A Fusion of GMCSF and IL-21 Initiates Hypersignaling Through the IL-21Rα Chain With Immune Activating and Tumoricidal Effects In Vivo
Bibliographic record
Abstract
We hypothesized that fusing granulocyte-macrophage colony-stimulation factor (GMCSF) and interleukin (IL)-21 as a single bifunctional cytokine (hereafter GIFT-21) would lead to synergistic anticancer immune effects because of their respective roles in mediating inflammation. Mechanistic analysis of GIFT-21 found that it leads to IL-21Ralpha-dependent STAT3 hyperactivation while also contemporaneously behaving as a dominant-negative inhibitor of GMCSF-driven STAT5 activation. GIFT-21's aberrant interactions with its cognate receptors on macrophages resulted in production of 30-fold greater amounts of IL-6, TNF-alpha, and MCP-1 when compared to controls. Furthermore, GIFT-21 treatment of primary B and T lymphocytes leads to STAT1-dependent apoptosis of IL-21Ralpha(+) lymphocytes. B16 melanoma cells gene-enhanced to produce GIFT-21 were immune rejected by syngeneic C57Bl/6 mice comparable to the effect of IL-21 alone. However, a significant GIFT-21-driven survival advantage was seen when NOD-SCID mice were implanted with GIFT-21-secreting B16 cells, consistent with a meaningful role of macrophages in tumor rejection. Because GIFT-21 leads to apoptosis of IL-21Ralpha(+) lymphocytes, we tested its cytolytic effect on IL-21Ralpha(+) EL-4 lymphoma tumors implanted in C57Bl/6 mice and could demonstrate a significant increase in survival. These data indicate that GIFT-21 is a novel IL-21Ralpha agonist that co-opts IL-21Ralpha-dependent signaling in a manner permissive for targeted cancer immunotherapy.
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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 | 0.000 |
| 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".