Interleukin-15 in cancer immunotherapy: IL-15 receptor complex versus soluble IL-15 in a cancer cell-delivered murine leukemia model
Bibliographic record
Abstract
Abstract Cancer immunotherapy endeavors to stimulate the immune system in order to recognize, reject and destroy tumor cells. Previously we have demonstrated that IL-12 is an ideal candidate for leukemia immunotherapy and there is a Phase 1 human trial underway at the Princess Margaret Cancer Center to test this approach in AML patients. In order to further our knowledge on immunomodulators we have expanded our studies to other cytokines such as IL-15. IL-15, either in its soluble form (IL-15sol) or complexed with IL-15Ra (IL-15Rc), has been shown to exhibit potent anti-tumor activities in various cancer studies. In this study we describe the impact of intraperitoneal IL-15 in a cancer cell delivered IL-15 immunotherapy approach using the 70Z/3-L leukemia mouse model. Whereas both forms of IL-15 led to significantly improved survival rates compared to the parent cell line, there were striking differences in the extent of the improved survival: mice receiving cancer cells secreting IL-15sol showed near 100% survival for up to 250 days, whereas mice receiving cancer cells secreting IL-15Rc started to perish around day 50 post-injection, with few survivors left on day 250. Interestingly, cell-secreted IL-15sol and IL-15Rc activated different cell types in the peritoneum, leading to different immune responses. IL-15Rc resulted in an influx and/or expansion of NK1.1+ natural killer cells in the peritoneum, while injection of cells secreting IL-15sol lead to an increased expansion of CD4+ and CD8+ T-cells. To our knowledge, this is the first study detailing a significantly different biological effect of cell-delivered IL-15Rc vs IL-15sol in a mouse cancer immunotherapy study, suggesting a different mechanism of action of the two IL-15 forms.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".