Identification of Crucial Genes Associated With MYCN-Driven Neuroblastoma Based on Single-Cell Analysis and Machine Learning

IF 3.1 2区医学 Q2 ONCOLOGY

Cancer Medicine Pub Date : 2025-07-02 DOI:10.1002/cam4.71008

Jiasi Zhang, Yichen Lei, Yaqin Wang, Wen Yu, Xiaoyan Zhao, Yongbing Zhu, Dedong Zhang, Siying Liu, Aiguo Liu

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Abstract

Background

Neuroblastoma (NB) with MYCN amplification is strongly correlated with high-risk stratification and poor prognosis. However, the underlying mechanisms remain incompletely understood. Elucidating these pathways is critical for advancing personalized treatments for MYCN-driven NB.

Methods

We performed single-cell transcriptomic analysis comparing NB samples with and without MYCN. Key genes were then identified using machine learning based random survival forest (RSF) and nomogram analyses. The influence of key genes on immune infiltration and molecular mechanisms driving NB progression were further investigated. Finally, we visualized the expression levels and global function of these genes in single-cell datasets and validated their expression in patient samples through RT-qPCR.

Results

Single-cell transcriptome analysis of GSE218450 identified marker genes specific to NB cells. RSF and nomogram analyses revealed that overexpression of CKB, PCSK1N, OTUB1, and VGF is associated with poor prognosis, whereas upregulation of NTRK3 indicates a favorable prognosis. These genes are significantly associated with immune cell infiltration and play an important role in modulating the immune microenvironment. Pathway analysis further showed that these genes influence critical signaling pathways, including the Wnt pathway, and interact with tumor-related genes. Additionally, we confirmed that CKB and PCSK1N are positively correlated with MYCN in NB cell lines and are significantly overexpressed in MYCN-amplified NB patients.

Conclusions

Our results provide molecular insights into the transcriptional changes associated with MYCN amplification in NB. In particular, the identification of CKB and PCSK1N suggests their potential role in driving tumor progression, making them promising targets for novel treatments in MYCN-driven NB.

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基于单细胞分析和机器学习的mycn驱动神经母细胞瘤相关关键基因鉴定

MYCN扩增的神经母细胞瘤（NB）与高危分层和不良预后密切相关。然而，潜在的机制仍然不完全清楚。阐明这些通路对于推进mycn驱动的NB的个性化治疗至关重要。方法进行单细胞转录组学分析，比较含有和不含有MYCN的NB样本。然后使用基于机器学习的随机生存森林（RSF）和nomogram分析来识别关键基因。进一步探讨了关键基因对免疫浸润的影响及NB进展的分子机制。最后，我们可视化了这些基因在单细胞数据集中的表达水平和整体功能，并通过RT-qPCR验证了它们在患者样本中的表达。结果GSE218450单细胞转录组分析鉴定出NB细胞特异性标记基因。RSF和nomogram分析显示，CKB、PCSK1N、OTUB1和VGF的过表达与预后不良相关，而NTRK3的上调则预示预后良好。这些基因与免疫细胞浸润显著相关，在调节免疫微环境中发挥重要作用。通路分析进一步表明，这些基因影响关键信号通路，包括Wnt通路，并与肿瘤相关基因相互作用。此外，我们证实CKB和PCSK1N在NB细胞系中与MYCN呈正相关，并且在MYCN扩增的NB患者中显著过表达。结论我们的研究结果为NB中MYCN扩增相关的转录变化提供了分子视角。特别是，CKB和PCSK1N的鉴定表明它们在驱动肿瘤进展中的潜在作用，使它们成为mycn驱动的NB的新治疗的有希望的靶点。

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来源期刊

Cancer Medicine ONCOLOGY-

CiteScore

5.50

自引率

2.50%

发文量

907

审稿时长

19 weeks

期刊介绍： Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas: Clinical Cancer Research Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations Cancer Biology: Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery. Cancer Prevention: Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach. Bioinformatics: Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers. Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.