Investigating the role of epigenetic remodelling in glioblastoma in response to therapy

Glioblastoma (GBM) is the most common and most deadly form of brain cancer. GBM tumours are solid but many of the cancer cells break away and invade the surrounding normal brain tissue, making complete surgical removal impossible. After surgery, patients commonly receive radio- and chemo-therapy but GBM tumours typically grow back within 6 to 9 months and are fatal. This is why brain tumours kill more people aged under 40 than any other cancer.
New drugs that were developed to target the DNA mutations that are commonly found in GBM tumours have failed to increase patient survival. It is now thought that this is because, although such mutations may have caused the tumour to form, they are not responsible for its continued growth and ability to resist treatment. To specifically identify what properties of GBM cancer cells do enable them to resist treatment, I have collected, characterised and compared paired GBM tumours from multiple patients i.e. the first tumour that was diagnosed and removed and the post-treatment recurrent tumour from cases where the latter also underwent surgery. I have found that a specific set of genes are universally altered in GBM by treatment, but whether they become more switched on or more switched off after therapy is patient dependent and enables them to be split into two classes. I will determine whether assignment to one class versus another alters the likely survival for GBM patients or can be used to better predict the likely benefit of treatment with one type of therapy versus another.
Furthermore, if the changes that I have observed in the specific genes are actually required by the GBM cells in order for them to survive treatment, then developing drugs to inhibit the changes may provide a more effective treatment for GBM. I plan to use my fellowship to test just that. I will use both computational analysis of patient datasets to reveal the biology underpinning the observed gene changes and further profiling of GBM tumour pairs to confirm whether the changes are driven by a single master regulator protein. I will then grow GBM tumours in the laboratory and use experimental approaches to stop them being able to undergo the observed changes, before administering the same radio- and chemo-therapy that patients receive to see if more cells die versus tumours where the changes are allowed to take place. Finally, I will determine whether drugs can be adapted or developed that restrict the gene changes in patients, making their GBM tumours more susceptible to killing as part of more effective treatment strategies.

There are currently no effective treatment options for glioblastoma (GBM) brain tumours. Standard treatment consists of surgery, radiotherapy and temozolomide (TMZ), but recurrence is inevitable. I will explore a new avenue of research into personalised medicine for more effective treatment of GBM. This will result in two main possible outputs with impact on non-academic stakeholders:
1. A biomarker that stratifies primary GBM patients into two classes with different survival or response to specific treatments. This would be a candidate for inclusion in clinical practice as a diagnostic test used by clinicians to manage patient expectations of life-expectancy and help them to advise on treatment options in relation to likely increased survival vs risk to quality of life. TIMING: 5-10 years
2. Novel, more effective, therapeutic strategies for treating GBM. TIMING: 7-15 years

The following groups will be affected by these outputs, and other aspects of the funded research as a whole:

A. Patients and the public: More accurate prognosis of primary GBM tumours will better inform patients on the likely progression of their disease and help them and their families to cope and prepare. It may also avoid unnecessarily debilitating treatments in cases where there is a little chance of an impact on survival or quality of life. More effective treatments will impact on quality of life and survival. Engagement activities throughout the award (Y1-7) will benefit patients and the public by empowering them to be part of the research effort.

B. NHS and clinicians (neuro-oncologists): A better understanding of disease progression will reduce staff time and cost implications to the NHS of administering ineffective treatments, and empower clinicians to better inform and advise patients. More effective treatments further equip clinicians to increase patient survival and quality of life, and additionally benefits the wider NHS through the provision of 'real world' evidence to support potentially expensive therapies. Diagnostic tests for GBM are not standardised across NHS Trusts, require multiple samples before they can be economically performed (leading to long wait times for results) and give results that can be subjectively interpreted. This causes frustration for neuro-oncologists, increased anxiety for patients and varying costs across the NHS, with 'poorer' Trusts using sub-standard techniques. The development of an advanced biomarker tests that address these issues will further benefit this group.

C. Cancer research charities: This project constitutes new avenues of brain cancer research, which will benefit charities (Y1+) because novel research routes instil confidence in the advancement of research and encourages donations. This will increase the funding available to apply these approaches to other brain cancer stages and types.

D. Medical technology innovators and companies: Experts in medical technology innovation will benefit from the identification of effective biomarkers, which require the development of accurate, rapid and economically viable tests or devices to enable their adoption within clinical practice.

E. Pharmaceutical companies: Increased understanding of mechanisms underpinning treatment resistance in GBM, and how they can be targeted, will benefit companies developing or repurposing drugs for this disease.

F. The government: This project will result in the training of highly skilled researchers in genomics and data analytics (including artificial intelligence), highlighted as areas of strength in which the government plans to further increase the UK's capacity over the next 20 years.

G. Research facilities: This project will maintain the health of genomics service provision in the UK by showing how the use of these services, and discussion with them to enable them to address current challenges, benefits scientific discovery.