Tonic-signaling chimeric antigen receptors drive human regulatory T cell exhaustion
Bibliographic record
Abstract
Regulatory T cell (Treg) therapy is a promising approach to improve outcomes in transplantation and autoimmunity. In conventional T cell therapy, chronic stimulation can result in poor in vivo function, a phenomenon termed exhaustion. Whether or not Tregs are also susceptible to exhaustion, and if so, if this would limit their therapeutic effect, was unknown. To “benchmark” exhaustion in human Tregs, we used a method known to induce exhaustion in conventional T cells: expression of a tonic-signaling chimeric antigen receptor (TS-CAR). We found that TS-CAR-expressing Tregs rapidly acquired a phenotype that resembled exhaustion and had major changes in their transcriptome, metabolism, and epigenome. Similar to conventional T cells, TS-CAR Tregs upregulated expression of inhibitory receptors and transcription factors such as PD-1, TIM3, TOX and BLIMP1, and displayed a global increase in chromatin accessibility-enriched AP-1 family transcription factor binding sites. However, they also displayed Treg-specific changes such as high expression of 4-1BB, LAP, and GARP. DNA methylation analysis and comparison to a CD8 + T cell-based multipotency index showed that Tregs naturally exist in a relatively differentiated state, with further TS-CAR-induced changes. Functionally, TS-CAR Tregs remained stable and suppressive in vitro but were nonfunctional in vivo, as tested in a model of xenogeneic graft-versus-host disease. These data are the first comprehensive investigation of exhaustion in Tregs and reveal key similarities and differences with exhausted conventional T cells. The finding that human Tregs are susceptible to chronic stimulation–driven dysfunction has important implications for the design of CAR Treg adoptive immunotherapy strategies.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".