Single-Cell RNA-Seq Dissects Specific Marker in Glioblastoma Based on Gene Regulatory Networks.

Background: Glioblastoma (GBM) is one of the most aggressive and common tumors of the central nervous system (CNS), distinguished by its significant intratumoral heterogeneity and poor prognosis, with a median overall survival of approximately 15 months. Recent advances in single-cell RNA sequencing (scRNA-seq) have provided deeper insights into the molecular subtypes and heterogeneity of GBM, which include the proneural (PN), classical (CL), and mesenchymal (MES) subtypes. Objectives: This study hypothesizes that constructing gene regulatory networks (GRNs) using single-cell RNA sequencing (scRNA-seq) data can elucidate the complex regulatory mechanisms underlying glioblastoma (GBM) heterogeneity. The primary aim is to identify key regulators and subtype-specific markers in GBM through the integration of scRNA-seq and GRNs, with the ultimate goal of discovering novel prognostic biomarkers that can improve patient stratification and treatment outcomes. Materials and Methods: Malignant cells were identified based on inferred copy number variations (CNVs) from scRNA-seq data. Consensus clustering of expression profiles was used to assign GBM subtypes. Analyses of differential gene expression, ligand-receptor interactions, pathway activities, and responses to immune checkpoint inhibitors were conducted. GRNs were constructed by retaining co-expressed transcription factor (TF)-gene pairs with enriched transcription-binding motifs. Bulk RNA-seq data were then used to validate marker expression and assess prognostic value. Results: Distinct functional roles and molecular characteristics were observed across GBM subtypes. Subtype-specific GRNs revealed both unique and shared regulatory features. GATA binding protein 3 (GATA3) emerged as a potential prognostic marker, showing correlation with homologous recombination deficiency (HRD) and patient outcomes. Conclusions: Subtype-resolved GRN analysis of GBM provides valuable insights into intratumoral heterogeneity and regulatory mechanisms. GATA3 may serve as a novel biomarker for prognosis and therapeutic stratification in GBM patients.