Establishment of Vasculogenic Mimicry-Correlated Model to Predict Prognosis and Therapeutic Efficacy in Patients With Glioblastoma

Background: Vasculogenic mimicry (VM) is a distinct process from angiogenesis in which cancer cells form tubular networks mimicking blood vessels, thereby supporting tumor growth and spread. VM in glioblastoma (GBM) contributes to treatment resistance and recurrence, limiting the efficacy of antiangiogenic therapy. Mounting evidence indicates that VM is essential for regulating the onset and progression of GBM. Hence, investigating the underlying mechanisms of VM development is a crucial route to identifying novel targets for antiangiogenic treatments in GBM. Methods: In this study, differentially expressed genes (DEGs) between normal and tumor tissues from the TCGA-GBM data set were overlapped with module genes showing the strongest association with VM, as identified through weighted gene coexpression network analysis (WGCNA), to derive a set of intersecting genes. After obtaining prognostic genes, a risk model was developed and subsequently validated. Then, univariate COX regression analysis and a nomogram were used for clinical correlation analysis and nomogram construction. Immune infiltration analysis was implemented. In the final phase of the study, potential therapeutic agents targeting prognostic genes were identified using the Comparative Toxicogenomics Database (CTD). Results: The authors identified 3 GBM-related prognostic genes (G0S2, LSP1, and STC1). The risk model constructed based on these 3 genes demonstrated general applicability, and the prognostic nomogram further showed good clinical predictive capability. Immune microenvironment infiltration analysis revealed that LSP1 had the highest positive correlation with central memory CD4 T cells. Finally, the authors predicted potential drugs targeting the prognostic genes and performed molecular docking. Conclusion: A VM-related model was constructed to assess the prognosis and therapeutic efficacy in patients with GBM, contributing to the management of GBM in clinical practice.