Advances in Single-Cell and Spatial Omics for Glioblastoma Precision Medicine

Glioblastoma is the most aggressive and fatal primary malignant brain tumour in adults, characterised by extensive intra-tumour heterogeneity, diffuse infiltration into surrounding brain tissue. Despite advances in surgery, radiotherapy, and chemotherapy, patient prognosis remains poor, underscoring the critical need for improved biological insight to guide precision medicine potential strategies. Although traditional bulk genomic and transcriptomic analyses have made a substantial contribution to understanding glioblastoma pathophysiology, such average molecular signals across cell populations obscures tumour microenvironment influence and clinically significant cellular states.

Recent advances in single-cell and spatial omics technologies have revolutionised glioblastoma research by enabling high-resolution analysis of tumour composition, cellular plasticity, and spatial organisation. These modalities have revealed that glioblastoma is composed of dynamic and plastic cellular states as opposed to fixed molecular subtypes, including stem-like and therapy-resistant populations that contribute to recurrence. The tumour architecture is preserved by spatially resolved transcriptomic and proteomic approaches, which reveal regional transcriptional programmes influenced by the tumour ecosystem. The findings provide a more resolved view of glioblastoma evolution and treatment resistance, challenging current classification systems. However, significant challenges remain in integrating these high-dimensional datasets, managing technical and computational demands, and translating these approaches into clinically scalable workflows which collectively hinder their translational adoption. This review aims to synthesise recent advances in glioblastoma single-cell and spatial omics, critically evaluating both advantages and limitations in understanding tumour heterogeneity and tumour microenvironmental interactions. Furthermore, it assesses the current challenges of glioblastoma precision medicine and evaluates the potential of these technologies to advance such approaches.