Harnessing nutrient scarcity for enhanced CAR-T-cell potency and safety in solid tumors
Bibliographic record
Abstract
Abstract Despite significant advancements, the effectiveness of chimeric antigen receptor (CAR)-T-cell-based therapies in solid tumors remains limited. Key challenges include on-target effects, off-tumor toxicity and reduced CAR-T-cell function within the tumor microenvironment, which is often characterized by metabolic stress triggered by factors such as amino acid scarcity. Activating transcription factor-4 (ATF4) and its upstream regulator GCN2 play crucial roles in the metabolic reprogramming and functionality of CD4 + and CD8 + T cells. ATF4 can be activated by various cellular stress signals, including amino acid deprivation. While ATF4 activation may be associated with T-cell dysfunction, its role in stress adaptation presents an opportunity for therapeutic intervention—particularly in the tumor microenvironment, where T-cell exhaustion is a major challenge. In this study, we developed a strategy to harness the GCN2‒ATF4 axis in CAR-T cells. We employed an amino acid-dependent inducible promoter, which triggers ATF4-dependent gene expression to regulate CAR expression in T cells under conditions of amino acid scarcity within the tumor microenvironment. In vitro and murine xenograft models demonstrate the potential of this system to effectively restrict CAR expression to the tumor site. This targeted strategy not only enhances safety by minimizing off-tumor activity but also CAR-T-cell fitness by reducing exhaustion. By validating this pathophysiologically regulatable CAR expression system for solid tumors, our findings address key limitations of current CAR-T-cell therapies and pave the way for innovative strategies targeting solid malignancies.
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".