Antiangiogenic Arming of an Oncolytic Vaccinia Virus Enhances Antitumor Efficacy in Renal Cell Cancer Models
Bibliographic record
Abstract
Oncolytic vaccinia viruses have shown compelling results in preclinical cancer models and promising preliminary safety and antitumor activity in early clinical trials. However, to facilitate systemic application it would be useful to improve tumor targeting and antitumor efficacy further. Here we report the generation of vvdd-VEGFR-1-Ig, a targeted and armed oncolytic vaccinia virus. Tumor targeting was achieved by deletion of genes for thymidine kinase and vaccinia virus growth factor, which are necessary for replication in normal but not in cancer cells. Given the high vascularization typical of kidney cancers, we armed the virus with the soluble vascular endothelial growth factor (VEGF) receptor 1 protein for an antiangiogenic effect. Systemic application of high doses of vvdd-VEGFR-1-Ig resulted in cytokine induction in an immunocompromised mouse model. Upon histopathological analysis, splenic extramedullary hematopoiesis was seen in all virus-injected mice and was more pronounced in the vvdd-VEGFR-1-Ig group. Analysis of the innate immune response after intravenous virus injection revealed high transient and dose-dependent cytokine elevations. When medium and low doses were used for intratumoral or intravenous injection, vvdd-VEGFR-1-Ig exhibited a stronger antitumor effect than the unarmed control. Furthermore, expression of VEGFR-1-Ig was confirmed, and a concurrent antiangiogenic effect was seen. In an immunocompetent model, systemic vvdd-VEGFR-1-Ig exhibited superior antitumor efficacy compared to the unarmed control virus. In conclusion, the targeted and armed vvdd-VEGFR-1-Ig has promising anticancer activity in renal cell cancer models. Extramedullary hematopoiesis may be a sensitive indicator of vaccinia virus effects in mice.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".