IL-21 Activates Both Innate and Adaptive Immunity to Generate Potent Antitumor Responses that Require Perforin but Are Independent of IFN-γ
Bibliographic record
Abstract
IL-21 is a key factor in the transition between innate and adaptive immune responses. We have used the cytokine gene therapy approach to study the antitumor responses mediated by IL-21 in the B16F1 melanoma and MethA fibrosarcoma tumor models in mice. Retrovirally transduced tumor cells secreting biologically functional IL-21 have growth patterns in vitro similar to that of control green fluorescent protein-transduced cells, but are completely rejected in vivo. We show that IL-21 activates NK and CD8(+) T cells in vivo, thus mediating complete rejection of poorly immunogenic tumors. Rejection of IL-21-secreting tumors requires the presence of cognate IL-21R and does not depend on CD4(+) T cell help. Interestingly, perforin, but not IFN-gamma or other major Th1 and Th2 cytokines (IL-12, IL-4, or IL-10), is required for the IL-21-mediated antitumor response. Moreover, IL-21 results in 50% protection and 70% cure of nonimmunogenic tumors when given before and after tumor challenge, respectively, in C57BL/6 mice. We conclude that IL-21 immunotherapy warrants clinical evaluation as a potential treatment for cancer.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".