A Novel Five Gene Signature Derived from Stem-Like Side Population Cells Predicts Overall and Recurrence-Free Survival in NSCLCReportar como inadecuado




A Novel Five Gene Signature Derived from Stem-Like Side Population Cells Predicts Overall and Recurrence-Free Survival in NSCLC - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

Gene expression profiling has been used to characterize prognosis in various cancers. Earlier studies had shown that side population cells isolated from Non-Small Cell Lung Cancer NSCLC cell lines exhibit cancer stem cell properties. In this study we apply a systems biology approach to gene expression profiling data from cancer stem like cells isolated from lung cancer cell lines to identify novel gene signatures that could predict prognosis. 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 stem like properties. Differentially expressed genes that were over or under-expressed at least two fold commonly in all 4 cell lines were identified. We found 354 were upregulated and 126 were downregulated in SP cells compared to MP cells; of these, 89 up and 62 downregulated genes average 2 fold changes were used for Principle Component Analysis PCA and MetaCore™ pathway analysis. The 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. Microarray data was validated using qRT-PCR on the 5 selected genes and all showed robust correlation between microarray and qRT-PCR. Further, we analyzed two independent gene expression datasets that included 360 lung adenocarcinoma patients from NCI Director-s Challenge Set for overall survival and 63 samples from Sungkyunkwan University SKKU for recurrence free survival. Kaplan-Meier and log-rank test analysis predicted poor survival of patients in both data sets. Our results suggest that genes involved in chromosome condensation are likely related with stem-like properties and might predict survival in lung adenocarcinoma. Our findings highlight a gene signature for effective identification of lung adenocarcinoma patients with poor prognosis and designing more aggressive therapies for such patients.



Autor: Deepak Perumal, Sandeep Singh, Sean J. Yoder, Gregory C. Bloom, Srikumar P. Chellappan

Fuente: http://plos.srce.hr/



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