10 squamous cell carcinomas (SCC) & matched normal tissue. Two further validation sets consisted of equal numbers of Ad and SCC tumour/normal pairs (124 in total). MiRNA was prepared from tumour and normal specimens using Qiagen MicroRNeasy kits. Reverse transcription and pre-amplification was performed using Applied Biosystems MegaPlex Pools and miRNAs were quantified on a 7900HT Real-Time PCR System with TaqMan Array Human MiRNA Card Set v3.0 (covering 754 human miRNAs). Ct values were exported using SDS v2.3 data and RQ Manager software and further analysed in Bioconductor. Validation qRTPCR was performed with individual miRNA assays, following reverse transcription with MegaPlex pools. Results: When Benjamin-Hoechst-adjusted-p value 4.0 fold-change in the cancer group. A subset of 22 miRNAs including miR-34a, miR-96, let-7g and miR-183 was identified with the greatest expression in tumours. Differential expression of all 22 miRNAs was confirmed in an independent set of 24 tumour/normal pairs. Using these 22 validated miRNAs we performed discriminative modelling and identified a model based on just 8 markers that gave a specificity of 100% and a sensitivity of 98%. This panel was validated, with 97% specificity and 91% sensitivity, in a 2nd independent sample set containing 48 tumours and paired normal samples. Conclusion: A number of miRNAs was identified that showed good discriminatory power individually, but greatest sensitivity and specificity when combined as an 8 member panel. The lung cancer specific miRNAs we have identified provide a potential source of early detection biomarkers. Their applicability to minimally-invasive samples is being evaluated in a range of samples including plasma and bronchial lavage. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4133. doi:1538-7445.AM2012-4133