Exogenous IL-33 overcomes T cell tolerance in acute myeloid leukemia
Bibliographic record
Abstract
Abstract Leukemic cells can be recognized and attacked by the immune system. However, emerging studies suggest that dominant peripheral tolerance is a major mechanism of immune escape in disseminated leukemia. Therefore, novel strategies are needed to overcome the tolerance and restore the anti-leukemia T cell function for both leukemia clearance and relapse prevention. Using an established murine acute myeloid leukemia (AML) model, we have demonstrated that systemic administration of recombinant IL-33 dramatically inhibits leukemia relapse and prolongs the survival of leukemia-bearing mice in a CD8+ T cell dependent manner. Exogenous IL-33 treatment enhanced anti-leukemia activity by increasing the expansion and IFN- g production of leukemia-reactive CD8+ T cells. Moreover, IL-33 induced dendritic cell (DC) maturation and activation in favor of its cross presentation ability to evoke a vigorous anti-leukemia immune response. Finally we found that the combination of PD-1 blockade with IL-33 further prolonged the survival with half of the mice achieving complete regression. Our data establish a role of exogenous IL-33 in reversing T cell tolerance and suggest its potential clinical implication into leukemia immunotherapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".