The aim of this study is to make preliminary assessment of PD-L1 and other immune related biomarkers that might act as predictors of anti-tumor activity of Nivolumab in patients with recurrent glioblastoma
The effect of Nivolumab in oncologic diseases is to modulate the immune system in order to generate and/or restore a durable anti-tumor response leading to clearance of tumor. Clinical data generated with Nivolumab monotherapy in a variety of settings support the hypothesis that blockade of the PD-1 pathway results in rejection of tumor by the host immune system. The precise mechanisms by which Nivolumab exerts its anti-tumor activity are still under investigation. To contribute to this knowledge, tumor tissue from primary operation for all patients and tumor tissue from patients in the surgical Arm A will be used for further analysis. Targeted sequencing with next generation sequencing (NGS) and Genome-wide Associations Studies (GWAS) with the use of single nucleotide polymorphism (SNP)-arrays and micro-array for expression profiling will be performed in order to describe the profile of the tumor. At Rigshospitalet has initiated a program of NGS of patients with GBM after informed content, by obtaining fresh tissue from primary or relapse surgery. In the surgical group (Arm A) of this study NGS will be repeated after one dose of Nivolumab. This information will be used in combination with the clinical observations for each patient receiving the combination of Nivolumab and Bevacizumab and the aim is that these results could be useful towards finding prognostic and/or predictive biomarkers in GBM. In order to study the interaction between tumor cells and the immune system investigation of intratumoral and peripheral changes in tumor-infiltration lymphocytes (TILs) will be performed. By looking at TILs and peripheral blood lymphocytes (PBLs) Surgical samples will be compared to sequencing of baseline surgical samples (before Nivolumab). The interaction of TILs and tumor cells will be assessed with in vitro functional assays of autologous tumor cell recognition. Functional patterns of antitumor CD8+ and CD4+ TILs and PBLs will be investigated, with assays combining characterization of major T cell functions and simultaneous surface staining of PD-1 after co-culture with autologous tumor cells. This may detect treatment-induced changes in the functional repertoires of CD4+ and CD8+ TILs both in the tumor microenvironment (TILs) and in the periphery (PBLs). It is expected that these analyses will reveal whether significant functional changes (defined as increased frequency of tumor-reactive T cells or as functional shifting from a monofunctional to a multifunctional profile) are induced in the whole repertoire of T cells, or whether these changes are restricted to PD-1 positive T cells. Regarding the immune-reactivity, CD8 T cell recognition of tumor-specific-antigens (TSA), i.e. and mutation derived neoepitopes will be analyzed in enrolled patients. To analyze for immune reactivity on a personalized basis by comprising epitope-maps based on both mutation-derived neoepitopes and shared tumor antigens selected based on the individual tumor mRNA expression level. For the prediction of mutation- and splice-variation derived epitopes, whole exome sequencing (WES) and mRNA sequencing will be conducted on tumor versus germline-control samples. Cancer-specific mutations, indels, frameshifts and splice variations will be mapped to predict T cell epitopes overlapping these regions based on the patient HLA type, using available prediction tools, netMHC. A pipeline for processing next-generation sequencing data into tumor-specific neo-epitope maps has been generated to include analyses of tumor heterogeneity and generate personalized peptide libraries for each patient and analyze for T cell recognition of personalized neoepitopes in each patient included in the study. A novel technology will tag and track multiple (\>1000) antigen specific T cell specificities based on their peptide-MHC (pMHC) recognition motif through a pMHC multimer with a co-attached 'DNA barcode'. Through use of this technology T cell recognition will be assessed against large libraries of peptides in limited biological samples, such as tissue biopsies, TILs and peripheral blood mononuclear cells (PBMCs). Data will reveal to what extend mutation and splice-variant derived neoepitopes are contributing to immune recognition as a consequence of checkpoint inhibition. If these are significantly recognized, then they are likely to play a crucial role for the clinical response to checkpoint inhibition.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
BASIC_SCIENCE
Masking
NONE
Enrollment
40
Treatment with the combination of Nivolumab and bevacizumab every 2 weeks
Treatment with the combination of Nivolumab and bevacizumab every 2 weeks
Rigshospitalet
Copenhagen, Denmark
Number of indels as determined using mRNA sequencing
whole exome sequencing (WES) and mRNA sequencing on tumor versus germline-control samples. We will map cancer-specific mutations, indels, frameshifts and splice variations, and predict T cell epitopes overlapping these regions based on the patient HLA type, using available prediction tools, netMHC
Time frame: 8 weeks
Progression-Free Survival (PFS)
Progression-Free Survival (PFS) in both treatment Arms
Time frame: 6 months
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