The Role of Coagulation-Related Genes in Glioblastoma: A Comprehensive Analysis of the Tumor Microenvironment, Prognosis, and Treatment.

Abstract

The influence of coagulation on glioma biology has not been comprehensively elucidated. This study explores the role of coagulation-related genes (CRGs) in glioblastoma (GBM) from the perspectives of the tumor microenvironment (TME), differences in coagulation function among GBM patients, treatment, and prognosis. Somatic mutation analysis was performed on single nucleotide polymorphism (SNP) and copy number variation data from GBM patients in the TCGA cohort. Publicly available single-cell RNA sequencing data were used to analyze the role of coagulation in the GBM TME and its underlying biological mechanisms. Unsupervised clustering of GBM patients from the CGGA693 cohort was conducted, and coagulation function for each patient was assessed using ssGSEA scoring. Prognosis was assessed with Kaplan-Meier survival analysis, and immune infiltration was analyzed through ESTIMATE. A risk signature based on five CRGs (CFI, GNG12, MMP2, LEFTY2, and SERPINC1) was constructed and validated using LASSO regression and random survival forest analyses to predict responses to immunotherapy and identify potential sensitive drugs. Finally, the roles of LEFTY2 and SERPINC1 in GBM progression was verified by immunohistochemistry, cell counting kit-8 (CCK8) assay and wound healing assay, and the anti-GBM effect of the drug PLX4720 was verified by CCK8 assay, wound healing assay, and colony formation assay. Somatic mutation analysis revealed SNP events of CRG mutations in 117 out of 461 GBM cases (25.38%). Single-cell analysis of the GBM TME revealed significant activation of the coagulation pathway in endothelial cells, with intercellular communication mediated via the SPP1-integrin pathway (p < 0.01). Clustering analysis and ssGSEA identified two coagulation-related subtypes in GBM: coagulation-activated and coagulation-inhibited subtypes. Patients in the coagulation-activated subtype exhibited shorter overall survival and poorer prognosis compared to those in the coagulation-inhibited subtype (p = 0.0085). Immune infiltration analysis showed lower tumor purity and higher levels of immune-suppressive cells in the coagulation-activated subtype (p < 0.001). The CRG-based risk signature accurately predicted prognosis (p < 0.0001) and responses to immunotherapy in the IMvigor210 cohort (p = 0.0062). Based on the risk model, PLX4720 was identified as a potential sensitive drug (p < 0.001), and drug validation experiments demonstrated that PLX4720 inhibited the proliferation and migration of glioma cells (p < 0.0001). In vitro experiments demonstrated that LEFTY2 and SERPINC1 were significantly overexpressed in GBM compared to normal brain tissue, and knockdown of LEFTY2 and SERPINC1 inhibited glioma cell proliferation and migration (p < 0.05). The CRG-based risk signature model effectively predicts the prognosis of GBM patients and aids in assessing the efficacy of ICI therapy and chemotherapy. Furthermore, the genes LEFTY2, SERPINC1 and the drug PLX4720 offer potential directions for the development of novel therapeutic strategies for GBM.