Glioma is the most common primary cancer of the central nervous system, and around 50% of patients present with the most aggressive form of the disease, glioblastoma. Conventional therapies, including surgery, radiotherapy, and pharmacotherapy (typically chemotherapy with temozolomide), have not resulted in major improvements in the survival outcomes of patients with glioblastoma. Reasons for this lack of progress include invasive tumour growth in an essential organ, which limits the utility of local therapy, as well as the protection of tumour cells by the blood-brain barrier, their intrinsic resistance to the induction of cell death, and lack of dependence on single, targetable oncogenic pathways, all of which impose challenges for systemic therapy. Furthermore, the unique immune environment of the central nervous system needs to be considered when pursuing immune-based therapeutic approaches for glioblastoma. Nevertheless, a range of different immunotherapies are currently being actively investigated in patients with this disease, spurred on by advances in immuno-oncology for other tumour types. Herein, we examine the current state of immunotherapy for gliomas, notably glioblastoma, the implications for combining the current standard-of-care treatment modalities with immunotherapies, potential biomarkers of response, and future directions for glioblastoma immuno-oncology.
Purpose Glioblastoma multiforme (GBM) is the most common primary brain tumor in adults, and radiation is one of the main treatment modalities. However, cure rates remain low despite best available therapies. Immunotherapy is a promising modality that could work synergistically with radiation, which has been shown to increase antigen presentation and promote a proinflammatory tumor microenvironment. Programmed-death-1 (PD-1) is a surface receptor expressed on activated and exhausted T cells, which mediate T cell inhibition upon binding with its ligand PD-L1, expressed on many tumor types including human GBMs. We tested the combination of anti-PD-1 immunotherapy with stereotactic radiosurgery in a mouse orthotopic GBM model. Methods and Materials We performed intracranial implantation of mouse glioma cell line GL261 transfected with luciferase into C57BL/6 mice. Mice were stratified into 4 treatment groups: (1) control; (2) radiation only; (3) anti-PD-1 antibody only; and (4) radiation plus anti-PD-1 antibody. Overall survival was quantified. The mice were killed on day 21 after implantation to assess immunologic parameters in the brain/tumor, cervical lymph nodes, and spleen. Results Improved survival was demonstrated with combination anti-PD-1 therapy plus radiation compared with either modality alone: median survival was 25 days in the control arm, 27 days in the anti-PD-1 antibody arm, 28 days in the radiation arm, and 53 days in the radiation plus anti-PD-1 therapy arm (P<.05 by log-rank Mantle-Cox). Long-term survival was seen only in the combined treatment arm, with a fraction (15%–40%) of animals alive at day 180+ after treatment. Immunologic data on day 21 after implantation showed increased tumor infiltration by cytotoxic T cells (CD8+/interferon-γ+/tumor necrosis factor-α+) and decreased regulatory T cells (CD4+/FOXP3) in the combined treatment group compared with the single modality arms. Conclusions The combination of PD-1 blockade and localized radiation therapy results in long-term survival in mice with orthotopic brain tumors. These studies provide strong preclinical evidence to support combination trials in patients with GBM.
IMPORTANCE Clinical outcomes for glioblastoma remain poor. Treatment with immune checkpoint blockade has shown benefits in many cancer types. To our knowledge, data from a randomized phase 3 clinical trial evaluating a programmed death-1 (PD-1) inhibitor therapy for glioblastoma have not been reported.OBJECTIVE To determine whether single-agent PD-1 blockade with nivolumab improves survival in patients with recurrent glioblastoma compared with bevacizumab. DESIGN, SETTING, AND PARTICIPANTSIn this open-label, randomized, phase 3 clinical trial, 439 patients with glioblastoma at first recurrence following standard radiation and temozolomide therapy were enrolled, and 369 were randomized. Patients were enrolled between September 2014 and May 2015. The median follow-up was 9.5 months at data cutoff of January 20, 2017. The study included 57 multicenter, multinational clinical sites.INTERVENTIONS Patients were randomized 1:1 to nivolumab 3 mg/kg or bevacizumab 10 mg/kg every 2 weeks until confirmed disease progression, unacceptable toxic effects, or death. MAIN OUTCOMES AND MEASURES The primary end point was overall survival (OS).RESULTS A total of 369 patients were randomized to nivolumab (n = 184) or bevacizumab (n = 185). The MGMT promoter was methylated in 23.4% (43/184; nivolumab) and 22.7% (42/185; bevacizumab), unmethylated in 32.1% (59/184; nivolumab) and 36.2% (67/185; bevacizumab), and not reported in remaining patients. At median follow-up of 9.5 months, median OS (mOS) was comparable between groups: nivolumab, 9.8 months (95% CI, 8.2-11.8); bevacizumab, 10.0 months (95% CI, 9.0-11.8); HR, 1.04 (95% CI, 0.83-1.30); P = .76. The 12-month OS was 42% in both groups. The objective response rate was higher with bevacizumab (23.1%; 95% CI, 16.7%-30.5%) vs nivolumab (7.8%; 95% CI, 4.1%-13.3%). Grade 3/4 treatment-related adverse events (TRAEs) were similar between groups (nivolumab, 33/182 [18.1%]; bevacizumab, 25/165 [15.2%]), with no unexpected neurological TRAEs or deaths due to TRAEs. CONCLUSIONS AND RELEVANCEAlthough the primary end point was not met in this randomized clinical trial, mOS was comparable between nivolumab and bevacizumab in the overall patient population with recurrent glioblastoma. The safety profile of nivolumab in patients with glioblastoma was consistent with that in other tumor types.
Purpose Checkpoint molecules like programmed death-1 (PD-1) and T-cell immunoglobulin mucin-3 (TIM-3) are negative immune regulators that may be upregulated in the setting of glioblastoma multiforme. Combined PD-1 blockade and stereotactic radiosurgery (SRS) have been shown to improve antitumor immunity and produce long-term survivors in a murine glioma model. However, tumor-infiltrating lymphocytes (TIL) can express multiple checkpoints, and expression of ≥2 checkpoints corresponds to a more exhausted T-cell phenotype. We investigate TIM-3 expression in a glioma model and the antitumor efficacy of TIM-3 blockade alone and in combination with anti-PD-1 and SRS. Experimental Design C57BL/6 mice were implanted with murine glioma cell line GL261-luc2 and randomized into 8 treatment arms: (i) control, (ii) SRS, (iii) anti-PD-1 antibody, (iv) anti-TIM-3 antibody, (v) anti-PD-1 + SRS, (vi) anti-TIM-3 + SRS, (vii) anti-PD-1 + anti-TIM-3, and (viii) anti-PD-1 + anti-TIM-3 + SRS. Survival and immune activation were assessed. Results Dual therapy with anti-TIM-3 antibody + SRS or anti-TIM-3 + anti-PD-1 improved survival compared with anti- TIM-3 antibody alone. Triple therapy resulted in 100% overall survival (P < 0.05), a significant improvement compared with other arms. Long-term survivors demonstrated increased immune cell infiltration and activity and immune memory. Finally, positive staining for TIM-3 was detected in 7 of 8 human GBM samples. Conclusions This is the first preclinical investigation on the effects of dual PD-1 and TIM-3 blockade with radiation. We also demonstrate the presence of TIM-3 in human glioblastoma multiforme and provide preclinical evidence for a novel treatment combination that can potentially result in long-term glioma survival and constitutes a novel immunotherapeutic strategy for the treatment of glioblastoma multiforme.
We introduce a method for learning pairwise interactions in a linear regression or logistic regression model in a manner that satisfies strong hierarchy: whenever an interaction is estimated to be nonzero, both its associated main effects are also included in the model. We motivate our approach by modeling pairwise interactions for categorical variables with arbitrary numbers of levels, and then show how we can accommodate continuous variables as well. Our approach allows us to dispense with explicitly applying constraints on the main effects and interactions for identifiability, which results in interpretable interaction models. We compare our method with existing approaches on both simulated and real data, including a genome-wide association study, all using our R package glinternet.
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