Abstract 156: Autophagic degradation of granzyme B impairs NK-mediated killing of hypoxic tumor cells
Bibliographic record
Abstract
Abstract Natural killer (NK) cells are effectors of the innate immune system, able to kill cancer cells through the release of the cytotoxic protease granzyme B. NK-based therapies have recently emerged as promising anticancer strategies. However, it is well established that hypoxic tumor microenvironment interferes with the antitumor function of immune cells and constitutes a major obstacle for defining cancer immunotherapies. Recent studies demonstrated that autophagy regulates the innate immune response by mechanisms which are not fully understood. In this study, we showed that hypoxia decreases breast cancer cell susceptibility to NK-mediated lysis by a mechanism involving the activation of autophagy in tumor cells. Targeting autophagy was sufficient to restore NK-mediated tumor cell killing. We showed that the resistance of hypoxic tumor cells was neither related to a defect in their recognition by NK cells, nor to a defect in the cytolytic function of NK cells toward hypoxic cells. We provided evidence that autophagy activation degrades NK-derived granzyme B in lysosomes of hypoxic cells making them less sensitive to NK-mediated killing. Genetic and pharmacological inhibition of autophagy restored granzyme B levels and reverted the resistance of hypoxic cells in vitro. Our results highlight autophagy as a critical factor in modulating NK-mediated anti-tumor immune response. We have validated this concept in vivo by showing that targeting autophagy significantly improved NK-mediated tumor shrinking in breast and melanoma models. This study provides a cutting-edge advance in our understanding of how hypoxia-induced autophagy impairs NK-mediated lysis and paves the way for formulating more effective NK-based antitumor therapy by combining autophagy inhibitors. Citation Format: Joanna Baginska, Elodie Viry, Guy Berchem, Aurélie Poli, Muhammad Zaeem Noman, Kris van Moer, Sandrine Medves, Takouhie Mgrditchian, Jacques Zimmer, Anais Oudin, Simone P. Niclou, R. Chris Bleackley, Salem Chouaib, Bassam Janji. Autophagic degradation of granzyme B impairs NK-mediated killing of hypoxic tumor cells. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 156. doi:10.1158/1538-7445.AM2014-156
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".