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剖析脑膜瘤中的内皮细胞格局:单细胞视角洞察亚群及其在肿瘤血管生成中的作用

Dissecting the endothelial cell landscape in meningioma: single-cell insights into + subpopulations and their role in tumor angiogenesis.

作者信息

Zhao Liang, Jia Hongling, Xiahou Zhikai, Ren Li, Song Yanbing, Xu Hao, Wang Zhihan, Xing Jin

机构信息

Department of Neurosurgery, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, China.

The First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.

出版信息

Front Immunol. 2025 May 27;16:1591125. doi: 10.3389/fimmu.2025.1591125. eCollection 2025.

DOI:10.3389/fimmu.2025.1591125
PMID:40496867
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12149221/
Abstract

BACKGROUND

Meningioma (MEN) is one of the most common intracranial tumors, with a significantly higher incidence rate in females than in males. Although the majority of cases are benign, tumors located in complex anatomical regions or classified as atypical or malignant have a high recurrence rate, underscoring the need to optimize therapeutic strategies to improve patient outcomes. Therefore, this study utilizes single-cell RNA-sequencing technology to investigate the interaction mechanisms between endothelial cells (ECs) and meningiomas, aiming to identify potential therapeutic targets for the treatment of MEN patients.

METHODS

Tissue origin analysis of different EC subpopulations was performed using Ro/e preference analysis. Gene Ontology and Gene Set Enrichment Analysis were employed to enrich and identify relevant biological processes. Slingshot and CytoTRACE were used to determine the differentiation trajectories of cell subpopulations. CellChat was utilized to predict intercellular communication between EC subpopulations and meningioma cells (MGCs). The transcription factor (TF) networks of EC subpopulations were constructed using pySCENIC, and the function of ETS1 was validated experiments.

RESULTS

The MEN and temporal lobe tissues' datasets were processed through quality control and screening, and dimensionality reduction clustering identified eight cell types. We found that ECs might play a role in MEN progression and further classified them into four subpopulations. Among these, the C2 + ECs were predominantly located at the later stages of differentiation in the Slingshot analysis, suggesting a critical role in MEN's development. Cell communication analysis revealed that MGCs might stimulate ECs to secrete angiopoietin via the MDK-NCL ligand-receptor pair, promoting angiogenesis and MEN's progression. Using pySCENIC analysis, the key TF ETS1 was identified. experiments demonstrated that ETS1 promoted ECs angiogenesis, proliferation, and migration, providing valuable insights for clinical strategies targeting MEN's treatment.

CONCLUSION

We identified a key ECs subpopulation, C2 + ECs, which was at a critical stage of MEN progression and might influence MEN development through the MK signaling pathway via the MDK-NCL ligand-receptor pair. Additionally, we discovered the critical TF ETS1 and validated through experiments that it promoted MEN's progression, offering a new perspective for clinical treatment strategies.

摘要

背景

脑膜瘤(MEN)是最常见的颅内肿瘤之一,女性发病率显著高于男性。尽管大多数病例为良性,但位于复杂解剖区域或分类为非典型或恶性的肿瘤复发率很高,这突出了优化治疗策略以改善患者预后的必要性。因此,本研究利用单细胞RNA测序技术研究内皮细胞(ECs)与脑膜瘤之间的相互作用机制,旨在确定治疗MEN患者的潜在治疗靶点。

方法

使用Ro/e偏好分析对不同EC亚群进行组织起源分析。采用基因本体论和基因集富集分析来富集和鉴定相关生物学过程。使用Slingshot和CytoTRACE确定细胞亚群的分化轨迹。利用CellChat预测EC亚群与脑膜瘤细胞(MGCs)之间的细胞间通讯。使用pySCENIC构建EC亚群的转录因子(TF)网络,并通过实验验证ETS1的功能。

结果

对MEN和颞叶组织的数据集进行质量控制和筛选,降维聚类确定了八种细胞类型。我们发现ECs可能在MEN进展中起作用,并将它们进一步分为四个亚群。其中,C2 + ECs在Slingshot分析中主要位于分化后期,表明在MEN发展中起关键作用。细胞通讯分析表明,MGCs可能通过MDK-NCL配体-受体对刺激ECs分泌血管生成素,促进血管生成和MEN进展。通过pySCENIC分析,确定了关键TF ETS1。实验表明ETS1促进ECs血管生成、增殖和迁移,为针对MEN治疗的临床策略提供了有价值的见解。

结论

我们确定了一个关键的ECs亚群,即C2 + ECs,它处于MEN进展的关键阶段,可能通过MDK-NCL配体-受体对经由MK信号通路影响MEN发展。此外,我们发现了关键TF ETS1,并通过实验验证它促进MEN进展,为临床治疗策略提供了新视角。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/54b051613bae/fimmu-16-1591125-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/ea7743baaf78/fimmu-16-1591125-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/a19e07c8721f/fimmu-16-1591125-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/910c248c2ed1/fimmu-16-1591125-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/c30ef954a7b4/fimmu-16-1591125-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/899fa2744ddc/fimmu-16-1591125-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/77c12c05b3b0/fimmu-16-1591125-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/c5063ffc9bc1/fimmu-16-1591125-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/54b051613bae/fimmu-16-1591125-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/ea7743baaf78/fimmu-16-1591125-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/a19e07c8721f/fimmu-16-1591125-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/910c248c2ed1/fimmu-16-1591125-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/c30ef954a7b4/fimmu-16-1591125-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/899fa2744ddc/fimmu-16-1591125-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/77c12c05b3b0/fimmu-16-1591125-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/c5063ffc9bc1/fimmu-16-1591125-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/12149221/54b051613bae/fimmu-16-1591125-g008.jpg

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