PTEN is required for human Treg suppression of costimulation in vitro
Bibliographic record
Abstract
Regulatory T-cell (Treg) therapy is under clinical investigation for the treatment of transplant rejection, autoimmune disease, and graft-versus-host disease. With the advent of genome editing, attention has turned to reinforcing Treg function for therapeutic benefit. A hallmark of Tregs is dampened activation of PI3K-AKT signaling, of which PTEN is a major negative regulator. Loss-of-function studies of PTEN, however, have not conclusively shown a requirement for PTEN in upholding Treg function and stability. Using CRISPR-based genome editing in human Tregs, we show that PTEN ablation does not cause a global defect in Treg function and stability; rather, it selectively blocks their ability to suppress antigen-presenting cells. PTEN-KO Tregs exhibit elevated glycolytic activity, upregulate FOXP3, maintain a Treg phenotype, and have no discernible defects in lineage stability. Functionally, PTEN is dispensable for human Treg-mediated inhibition of T-cell activity in vitro and in vivo but is required for suppression of costimulatory molecule expression by antigen-presenting cells. These data are the first to define a role for a signaling pathway in controlling a subset of human Treg activity. Moreover, they point to the functional necessity of PTEN-regulated PI3K-AKT activity for optimal human Treg function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".