Eight-Signature Classifier for Prediction of Nasopharyngeal Carcinoma Survival

Abstract

Purpose Currently, nasopharyngeal carcinoma (NPC) prognosis evaluation is based primarily on the TNM staging system. This study aims to identify prognostic markers for NPC. Patients and Methods We detected expression of 18 biomarkers by immunohistochemistry in NPC tumors from 209 patients and evaluated the association between gene expression level and disease-specific survival (DSS). We used support vector machine (SVM) –based methods to develop a prognostic classifier for NPC (NPC-SVM classifier). Further validation of the NPC-SVM classifier was performed in an independent cohort of 1,059 patients. Results The NPC-SVM classifier integrated patient sex and the protein expression level of seven genes, including Epstein-Barr virus latency membrane protein 1, CD147, caveolin-1, phospho-P70S6 kinase, matrix metalloproteinase 11, survivin, and secreted protein acidic and rich in cysteine. The NPC-SVM classifier distinguished patients with NPC into low- and high-risk groups with significant differences in 5-year DSS in the evaluated patients (87% v 37.7%; P < .001) in the validation cohort. In multivariate analysis adjusted for age, TNM stage, and histologic subtype, the NPC-SVM classifier was an independent predictor of 5-year DSS in the evaluated patients (hazard ratio, 4.9; 95% CI, 3.0 to 7.9) in the validation cohort. Conclusion As a powerful predictor of 5-year DSS among patients with NPC, the newly developed NPC-SVM classifier based on tumor-associated biomarkers will facilitate patient counseling and individualize management of patients with NPC.