PURPOSE: Several microarray studies have reported gene expression signatures that classify non-small-cell lung carcinoma (NSCLC) patients into different prognostic groups. However, the prognostic gene lists reported to date overlap poorly across studies, and few have been validated independently using more quantitative assay methods. PATIENTS AND METHODS: The expression of 158 putative prognostic genes identified in previous microarray studies was analyzed by reverse transcription quantitative polymerase chain reaction in the tumors of 147 NSCLC patients. Concordance indices and risk scores were used to identify a stage-independent set of genes that could classify patients with significantly different prognoses. RESULTS: We have identified a three-gene classifier (STX1A, HIF1A, and CCR7) for overall survival (hazard ratio = 3.8; 95% CI, 1.7 to 8.2; P < .001). The classifier was also able to stratify stage I and II patients and further improved the predictive ability of clinical factors such as histology and tumor stage. The predictive value of this three-gene classifier was validated in two large independent microarray data sets from Harvard and Duke Universities. CONCLUSION: We have identified a new three-gene classifier that is independent of and improves on stage to stratify early-stage NSCLC patients with significantly different prognoses. This classifier may be tested further for its potential value to improve the selection of resected NSCLC patients in adjuvant therapy.
PURPOSE: Several microarray studies have reported gene expression signatures that classify non-small-cell lung carcinoma (NSCLC) patients into different prognostic groups. However, the prognostic gene lists reported to date overlap poorly across studies, and few have been validated independently using more quantitative assay methods. PATIENTS AND METHODS: The expression of 158 putative prognostic genes identified in previous microarray studies was analyzed by reverse transcription quantitative polymerase chain reaction in the tumors of 147 NSCLCpatients. Concordance indices and risk scores were used to identify a stage-independent set of genes that could classify patients with significantly different prognoses. RESULTS: We have identified a three-gene classifier (STX1A, HIF1A, and CCR7) for overall survival (hazard ratio = 3.8; 95% CI, 1.7 to 8.2; P < .001). The classifier was also able to stratify stage I and II patients and further improved the predictive ability of clinical factors such as histology and tumor stage. The predictive value of this three-gene classifier was validated in two large independent microarray data sets from Harvard and Duke Universities. CONCLUSION: We have identified a new three-gene classifier that is independent of and improves on stage to stratify early-stage NSCLCpatients with significantly different prognoses. This classifier may be tested further for its potential value to improve the selection of resected NSCLCpatients in adjuvant therapy.
Authors: Johannes R Kratz; Jianxing He; Stephen K Van Den Eeden; Zhi-Hua Zhu; Wen Gao; Patrick T Pham; Michael S Mulvihill; Fatemeh Ziaei; Huanrong Zhang; Bo Su; Xiuyi Zhi; Charles P Quesenberry; Laurel A Habel; Qiuhua Deng; Zongfei Wang; Jiangfen Zhou; Huiling Li; Mei-Chun Huang; Che-Chung Yeh; Mark R Segal; M Roshni Ray; Kirk D Jones; Dan J Raz; Zhidong Xu; Thierry M Jahan; David Berryman; Biao He; Michael J Mann; David M Jablons Journal: Lancet Date: 2012-01-27 Impact factor: 79.321
Authors: Paul C Boutros; Suzanne K Lau; Melania Pintilie; Ni Liu; Frances A Shepherd; Sandy D Der; Ming-Sound Tsao; Linda Z Penn; Igor Jurisica Journal: Proc Natl Acad Sci U S A Date: 2009-02-05 Impact factor: 11.205
Authors: Stephenie D Prokopec; John D Watson; Daryl M Waggott; Ashley B Smith; Alexander H Wu; Allan B Okey; Raimo Pohjanvirta; Paul C Boutros Journal: RNA Date: 2012-11-20 Impact factor: 4.942