Identification and validation of a novel five-gene signature in high-risk MYCN-not-amplified neuroblastoma

High-risk neuroblastoma patients often have poor outcomes despite multi-treatment options. The risk stratification of high-risk MYCN-not-amplified (HR-MYCN-NA) patients remains difficult. This study aims to identify a gene set signature that can help further stratify HR-MYCN-NA patients for a potential personalized therapeutic strategy.

Three microarrays and one single-cell RNA sequence dataset were acquired and analyzed. Firstly, the prognostic-related genes (PRGs) in HR-MYCN-NA tumor cells were identified using TARGET-NB and GSE137804 datasets. Then, the prognostic model was established by LASSO-Cox regression, and verified in external cohort (GSE49710, GSE45547). Moreover, a time-dependent receiver operating characteristic curve (ROC) and area under the ROC (AUC) was used to assess survival prediction. A nomogram was established to predict the 1-, 3- and 5-year overall survival (OS) of HR-MYCN-NA patients.

In the training set, a five-PRGs signature, which include GAL, GFRA3, MARCKS, PSMD13, and ZNHIT3 genes, was identified and successfully stratified HR-MYCN-NA patients into ultra-high risk (UHR) and high-risk (HR) subtypes (HR = 4.29, P < 0.001). ROC curve analysis confirmed its predictive power (AUC = 0.74-0.82), suggesting a good predictive efficacy. Consistently, high-risk scores also predicted worse OS (HR = 2, P = 0.033) in the external validation dataset (AUC = 0.67-0.71). Moreover, the overall C-index of the nomogram was 0.75 (P < 0.001), which indicated good agreement between the observed and predicted survival rates. Further integrating the five PRGs signature with clinical factors, these 5 gene signature (HR = 4.45, P < 0.001) and tumor grade (HR = 4.15, P = 0.02) were found to be independent prognostic factors for HR-MYCN-NA patients.

The novel five PRGs signature could well predict the survival of HR-MYCN-NA patients, which may provide constructive information for these subsets.