Prediction of clinical outcome and biological characterization of neuroblastoma by expression profiling

Although numerous prognostic factors have been identified, precise risk evaluation in individual neuroblastoma patients remains difficult. To define a reliable predictor for event-free survival after first-line therapy and to identify gene signatures characteristic for clinical and biological subgroups, we performed expression profiling of 68 primary neuroblastomas of all stages by Affymetrix U95A arrays. Expression data from subgroups were analyzed using machine learning methods. Recurrence of neuroblastoma within two years of diagnosis was correctly predicted in 83% of cases using support vector machines (SVM)…