Preclinical assessment of antigen-specific chimeric antigen receptor regulatory T cells for use in solid organ transplantation
Why this work is in the frame
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Bibliographic record
Abstract
A primary goal in transplantation medicine is the induction of a tolerogenic environment for prevention of transplant rejection without the need for long-term pharmacological immunosuppression. Generation of alloantigen-specific regulatory T cells (Tregs) by transduction with chimeric antigen receptors (CARs) is a promising strategy to achieve this goal. This publication reports the preclinical characterization of Tregs (TR101) transduced with a human leukocyte antigen (HLA)-A*02 CAR lentiviral vector (TX200) designated to induce immunosuppression of allograft-specific effector T cells in HLA-A*02-negative recipients of HLA-A*02-positive transplants. In vitro results demonstrated specificity, immunosuppressive function, and safety of TX200-TR101. In NOD scid gamma (NSG) mice, TX200-TR101 prevented graft-versus-host disease (GvHD) in a xenogeneic GvHD model and TX200-TR101 Tregs localized to human HLA-A*02-positive skin transplants in a transplant model. TX200-TR101 persisted over the entire duration of a 3-month study in humanized HLA-A*02 NSG mice and remained stable, without switching to a proinflammatory phenotype. Concomitant tacrolimus did not impair TX200-TR101 Treg survival or their ability to inhibit peripheral blood mononuclear cell (PBMC) engraftment. These data demonstrate that TX200-TR101 is specific, stable, efficacious, and safe in preclinical models, and provide the basis for a first-in-human study.
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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 | 0.001 | 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) | 0.004 | 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