Identification of Potential Prognostic Genes for Neuroblastoma - Zhong, Xiaodan; Liu, Yuanning; Liu, Haiming; Zhang, Yutong; Wang, Linyu; Zhang, Hao (Frontiers in Genetics, 2018)
Background and Objective: Neuroblastoma (NB), the most common pediatric solid tumor apart from brain tumor, is associated with a dismal long-term survival. The aim of this study was to identify a gene signature to predict the prognosis of NB patients. Materials and Methods: GSE49710 dataset from the Gene Expression Omnibus (GEO) database was downloaded and differentially expressed genes (DEGs) were analyzed using R package “limma” and SPSS software. The gene ontology (GO) and pathway enrichment analysis were established via DAVID database. The gene signature in predicting the prognosis was picked out by risk score model. Simultaneously, the receiving operating characteristic (ROC) and Kaplan-Meier curve were plotted. GSE45480 and GSE16476 datasets were employed to validate the robustness of the gene signature. Results: A total of 131 DEGs were identified, which were mainly enriched in cancer-related pathways. The four-gene signature (ERCC6L, AHCY, STK33, and NCAN) was selected to predict the prognosis in NB patients, its area under the curve (AUC) could reach 0.86, and Cox regression analysis revealed that the 4-gene signature was an independent prognostic factor of the overall survival and event-free survival. Additionally, the robustness of discriminating different groups of the 4-gene signature was verified to have a commendable performance in GSE45480 and GSE49710. Conclusion: The present study identified a gene-signature in predicting the prognosis in NB, which may provide novel prognostic markers, and some of the genes may be as treatment targets according to biological experiments in the future.