A five-gene signature and clinical outcome in non-small-cell lung cancer

Hsuan Yu Chen, Sung Liang Yu, Chun Houh Chen, Gee Chen Chang, Chih Yi Chen, Ang Yuan, Chiou Ling Cheng, Chien Hsun Wang, Harn Jing Terng, Shu Fang Kao, Wing Kai Chan, Han Ni Li, Chun Chi Liu, Sher Singh, Wei J. Chen, Jeremy J.W. Chen, Pan Chyr Yang

Research output: Contribution to journalArticle

653 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)11-20
Number of pages10
JournalNew England Journal of Medicine
Volume356
Issue number1
DOIs
Publication statusPublished - 2007 Jan 4

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Non-Small Cell Lung Carcinoma
Genes
Survival
Decision Trees
Decision Support Techniques
Reverse Transcriptase Polymerase Chain Reaction
Gene Expression
Recurrence
Microarray Analysis
Real-Time Polymerase Chain Reaction
Lung Neoplasms

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Chen, H. Y., Yu, S. L., Chen, C. H., Chang, G. C., Chen, C. Y., Yuan, A., ... Yang, P. C. (2007). A five-gene signature and clinical outcome in non-small-cell lung cancer. New England Journal of Medicine, 356(1), 11-20. https://doi.org/10.1056/NEJMoa060096

A five-gene signature and clinical outcome in non-small-cell lung cancer. / Chen, Hsuan Yu; Yu, Sung Liang; Chen, Chun Houh; Chang, Gee Chen; Chen, Chih Yi; Yuan, Ang; Cheng, Chiou Ling; Wang, Chien Hsun; Terng, Harn Jing; Kao, Shu Fang; Chan, Wing Kai; Li, Han Ni; Liu, Chun Chi; Singh, Sher; Chen, Wei J.; Chen, Jeremy J.W.; Yang, Pan Chyr.

In: New England Journal of Medicine, Vol. 356, No. 1, 04.01.2007, p. 11-20.

Research output: Contribution to journalArticle

Chen, HY, Yu, SL, Chen, CH, Chang, GC, Chen, CY, Yuan, A, Cheng, CL, Wang, CH, Terng, HJ, Kao, SF, Chan, WK, Li, HN, Liu, CC, Singh, S, Chen, WJ, Chen, JJW & Yang, PC 2007, 'A five-gene signature and clinical outcome in non-small-cell lung cancer', New England Journal of Medicine, vol. 356, no. 1, pp. 11-20. https://doi.org/10.1056/NEJMoa060096
Chen, Hsuan Yu ; Yu, Sung Liang ; Chen, Chun Houh ; Chang, Gee Chen ; Chen, Chih Yi ; Yuan, Ang ; Cheng, Chiou Ling ; Wang, Chien Hsun ; Terng, Harn Jing ; Kao, Shu Fang ; Chan, Wing Kai ; Li, Han Ni ; Liu, Chun Chi ; Singh, Sher ; Chen, Wei J. ; Chen, Jeremy J.W. ; Yang, Pan Chyr. / A five-gene signature and clinical outcome in non-small-cell lung cancer. In: New England Journal of Medicine. 2007 ; Vol. 356, No. 1. pp. 11-20.
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AU - Chen, Chih Yi

AU - Yuan, Ang

AU - Cheng, Chiou Ling

AU - Wang, Chien Hsun

AU - Terng, Harn Jing

AU - Kao, Shu Fang

AU - Chan, Wing Kai

AU - Li, Han Ni

AU - Liu, Chun Chi

AU - Singh, Sher

AU - Chen, Wei J.

AU - Chen, Jeremy J.W.

AU - Yang, Pan Chyr

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N2 - 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.

AB - 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.

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