IL-28 Elicits Antitumor Responses against Murine Fibrosarcoma
Bibliographic record
Abstract
IL-28 is a recently described antiviral cytokine. In this study, we investigated the biological effects of IL-28 on tumor growth to evaluate its antitumor activity. IL-28 or retroviral transduction of the IL-28 gene into MCA205 cells did not affect in vitro growth, whereas in vivo growth of MCA205IL-28 was markedly suppressed along with survival advantages when compared with that of controls. When the metastatic ability of IL-28-secreting MCA205 cells was compared with that of controls, the expression of IL-28 resulted in a potent inhibition of metastases formation in the lungs. IL-28-mediated suppression of tumor growth was mostly abolished in irradiated mice, indicating that irradiation-sensitive cells, presumably immune cells, are primarily involved in the IL-28-induced suppression of tumor growth. In vivo cell depletion experiments displayed that polymorphonuclear neutrophils, NK cells, and CD8 T cells, but not CD4 T cells, play an equal role in the IL-28-mediated inhibition of in vivo tumor growth. Consistent with these findings, inoculation of MCA205IL-28 into mice evoked enhanced IFN-gamma production and cytotoxic T cell activity in spleen cells. Antitumor action of IL-28 is partially dependent on IFN-gamma and is independent of IL-12, IL-17, and IL-23. IL-28 increased the total number of splenic NK cells in SCID mice and enhanced IL-12-induced IFN-gamma production in vivo and expanded spleen cells in C57BL/6 mice. Moreover, IL-12 augmented IL-28-mediated antitumor activity in the presence or absence of IFN-gamma. These findings indicate that IL-28 has bioactivities that induce innate and adaptive immune responses against tumors.
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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".