本研究旨在分析神经母细胞瘤（NB）的临床特征、细胞类型和肿瘤微环境的分子特征，以更好地预测其预后。从基因表达数据库（GEO: GSE62564）和ArrayExpress（登记号：E-MTAB-8248）获取了498例NB患者的基因表达数据和临床信息。利用R基因集变异分析（GSVA）软件包进行单样本基因集富集分析（ssGSEA）来估计相对细胞数量。我们进行了Cox回归分析，以确定表明细胞亚群的标记基因，并将其与预后相关的临床因素相结合，建立了一种新的预后模型。来自E-MTAB-8248队列的数据验证了预后模型的预测准确性。利用R Seurat软件包分析了单细胞RNA测序数据。对每个基因进行多因素生存分析，使用临床特征作为辅助因素，确定了与事件无进展生存（EFS）和总体生存（OS）均显著相关的34个预后基因（对数秩检验，P值<0.05）。通路富集分析显示，这些预后基因在NB具有间充质特征和蛋白翻译的标记基因中高度富集。最终，选择USP39、RPL8、IL1RAPL1、MAST4、CSRP2、ATP5E、国际神经母细胞瘤分期系统（INSS）分期、年龄和MYCN状态来构建NB风险分层的优化Cox模型。将这些样本根据风险评分的中位数作为分界点分为两组。贫预后组（PP）样本的预后显著较差，优预后组（GP）样本的预后显著较好（对数秩检验，P值<0.0001，中位EFS：640.5 vs. 2247天，中位OS：1279.5 vs. 2519天）。此风险模型也可作为独立于MYCN状态、年龄和分期的预后指标。最后，通过单细胞RNA测序数据，我们发现作为重要的预后标志物，USP39可能参与NB的RNA剪接调控。本研究建立了基于基因签名和临床特征的多因素Cox模型，以更好地预测NB的预后，并揭示了NB细胞的间充质标志基因，尤其是USP39，在预后差的患者中比预后好的患者更丰富。关键信息：本研究建立了基于基因签名和临床特征的多因素Cox模型，以更好地预测NB的预后，并揭示了NB细胞的间充质标志基因，尤其是USP39，在预后差的患者中比预后好的患者更丰富。选择USP39、RPL8、IL1RAPL1、MAST4、CSRP2、ATP5E、国际神经母细胞瘤分期系统（INSS）分期、年龄和MYCN状态构建了NB风险分层的优化Cox模型。将这些样本根据风险评分的中位数作为分界点分为两组。贫预后组（PP）样本的预后显著较差，优预后组（GP）样本的预后显著较好。最后，通过单细胞RNA测序数据，我们发现作为重要的预后标志物，USP39可能参与NB的RNA剪接调控。© 2023. 作者（根据Springer Nature的独家许可）发表于Springer-Verlag GmbH, 德国。

This study aimed to analyze the clinical characteristics, cell types, and molecular characteristics of the tumor microenvironment to better predict the prognosis of neuroblastoma (NB). The gene expression data and corresponding clinical information of 498 NB patients were obtained from the Gene Expression Omnibus (GEO: GSE62564) and ArrayExpress (accession: E-MTAB-8248). The relative cell abundances were estimated using single-sample gene set enrichment analysis (ssGSEA) with the R gene set variation analysis (GSVA) package. We performed Cox regression analyses to identify marker genes indicating cell subsets and combined these with prognostically relevant clinical factors to develop a new prognostic model. Data from the E-MTAB-8248 cohort verified the predictive accuracy of the prognostic model. Single-cell RNA-seq data were analyzed by using the R Seurat package. Multivariate survival analysis for each gene, using clinical characteristics as cofactors, identified 34 prognostic genes that showed a significant correlation with both event-free survival (EFS) and overall survival (OS) (log-rank test, P value < 0.05). The pathway enrichment analysis revealed that these prognostic genes were highly enriched in the marker genes of NB cells with mesenchymal features and protein translation. Ultimately, USP39, RPL8, IL1RAPL1, MAST4, CSRP2, ATP5E, International Neuroblastoma Staging System (INSS) stage, age, and MYCN status were selected to build an optimized Cox model for NB risk stratification. These samples were divided into two groups using the median of the risk score as a cutoff. The prognosis of samples in the poor prognosis group (PP) was significantly worse than that of samples in the good prognosis group (GP) (log-rank test, P value < 0.0001, median EFS: 640.5 vs. 2247 days, median OS: 1279.5 vs. 2519 days). The risk model was also regarded as a prognostic indicator independent of MYCN status, age, and stage. Finally, through scRNA-seq data, we found that as an important prognostic marker, USP39 might participate in the regulation of RNA splicing in NB. Our study established a multivariate Cox model based on gene signatures and clinical characteristics to better predict the prognosis of NB and revealed that mesenchymal signature genes of NB cells, especially USP39, were more abundant in patients with a poor prognosis than in those with a good prognosis. KEY MESSAGES: Our study established a multivariate Cox model based on gene signatures and clinical characteristics to better predict the prognosis of NB and revealed that mesenchymal signature genes of NB cells, especially USP39, were more abundant in patients with a poor prognosis than in those with a good prognosis. USP39, RPL8, IL1RAPL1, MAST4, CSRP2, ATP5E, International Neuroblastoma Staging System (INSS) stage, age, and MYCN status were selected to build an optimized Cox model for NB risk stratification. These samples were divided into two groups using the median of the risk score as a cutoff. The prognosis of samples in the poor prognosis group (PP) was significantly worse than that of samples in the good prognosis group (GP). Finally, through scRNA-seq data, we found that as an important prognostic marker, USP39 might participate in the regulation of RNA splicing in NB.© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.