Integration of exogenous and endogenous co-stimulatory signals by CAR-Tregs
Bibliographic record
Abstract
ABSTRACT Regulatory T cells (Tregs) expressing chimeric antigen receptors (CAR) are a promising tool to promote transplant tolerance. The relationship between CAR structure and Treg function was studied in xenogeneic, immunodeficient mice, revealing advantages of CD28-encoding CARs. However, these models could underrepresent interactions between CAR-Tregs, antigen-presenting cells (APCs) and donor-specific antibodies. We generated mouse Tregs expressing HLA-A2-specific CARs with different costimulatory domains and compared their function in vitro and in vivo. In vitro assays revealed the CD28-encoding CAR had superior antigen-specific suppression, proliferation and cytokine production. In contrast, in vivo protection from skin allograft rejection and alloantibody production was similar between Tregs expressing CARs encoding CD28, ICOS or PD1, but not GITR, 41BB or OX40, co-stimulatory domains. To reconcile in vitro and in vivo data, we analyzed effects of a CAR encoding CD3ζ but no co-stimulatory domain. These data revealed that exogenous co-stimulation via APCs can compensate for the lack of a CAR-encoded CD28 domain. Thus, Tregs expressing a CAR with or without CD28 are functionally equivalent in vivo. This study reveals a new dimension of CAR-Treg biology and has important implications for the design of CARs for clinical use in Tregs.
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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) | 0.001 | 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".