Abstract 3153: Targeting the stress response kinase GCN2 to restore immunity in the tumor microenvironment
Bibliographic record
Abstract
Abstract Recent advances in cancer metabolism suggest that targeting amino acid metabolism represents a promising strategy for the development of novel therapeutic agents. Tumor, stromal and myeloid-derived suppressor cells (MDSC) within the tumor microenvironment (TME) create a nutrient-poor environment that inhibit immune function and support tumor growth. GCN2 (general control nonderepressible 2), a stress response kinase, plays a key role in maintaining cellular homeostasis under a wide range of stressors. Phosphorylation of GCN2 (pGCN2) in response to stress leads to inhibition of global protein synthesis and subsequently leads to 1) T cell anergy and apoptosis, 2) enhanced MDSC-dependent immune suppression and 3) tumor cell survival. Collectively, these roles suggest that GCN2 inhibition could have both a direct anticancer and an immune-activating effect. Treating nutrient-deprived T cells in vitro with a RAPT GCN2 inhibitor (RPT-GCN2i) rescued CD4+ and CD8+ T cell proliferation and effector functions. The RPT-GCN2i also reversed T cell suppression mediated by MDSCs derived from healthy donors or cancer patients. Using syngeneic mouse tumor models, we demonstrated that translational induction of activating transcription factor 4 (ATF4) is a strong marker of GCN2 pathway activation in vivo. Oral administration of an RPT-GCN2i exhibited notable drug-target occupancy and potently inhibited GCN2 kinase and ATF4 in the TME. RPT-GCN2i as a single agent and in combination with checkpoint blockade or angiogenesis inhibitor (anti-VEGFR) led to delays in tumor growth rate in various syngeneic tumor models. In addition, GCN2 inhibition redirected MDSC within the TME from a suppressive to inflammatory phenotype through downregulation of Arg1 and iNOS. Our results show that inhibition of GCN2 is an attractive approach for enhancing antitumor immune response and therefore GCN2 is a promising therapeutic target for the treatment of cancer. Citation Format: Lisa Marshall, Buvana Ravishankar, Urvi Kolhatkar, Mengshu Xu, Lavanya Adusumilli, Deepa Pookot, Thant Zaw, Chandru Ramana, Raashi Sreenivasan, Mikhail Zibinsky, Jeffrey Jackson, Grant Shibuya, Paul Leger, Omar Robles, Anqi Ma, Andrew Ng, Anton Shakhmin, Justy Guagua, Scott Jacobson, Steve Wong, Delia Bradford, Tracy L. McGaha, M Teresa Ciudad, James E. Talmadge, Holly C. Britton, George Katibah, Gene Cutler, David Wustrow, Paul D. Kassner, Dirk G. Brockstedt. Targeting the stress response kinase GCN2 to restore immunity in the tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3153.
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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) | 0.002 | 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 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".