BACKGROUND: Current staging methods are inadequate for predicting the outcome of treatment of non-small-cell lung cancer (NSCLC). We developed a five-gene signature that is closely associated with survival of patients with NSCLC. METHODS: We used computer-generated random numbers to assign 185 frozen specimens for microarray analysis, real-time reverse-transcriptase polymerase chain reaction (RT-PCR) analysis, or both. We studied gene expression in frozen specimens of lung-cancer tissue from 125 randomly selected patients who had undergone surgical resection of NSCLC and evaluated the association between the level of expression and survival. We used risk scores and decision-tree analysis to develop a gene-expression model for the prediction of the outcome of treatment of NSCLC. For validation, we used randomly assigned specimens from 60 other patients. RESULTS: Sixteen genes that correlated with survival among patients with NSCLC were identified by analyzing microarray data and risk scores. We selected five genes (DUSP6, MMD, STAT1, ERBB3, and LCK) for RT-PCR and decision-tree analysis. The five-gene signature was an independent predictor of relapse-free and overall survival. We validated the model with data from an independent cohort of 60 patients with NSCLC and with a set of published microarray data from 86 patients with NSCLC. CONCLUSIONS: Our five-gene signature is closely associated with relapse-free and overall survival among patients with NSCLC. Copyright 2007 Massachusetts Medical Society.
BACKGROUND: Current staging methods are inadequate for predicting the outcome of treatment of non-small-cell lung cancer (NSCLC). We developed a five-gene signature that is closely associated with survival of patients with NSCLC. METHODS: We used computer-generated random numbers to assign 185 frozen specimens for microarray analysis, real-time reverse-transcriptase polymerase chain reaction (RT-PCR) analysis, or both. We studied gene expression in frozen specimens of lung-cancer tissue from 125 randomly selected patients who had undergone surgical resection of NSCLC and evaluated the association between the level of expression and survival. We used risk scores and decision-tree analysis to develop a gene-expression model for the prediction of the outcome of treatment of NSCLC. For validation, we used randomly assigned specimens from 60 other patients. RESULTS: Sixteen genes that correlated with survival among patients with NSCLC were identified by analyzing microarray data and risk scores. We selected five genes (DUSP6, MMD, STAT1, ERBB3, and LCK) for RT-PCR and decision-tree analysis. The five-gene signature was an independent predictor of relapse-free and overall survival. We validated the model with data from an independent cohort of 60 patients with NSCLC and with a set of published microarray data from 86 patients with NSCLC. CONCLUSIONS: Our five-gene signature is closely associated with relapse-free and overall survival among patients with NSCLC. Copyright 2007 Massachusetts Medical Society.
Authors: Rex Chin Wei Yung; Susan Otell; Peter Illei; Douglas P Clark; David Feller-Kopman; Lonny Yarmus; Frederic Askin; Edward Gabrielson; Qing Kay Li Journal: Cancer Cytopathol Date: 2011-12-05 Impact factor: 5.284
Authors: Dung-Tsa Chen; Ying-Lin Hsu; William J Fulp; Domenico Coppola; Eric B Haura; Timothy J Yeatman; W Douglas Cress Journal: J Natl Cancer Inst Date: 2011-12-08 Impact factor: 13.506
Authors: Raymond U Osarogiagbon; Holly L Hilsenbeck; Elizabeth W Sales; Allen Berry; Robert W Jarrett; Christopher S Giampapa; Clara N Finch-Cruz; David Spencer Journal: Transl Lung Cancer Res Date: 2015-08