For neuroblastoma, the most common extracranial tumour of childhood, identification of new biomarkers and potential therapeutic targets is mandatory to improve risk stratification and survival rates. MicroRNAs are deregulated in most cancers, including neuroblastoma. In this study, we analysed 430 miRNAs in 69 neuroblastomas by stem-loop RT-qPCR. Prediction of event-free survival (EFS) with support vector machines (SVM) and actual survival times with Cox regression-based models (CASPAR) were highly accurate and were independently validated. SVM-accuracy for prediction of EFS was 88.7% (95% CI: 88.5-88.8%). For CASPAR-based predictions, 5y-EFS probability was 0.19% (95% CI: 0-38%) in the CASPAR-predicted short survival group compared with 0.78% (95%CI: 64-93%) in the CASPAR-predicted long survival group. Both classifiers were validated on an independent test set yielding accuracies of 94.74% (SVM) and 5y-EFS probabilities as 0.25 (95% CI: 0.0-0.55) for short versus 1 6 0.0 for long survival (CASPAR), respectively. Amplification of the MYCN oncogene was highly correlated with deregulation of miRNA expression. In addition, 37 miRNAs correlated with TrkA expression, a marker of excellent outcome, and 6 miRNAs further analysed in vitro were regulated upon TrkA transfection, suggesting a functional relationship. Expression of the most significant TrkA-correlated miRNA, miR-542-5p, also discriminated between local and metastatic disease and was inversely correlated with MYCN amplification and event-free survival. We conclude that neuroblastoma patient outcome prediction using miRNA expression is feasible and effective. Studies testing miRNA-based predictors in comparison to and in combination with mRNA and aCGH information should be initiated. Specific miRNAs (e.g., miR-542-5p) might be important in neuroblastoma tumour biology, and qualify as potential therapeutic targets.Relapse or progression of advanced stage neuroblastoma (NB), the most common extracranial solid tumour of childhood, represents a major treatment challenge in paediatric oncology. Almost one third of all children with advanced stage NB is incurable, and NB accounts for approximately 15% of all childhood cancer deaths. Neuroblastoma is clinically heterogeneous. Tumours of patients with favourable disease may undergo spontaneous regression or differentiation even without therapy. In contrast, patients with unfavourable NB die despite intensive therapy. Favourable tumours are most often localised, stage 1 or 2 tumours, and unfavourable are most often stage 4, metastasised tumours. Stage 4 tumours are metastasised tumours in patients under 1 year of age, which often undergo spontaneous regression with no or minimal therapy. The tumour biology of unfavourable NB is characterised by MYCN amplification, low expression of the TrkA receptor tyrosine kinase and distinct chromosomal aberrations (reviewed in Refs. 1 and 2). Survival rates of patients with unfavourable NB can only be improved by a better understanding of the molecular pathogenesis of NB. This may...

Purpose More accurate assessment of prognosis is important to further improve the choice of risk-related therapy in neuroblastoma (NB) patients. In this study, we aimed to establish and validate a prognostic miRNA signature for children with NB and tested it in both fresh frozen and archived formalin-fixed paraffin-embedded (FFPE) samples. Experimental Design Four hundred-thirty human mature miRNAs were profiled in two patient subgroups with maximally divergent clinical courses. Univariate logistic regression analysis was used to select miRNAs correlating with NB patient survival. A 25-miRNA gene signature was built using 51 training samples, tested on 179 test samples, and validated on an independent set of 304 fresh frozen tumor samples and 75 archived FFPE samples. Results The 25-miRNA signature significantly discriminates the test patients with respect to progression-free and overall survival (P < 0.0001), both in the overall population and in the cohort of high-risk patients. Multivariate analysis indicates that the miRNA signature is an independent predictor of patient survival after controlling for current risk factors. The results were confirmed in an external validation set. In contrast to a previously published mRNA classifier, the 25-miRNA signature was found to be predictive for patient survival in a set of 75 FFPE neuroblastoma samples. Conclusions In this study, we present the largest NB miRNA expression study so far, including more than 500 NB patients. We established and validated a robust miRNA classifier, able to identify a cohort of high-risk NB patients at greater risk for adverse outcome using both fresh frozen and archived material.