Practical Review on Preclinical Human 3D Glioblastoma Models: Advances and Challenges for Clinical Translation

Area of Science:

• Neuro-oncology
• Cancer Biology
• Biomedical Engineering

Background:

• The Stupp protocol, established 15 years ago, remains the standard of care for glioblastomas (GBM), yet significant clinical advances and improved patient survival are lacking.
• Intra- and inter-tumoral complexities and the tumor microenvironment's role in treatment resistance highlight the need for better preclinical models.
• Bridging the gap between preclinical models and clinical samples is crucial for enhancing the success rate of glioblastoma clinical trials.

Purpose of the Study:

• To review the history, development, and utility of various 3D human glioblastoma models.
• To assess the suitability of different 3D models in recapitulating glioblastoma complexity and aiding therapeutic development.

Main Methods:

• Comprehensive literature review focusing on 3D human glioblastoma models.
• Analysis of established 3D models including spheroids, tumorospheres, organotypic slices, explants, tumoroids, and glioblastoma-derived cerebral organoids.
• Discussion of the evolution and application of these models in glioblastoma research.

Main Results:

• Various 3D human glioblastoma models have been developed, offering improved physiological relevance compared to traditional 2D cultures.
• These models, including spheroids, tumorospheres, organotypic slices, explants, tumoroids, and organoid-derived models, provide platforms to study glioblastoma heterogeneity and microenvironment interactions.
• The utility of each 3D model varies, with specific models showing promise for different research applications, from drug screening to mechanistic studies.

Conclusions:

• 3D human glioblastoma models represent a significant advancement over historical models, offering better recapitulation of tumor biology.
• Continued development and critical evaluation of these models are essential for advancing glioblastoma research and improving therapeutic strategies.
• These models hold promise for enhancing the predictive power of preclinical studies and ultimately improving clinical trial success rates for glioblastoma patients.