A 12-gene set predicts survival benefits from adjuvant chemotherapy in non-small cell lung cancer patients

Prospectively identifying who will benefit from adjuvant chemotherapy (ACT) would improve clinical decisions for non-small cell lung cancer (NSCLC) patients. In this study, we aim to develop and validate a functional gene set that predicts the clinical benefits of ACT in NSCLC. An 18-hub-gene progno...

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Published in:Clinical cancer research Vol. 19; no. 6; pp. 1577 - 1586
Main Authors: Tang, Hao, Xiao, Guanghua, Behrens, Carmen, Schiller, Joan, Allen, Jeffrey, Chow, Chi-Wan, Suraokar, Milind, Corvalan, Alejandro, Mao, Jianhua, White, Michael A, Wistuba, Ignacio I, Minna, John D, Xie, Yang
Format: Journal Article
Language:English
Published: United States 15-03-2013
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Summary:Prospectively identifying who will benefit from adjuvant chemotherapy (ACT) would improve clinical decisions for non-small cell lung cancer (NSCLC) patients. In this study, we aim to develop and validate a functional gene set that predicts the clinical benefits of ACT in NSCLC. An 18-hub-gene prognosis signature was developed through a systems biology approach, and its prognostic value was evaluated in six independent cohorts. The 18-hub-gene set was then integrated with genome-wide functional (RNAi) data and genetic aberration data to derive a 12-gene predictive signature for ACT benefits in NSCLC. Using a cohort of 442 stage I to III NSCLC patients who underwent surgical resection, we identified an 18-hub-gene set that robustly predicted the prognosis of patients with adenocarcinoma in all validation datasets across four microarray platforms. The hub genes, identified through a purely data-driven approach, have significant biological implications in tumor pathogenesis, including NKX2-1, Aurora Kinase A, PRC1, CDKN3, MBIP, and RRM2. The 12-gene predictive signature was successfully validated in two independent datasets (n = 90 and 176). The predicted benefit group showed significant improvement in survival after ACT (UT Lung SPORE data: HR = 0.34, P = 0.017; JBR.10 clinical trial data: HR = 0.36, P = 0.038), whereas the predicted nonbenefit group showed no survival benefit for 2 datasets (HR = 0.80, P = 0.70; HR = 0.91, P = 0.82). This is the first study to integrate genetic aberration, genome-wide RNAi data, and mRNA expression data to identify a functional gene set that predicts which resectable patients with non-small cell lung cancer will have a survival benefit with ACT.
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ISSN:1078-0432
1557-3265
DOI:10.1158/1078-0432.ccr-12-2321