Targeting regulatory T cell metabolism in disease: Novel therapeutic opportunities
Bibliographic record
Abstract
Regulatory T cells (Tregs) are essential for immune homeostasis and suppression of pathological autoimmunity but can also play a detrimental role in cancer progression via inhibition of anti-tumor immunity. Thus, there is broad applicability for therapeutic Treg targeting, either to enhance function, for example, through adoptive cell therapy (ACT), or to inhibit function with small molecules or antibody-mediated blockade. For both of these strategies, the metabolic state of Tregs is an important consideration since cellular metabolism is intricately linked to function. Mounting evidence has shown that targeting metabolic pathways can selectively promote or inhibit Treg function. This review aims to synthesize the current understanding of Treg metabolism and discuss emerging metabolic targeting strategies in the contexts of transplantation, autoimmunity, and cancer. We discuss approaches to gene editing and cell culture to manipulate Treg metabolism during ex vivo expansion for ACT, as well as in vivo nutritional and pharmacological interventions to modulate Treg metabolism in disease states. Overall, the intricate connection between metabolism and phenotype presents a powerful opportunity to therapeutically tune Treg function.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".