Human OX40L–CAR-T <sub>regs</sub> target activated antigen-presenting cells and control T cell alloreactivity
Bibliographic record
Abstract
Regulatory T cells (T regs ) make major contributions to immune homeostasis. Because T reg dysfunction can lead to both allo- and autoimmunity, there is interest in correcting these disorders through T reg adoptive transfer. Two of the central challenges in clinically deploying T reg cellular therapies are ensuring phenotypic stability and maximizing potency. Here, we describe an approach to address both issues through the creation of OX40 ligand (OX40L)–specific chimeric antigen receptor (CAR)–T regs under the control of a synthetic forkhead box P3 ( FOXP3 ) promoter. The creation of these CAR-T regs enabled selective T reg stimulation by engagement of OX40L, a key activation antigen in alloimmunity, including both graft-versus-host disease and solid organ transplant rejection, and autoimmunity, including rheumatoid arthritis, systemic sclerosis, and systemic lupus erythematosus. We demonstrated that OX40L–CAR-T regs were robustly activated in the presence of OX40L-expressing cells, leading to up-regulation of T reg suppressive proteins without induction of proinflammatory cytokine production. Compared with control T regs , OX40L–CAR-T regs more potently suppressed alloreactive T cell proliferation in vitro and were directly inhibitory toward activated monocyte-derived dendritic cells (DCs). We identified trogocytosis as one of the central mechanisms by which these CAR-T regs effectively decrease extracellular display of OX40L, resulting in decreased DC stimulatory capacity. OX40L–CAR-T regs demonstrated an enhanced ability to control xenogeneic graft-versus-host disease compared with control T regs without abolishing the graft-versus-leukemia effect. These results suggest that OX40L–CAR-T regs may have wide applicability as a potent cellular therapy to control both allo- and autoimmune diseases.
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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 | 0.001 |
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".