Type I IFN signaling on dendritic cells is required for NK cell-mediated anti-tumor immunity
Bibliographic record
Abstract
NK cells play a vital role in innate anti-tumor immunity. Crosstalk between NK cells and dendritic cells (DCs) has come to the forefront in protection against tumors in the context of DC vaccines. We previously discovered that NK cell activation mediates the anti-tumor activity elicited by DC vaccines in response to melanoma tumor challenge in a murine lung metastasis model. In this study, we sought to explore the mechanism behind this NK-DC communication, specifically looking at the involvement of IL-15 and type I IFN signaling. Using DCs from IL-15(-/-) and IL-15Rα(-/-) mice, we found that the anti-tumor effect of the vaccine remained comparable with DCs from wild type mice. Moreover, DCs derived from IFN-α/βR(-/-) mice also maintained their anti-tumor effect. Interestingly, endogenous DCs were found to accumulate in the draining lymph nodes post-immunization and their depletion abolished the anti-tumor effect of the vaccine. Our findings suggest the important role that type I IFN signaling and endogenous DCs play in DC vaccine-mediated anti-tumor protection. Our data suggest that type I IFNs from vaccine DCs activate host DCs to provide NK cell-mediated anti-tumor immunity.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".