Engineering therapeutic T cells to suppress alloimmune responses using TCRs, CARs, or BARs
Bibliographic record
Abstract
Adoptive cell therapy with therapeutic T cells has become one of the most promising strategies to stimulate or suppress immune responses. Using virus-mediated genetic manipulation, the antigen specificity of T cells can now be precisely redirected. Tailored specificity has not only overcome technical limitations and safety concerns but also considerably broadened the spectrum of therapeutic applications. Different T cell–engineering strategies have now become available to suppress alloimmune responses. We first provide an overview of the allorecognition pathways and effector mechanisms that are responsible for alloimmune injuries in the setting of vascularized organ transplantation. We then discuss the potential to use different T cell–engineering approaches to suppress alloimmune responses. Specifically, expression of allospecific T cell receptors, single-chain chimeric antigen receptors, or antigen domains recognized by B cell receptors (B cell antibody receptors) in regulatory or cytotoxic T cells are considered. The ability of these strategies to control the direct or indirect pathways of allorecognition and the cellular or humoral alloimmune responses is discussed. An intimate understanding of the complex interplay that occurs between the engineered T cells and the alloimmune players is a necessary prerequisite for the design of safe and successful strategies for precise immunomodulation in transplantation. Adoptive cell therapy with therapeutic T cells has become one of the most promising strategies to stimulate or suppress immune responses. Using virus-mediated genetic manipulation, the antigen specificity of T cells can now be precisely redirected. Tailored specificity has not only overcome technical limitations and safety concerns but also considerably broadened the spectrum of therapeutic applications. Different T cell–engineering strategies have now become available to suppress alloimmune responses. We first provide an overview of the allorecognition pathways and effector mechanisms that are responsible for alloimmune injuries in the setting of vascularized organ transplantation. We then discuss the potential to use different T cell–engineering approaches to suppress alloimmune responses. Specifically, expression of allospecific T cell receptors, single-chain chimeric antigen receptors, or antigen domains recognized by B cell receptors (B cell antibody receptors) in regulatory or cytotoxic T cells are considered. The ability of these strategies to control the direct or indirect pathways of allorecognition and the cellular or humoral alloimmune responses is discussed. An intimate understanding of the complex interplay that occurs between the engineered T cells and the alloimmune players is a necessary prerequisite for the design of safe and successful strategies for precise immunomodulation in transplantation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".