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Decoding glioblastoma evolution and heterogeneity through mechanistic modeling: implications for clinical translation
Haowu Jiang1, Wan Zhao2, Hui Zhou3
1Department of Otolaryngology-Head and Neck Surgery, The First Affiliated Hospital of USTC, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, Hefei National Research Center for Physical Sciences at the Microscale, Division of Life Sciences and Medicine, University of Science and Technology of China, No.96, JinZhai Road, Baohe District, Hefei, Anhui, 230026, People's Republic of China. haowu.jiang@ustc.edu.cn.
Glioblastoma (GBM) is a deadly brain tumor with complex evolution. New models are improving our understanding of GBM heterogeneity and recurrence for better treatment strategies.
Area of Science:
- Neuro-oncology
- Cancer Biology
- Genomics
Background:
- Glioblastoma (GBM) is a highly aggressive adult primary brain tumor.
- GBM exhibits significant heterogeneity across genomic, cellular, spatial, and microenvironmental aspects.
- Tumor evolution involves genetic, epigenetic, transcriptional, and immune remodeling, leading to therapeutic resistance.
Purpose of the Study:
- To review current models for studying GBM evolution and heterogeneity.
- To discuss how integrated model pipelines can enhance preclinical drug testing and treatment prediction.
- To explore advancements in understanding GBM origin from neural stem/progenitor cells and the role of glioblastoma stem cells (GSCs).
Main Methods:
- Single-cell profiling
- Spatial transcriptomics
- Lineage tracing
- Organoid culture
- 3D bioprinting
- Genetically engineered models
- AI-assisted computational modeling
Main Results:
- No single model fully recapitulates human GBM heterogeneity, recurrence, treatment history, and tumor-microenvironment interactions.
- Recent technological advances have improved the study of GBM processes.
- Reconciling hierarchical stem cell models with dynamic state plasticity models remains a key challenge.
Conclusions:
- Model selection for GBM research should be guided by specific mechanistic questions.
- Integrated model pipelines hold promise for improving preclinical research and precision neuro-oncology.
- Further development of comprehensive models is crucial for advancing GBM treatment.
