Attenuating Regulatory T Cell Induction by TLR Agonists through Inhibition of p38 MAPK Signaling in Dendritic Cells Enhances Their Efficacy as Vaccine Adjuvants and Cancer Immunotherapeutics
Bibliographic record
Abstract
TLR ligands are potent adjuvants and promote Th1 responses to coadministered Ags by inducing innate IL-12 production. We found that TLR ligands also promote the induction of IL-10-secreting regulatory T (Treg) cells through p38 MAPK-induced IL-10 production by dendritic cells (DC). Inhibition of p38 suppressed TLR-induced IL-10 and PGE(2) and enhanced IL-12 production in DC. Incubation of Ag-pulsed CpG-stimulated DC with a p38 inhibitor suppressed their ability to generate Treg cells, while enhancing induction of Th1 cells. In addition, inhibition of p38 enhanced the antitumor therapeutic efficacy of DC pulsed with Ag and CpG and this was associated with an enhanced frequency of IFN-gamma-secreting T cells and a reduction of Foxp3(+) Treg cells infiltrating the tumors. Furthermore, addition of a p38 inhibitor to a pertussis vaccine formulated with CpG enhanced its protective efficacy in a murine respiratory challenge model. These data demonstrate that the adjuvant activity of TLR agonists is compromised by coinduction of Treg cells, but this can be overcome by inhibiting p38 signaling in DC. Our findings suggest that p38 is an important therapeutic target and provides a mechanism to enhance the efficacy of TLR agonists as vaccine adjuvants and cancer immunotherapeutics.
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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) | 0.000 | 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 | 0.001 |
| 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".