A Functional GM-CSF Receptor on Dendritic Cells Is Required for Efficient Protective Anti-Tumor Immunity
Bibliographic record
Abstract
Dendritic cells (DC) play a major role during the priming phase of anti-tumor immunization, as they are required for an efficient tumor-associated antigens presentation. At least one dendritic cell-based therapy has already been successfully approved by regulators for clinical application in prostate cancer patients. Moreover, DC development is dependent on the granulocyte macrophage colony stimulating factor (GM-CSF), a cytokine that has been successfully used as a potent inducer of anti-tumoral immunity. To better understand the relation between DC and GM-CSF in anti-tumor immunity, we studied the DC function in mice lacking the cytokine receptor common subunit beta (βc-/-) for GM-CSF, IL-3 and IL-5 and immunized with irradiated tumor cells. Such immunization induces a protective, specific tumor immunization in wild-type mice, while βc-/- mice failed to mount an immune response. Upon in vitro stimulation, DC from βc-/- mice (DCβc-/-) are unable to undergo a full maturation level. In vivo experiments show that they lack the ability to prevent tumor growth, in contrast to DCWT. Moreover, matured DCWT rescued immunization in βc-/- mice. DC maturation is dependent on a functional pathway involving GM-CSF signaling through a biologically functional receptor. These findings may contribute to new strategies for efficient anti-tumor immunotherapies.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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; both teacher heads agree on what is shown here.
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".