Atim-01. Nivolumab and Bevacizumab for Recurrent Glioblastoma; A Translational Trial in Progress

Abstract

Glioblastoma multiforme (GBM) is an aggressive brain tumor with a poor prognosis. Standard of care at diagnosis is surgical resection, followed by radiation and temozolomide. Receiving this therapy, the median survival is 14.6 months [1]. We have no standard treatment for relapse and known options have limited effect. There is an urgent need for novel treatment interventions to improve clinical outcomes and quality of life. Recently, improved overall survival has been achieved with immune therapeutics in melanoma and renal cell carcinoma. Accordingly, it has been posited that immunotherapy may offer promise in other difficult cancers such as GBM [2]. We present our translational study; a phase II open label, two-armed translational study of Nivolumab and Bevacizumab for recurrent GBM, who have failed Stupp’s regime [1]. Patients are included in two arms depending on possibly salvage neurosurgical resection. Both arms receive Nivolumab and Bevacizumab administrated every second weekend, but the surgical arm also receive Nivolumab 7 days prior surgery. We expect 40 patients; 20 in each arm. Enrollment period is expected to 20 months, started October 2018. Our primary objective is to make preliminary assessment of immune related biomarkers, including PD-L1; therefore, we perform full genome sequencing on tumor biopsies from the surgical arm and on blood samples from both arms. We evaluate changes in the transcriptomic landscape caused by the check-point inhibition and relation to response as compared with baseline sequencing data, as well as the impact of tumor mutation burden and neoepitope load. We investigate the tumor microenvironment by harvesting tumor infiltrating lymphocytes and study the composition by flow-cytometry. The patients are evaluated by blood samples, FET-PET as wells as clinical examinations to evaluate PFS and OS. Overall the study will provide us with a unique possibility to investigate and thereof predict which patients will profit from the treatment.