CAR Treg synergy with anti-CD154 promotes infectious tolerance and dictates allogeneic heart transplant acceptance
Bibliographic record
Abstract
Successful allograft-specific tolerance induction would eliminate the need for daily immunosuppression and improve posttransplant quality of life. Adoptive cell therapy with regulatory T cells expressing donor-specific chimeric antigen receptors (CAR Tregs) is a promising strategy but, as monotherapy, cannot prolong survival with allografts with multiple MHC mismatches. Using an HLA-A2-transgenic haplo-mismatched heart transplantation model in immunocompetent C57BL/6 recipients, we showed that HLA-A2-specific CAR (A2.CAR) Tregs were able to synergize with a low dose of anti-CD154 to enhance graft survival. Using haplo-mismatched grafts expressing the 2W-OVA transgene and tetramer-based tracking of 2W- and OVA-specific T cells, we showed that in mice with accepted grafts, A2.CAR Tregs inhibited donor-specific T cell, B cell, and antibody responses and promoted a substantial increase in endogenous FOXP3+ Tregs with indirect donor specificity. By contrast, in mice where A2.CAR Tregs failed to prolong graft survival, FOXP3- A2.CAR T cells preferentially accumulated in rejecting allografts, and endogenous donor-specific responses were not controlled. This study therefore provides evidence for synergy between A2.CAR Tregs and CD154 blockade to promote infectious tolerance in immunocompetent recipients of haplo-mismatched heart grafts and defines features of A2.CAR Tregs when they fail to reshape host immunity toward allograft tolerance.
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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".