Targeting the adenosine 2A receptor enhances chimeric antigen receptor T cell efficacy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Chimeric antigen receptor (CAR) T cells have been highly successful in treating hematological malignancies, including acute and chronic lymphoblastic leukemia. However, treatment of solid tumors using CAR T cells has been largely unsuccessful to date, partly because of tumor-induced immunosuppressive mechanisms, including adenosine production. Previous studies have shown that adenosine generated by tumor cells potently inhibits endogenous antitumor T cell responses through activation of adenosine 2A receptors (A2ARs). Herein, we have observed that CAR activation resulted in increased A2AR expression and suppression of both murine and human CAR T cells. This was reversible using either A2AR antagonists or genetic targeting of A2AR using shRNA. In 2 syngeneic HER2+ self-antigen tumor models, we found that either genetic or pharmacological targeting of the A2AR profoundly increased CAR T cell efficacy, particularly when combined with PD-1 blockade. Mechanistically, this was associated with increased cytokine production of CD8+ CAR T cells and increased activation of both CD8+ and CD4+ CAR T cells. Given the known clinical relevance of the CD73/adenosine pathway in several solid tumor types, and the initiation of phase I trials for A2AR antagonists in oncology, this approach has high translational potential to enhance CAR T cell efficacy in several cancer types.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it