Originally published as JCO Early Release 10.1200/JCO.2008.16.6991 on February 2 2009

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Three Immunomarker Support Vector Machines–Based Prognostic Classifiers for Stage IB Non–Small-Cell Lung Cancer

Zhi-Hua Zhu, Bing-Yu Sun, Yun Ma, Jian-Yong Shao, Hao Long, Xu Zhang, Jian-Hua Fu, Lan-Jun Zhang, Xiao-Dong Su, Qiu-Liang Wu, Peng Ling, Ming Chen, Ze-Ming Xie, Yi Hu, Tie-Hua Rong

From the Departments of Thoracic Oncology, Pathology, and Radiation Oncology, State Key Laboratory of Oncology in South China, Cancer Center, Lung Cancer Research Center; and Reproductive Research Center, the Second Affiliated Hospital, Sun Yat-sen University, Guangzhou; and Institute of Intelligence Machine, Chinese Academy of Sciences, Hefei, People's Republic of China.

Corresponding author: Tie-Hua Rong, MD, Department of Thoracic Oncology, Cancer Center of Sun Yat-Sen University, 651 Dongfeng Rd E, Guangzhou 510060, People's Republic of China; e-mail: rongth{at}live.cn.

Purpose Approximately 30% of patients with stage IB non–small-cell lung cancer (NSCLC) die within 5 years after surgery. Current staging methods are inadequate for predicting the prognosis of this particular subgroup. This study identifies prognostic markers for NSCLC.

Patients and Methods We used computer-generated random numbers to study 148 paraffin-embedded specimens for immunohistochemical analysis. We studied gene expression in paraffin-embedded specimens of lung cancer tissue from 73 randomly selected patients with stage IB NSCLC who had undergone radical surgical resection and evaluated the association between the level of expression and survival. We used support vector machines (SVM)–based methods to develop three immunomarker-SVM–based prognostic classifiers for stage IB NSCLC. For validation, we used randomly assigned specimens from 75 other patients.

Results We devised three immunomarker-SVM–based prognostic classifiers, including SVM1, SVM2, and SVM3, to refine prognosis of stage IB NSCLC successfully. The SVM1 model integrates age, cancer cell type, and five markers, including CD34MVD, EMA, p21ras, p21WAF1, and tissue inhibitors of metalloproteinases (TIMP) –2. The SVM2 model integrates age, cancer cell type, and 19 markers, including BCL2, caspase-9, CD34MVD, low-molecular-weight cytokeratin, high-molecular-weight cytokeratin, cyclo-oxygenase-2, EMA, HER2, matrix metalloproteinases (MMP) –2, MMP-9, p16, p21ras, p21WAF1, p27kip1, p53, TIMP-1, TIMP-2, vascular endothelial growth factor (VEGF), and β-catenin. The SVM3 model consists of SVM1 and SVM2. The three models were independent predictors of overall survival. We validated the classifiers with data from an independent cohort of 75 patients with stage IB NSCLC.

Conclusion The three immunomarker-SVM–based prognostic characteristics are closely associated with overall survival among patients with stage IB NSCLC.

Z.-H.Z., B.-Y.S., and Y.M. contributed equally to this article.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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