Integration of mRNA and microRNA profiles as prognostic and predictive markers in lung adenocarcinoma
7522 Background: Lung adenocarcinoma (ADC) is a distinct biologic entity with unique gene amplifications (Weir B, Nature 2008). Yet, comprehensive transcriptomic analysis, including microRNAs, specific to lung ADC are lacking. Methods: Using mRNA expression data from a discovery cohort of 154 patients with histologically proven early stage (I and II) lung ADC, signatures of oncogenic pathway and tumor microenvironment status were applied and further organized by hierarchical clustering to develop a metagene model. Further, using in vitro assays in a large cohort of lung ADC cell lines (n = 42) with corresponding mRNA and microRNA data, novel microRNAs associated with a poor prognosis and their relationship to cisplatin resistance was elucidated. Results: In the discovery cohort of 154 patients with early stage disease, activation of oncogenic pathways associated with wound healing (angiogenesis), chromosomal instability, and STAT signaling were associated with an increased risk of recurrence (p<0.001). Utilizing the extremes of survival to identify cohorts of patients as high and low risk phenotypes, using bayesian regression, a 100 gene signature (‘metagene') that captured the diversity of signaling pathways unique to patients at increased risk of recurrence was identified and validated in an independent cohort (n = 364) of lung ADC samples with 78.3% accuracy. Kaplan Meier survival analysis and multivariate analysis further confirmed the independent prognostic value of the 100 gene signature (p= 0.007). Using in vitro cell proliferation assays, predicted high risk lung ADC cell lines were identified as being more resistant to cisplatin therapy than those predicted to be low risk (p=0.001). In a novel manner, we also identified several microRNAs (miR-215, miR-98, miR- 643, let-7b, miR-665, miR-629) associated with a high risk of recurrence and more importantly cisplatin resistance. Conclusions: mRNA and microRNA profiles reflect unique aspects of individual tumors and may characterize histology-specific tumor heterogeneity in lung ADC, providing an opportunity to better characterize the oncogenic process and refine therapeutic options. No significant financial relationships to disclose.