Identification of diverse tumor endothelial cell populations in malignant glioma
Background: Glioblastoma is the most common and aggressive type of primary brain tumor, as most patients succumb to the disease less than two years after diagnosis. Critically, studies demonstrate that glioma recruits surrounding blood vessels, while some work suggests that tumor stem cells themselves directly differentiate into endothelial cells, yet the molecular and cellular dynamics of the endothelium in glioma are poorly characterized. The goal of this study was to establish molecular and morphological benchmarks for tumor associated vessels (TAVs) and tumor derived endothelial cells (TDECs) during glioblastoma progression. Methods: Using In-Utero Electroporation and CRISPR/Cas9 genome engineering to generate a native, immunocompetent mouse model of glioma, we characterized vascular-tumor dynamics in three dimensions during tumor progression. We employed bulk and single-cell RNA-Sequencing to elucidate the relationship between TAVs and TDECs. We confirmed our findings in a patient derived orthotopic xenograft (PDOX) model. Results: Using a mouse model of glioma, we identified progressive alteration of vessel function and morphogenesis over time. We also showed in our mouse model that TDECs are a rare subpopulation that contributes to vessels within the tumor, albeit to a limited degree. Furthermore, transcriptional profiling demonstrates that both TAVs and TDECs are molecularly distinct, and both populations feature extensive molecular heterogeneity. Finally, the distinct molecular signatures of these heterogeneous populations are also present in human glioma. Conclusions: Our findings show extensive endothelial heterogeneity within the tumor and tumor microenvironment and provide insights into the diverse cellular and molecular mechanisms that drive glioma vascularization and angiogenesis during tumorigenesis.Keywords: angiogenesis; glioma; lymphangiogenesis; tumor-associated vessels (TAVs); tumor-derived endothelial cells (TDECs).
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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