Abstract
Glioblastoma, one of the most aggressive and heterogeneous malignant tumors, presents significant challenges for clinical management due to its cellular and metabolic complexity. This review integrates recent advancements in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics to elucidate glioblastoma's cellular heterogeneity and metabolic reprogramming. Diverse cellular subpopulations, including malignant proliferative cells, stem-like cells, mesenchymal-like cells, and immune-related cells, contribute to tumor progression, treatment resistance, and microenvironmental interactions. Spatial transcriptomics has further revealed distinct spatial distributions of these subpopulations, highlighting differences in metabolic activities between the tumor core and periphery. Key metabolic adaptations, such as enhanced glycolysis, fatty acid oxidation, and glutamine metabolism, play critical roles in supporting tumor growth, immune evasion, and therapeutic resistance. Targeting these metabolic pathways, especially in combination with immunotherapy, represents a promising avenue for glioblastoma treatment. This review emphasizes the importance of integrating single-cell and spatial multi-omics technologies to decode glioblastoma's metabolic landscape and explore novel therapeutic strategies. By addressing current challenges, such as metabolic redundancy and spatiotemporal dynamics, this work provides insights into advancing precision medicine for glioblastoma.