A Critical Role for Mast Cells and Mast Cell-Derived IL-6 in TLR2-Mediated Inhibition of Tumor Growth
Bibliographic record
Abstract
Several TLR agonists are effective in tumor immunotherapy, but their early innate mechanisms of action, particularly those of TLR2 agonists, are unclear. Mast cells are abundant surrounding solid tumors where they are often protumorigenic and enhance tumor angiogenesis. However, antitumor roles for mast cells have also been documented. The impact of mast cells may be dependent on their activation status and mediator release in different tumors. Using an orthotopic melanoma model in wild-type C57BL/6 and mast cell-deficient Kit(W-sh/W-sh) mice and a complementary Matrigel-tumor model in C57BL/6 mice, mast cells were shown to be crucial for TLR2 agonist (Pam(3)CSK(4))-induced tumor inhibition. Activation of TLR2 on mast cells reversed their well-documented protumorigenic role. Tumor growth inhibition after peritumoral administration of Pam(3)CSK(4) was restored in Kit(W-sh/W-sh) mice by local reconstitution with wild-type, but not TLR2-deficient, mast cells. Mast cells secrete multiple mediators after Pam(3)CSK(4) activation, and in vivo mast cell reconstitution studies also revealed that tumor growth inhibition required mast cell-derived IL-6, but not TNF. Mast cell-mediated anticancer properties were multifaceted. Direct antitumor effects in vitro and decreased angiogenesis and recruitment of NK and T cells in vivo were observed. TLR2-activated mast cells also inhibited the growth of lung cancer cells in vivo. Unlike other immune cells, mast cells are relatively radioresistant making them attractive candidates for combined treatment modalities. This study has important implications for the design of immunotherapeutic strategies and reveals, to our knowledge, a novel mechanism of action for TLR2 agonists in vivo.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".