BRAIN Surgical Tissue for Advanced Tumour models in Precision medicine: Developing the BRAIN-STAT pathway. (15th October 2021)

• Record Type: Journal Article
• Authors: Wykes, Victoria; Finch, Alina; Blakeway, Daniel; Bardella, Chiara; Pohl, Ute; Beggs, Andrew; Watts, Colin
• Is Part Of: Neuro-oncology. Volume 23: Supplement 4(2021)
• Page Start: iv19
• Page End: iv20
• Publication Date: 2021-10-15
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noab195.050
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: Aims: There are approximately four thousand neuro-oncology procedures in the UK per annum. Many of these result in tissue and biofluid specimens that are surplus to diagnostic requirement and can be collected as standard of clinical care. However, developing technologies and treatments for precision medicine require access to a range of individualised biospecimens paired with deep clinical phenotyping data. Here, we present Brain Surgical Tissue for Advanced Tumour Models (BRAINSTAT) programme, an infrastructure that has been established between Queen Elizabeth Hospital, Birmingham and the University of Birmingham, to collect, structure and store these resources and also maximise their value for research over the long-term. Using this approach our aim is to provide high-quality, annotated resources to help develop novel treatments for patients with brain tumours. Method: BRAINSTAT infrastructure allows: Prospective consent Biospecimens, including tumour tissue (brain and other primary in the case of metastasis), cyst fluid, dura, skin, CSF, blood (matched "germ-line" and for circulating cell free tumour DNA analysis), urine and saliva can be collected. Consent for long term follow-up, is either via clinic or NHS digital. More limited consent for non-oncological neurosurgical cohorts (e.g. epilepsy or vascular) and healthy volunteers allow healthy access-tissue and biofluids to be collected. B. Rapid transfer of fresh surgical tissue samples: Strong collaborative links and close physical proximity between operating theatre and laboratory allows rapid transfer of biospecimens minimising transit time. C. Standardised annotation across disciplines The RedCAP database system allows granular control over data-access, and each specialist research team is provided access only to the sub-sections relevant to them. All users must have Good Clinical Practice certification and GDPR training, prior to access of the BRAINSTAT database. Results: Between 25/11/2019-16/03/2020 and 27/07/2020-16/11/2020, 65 patients were consented for BRAINSTAT at the weekly neurosurgical oncology clinic. (Recruitment gaps due to the SARS-COVID 19 pandemic). Pathological diagnosis of surplus tissue collected included: 37 high grade glioma, 3 low grade glioma and 16 brain metastasis including: (6 lung, 6 breast, 2 colorectal, 1 oesophageal, 1 endometrial). Meningioma (5 WHO I; 1 WHO III) 1 patient undergoing anterior temporal lobectomy for hippocampal sclerosis contributed access tissue from the lateral neocortex. 1 patient had a non- neoplastic, non-diagnostic sample. All patients had matched "germ-line" blood samples. Median time from resection to arrival in the laboratory was 10 minutes (range 4-31). Standardised operating protocols to optimise this have been developed. Glioblastoma and breast-brain metastasis tumourspheres and cerebral organoids are currently being validated. Conclusion: Despite the challenges of the pandemic we have established a viable tissue pipeline from neurosurgical operating theatre to our university laboratories. We are developing clinically annotated human brain tumour cell lines, stem cells and 3D organoid models, principally for commonly encountered brain tumours such as glioma and metastasis. The research sets the foundation for a multitude of downstream applications including: - Building more complex organoid cultures e.g. by including other cell types such as healthy brain cells and endothelial cells allowing future experiments to more accurately model tumour growth. - Developing high-throughput, patient-specific drug screens of novel drugs and drug combinations using these 3D tumour models aiming to more effectively treat tumour proliferation and spread. These patient avatars will help inform and test more "stratified" personal medical treatments and will provide opportunities to allow earlier intervention with the aim of improving survival, coupled with a better quality of life.