P17.11.A DEVELOPMENT AND CHARACTERISATION OF THE QCELL-R RECURRENT GLIOBLASTOMA PRIMARY CELL LINE RESOURCE: MODELS TO DRIVE BREAKTHROUGH DISCOVERIES IN BRAIN CANCER

Abstract

Abstract BACKGROUND Glioblastoma (GBM) is the most aggressive brain tumour in adults, with a median survival of only 15 months. Despite aggressive treatment with chemotherapy using temozolomide and radiotherapy, GBM has a high prevalence of recurrence with almost all cases recurring within the first year. This highlights a clear need to develop a deeper understanding of GBM recurrence and to develop effective models to test novel therapies. The vast inter- and intra-tumoural heterogeneity and tumour cell plasticity are complicating the development of effective therapies for brain cancer patients. Large-scale genomic analyses of primary and recurrent human GBM tumour samples have revealed a complex genomic architecture. However, the majority of GBM discovery science has been conducted in treatment naïve tumour models, which fail to capture therapy resistance and tumour evolution. Hence, these changes have been difficult to link to GBM growth and functional cell properties upon recurrence. MATERIAL AND METHODS To address this, we have developed the QCell-R resource, a collection of functional models of recurrent GBM. In collaboration with the Royal Brisbane and Women’s Hospital (RBWH), pair-matched patient tumour samples from the initial resection and at recurrence post-therapy have been collected. From these tissue specimens, in vitro cell lines in both 2D and 3D cultures and in vivo orthotopic xenograft models have been developed. Response to standard of care therapy (temozolomide and radiotherapy) were assessed using IncuCyte proliferation assays. Bulk mRNA, scRNA and exome sequencing were also performed. RESULTS QCell-R consists of 11 patient-derived recurrent GBM models, with the time between resections varying from 5-13 months. There are four pair-matched QCell-R models, as well as three standalone recurrent models. Response to standard of care therapy varied between models, with one model exhibiting a four fold higher growth rate-50 (GR50) after temozolomide treatment and a 2.7 fold increase in radiation resistance compared to the matched treatment naïve counterpart. The mRNA and scRNA sequencing has been compared to publicly available datasets to identify genes of interest that may be targetable in recurrence to test in these models. CONCLUSION QCell-R represents a valuable resource to define novel therapies for recurrent GBM. Elucidation of tumour heterogeneity and tumour evolution will identify targetable genes contributing to therapy resistance in these models. Identifying these targetable genes from QCell-R allows the development of novel treatments, creating strategies that may reduce the rate of recurrence by limiting therapy resistance and inhibiting recurrence-initiating cells.