Ex-vivo model develops insights on minimal residual disease in glioblastoma, suggesting new treatment strategies.
AIMS Glioblastoma (GBM) is the most common and aggressive primary brain tumour. Recurrence following stan- dard of care is inevitable due to an inability to eradicate all tumour cells with surgery and the stark chemo- radioresistance of the residual population. The underpinning mechanisms remain poorly understood, largely due to the inaccessibility of the residual cells that remain immediately after treatment, known as the minimal residual disease (MRD), in patients. To overcome this, we aim to develop a novel ex-vivo model system of the MRD in human GBM and use it to unravel the molecular basis of resistance. METHODS Primary brain tumour tissue collected from bulk and infiltrative margins of GBM during debulking surgery, was used to generate organotypic tissue slices. To optimise culture conditions, we tested the effect of using different collection and culture mediums, recovery methods and sectioning conditions to preserve different cell types and ensure optimal tissue viability. To determine an appropriate treatment regimen to achieve minimal residual disease, brain slices were then exposed to varying doses of temozolomide and radiotherapy. Tissue viability was analysed using mass cytometry, flow cytometry and TUNEL assays. RESULTS We have determined optimal culture conditions to achieve minimal loss of tissue viability that reflect both, resected and residual tumour populations. We further identified treatment schedules that recapitulate current clinical standard of care to model MRD. Future work will be devoted to optimising mass cytometry panels to analyse cell signalling, cell death and DNA damage response pathways alongside cell fate markers. CONCLUSION Our ex-vivo model of MRD and associated molecular profiling pipeline will enable mechanistic understanding of resistance mechanisms in GBM, ultimately providing a platform for the identification of novel targetable biological vulnerabilities for suppressing recurrence in GBM.
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Patel et al. (2025) studied this question.
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