T-Cell Dysfunction as a Limitation of Adoptive Immunotherapy: Current Concepts and Mitigation Strategies
Bibliographic record
Abstract
Over the last decades, cellular immunotherapy has revealed its curative potential. However, inherent physiological characteristics of immune cells can limit the potency of this approach. Best defined in T cells, dysfunction associated with terminal differentiation, exhaustion, senescence, and activation-induced cell death, undermine adoptive cell therapies. In this review, we concentrate on how the multiple mechanisms that articulate the various forms of immune dysfunction impact cellular therapies primarily involving conventional T cells, but also other lymphoid subtypes. The repercussions of immune cell dysfunction across the full life cycle of cell therapy, from the source material, during manufacturing, and after adoptive transfer, are discussed, with an emphasis on strategies used during ex vivo manipulations to limit T-cell dysfunction. Applicable to cellular products prepared from native and unmodified immune cells, as well as genetically engineered therapeutics, the understanding and potential modulation of dysfunctional features are key to the development of improved cellular immunotherapies.
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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) | 0.001 | 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) | 0.001 | 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".