Synergistic Engagement of an Ineffective Endogenous Anti-Tumor Immune Response and Induction of IFN-γ and Fas-Ligand-Dependent Tumor Eradication by Combined Administration of IL-18 and IL-2
Bibliographic record
Abstract
IFN-gamma is a critical component of the endogenous and many cytokine-induced antitumor immune responses. In this study we have shown that the combination of IL-18 and IL-2 (IL-18/IL-2) synergistically enhances IFN-gamma production both in vitro and in vivo, and synergizes in vivo to induce complete durable regression of well-established 3LL tumors in >80% of treated mice. We have observed a nascent, but ineffective, host immune response against 3LL that depends on endogenous IFN-gamma and IL-12 production and the Fas/Fas ligand (Fas-L) pathway. The combined administration of IL-18/IL-2 engages this endogenous response to induce tumor regression via a mechanism that is independent of NK and NKT cells or IL-12, but is critically dependent on CD8(+) T cells, IFN-gamma, and the Fas/Fas-L pathway. These studies demonstrate the importance of IFN-gamma as well as the Fas/Fas-L pathway in both endogenous and cytokine-driven antitumor immune responses engaged by IL-18/IL-2 and provide preclinical impetus for clinical investigation of this potent anti-tumor combination.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".