A critical role for mast cells in TLR2-mediated inhibition of tumor growth <i>in vivo</i> (101.24)
Bibliographic record
Abstract
Abstract Mast cells are abundant surrounding solid tumors where they typically promote angiogenesis and enhance tumor growth and metastasis. In the context of infection, mast cells respond to pathogens via innate immune receptors, including TLR, to produce mediators which aid host defense and cell recruitment. Some TLR agonists are effective in tumor immunotherapy but the role of mast cells in their mechanism of action is unclear. Using a melanoma model in wild-type C57BL/6 and mast cell deficient KitW-sh/W-sh mice, mast cells were shown to be crucial for TLR2-agonist (Pam3CSK4) induced tumor growth inhibition. Activation of TLR2 on mast cells reversed their established pro-tumorigenic role. The tumor inhibitory effects of Pam3CSK4 were restored in KitW-sh/W-sh mice by local reconstitution with wild-type, but not TLR2-deficient mast cells. Tumor growth inhibition occurred independent of mast cell derived TNF and tumor cytotoxicity but was associated with angiogenesis suppression and NK and T cell recruitment. The mast cell mediated, tumor inhibitory effects of Pam3CSK4 were also observed in an LLC1 lung cancer model. This study reveals a novel mechanism of action for TLR2 agonists in vivo and has important implications for the design of immunotherapeutic strategies harnessing the innate immune functions of mast cells.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".