Abstract B034: Smac mimetics synergistically improve the efficacy of cancer immunotherapies including immune checkpoint blockade in preclinical models
Bibliographic record
Abstract
Abstract Aim: To demonstrate the immune potentiating effects of small-molecule inhibitor-of-apoptosis (IAP) antagonists, known as Smac mimetics, with current standard-of-care cancer immunotherapies. Background: Smac mimetic compounds (SMCs) are synthetic small-molecule antagonists of the cellular inhibitor of apoptosis, cIAP1 and cIAP2, proteins. The IAPs act at a critical nexus in the cancer cell, capable of suppressing intrinsic cell death and avoiding immune-mediated killing of the target cancer cell. The cIAPs are essential mediators of TNF cytokine superfamily signaling which is responsible for the activation of classical and alternative NF-κB survival pathways. SMCs cause the rapid loss of cIAP1/2 proteins by ubiquitin-induced and proteasomal-mediated degradation. SMCs sensitize tumor cells to TNFα-mediated killing by blocking the formation of the RIP1 signalosome and by generating RIP1 death-inducing complexes, the ripoptosome and the necrosome. In addition, SMCs by depleting cIAPs in immune cells promote anti-tumor immunity by inducing T-cell co-stimulation, resulting in a multi-pronged cytolytic attack against tumor cells. SMCs are in early stage clinical trials for cancer and have proven safe as single agents or in combination with chemotherapy. Methodology: We tested various combination immunotherapies in vitro and in vivo in multiple different orthotopic models of cancer, including glioblastoma, in immunocompetent mice to ascertain tumor responses. In addition, we elucidated the role of cytokines and immune cells in the efficacy observed. Results: SMCs dramatically enhanced the anti-tumor effects of Toll-like receptor agonists, recombinant type-1 interferon, BCG vaccine or oncolytic rhabdoviruses in models of cancer. Importantly, we observed for the first time remarkable synergy between SMCs and immune checkpoint inhibitor biologics (e.g. anti-PD1, anti-CTLA-4 monoclonal antibodies) in brain tumor models for which neither single agent had any significant activity. We now demonstrate that SMCs induce long-term cancer immunity that is dependent on cytotoxic T-cell activity. Furthermore, SMCs cooperate with anti-PD1 immune checkpoint inhibitors to induce durable cures in aggressive tumor. We demonstrate that both the innate and adaptive immune response are responsible for the anti-tumor responses and the generation of durable cures in these models. Cytokine neutralization and immune-cell depletion experiments point to key roles for TNFα, interferons, macrophages and CD8-positive killer T-cells in the combination immunotherapy effects observed. Conclusions: SMCs can make use of both innate and adaptive immunity to eradicate cancers in mice. Smac mimetic small-molecules represent a novel and universal form of cancer immunotherapy that greatly compliments immune checkpoint blockade. This highly effective combination approach is readily translatable to the clinic. (Acknowledgements: This project was supported by an Impact grant co-funded by CCSRI and Brain Canada, and by operating grants from CIHR). Citation Format: Eric LaCasse, Shawn Beug, Cristin Healey, Caroline Beauregard, Tarun Sanda, Tommy Alain, Robert Korneluk. Smac mimetics synergistically improve the efficacy of cancer immunotherapies including immune checkpoint blockade in preclinical models [abstract]. In: Proceedings of the Second CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; 2016 Sept 25-28; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(11 Suppl):Abstract nr B034.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".