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Review
. 2019 Sep 6;12(9):dmm040386.
doi: 10.1242/dmm.040386.

Experimental models and tools to tackle glioblastoma

Affiliations
Review

Experimental models and tools to tackle glioblastoma

Faye L Robertson et al. Dis Model Mech. .

Abstract

Glioblastoma multiforme (GBM) is one of the deadliest human cancers. Despite increasing knowledge of the genetic and epigenetic changes that underlie tumour initiation and growth, the prognosis for GBM patients remains dismal. Genome analysis has failed to lead to success in the clinic. Fresh approaches are needed that can stimulate new discoveries across all levels: cell-intrinsic mechanisms (transcriptional/epigenetic and metabolic), cell-cell signalling, niche and microenvironment, systemic signals, immune regulation, and tissue-level physical forces. GBMs are inherently extremely challenging: tumour detection occurs too late, and cells infiltrate widely, hiding in quiescent states behind the blood-brain barrier. The complexity of the brain tissue also provides varied and complex microenvironments that direct cancer cell fates. Phenotypic heterogeneity is therefore superimposed onto pervasive genetic heterogeneity. Despite this bleak outlook, there are reasons for optimism. A myriad of complementary, and increasingly sophisticated, experimental approaches can now be used across the research pipeline, from simple reductionist models devised to delineate molecular and cellular mechanisms, to complex animal models required for preclinical testing of new therapeutic approaches. No single model can cover the breadth of unresolved questions. This Review therefore aims to guide investigators in choosing the right model for their question. We also discuss the recent convergence of two key technologies: human stem cell and cancer stem cell culture, as well as CRISPR/Cas tools for precise genome manipulations. New functional genetic approaches in tailored models will likely fuel new discoveries, new target identification and new therapeutic strategies to tackle GBM.

Keywords: Brain tumour; CRISPR/Cas9; Cancer; Central nervous system; GBM; Human; In vitro; Mouse; Xenograft.

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Conflict of interest statement

Competing interestsThe authors declare no competing or financial interests.

Figures

Fig. 1.
Fig. 1.
Important challenges in understanding the biology of GBM. GBM stem cells exist in various states (dormant/quiescent, activated/quiescent or proliferative) that are influenced by diverse tumour microenvironments (TMEs). Complex niches, immune interactions and physical forces/mechanosignalling are all poorly understood areas of GBM biology. How these influence tumour cell signalling circuits and the subsequent transcriptional and epigenetic changes in GSC fate is an area of active research. Targeting both the quiescent and proliferative tumour populations will be vital for any successful therapeutic strategy.
Fig. 2.
Fig. 2.
Sources of GBM tumour cells and their capture in vitro. Tumour tissue and tumour cell populations can be obtained from rodent models (see Fig. 3) or patients (adult or paediatric). Tumour-initiating cells can be maintained in culture using neural-stem-cell culture conditions (serum-free media with growth factors EGF and FGF2). These can be expanded in suspension as spheres or organoids, or in an adherent monolayer. Clonal cell lines can be obtained, and cells plated in microtiter plates for arrayed genetic or chemical screens. Cells and tumour explants can also be engrafted on brain slice cultures to model tumour-host interactions.
Fig. 3.
Fig. 3.
Engineering NSCs and GSCs with CRISPR-based genome editing. A variety of different genetic or epigenetic manipulations can be introduced using CRISPR/Cas-assisted gene engineering, either mutations (bottom left) or knock-in alleles (bottom right). ex1/2, exon 1/2; NSC, neural stem cell; GSC, glioblastoma stem cell; eGSC, engineered glioblastoma stem cell; GFP, green fluorescent protein; LOF, loss of function; TV, targeting vector.
Fig. 4.
Fig. 4.
In vivo mouse models can be generated through transplantation of cells or tumour tissues, or through engineered driver mutations (by breeding or somatic mutation). (Top panel) Shown are foetal, postnatal and adult brain injections of either tumour explants, cells, CRISPR ribonucleoproteins, plasmids or viral vectors (viral delivery of genetic material). Bottom panel: in vivo mouse models can also be generated by breeding animals that carry germline mutations.

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