Mast cells as targets for immunotherapy of solid tumors
Bibliographic record
Abstract
Mast cells have historically been studied mainly in the context of allergic disease. In recent years, we have come to understand the critical importance of mast cells in tissue remodeling events and their role as sentinel cells in the induction and development of effective immune responses to infection. Studies of the role of mast cells in tumor immunity are more limited. The pro-tumorigenic role of mast cells has been widely reported. However, mast cell infiltration predicts improved prognosis in some cancers, suggesting that their prognostic value may be dependent on other variables. Such factors may include the nature of local mast cell subsets and the various activation stimuli present within the tumor microenvironment. Experimental models have highlighted the importance of mast cells in orchestrating the anti-tumor events that follow immunotherapies that target innate immunity. Mast cells are long-lived tissue resident cells that are abundant around many solid tumors and are radiation resistant making them unique candidates for combined treatment modalities. This review will examine some of the key roles of mast cells in tumor immunity, with a focus on potential immunotherapeutic interventions that harness the sentinel role 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".