Combining vanadyl sulfate with Newcastle disease virus potentiates rapid innate immune-mediated regression with curative potential in murine cancer models
Bibliographic record
Abstract
The avian paramyxovirus, Newcastle disease virus (NDV), is a promising oncolytic agent that has been shown to be safe and effective in a variety of pre-clinical cancer models and human clinical trials. NDV preferentially replicates in tumor cells due to signaling defects in apoptotic and antiviral pathways acquired during the transformation process and is a potent immunostimulatory agent. However, when used as a monotherapy NDV lacks the ability to consistently generate durable remissions. Here we investigate the use of viral sensitizer-mediated combination therapy to enhance the anti-neoplastic efficacy of NDV. Intratumoral injection of vanadyl sulfate, a pan-inhibitor of protein tyrosine phosphatases, in combination with NDV significantly increased the number and activation status of natural killer (NK) cells in the tumor microenvironment, concomitant with increased expression of interferon-β, granulocyte-macrophage colony-stimulating factor, and monocyte chemoattractant protein-1, leading to rapid tumor regression and long-term cures in mice bearing syngeneic B16-F10 melanomas. The anti-tumor efficacy of this combination therapy was abrogated when NK cells were depleted and when interferon-β expression was transiently suppressed. Tumor-specific CD8 + T cell responses were not detected, nor were mice whose tumors regressed protected from re-challenge. This suggested efficacy of the combination therapy predominantly relied on the innate immune system. Importantly, efficacy was not limited to melanoma; it was also demonstrated in a murine prostate cancer model. Taken together, these results suggest that combining NDV with vanadyl sulfate potentiates an innate immune response that can potentiate rapid clearance of tumors, with type I interferon signaling and NK cells being important mechanisms of action.
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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 | 0.001 |
| 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".