Project description:<p>In this prospective study, we performed genome-wide tumor/normal exome sequencing and tumor RNA-sequencing for recurrent glioblastoma patients. A subset of patients had both enhancing tumor and non-enhancing tissue sequenced to investigate spatial heterogeneity of this disease. Together, this information builds our understanding of the genomic underpinnings of glioblastoma, and contributes toward the knowledge base for identifying and developing more effective treatments for patients with glioblastoma.</p>
Project description:Glioblastoma remains incurable and, due to its infiltrative growth, high levels of treatment resistance and population of glioma initiating/stem cells (GICs), recurs in all patients. Here we design and characterize a novel induced-recurrence model in which mice xenografted with primary patient-derived GICs are treated with a therapeutic regimen closely recapitulating patient standard of care, followed by monitoring until tumours recur (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 GICs enabled patient-specific evaluation of the faithfulness with which the model recapitulated phenotypes associated with the true recurrence. Through comprehensive multi-omic analyses, we showed that the IR-PDX model recapitulated genomic, epigenetic, and transcriptional state heterogeneity changes 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, in which the IR-PDX model is developed between first diagnosis and disease progression to identify target-drug candidates for use as second line of treatment at recurrence.
Project description:Glioblastoma remains incurable and, due to its infiltrative growth, high levels of treatment resistance and population of glioma initiating/stem cells (GICs), recurs in all patients. Here we design and characterize a novel induced-recurrence model in which mice xenografted with primary patient-derived GICs are treated with a therapeutic regimen closely recapitulating patient standard of care, followed by monitoring until tumours recur (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 GICs enabled patient-specific evaluation of the faithfulness with which the model recapitulated phenotypes associated with the true recurrence. Through comprehensive multi-omic analyses, we showed that the IR-PDX model recapitulated genomic, epigenetic, and transcriptional state heterogeneity changes 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, in which the IR-PDX model is developed between first diagnosis and disease progression to identify target-drug candidates for use as second line of treatment at recurrence.
Project description:Glioblastoma remains incurable and, due to its infiltrative growth, high levels of treatment resistance and population of glioma initiating/stem cells (GICs), recurs in all patients. Here we design and characterize a novel induced-recurrence model in which mice xenografted with primary patient-derived GICs are treated with a therapeutic regimen closely recapitulating patient standard of care, followed by monitoring until tumours recur (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 GICs enabled patient-specific evaluation of the faithfulness with which the model recapitulated phenotypes associated with the true recurrence. Through comprehensive multi-omic analyses, we showed that the IR-PDX model recapitulated genomic, epigenetic, and transcriptional state heterogeneity changes 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, in which the IR-PDX model is developed between first diagnosis and disease progression to identify target-drug candidates for use as second line of treatment at recurrence.