Abstract
BackgroundCredible prognostic stratification remains a challenge for neuroblastoma (NBL) with variable clinical manifestations. RNA expression signatures might predict the outcomes; notwithstanding, independent cross-platform validation is still rare. MethodsRNA expression data were obtained from NBL patients and then analyzed. In TARGET-NBL data, an RNA-based prognostic signature was developed and validated. Survival prediction was assessed using a time-dependent receiver operating characteristic (ROC) curve. Functional enrichment analysis of the RNAs was conducted using bioinformatics methods. ResultsA total of 1,119 differentially expressed RNAs and 149 prognosis-related RNAs were identified sequentially. Then, in the training cohort, 12 RNAs were identified as significantly associated with overall survival (OS) and were combined to develop a model that stratified NBL patients into low- and high-risk groups. Twelve RNA signature high-risk patients had poorer OS in the training cohort (n=105, Hazard Ratios (HR)= 0.10 (0.05-0.20), P<0.001) and in the validation cohort (n=44, HR=0.25 (0.09-0.69), P=0.008). ROC curve analysis also showed that both the training and validation cohorts performed well in predicting OS (12-month AUC values of 0.852 and 0.438, 36-month AUC values of 0.824 and 0.737, and 60-month AUC values of 0.802 and 0.702, respectively). Moreover, these 12 RNAs may be involved in certain events that are known to be associated with NBL through functional enrichment analysis. ConclusionsThis study identified and validated a novel 12-RNA prognostic signature to reliably distinguish NBL patients at low and high risk of death. Further larger, multicenter prospective studies are desired to validate this model. Legal entity responsible for the studyThe authors. FundingNational Natural Science Foundation of China (Grant No. 81660512). DisclosureAll authors have declared no conflicts of interest.
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