The process of angiogenesis is the growth of new capillaries from pre-existing vessels. Glioblastoma (GBM) is a highly vascularised tumour and the growth of glioma is extremely dependent on the formation of new blood vessels. Endothelial cells (ECs) dynamically modify their behavior during angiogenesis, resulting in changes in differentiation, proliferation, migration, polarity, metabolism, and cell-cell communication. These modifications are assumed to integrate many external inputs, but they also govern ECs' ability to respond to environmental stimuli, such as up- or down-regulation of surface receptor expression. In recent studies, TAM-derived factor (sema4d) has been shown to promote pericyte recruitment in neovascularization and cellular communication between glioma stem cell-derived perivascular cells and endothelial cells, directly contributing to vascular stability in gliomas. FAK proteins may increase angiogenesis in gliomas by triggering endothelial cell migration, according to research on endothelial cells and angiogenesis in gliomas. High-grade gliomas have higher FAK expression compared to low-grade gliomas and are associated with poorer survival. As a result, there has been interest in anti-angiogenic therapies targeting endothelial cells, which include inhibiting the proliferation of gliomas through the use of angiogenesis-inhibiting factors and drugs to inhibit the formation of new tumor blood vessels.
Characterization of ECs in normal brain tissue and GBM based on bulk RNAseq data is often limited. In studies of endothelial cells, it is often impossible to infer the effects of other cell types because of GBM cell heterogeneity. In this study we characterised the brain and GBM endothelial cells in more detail by integrating 10 × scRNA-seq and bulk RNA-seq data, and used the mark gene of endothelial cells to build a prognostic model for GBM patients. We found that the constructed prognostic model could effectively classify patients in the TCGA and CGGA cohorts into high- and low-risk groups. In addition, we explored survival status, clinical relevance, mutational status and tumour immune infiltration in the different groups. Our study showed that higher risk scores were associated with poorer prognosis, lower frequency of IDH mutations and upregulation of immune checkpoints such as PD-L1 in patients. We therefore suggest that patients with higher risk scores may be more likely to receive immunotherapy. In addition, we identified two different subtypes using the NMF algorithm. All patients in cluster 1 were immune C4 subtypes, which were associated with a worse prognosis. We observed that the different subtypes had different prognostic and TME components. Group 1 was associated with a poorer clinical outcome and high infiltration levels of fibroblasts, whereas group 2 was associated with a better clinical outcome and high infiltration levels of cytotoxic lymphocytes. Fibroblasts can support tumor growth by depleting glucose.
We first identified mark genes in endothelial cells by means of single-cell sequencing, followed by LASSO and Cox regression analysis to identify four hub genes, including TUBA1C, RPS4X, KDELR2 and SLC40A1 to model prognosis. TUBA1C is an isoform of alpha-microtubule protein that serves as a core component of the eukaryotic cytoskeleton and plays a cell division, formation, motility and intracellular trafficking [39, 40]. In addition, the biological functions of microtubule proteins have been linked to cancer development, neurodevelopment and neurodegenerative diseases. In a recent study, TUBA1C expression was significantly higher in gliomas than in normal brain tissue and indicated a poorer prognosis. In addition, knockdown of TUBA1C also inhibited proliferation and migration of glioma cells, leading to apoptosis and G2/M phase arrest. Studies on the oncogenic ribosomal protein S4 X-linked (RPS4X) have found that RPS4X increases cisplatin resistance after depletion of specific small interfering rna's. RPS4X is associated with ovarian cancer stage and its low expression is also associated with poor survival and disease progression, but there are no reports on RPS4X in glioma. In hepatocellular carcinoma, RPS4X is required for SLFN11 inactivation in the mTOR signalling pathway. Interestingly, the KDEL receptor (KDELR2) can also target and promote the growth of HIF1a through the mTOR signaling pathway to guide glioblastoma. In addition, KDELR2 knockdown reduces cell viability, promotes G1 phase cell cycle arrest and induces apoptosis. kDELR2 can regulate cellular function in glioma cells by targeting CCND1. Solute carrier family 40 member 1 (SLC40A1) is a gene encoding an iron transporter protein. Studies in multiple myeloma and ovarian cancer have shown that SLC40A1 inhibits tumour cell growth and reduces resistance to chemotherapy[47, 48]. Only one recent bioinformatics study has suggested that the ferroptosis suppressor SLC40A1 is associated with immunosuppression in gliomas and that acetaminophen may exert antitumor effects in GBM by modulating SLC40A1-induced death. The CGGA external validation cohort was also employed to confirm its predictive capacity, and both cohorts showed similar results. The findings revealed that the prognostic model developed exhibited independent predictive power in predicting OS in GBM patients. The status of genetic mutations and immunological function in different risk categories were then studied. We found no significant differences in gene mutations such as TP53 and PTEN between the high-risk group and the low-risk group, yet the high-risk group did not have any IDH mutations. 2016 WHO classification clearly indicates a significant difference between IDH mutant GBM and IDH wild-type GBM, while IDH wild-type GBM has a poorer prognosis. This further validates the reliability of our model. In addition, we also investigated the relationship between risk score and TMB values and PD-L1 expression levels. Disappointingly, higher risk scores did not correlate significantly with higher TMB values (figure S3 A). A key mediator of immunosuppression in GBM is PD-L1, and although only a fraction of GBM cells express PD-L1, the tumour microenvironment is deficient in the expression of PD-L1.
Finally, immune checkpoint blockade treatment may be more effective in individuals with higher risk ratings. The developed prognostic model might be used as a predictive biomarker for immunotherapy patients. The CGGA external validation cohort was also employed to confirm the accuracy of the model in predicting OS in these individuals. Our research does, however, have certain inevitable flaws. To begin with, all of these findings are based on bioinformatic studies and will require further experimental confirmation. To corroborate our findings, we created an endothelial cell-based biomarker that will need to be tested in large-scale clinical studies.