Background Neuroblastoma (NB) is the most common extracranial solid tumor in children and is characterized by marked clinical and molecular heterogeneity. Genomic alterations play a critical role in NB pathogenesis; however, population-specific mutational features remain insufficiently characterized, particularly among Chinese patients. Methods Whole-exome sequencing (WES) was performed on tumor, para-tumor, and matched peripheral blood samples from nine pathologically confirmed Chinese patients with NB. Somatic variant profiles were compared with four publicly available NB datasets from cBioPortal, published in 2012, 2013, 2015, and 2023. Mutational patterns, recurrently altered genes, and Gene Ontology (GO) enrichment were analyzed using R version 4.3.2 and clusterProfiler version 4.10.0. Results A total of 77 missense variants were identified in our cohort. Single-nucleotide polymorphisms (SNPs) represented the predominant variant type, and C > T substitutions were the most frequent nucleotide change. MAP1A variants, comprising two missense variants in one patient, and RBM33 variants, comprising two distinct variants in two patients, were detected in our cohort and, to the best of our knowledge, have not been previously reported in NB, although their frequencies were low. No MYCN amplification or variants in ALK , ATRX , or DAXX were detected. Comparative analysis with the cBioPortal datasets revealed no somatic variants universally shared across all cohorts. In addition, high-risk patients exhibited distinct mutational patterns, with enrichment of the Gene Ontology term “collagen-containing extracellular matrix.” Conclusions These findings highlight the molecular diversity of NB and suggest the presence of potential population-specific genetic features in Chinese patients. The low-frequency MAP1A and RBM33 variants identified in this cohort warrant further validation in larger, independent cohorts. Moreover, the enrichment of extracellular matrix–related pathways in high-risk NB supports further investigation of tumor–microenvironment interactions as potential therapeutic targets.
Wang et al. (2026) studied this question.