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Abstract：
Neuroblastoma (NB) is the most prevalent malignant solid tumor in children. Tumor metabolism, including lipid, amino acid, and glucose metabolism, is intricately linked to the genesis and progression of tumors. This study aimed to establish a prognostic gene signature for NB patients, based on metabolism-related genes, and to investigate a treatment approach that could enhance the survival rate of high-risk NB patients. From the NB dataset GSE49710, we identified metabolism-related gene markers utilizing the \"limma\" R package and univariate Cox analysis combined with least absolute shrinkage and selection operator (LASSO) regression analysis. We explored the correlation between these gene markers and the overall survival of NB patients. Gene set enrichment analysis (GSEA) and single-sample GSEA algorithms were used to assess the differences in metabolism and immune status. Furthermore, we examined the association between metabolic subgroups and drug responsiveness. Concurrently, data downloaded from TARGET and MTAB were used for external verification. Using multicolor immunofluorescence and immunohistochemistry, we investigated the relationship between the lipid metabolism-related gene ELOVL6 with both the International Neuroblastoma Staging System classification of NB and survival rate. Finally, we explored the effect of high ELOVL6 expression on the immune microenvironment in NB using flow cytometry. We identified an eight-gene signature comprising metabolism-related genes in NB: ELOVL6, OSBPL9, RPL27A, HSD17B3, ACHE, AKR1C1, PIK3R1, and EPHX2. This panel effectively predicted disease-free survival, and was validated using an internal dataset from GSE49710 and two external datasets from the TARGET and MTAB databases. Moreover, our findings confirmed that ELOVL6 fosters an immunosuppressive microenvironment and contributes to the malignant progression in NB. The eight-gene signature is significant in predicting the prognosis of NB, effectively classifying patients into high- and low-risk groups. This classification may guide the development of innovative treatment strategies for these patients. Notably, the signature gene ELOVL6 markedly encourages an immunosuppressive microenvironment and malignant progression in NB.
摘要：
神经母细胞瘤（NB）是儿童最常见的恶性实体瘤。肿瘤代谢,包括脂质，氨基酸,和葡萄糖代谢，与肿瘤的发生和发展有着千丝万缕的联系.本研究旨在建立NB患者的预后基因标记,基于代谢相关基因，探讨提高高危NB患者生存率的治疗方法。从NB数据集GSE49710中，我们使用“limma”R包和单变量Cox分析结合最小绝对收缩和选择算子（LASSO）回归分析确定了与代谢相关的基因标记。我们探讨了这些基因标记与NB患者总体生存率之间的相关性。使用基因集富集分析（GSEA）和单样品GSEA算法来评估代谢和免疫状态的差异。此外，我们研究了代谢亚组与药物反应性之间的关联.同时,从TARGET和MTAB下载的数据用于外部验证.使用多色免疫荧光和免疫组织化学，我们调查了脂质代谢相关基因ELOVL6与国际神经母细胞瘤分期系统分类NB和生存率之间的关系。最后,我们使用流式细胞术研究了高ELOVL6表达对NB免疫微环境的影响。我们在NB中鉴定了包含代谢相关基因的8个基因标签：ELOVL6，OSBPL9，RPL27A，HSD17B3,ACHE,AKR1C1、PIK3R1和EPHX2。这个小组有效地预测了无病生存率，并使用来自GSE49710的内部数据集和来自TARGET和MTAB数据库的两个外部数据集进行了验证。此外，我们的研究结果证实,ELOVL6促进了免疫抑制微环境,并有助于NB的恶性进展.8个基因标记对预测NB的预后有重要意义。有效地将患者分为高风险和低风险组。这种分类可以指导针对这些患者的创新治疗策略的开发。值得注意的是,特征基因ELOVL6显著促进NB的免疫抑制微环境和恶性进展.
