We are delighted to announce that Michael Bryan (pictured above) has been awarded the prestigious British Neuro-Oncology Society (BNOS) Young Investigator of the Year Award for 2026. This award, co-sponsored by Brain Tumour Research, recognises young researchers who have made outstanding contributions to neuro-oncology in the UK.
Michael is an exceptional early-career scientist undertaking an MB-PhD. He is completing the research component of his PhD at the University of Oxford, where he is investigating how computational modelling and artificial intelligence (AI) can help design more effective cancer vaccines for people living with glioblastoma, the most common high-grade brain tumour in adults.
An MB-PhD is a programme which enables medical students to pause their clinical training to complete a PhD before finishing their medical degree. These programmes are invaluable in developing a new generation of clinical academics with first-hand experience of patient care and cutting-edge research. By bridging the gap between the laboratory and the clinic, people such as Michael play a crucial role in making sure that research remains grounded in real patient needs.
Our Research Communications Manager, Nicola Gale, sat down with Michael to find out more about his research and what the future could hold for cancer vaccines in brain tumours.
What inspired you to pursue both medicine and research, and why focus on brain tumours?
My route into medicine was unconventional. I started out as a police officer with the Met in London. Being first on scene to serious incidents made me realise quickly how valuable medical skills are when people’s lives are on the line. That led me into medical school, initially thinking I might become a surgeon.
As I learned more, I became really interested in cancer, especially whether we could detect it earlier and intervene before it becomes harder to treat. I was lucky to spend a year at Harvard Medical School in the United States working on a blood test for early cancer detection, and that’s what really sparked my interest in research.
Brain tumours stood out to me because they’re complex. They adapt, evolve under treatment, and can suppress the immune system, so they’re particularly hard to treat.
At the same time, during my first year of medical school, I had a mentor who was a GP in Scotland. He was incredibly supportive and gave me a lot of guidance. By my second year, he’d been diagnosed with aggressive glioblastoma. Seeing someone who’d helped shape my early career face that diagnosis was difficult, and it made it very personal.
I think that’s what really pushed me to focus on understanding these tumours better and finding smarter ways to treat them.
When people hear “vaccine”, they think of preventing disease. What is a cancer vaccine, and how is it different?
Instead of preventing an infection, a cancer vaccine teaches the immune system to recognise a patient’s own tumour.
We do that by sequencing the tumour’s genetic code (DNA) and identifying the mutations or changes that make it different from healthy cells. We then identify the tumour-specific changes most likely to be recognised by immune cells and incorporate them into a personalised vaccine. The aim is to help the immune system find and attack cancer cells more effectively.
That’s what we mean by a personalised cancer vaccine, and it is the type of vaccine I am working on.
But there are other types as well. There are off-the-shelf vaccines currently in development that target common mutations seen across multiple patients, as well as preventative, or prophylactic, cancer vaccines. These could be used in people at high risk, for example if they have a precancerous condition or a higher risk of developing cancer.
So, it’s quite a broad field, but the main idea is using the immune system in a more targeted way to recognise and attack cancer.
You are researching ‘computational approaches for vaccine design’. Can you explain what that means and how it works in practice?
When I talk about computational approaches for vaccine design, I mean using data and computer models to help us make better decisions about how to design these vaccines.
There are a few main challenges we’re trying to solve. The first is choosing the right targets. These are the parts of the tumour that the immune system is most likely to recognise. We use machine learning to sort through large amounts of data and try to identify which tumour-specific changes are most likely to be displayed on the surface of cancer cells and recognised by T cells (immune cells that target and destroy other cells).
The second is working out which combinations of targets are most effective. This includes thinking about how vaccines might be used alongside other treatments. For example, approaches that hit two vulnerabilities in the tumour at the same time, to try to improve the overall response while still sparing healthy tissue.
And then the third, which is probably the most exciting, is trying to anticipate how tumours evolve. Rather than designing a vaccine just for the tumour we see today, we try to think ahead. If the tumour escapes the immune system, how might it do that? Does it lose a mutation, gain a new one, or switch off the signals that help the immune system recognise it?
By understanding those potential escape routes, we can design vaccines that remain effective for longer because they account for how the tumour may adapt over time.
What has been the most rewarding moment in your research so far?
That's a really tough question; there are a couple of moments that stand out.
One highlight was presenting my work at the American Society of Clinical Oncology (ASCO), and seeing the level of interest from clinicians, scientists, and patients. What struck me was how many different perspectives were brought to the same challenge, and how collaborative the field can be when people are focused on improving outcomes.
More than anything, though, the most meaningful part has been meeting patients and hearing their stories. Those conversations provide a constant reminder of why this work matters and help keep research connected to the realities of living with a brain tumour. It’s also reinforced my desire to return to medical training, so I can spend more time caring for patients and make sure my research remains focused on the challenges that matter most to patients and their families.
What would you like people affected by brain tumours to know about the progress being made?
We know that current treatments aren’t good enough, and that a diagnosis of a brain tumour can be really difficult for both patients and their families.
What gives me hope is the number of people committed to changing that. There’s a growing community all working towards the same goal of developing better treatments and improving outcomes. For many of us, this is a long-term commitment. It’s what drives us to keep asking the difficult questions and testing new ideas.
If there is one thing I would want patients to know, it is that there are many people working tirelessly to understand these diseases and develop more effective treatments. Progress can sometimes feel slower than any of us would like, but it is happening, and we are not going to stop pushing forward. Every day, people across the world are working to bring us closer to better options for patients and families affected by brain tumours.
Brain Tumour Research is proud to co-sponsor this award, highlighting our commitment to supporting Early Career Researchers and growing capacity within neuro-oncology research.
As part of this honour, Michael presented his research at the BNOS Annual Conference in London this week and will receive £2,000 to attend other neuro-oncology conferences.
You can help us continue to fund game-changing research by setting up a regular donation or making a one-off donation to support our vital work today. Any amount you can give will help us change the story for brain tumour patients and their loved ones.
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