A novel treatment stratification system for current low- and intermediate-risk neuroblastoma patients using gene expression-based classification

To improve risk estimation of low- and intermediate-risk neuroblastoma patients, we determined gene expression profiles of 709 primary neuroblastoma samples using 44 K oligonucleotide-microarrays. A prognostic gene expression-based classifier was generated using a training set of 75 samples and evaluated on the remaining 634 test set patients. In the low- and intermediate subgroup of patients (n = 413), the classifier predicted event-free (EFS) and overall survival (OS) accurately (EFS, 0.846 ± 0.020 vs. 0.376 ± 0.071; OS 0.996 ± 0.004 vs. 0.699 ± 0.070; both p < 0.001). In univariate Cox regression models based on EFS and OS, the classifier was a significant prognostic marker (EFS, hazard ratio 5.0, 95% CI 3.2 to 7.8; OS, hazard ratio 40.5, 95% CI 11.8 to 139.3; both p < 0.001). We therefore suggest to implementing the classifier in the upcoming German neuroblastoma trial. Based on subgroup analyses, we propose to reduce treatment intensity of favourably classified patients currently considered to be at intermediate risk, and to intensify treatment of unfavourably classified patients > 18 months at diagnosis with localized disease and patients with stage 4S neuroblastoma.