A novel model of glioblastoma recurrence to identify therapeutic vulnerabilities.

一种用于识别治疗弱点的胶质母细胞瘤复发新模型

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作者:Lucchini Sara, Nicholson James G, Zhang Xinyu, Househam Jacob, Lim Yau Mun, Mossner Maximilian, Millner Thomas O, Brandner Sebastian, Graham Trevor, Marino Silvia
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.

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