Transitioning pre-clinical glioblastoma models to clinical settings with biomarkers identified in 3D cell-based models: A systematic scoping review
Glioblastoma (GBM) remains incurable despite the overwhelming discovery of 2-dimensional (2D) cell-based potential therapeutics since the majority of them have met unsatisfactory results in animal and clinical settings. Incremental empirical evidence has laid the widespread need of transitioning 2D...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2022
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/22078187bebb4e2f852bcf6562545ce0 |
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| Sumario: | Glioblastoma (GBM) remains incurable despite the overwhelming discovery of 2-dimensional (2D) cell-based potential therapeutics since the majority of them have met unsatisfactory results in animal and clinical settings. Incremental empirical evidence has laid the widespread need of transitioning 2D to 3-dimensional (3D) cultures that better mimic GBM’s complex and heterogenic nature to allow better translation of pre-clinical results. This systematic scoping review analyses the transcriptomic data involving 3D models of GBM against 2D models from 22 studies identified from four databases (PubMed, ScienceDirect, Medline, and Embase). From a total of 499 genes reported in these studies, 313 (63%) genes were upregulated across 3D models cultured using different scaffolds. Our analysis showed that 4 of the replicable upregulated genes are associated with GBM stemness, epithelial to mesenchymal transition (EMT), hypoxia, and migration-related genes regardless of the type of scaffolds, displaying close resemblances to primitive undifferentiated tumour phenotypes that are associated with decreased overall survival and increased hazard ratio in GBM patients. The upregulation of drug response and drug efflux genes (e.g. cytochrome P450s and ABC transporters) mirrors the GBM genetic landscape that contributes to in vivo and clinical treatment resistance. These upregulated genes displayed strong protein-protein interactions when analysed using an online bioinformatics software (STRING). These findings reinforce the need for widespread transition to 3D GBM models as a relatively inexpensive humanised pre-clinical tool with suitable genetic biomarkers to bridge clinical gaps in potential therapeutic evaluations. |
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