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New glioblastoma imaging shows how tumour cells respond to treatment

Innovative imaging technology and machine learning developed by our Future Leader, Dr Spencer Watson, helps us understand how glioblastomas respond to treatment.

Vibrant cell close-up highlights glioblastoma treatment effects.

This new research allows scientists to visualise glioblastoma cells relative to all other cells in the brain that surround the tumour. This is the first time anyone has ever done this.

The technology, coupled with machine learning, allowed researchers at the University of Lausanne, Switzerland to better understand how glioblastoma cells respond to radiotherapy. Our Future Leaders programme, which supports the very best researchers in the brain tumour field, helped fund this work.

Glioblastoma imaging

The new glioblastoma imaging technology, called Hyperplexed Immunofluorescence Imaging (HIFI), shows that changes in the tumour microenvironment occur after radiotherapy.

The tumour microenvironment is all the cells around the tumour that play a vital role in helping the tumour grow and survive. Glioblastomas are renowned for re-programming nearby cells to protect it from the immune system and the treatments that we currently have to kill the tumour cells.

Until now, limitations in existing imaging technology have made it difficult to visualise the brain tumour and its microenvironment at once. This novel technology overcomes these limitations and allows researchers to accurately visualise very large areas of brain tumours to analyse lots of cells in relation to one another.

HIFI allows for simultaneous analysis of more than 45 different markers in fragile brain tissue sections with high magnification. These markers highlight different areas of the brain and tumour. This new technique is cost-effective and helps researchers understand how cells and proteins interact in time and space. The researchers also hope it can be used in other cancers and tissue samples.

Machine Learning

The imaging also integrates machine learning and AI. This helps analyse the tumour microenvironment, as it can be far too complex for people to do on their own. With machine learning, many samples can be analysed and lots more data can be collected in a shorter timeframe compared to using scientists alone.

Glioblastoma response to radiotherapy

This is a HIFI image of a mouse glioblastoma using the new glioblastoma imaging technology developed by researchers. The image shows the mouse brain in purple and the tumour on the left in a blue/green colour.
This is a HIFI image of a mouse glioblastoma.
Colours: Collagen in red, neurons in magenta, vessels in yellow, astrocytes in cyan, and tumour cells in green 

Carried out in preclinical mouse models, this research compared primary glioblastoma models with models where cancer had spread to the brain from another part of the body. In this case, breast-brain metastasis models. Results showed that in the glioblastoma model, immune cells undergo extensive changes in response to radiotherapy, while the brain metastasis model does not.

This shows that there are very different responses to radiation between different brain tumour models, despite having equivalent radiotherapy benefit.  

This research is helping scientists understand how glioblastoma cells become resistant to treatment. It also emphasises the importance of understanding the environment around the tumour if we are going to develop new treatments to find a cure for this devastating disease.  

The team of researchers hope to use this glioblastoma imaging to improve their understanding of this aggressive brain tumour.

This research helps us understand the different ways brain tumours can resist and survive treatments such as radiotherapy, which in turns helps us find better ways to specifically target these survival strategies to improve our therapies. These kinds of tumour microenvironment studies really benefit from new imaging techniques that help us analyse the entire complex microenvironment all at once. But these new technologies can be prohibitively expensive, and often don’t meet the needs of cancer researchers. We hope that our new open-source method will democratise high-dimensional imaging, and spur other researchers to adopt this approach to take on more innovative and ambitious research questions.

Dr Spencer Watson, lead researcher for this project and one of The Brain Tumour Charity’s Future Leaders
Headshot of Dr Simon Newman, Chief Scientific Officer at The Brain Tumour Charity

Research that paves the way for a better understanding of brain tumours is essential if we are to find better and kinder treatments. We are proud of The Brain Tumour Charity’s Future Leaders programme as it identifies and nurtures the next generation of researchers building capacity and expertise for the future of research into brain tumours. Dr Watson’s work uses novel imaging to further understand glioblastoma and the environment that surrounds it, this more detailed understanding could open doors for new treatments in the future.

Dr Simon Newman, Chief Scientific Officer at The Brain Tumour Charity

Find out more about this research

Dr Spencer Watson

Spencer is a Postdoctoral Researcher in the Ludwig Institute for Cancer Research at the University of Lausanne’s Department of Oncology. He is studying the environment around brain tumours to better understand how we can improve treatments.

Dr Spencer Watson smiles with a lake in the background. Dr Watson is one of our Future Leaders