Tumor microenvironment variation implicates immune alterations and correlates with prognosis in patients with glioma

Abstract

Abstract To investigate the microenvironment composition of gliomas and the associated clinical significance, we analyzed single-cell RNA sequencing and bulk RNA-seq data from glioma samples. Cell trajectory analysis identified five trajectories with distinct cell states and corresponding trajectory-related genes (TRGs). TRG-based clustering segregated patients with glioma with different overall survival, clinicopathological features, immune infiltration status, and immune checkpoint gene (ICG) expression levels. Notably, a worse prognosis was seen in patients with a higher immune score, lower tumor purity, higher M0 macrophage and regulatory T (Treg) cell infiltration, and increased ICG expression. Further survival analysis and functional enrichment analysis revealed a close relationship between prognosis and ICG-associated immunosuppressive pathways. Candidate prognostic genes were obtained using WGCNA analysis and differential expression analysis. LASSO and multivariate regression analysis were used to establish a prognostic prediction model. The prognostic risk-scoring signature including 12 genes successfully predicted patient survival with acceptable AUC values. A nomogram was constructed to evaluate the contribution of the risk signature to patient prognosis. This study highlights the potential involvement of tumor microenvironment variation and immune alteration in glioma progression and establishes a TRG-based prognostic model to predict patient clinical outcomes.