Abstract

Abstract Glioblastoma (GBM) is the most common and deadly type of malignant brain cancer in adults. While current standard of care which combines resection, radiation therapy (RT) and Temozolomide (TMZ) effectively eliminates primary disease, recurrence is inevitable, occurs rapidly following treatment and is ultimately lethal due to limited therapeutic opportunities of recurrent GBM. Hypermutation has been reported to occur in a subset of both low and high-grade gliomas and emerges after exposure to TMZ. Mutational inactivation and loss of mismatch repair (MMR) gene expression lead to the accumulation of single nucleotide polymorphisms throughout the genome. To date, the gain of hypermutation and subsequent therapeutic responses are still largely unknown. We hypothesized that hypermutant (HM) and non-hypermutant (NH) tumors represent two recurrent GBM subtypes, which has distinct therapeutic vulnerabilities. In addition, given the lack of concordance between microsatellite instability (MSI) and occurrence of hypermutation in GBM, we sought to derive a limited gene panel which can be used as surrogate biomarker for hypermutation following TMZ to replace whole exome sequencing (WES). Using public datasets, we demonstrated that recurrent GBM can be clustered into two subtypes: HM and NH. We used matched primary and recurrent GBM datasets to derive a gene panel signature, which is uniquely mutated at recurrence in HM GBM and confirmed the specificity of this panel in an independent dataset. Furthermore, we utilized patient derived xenograft (PDX) models to generate pre-clinical models and demonstrated that HM recurrent GBM are more immune responsive while NH recurrent GBM maintained sensitivity to a range of alternate chemotherapies such as cisplatin and RT. Finally, we demonstrated that this signature is represented in exosomes and can be enriched by use of tumor specific antibody capture methods to improve the sensitivity of hypermutation detection in liquid biopsy.

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