Our research

We use cutting-edge research methods to advance biological, clinical and epidemiological understanding of brain tumours. Our work in glioma stem cell biology focuses on characterising molecular variations between tumours in different patients to enable personalised cancer care. Novel biomarkers for brain tumour detection using spectroscopy and liquid biopsy are also areas of active research. Drug discovery is an important aspect of our research, and we use next-generation sequencing data and machine learning methods to enable high-throughput in silico drug screening algorithms. To evaluate clinical determinants of treatment outcomes, we curate a database containing detailed information from >1,500 consecutive brain tumour patients diagnosed in Southeast Scotland. We use advanced statistical models to assess aspects of clinical care that can have an immediate impact on patient outcomes and test hypotheses generated from preclinical studies. Routine healthcare data constitutes a major focus of our work, which allows us to examine changes in clinical practice and patient outcomes at the population level. Our unit also supports the SPRING trial, Tessa Jowell BRAIN MATRIX trial, and FUTURE-GB trial.

Our brain tumour research portfolio spanning preclinical studies to randomised controlled trials demonstrates our commitment to translational research. Edinburgh Cancer Research Centre is a Cancer Research UK Brain Tumour Centre of Excellence, and our high-quality clinical care is recognised by the Tessa Jowell Centre of Excellence status.

Selected recent publications

• Glioblastomas acquire myeloid-affiliated transcriptional programs via epigenetic immunoediting to elicit immune evasion. Gangoso et al., Cell 2021. 184(9):2454-2470.
• Might changes in diagnostic practice explain increasing incidence of brain and central nervous system tumors? A population-based study in Wales (United Kingdom) and the United States. Poon et al., Neuro-Oncology 2022. 23(6):979–989.
• Clinical validation of a spectroscopic liquid biopsy for earlier detection of brain cancer. Cameron et al., Neuro-Oncology Advances 2022. 4(1):vdac024.
• Development of prediction models for one-year brain tumour survival using machine learning: a comparison of accuracy and interoperability. Charlton et al., Computer Methods and Programs in Biomedicine 2023. 233:107482. 

We lead the NIHR-funded DENS trial (NIHR131118) that aims to determine whether earlier removal of a hard collar is associated with a better quality of life in older and frail patients with a fracture of the odontoid process bone in the neck. In collaboration with the British Neurosurgical Trainee Research Collaborative, members of our team lead the core study group in the Understanding Cauda Equina Study (UCES). UCES is a prospective multi-centre national study that describes clinical practice, patient outcomes and determinants of outcomes in people who underwent surgery for cauda equina syndrome. Other research interests include developing a core outcome set for cervical spine diseases and the assessment of clinical variables associated with outcomes in patients with ankylosing spondylitis.

Selected publications

• Presentation, management, and outcomes of cauda equina syndrome up to one year after surgery, using clinician and participant reporting: a multi-centre prospective cohort study. Woodfield et al., The Lancet Regional Health 2023. 42:100545.
• Duration of External Neck Stabilisation (DENS) following odontoid fracture in older or frail adults: protocol for a randomised controlled trial of collar versus no collar. Woodfield et al., BMJ Open 2022. 12(7):e057753.
• A systematic review identifying outcome measures used in evaluating adults sustaining cervical spine fractures. Copley et al., European Spine Journal 2022. 31(12):3365-3377.

We are interested in why inflammatory responses to acute brain injury varies in people with a brain haemorrhage and how these variations can affect outcomes. Our approach uses preclinical models to investigate cellular interactions in response to brain haemorrhage. Clinical correlation is achieved by examining brain tissue and clinical data from patients who have died following brain haemorrhage to identify what modifiable factors are translatable to human disease. Working with colleagues in Research to Understand Stroke due to brain Haemorrhage (RUSH), we conduct clinical epidemiological studies to improve outcomes for people with stroke due to brain haemorrhage. We also lead the Sodium after Subarachnoid Haemorrhage (SASH) project together with NSAMR and the BNTRC. SASH is a prospective multicentre cohort study evaluating whether current UK management of patients following spontaneous subarachnoid haemorrhage adheres to national guidelines. This project also explores the association between low sodium levels and patient outcomes.

Selected publications

• Risks of recurrent stroke and all serious vascular events after spontaneous intracerebral haemorrhage: pooled analyses of two population-based studies. Li et al., The Lancet Neurology 2021. 20(6):437-447.
• Association of baseline hematoma and edema volumes with one-year outcome and long-term survival after spontaneous intracerebral hemorrhage: A community-based inception cohort study. Loan et al., International Journal of Stroke 2021. 16(7):828-839.
• Secondary injury and inflammation after intracerebral haemorrhage: a systematic review and meta-analysis of molecular markers in patient brain tissue. Loan et al., Journal of Neurology, Neurosurgery & Psychiatry 2022. 93(2):126-132.
• Prospective, multicentre study of screening, investigation and management of hyponatraemia after subarachnoid haemorrhage in the UK and Ireland. Loan et al., Stroke and Vascular Neurology 2022. svn-2022-001583.

Our research in traumatic brain injury includes clinical epidemiological and blood biomarker research. Optimisation of early patient assessment is a core interest. We evaluate different bedside assessment tools for prognostication. Key research includes the development of the GCS-Pupils score, GCS-P age CT charts, and the GCS verbal imputation tool. We are interested in dysfunction of the pituitary gland, a pea-sized gland closely associated with the brain, in people with traumatic brain injury. Our team also is developing a blood biomarker for the rapid assessment of patients with mild traumatic brain injury to determine who actually needs brain imaging.  

Selected publications

• Simplifying the use of prognostic information in traumatic brain injury. Part 1: The GCS-Pupils score: an extended index of clinical severity. Brennan et al., Journal of Neurosurgery 2018. 128(6):1612–1620.
• Simplifying the use of prognostic information in traumatic brain injury. Part 2: Graphical presentation of probabilities. Brennan et al., Journal of Neurosurgery 2018. 128(6):1621–1634.
• A practical method for dealing with missing Glasgow Coma Scale verbal component scores. Brennan et al., Journal of Neurosurgery 2020. 135(1)1:214–219.

• Prevalence of Anterior Pituitary Dysfunction Twelve Months or More following Traumatic Brain Injury in Adults: A Systematic Review and Meta-Analysis. Emelifeonwu et al., Journal of Neurotrauma 2020. 37(2):217-226. 

Many of our research projects have collaborators locally, nationally and internationally.

Clinical Natural Language Processing Group – we work with the Edinburgh Clinical NLP Group on the Whole population Automated Reading of Brain imaging reports in Linked Electronic health Records (WARBLER) study. We apply a computer technique called natural language processing that ‘read’ radiology reports to extract clinical information stored within these reports. By linking to other routine healthcare data generated from day-to-day clinical services, we can assess determinants of outcomes at scale in the whole of Scotland. Conditions we focus on here include brain tumours and chronic subdural haematoma

Artificial Intelligence and its Applications Institute (AIAI) – with the increase in healthcare data, we collaborate with colleagues in AIAI to develop scalable and clinically relevant projects to better understand determinants of health and disease in people with neurosurgical conditions. Examples of these project include the use of explainable artificial intelligence methods for brain tumour diagnosis and causal inference analysis in chronic subdural haematoma prognosis.

British Neurosurgical Trainee Research Collaborative (BNTRC) – our trainees contribute to national collaborative projects hosted by the BNTRC, taking the lead role in three projects (chronic subdural haematoma audit, extra-ventricular drainage audit, and Understanding Cauda Equina Study). They continue to shape the landscape of collaborative neurosurgical research through memberships in the BNTRC committee.