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多组学分析揭示神经母细胞瘤分子特征可预测风险分层及肿瘤微环境差异。

Multiomics Analysis Reveals Neuroblastoma Molecular Signature Predicting Risk Stratification and Tumor Microenvironment Differences.

作者信息

Zhou Xing, Zhou Zhaokai, Qin Xiaohan, Cheng Jian, Fu Yongcheng, Wang Yuanyuan, Wang Jingyue, Qin Pan, Zhang Da

机构信息

Department of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China.

Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China.

出版信息

J Proteome Res. 2025 Apr 4;24(4):1606-1623. doi: 10.1021/acs.jproteome.4c00882. Epub 2025 Jan 6.

DOI:10.1021/acs.jproteome.4c00882
PMID:39762147
Abstract

Neuroblastoma (NB) remains associated with high mortality and low initial response rate, especially for high-risk patients, thus warranting exploration of molecular markers for precision risk classifiers. Through integrating multiomics profiling, we identified a range of hub genes involved in cell cycle and associated with dismal prognosis and malignant cells. Single-cell transcriptome sequencing revealed that a subset of malignant cells, subcluster 1, characterized by high proliferation and dedifferentiation, was strongly correlated with the hub gene signature and orchestrated an immunosuppressive tumor microenvironment (TME). Furthermore, we constructed a robust malignant subcluster 1 related signature (MSRS), which was an independent prognostic factor and superior to other clinical characteristics and published signatures. Besides, TME differences conferred remarkably distinct therapeutic responses between high and low MSRS groups. Notably, polo-like kinase-1 (PLK1) was one of the most crucial contributors to MSRS and remarkably correlated with malignant subcluster 1, and PLK1 inhibition was effective for NB treatment as demonstrated by analysis and experiments. Overall, our study constructs a novel molecular model to further guide the clinical classification and individualized treatment of NB.

摘要

神经母细胞瘤(NB)仍然与高死亡率和低初始缓解率相关,尤其是对于高危患者而言,因此有必要探索用于精准风险分类器的分子标志物。通过整合多组学分析,我们鉴定出一系列参与细胞周期且与不良预后及恶性细胞相关的枢纽基因。单细胞转录组测序显示,以高增殖和去分化为特征的一部分恶性细胞亚群1与枢纽基因特征密切相关,并构建了一个免疫抑制性肿瘤微环境(TME)。此外,我们构建了一个强大的恶性亚群1相关特征(MSRS),它是一个独立的预后因素,优于其他临床特征和已发表的特征。此外,TME差异在高MSRS组和低MSRS组之间赋予了显著不同的治疗反应。值得注意的是,polo样激酶-1(PLK1)是MSRS的最关键贡献者之一,并且与恶性亚群1显著相关,分析和实验表明PLK1抑制对NB治疗有效。总体而言,我们的研究构建了一种新型分子模型,以进一步指导NB的临床分类和个体化治疗。

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