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Glioblastoma Relapse Post-Resection Model for Therapeutic Hydrogel Investigations
Published on: February 24, 2023
A novel model of glioblastoma recurrence to identify therapeutic vulnerabilities
Sara Lucchini1, James G Nicholson1, Xinyu Zhang1
1Brain Tumour Research Centre, Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University London, London, UK.
Abstract:
Glioblastoma remains incurable and recurs in all patients. Here we design and characterize a novel induced-recurrence model in which mice xenografted with primary patient-derived glioma initiating/stem cells (GIC) are treated with a therapeutic regimen closely recapitulating patient standard of care, followed by monitoring until tumours recur (induced recurrence patient-derived xenografts, IR-PDX). By tracking in vivo tumour growth, we confirm the patient specificity and initial efficacy of treatment prior to recurrence. Availability of longitudinally matched pairs of primary and recurrent GIC enabled patient-specific evaluation of the fidelity with which the model recapitulated phenotypes associated with the true recurrence. Through comprehensive multi-omic analyses, we show that the IR-PDX model recapitulates aspects of genomic, epigenetic, and transcriptional state heterogeneity upon recurrence in a patient-specific manner. The accuracy of the IR-PDX enabled both novel biological insights, including the positive association between glioblastoma recurrence and levels of ciliated neural stem cell-like tumour cells, and the identification of druggable patient-specific therapeutic vulnerabilities. This proof-of-concept study opens the possibility for prospective precision medicine approaches to identify target-drug candidates for treatment at glioblastoma recurrence.
Insights
A new glioblastoma model accurately mimics tumor recurrence in patients. This allows for personalized treatment strategies and identifies potential drug targets for recurrent brain tumors.
Area of Science:
- Neuro-oncology
- Cancer Biology
- Translational Medicine
Background:
- Glioblastoma (GBM) is an aggressive brain tumor with a poor prognosis.
- Tumor recurrence is inevitable in all GBM patients, necessitating effective therapeutic strategies.
- Current models often fail to fully recapitulate the complexity of GBM recurrence.
Purpose of the Study:
- To develop and characterize a novel induced-recurrence model for glioblastoma (IR-PDX).
- To evaluate the patient-specific recapitulation of genomic, epigenetic, and transcriptional phenotypes upon recurrence.
- To identify novel therapeutic vulnerabilities and biological insights associated with glioblastoma recurrence.
Main Methods:
- Generation of induced recurrence patient-derived xenografts (IR-PDX) using patient-derived glioma initiating cells (GIC).
- Treatment of xenografted mice with a regimen mimicking standard patient care, followed by monitoring for tumor recurrence.
- Comprehensive multi-omic analyses (genomic, epigenetic, transcriptional) of matched primary and recurrent GIC.
- In vivo tumor growth tracking and phenotypic evaluation.
Main Results:
- The IR-PDX model accurately recapitulates patient-specific glioblastoma recurrence.
- Multi-omic analyses confirm the model's fidelity in reflecting genomic, epigenetic, and transcriptional heterogeneity upon recurrence.
- Novel biological insights revealed a link between glioblastoma recurrence and ciliated neural stem cell-like tumor cells.
- Identification of druggable, patient-specific therapeutic vulnerabilities for recurrent glioblastoma.
Conclusions:
- The IR-PDX model serves as a powerful tool for studying glioblastoma recurrence.
- This model enables patient-specific evaluation of therapeutic strategies and biological mechanisms.
- The findings support the development of precision medicine approaches for treating recurrent glioblastoma.
