Abstract 3007: A novel five gene signature predicts overall and recurrence-free survival in NSCLC (2012)

Abstract Gene expression profiling has been used to characterize prognosis in various cancers. Applying systems biology approach to cancer stem cell data generated from expression profiling of cell lines, a novel 5 gene signature was identified. Earlier studies had shown that side population cells isolated from established Non-Small Cell Lung Cancer (NSCLC) cell lines exhibit cancer stem cell properties. Microarray data from side population (SP) and main population (MP) cells isolated from 4 NSCLC lines (A549, H1650, H460, H1975) were used to examine gene expression profiles associated with stemness. Total RNA extracted from SP and MP samples were used to generate cRNA targets, which were hybridized to Human Genome U133A Plus 2.0 probe arrays. Raw data was processed and the mean center expression level for each gene was determined. We searched for differentially expressed genes that were over or under-expressed at least two fold commonly in all 4 cell lines. It was found that 354 genes were upregulated and 126 genes were downregulated in SP cells from all the 4 cell lines, compared to MP cells; of these, 89 up and 62 downregulated genes (average 2 fold changes) were used for Principle Component Analysis (PCA) and MetaCoreTM pathway analysis. Pathway analysis demonstrated representation of 4 up regulated genes (TOP2A, AURKB, BRRN1, CDK1) in chromosome condensation pathway and 1 down regulated gene FUS in chromosomal translocation. The microarray data was validated using quantitative RT-PCR on the 5 selected genes and all showed robust correlations between microarray and qRT-PCR expression data. Further, we analyzed two independent microarray gene expression datasets that included 361 lung adenocarcinoma patients from NCI Director's Challenge Set (DCS) for overall survival (OS) and 63 adenocarcinoma patients from Sungkyunkwan University (SKKU) for recurrence free survival (RFS). Statistical analyses were done using R package. Expression values were normalized using MAS5.0 and median expression values were used to dichotomize into low and high expression levels for 5 genes. To determine whether the gene signature correlates with poor prognosis, we performed Kaplan-Meier and log-rank test analysis. Kaplan-Meier analysis for survival showed significant trend for all the 5 genes. These genes predicted poor survival of patients in 361 DCS as well as 63 adenocarcinoma samples from SKKU. Our results suggest that genes involved in chromosome condensation are likely related with cancer stem cell like properties and therefore predict survival in lung adenocarcinoma. Further studies are needed to validate the key genes to provide potential new targets to intervene progression of lung adenocarcinoma. Our findings highlight gene signature for effective identification of lung adenocarcinoma patients with poor prognosis and designing more aggressive or tailored therapeutic properties for such patients. 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 3007. doi:1538-7445.AM2012-3007