UV-inactivated HSV-1 potently activates NK cell killing of leukemic cells
Bibliographic record
Abstract
Herein we demonstrate that oncolytic herpes simplex virus-1 (HSV-1) potently activates human peripheral blood mononuclear cells (PBMCs) to lyse leukemic cell lines and primary acute myeloid leukemia samples, but not healthy allogeneic lymphocytes. Intriguingly, we found that UV light-inactivated HSV-1 (UV-HSV-1) is equally effective in promoting PBMC cytolysis of leukemic cells and is 1000- to 10 000-fold more potent at stimulating innate antileukemic responses than UV-inactivated cytomegalovirus, vesicular stomatitis virus, reovirus, or adenovirus. Mechanistically, UV-HSV-1 stimulates PBMC cytolysis of leukemic cells, partly via Toll-like receptor-2/protein kinase C/nuclear factor-κB signaling, and potently stimulates expression of CD69, degranulation, migration, and cytokine production in natural killer (NK) cells, suggesting that surface components of UV-HSV-1 directly activate NK cells. Importantly, UV-HSV-1 synergizes with interleukin-15 (IL-15) and IL-2 in inducing activation and cytolytic activity of NK cells. Additionally, UV-HSV-1 stimulates glycolysis and fatty acid oxidation-dependent oxygen consumption in NK cells, but only glycolysis is required for their enhanced antileukemic activity. Last, we demonstrate that T cell-depleted human PBMCs exposed to UV-HSV-1 provide a survival benefit in a murine xenograft model of human acute myeloid leukemia (AML). Taken together, our results support the preclinical development of UV-HSV-1 as an adjuvant, alone or in combination with IL-15, for allogeneic donor mononuclear cell infusions to treat AML.
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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) | 0.002 | 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".