A 12-Gene Set Predicts Survival Benefits from Adjuvant Chemotherapy in Non–Small Cell Lung Cancer Patients

• 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
• Subjects: Adult; Aged; Carcinoma, Non-Small-Cell Lung - drug therapy; Carcinoma, Non-Small-Cell Lung - genetics; Carcinoma, Non-Small-Cell Lung - pathology; Chemotherapy, Adjuvant; Clinical Trials as Topic; Female; Gene Expression Regulation, Neoplastic; Genome, Human; Humans; Kaplan-Meier Estimate; Lung Neoplasms - drug therapy; Lung Neoplasms - genetics; Lung Neoplasms - mortality; Male; Middle Aged; Neoplasm Proteins - genetics; Neoplasm Staging; Prognosis; RNA Interference; Systems Biology; Treatment Outcome
• ISSN: 1078-0432; 1557-3265; 1557-3265
• DOI: 10.1158/1078-0432.CCR-12-2321

Purpose: 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. Experimental Design: 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. Results: 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). Conclusions: 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. Clin Cancer Res; 19(6); 1577–86. ©2013 AACR.