Mapping Glioma Progression: Single-Cell RNA Sequencing Illuminates Cell-Cell Interactions and Immune Response Variability

Background: Glioma, the most common primary tumor of the central nervous system, is marked by significant heterogeneity, presenting major challenges for therapeutic approaches and prognostic evaluations. This study explores the interactions between malignant glioma cells and macrophages/monocytes and their influence on tumor progression and treatment responses, using comprehensive single-cell RNA sequencing analysis. Methods: We integrated RNA-seq data from the TCGA and CGGA databases and performed an in-depth analysis of glioma samples using single-cell RNA sequencing, functional enrichment analysis, developmental trajectory analysis, cell-cell communication analysis, and gene regulatory network analysis. Furthermore, we developed a prognostic model based on risk scores and assessed its predictive performance through immune cell infiltration analysis and evaluation of immune treatment responses. Results: We identified 14 distinct glioma cellular subpopulations and 7 primary cell types, alongside 4 macrophage/monocyte subtypes. Developmental trajectory analysis provided insights into the origins and heterogeneity of both malignant cells and macrophages/monocytes. Cell communication analysis revealed that macrophages and monocytes interact with malignant cells through several pathways, including the MIF (Macrophage Migration Inhibitory Factor) and SPP1 (Secreted Phosphoprotein 1) pathways, engaging in key ligand-receptor interactions that influence tumor behavior. Stratification based on these communication characteristics showed a significant correlation with overall survival (OS). Additionally, immune cell infiltration analysis highlighted variations in immune cell abundance across different subgroups, which may be linked to differing responses to immunotherapy. Our predictive model, consisting of 29 prognostic genes, demonstrated high accuracy and robustness across multiple independent cohorts. Conclusion: This study unveils the intricate heterogeneity of the glioma microenvironment, enhancing our understanding of the diverse characteristics of glioma cell subpopulations. It also lays the groundwork for the development of therapeutic strategies and prognostic models that specifically target the glioma microenvironment.