A 3D in vitro glioblastoma cell culture system for identification and evaluation of novel radiosensitisers reducing rodent xenograft studies

Lead Research Organisation: University of Glasgow
Department Name: College of Medical, Veterinary &Life Sci


Glioblastoma is the most common primary brain tumour and is currently incurable. Despite aggressive treatment involving surgery, radiotherapy and chemotherapy, average life expectancy for glioblastoma patients is about one year. Over the past ten years many large, international clinical trials have tested new treatments but none of them has been successful. This is particularly disappointing because many of the new 'targeted' drugs being tested in these trials seemed to be effective when tested in the laboratory. When glioblastoma cells are cultured in the laboratory they are usually grown as single layers of cells in plastic flasks. These 2-dimensional (2D) cell culture conditions cause marked changes in the shape and behaviour of the tumour cells which affect the way they respond to cancer treatments including radiotherapy and targeted drugs.

Because many new drugs appear to be effective in 2D cell cultures, they are then tested in mice and rats implanted with glioblastoma cells. Some drugs show promising results in these animal experiments but are still not effective when tested in patients. So, we need a different method for developing and testing new treatments. First we need to understand why glioblastomas are resistant to radiotherapy, chemotherapy and the new targeted drugs. Then we need to develop new treatments that overcome these mechanisms of resistance. To avoid treating large numbers of animals with ineffective drugs, we also need to be more confident that drugs will work in patients before we start performing animal experiments.

To address these issues we have developed a new, 3D model of glioblastoma that can be grown in the laboratory using tumour cells from patients with glioblastoma. These cells are grown on polystyrene scaffolds coated with special proteins found in glioblastomas, and are nourished with specialised growth factors that are also present in glioblastomas. We have shown that this 3D model contains many of the features that we see in tumours in patients. More importantly, we have shown that drugs which work in patients also work in the 3D model, while drugs which don't work in patients have no effect in the 3D model. Some of these drugs had opposite effects on cells grown in 2D and 3D conditions.

Because we have confidence in the 3D model, we believe it will be valuable to look for genes and proteins that are switched on when 3D cells are treated with radiotherapy, and then test new drugs that can block the effects of these genes and proteins. We have already found several genes that are switched on by radiotherapy in 3D but not 2D cells, and our early experiments suggest that we can overcome resistance to radiotherapy by targeting these genes. in this way we will identify new drugs that are much more likely to be effective in patients.

However we realise that our current 3D model is rather simple and that lots of other cells and structures in glioblastoma might be important. Tumour blood vessels are particularly influential because the cells that line them (endothelial cells) produce chemicals that nourish the tumour cells and make them resistant to radiotherapy. We will therefore develop a more complex 3D model composed of glioblastoma cells and human brain microvascular endothelial cells and see if the new drugs are also effective in this new 'multicellular' model. At the same time we will investigate how the the different cell types interact and how this causes resistance to treatment. Finally, we will convert the new 3D model into a format that allows 'high throughput screening' of new drugs. This will allow us and other researchers around the world to test very large numbers of new drugs as efficiently as possible.

Overall we aim to improve treatments for glioblastoma patients while reducing the number of animal experiments. We will achieve these aims by developing a new 3D model of glioblastoma that accurately predicts which new drugs will be effective in patients.

Technical Summary

Glioblastoma (GBM) is the most common primary brain tumor. Tumors exhibit inherent chemo- and radioresistance which has been attributed to a subpopulation of cancer cells termed 'GBM stem-like cells' (GSC), and almost inevitably recur. While preclinical studies have shown promising activity of several molecularly targeted agents against GBM cell lines, these agents have failed to improve clinical outcomes for patients. The failure of drug-radiation combinations with promising preclinical data to translate into effective clinical treatments may relate to the frequent use of established GBM cell lines in simplified two-dimensional (2D) in vitro cultures. We have developed a novel 3D-Alvetex GBM model system that recapitulates key histological features of GBM including high cellularity, sparse extracellular matrix and presence of GSC. Using this model, we have reproduced clinical outcomes including (i) lack of response to EGFR-directed therapies alone and in combination with radiation and (ii) enhancement of radiosensitivity by VEGF targeting, providing evidence for this culture model as a clinically relevant platform for evaluating targeted therapies alone and in combination with radiation. Genomic characterisation (RNA-Seq) of two different primary GBM cell lines grown in this 3D system, has identified 71 transcripts that are upregulated following radiation treatment. Following validation of transcripts for which inhibitors are commercially available, using RT-PCR in the 3D model and IHC in an existing human GBM TMA and in house human orthotopic glioblastoma xenografts, we will evaluate the radiosensitising properties of target inhibitors in the 3D model and in a novel multicellular 'perivascular niche' system comprising 3D GSC and human brain endothelial cells. We believe that our models will provide meaningful preclinical assessment of novel molecular targets, improving accuracy of in vitro drug evaluation while reducing and partially replacing in vivo models.


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