Identification of a Five-Gene Signature Derived From MYCN Amplification and Establishment of a Nomogram for Predicting the Prognosis of Neuroblastoma - Xia, Yuren; Li, Xin; Tian, Xiangdong; Zhao, Qiang (Frontiers in Molecular Biosciences, 2021)
Background: Neuroblastoma (NB), the most common solid tumor in children, exhibits vastly different genomic abnormalities and clinical behaviors. While significant progress has been made on the research of relations between clinical manifestations and genetic abnormalities, it remains a major challenge to predict the prognosis of patients to facilitate personalized treatments. Materials and Methods: Six datasets of gene expression and related clinical data were downloaded from the Gene Expression Omnibus (GEO) database, ArrayExpress database and Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. According to the presence or absence of MYCN amplification, patients were divided into two groups. Differentially expressed genes (DEGs) were identified between the two groups. Enrichment analyses of these DEGs were performed to dig further into the molecular mechanism of NB. Stepwise Cox regression analyses were used to establish a five-gene prognostic signature whose predictive performance was further evaluated by external validation. Multivariate Cox regression analyses were used to explore independent prognostic factors for NB. The relevance of immunity was evaluated by using algorithms, and a nomogram was constructed. Results: A five-gene signature comprising CPLX3, GDPD5, SPAG6, NXPH1 and AHI1 was established. The five-gene signature had good performance in predicting survival and was demonstrated to be superior to International Neuroblastoma Staging System (INSS) staging and MYCN amplification status. Finally, a nomogram based on the five gene signature was established, and its clinical efficacy was demonstrated. Conclusion: Collectively, our study developed a novel five-gene signature and successfully built a prognostic nomogram that accurately predicted survival in NB. The findings presented here could help to stratify patients into subgroups and determine the optimal individualized therapy.