IL-15 Can Signal via IL-15Rα, JNK, and NF-κB To Drive RANTES Production by Myeloid Cells
Bibliographic record
Abstract
IL-15 plays many important roles within the immune system. IL-15 signals in lymphocytes via trans presentation, where accessory cells such as macrophages and dendritic cells present IL-15 bound to IL-15Rα in trans to NK cells and CD8(+) memory T cells expressing IL-15/IL-2Rβ and common γ chain (γ(c)). Previously, we showed that the prophylactic delivery of IL-15 to Rag2(-/-)γ(c)(-/-) mice (mature T, B, and NK cell negative) afforded protection against a lethal HSV-2 challenge and metastasis of B16/F10 melanoma cells. In this study, we demonstrated that in vivo delivery of an adenoviral construct optimized for the secretion of human IL-15 to Rag2(-/-)γ(c)(-/-) mice resulted in significant increases in spleen size and cell number, leading us to hypothesize that IL-15 signals differently in myeloid immune cells compared with lymphocytes, for which IL-15/IL-2Rβ and γ(c) expression are essential. Furthermore, treatment with IL-15 induced RANTES production by Rag2(-/-)γ(c)(-/-) bone marrow cells, but the presence of γ(c) did not increase bone marrow cell sensitivity to IL-15. This IL-15-mediated RANTES production by Rag2(-/-)γ(c)(-/-) bone marrow cells occurred independently of the IL-15/IL-2Rβ and Jak/STAT pathways and instead required IL-15Rα signaling as well as activation of JNK and NF-κB. Importantly, we also showed that the trans presentation of IL-15 by IL-15Rα boosts IL-15-mediated IFN-γ production by NK cells but reduces IL-15-mediated RANTES production by Rag2(-/-)γ(c)(-/-) myeloid bone marrow cells. Our data clearly show that IL-15 signaling in NK cells is different from that of myeloid immune cells. Additional insights into IL-15 biology may lead to novel therapies aimed at bolstering targeted immune responses against cancer and infectious disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".