Deletion of Apoptosis Inhibitor F1L in Vaccinia Virus Increases Safety and Oncolysis for Cancer Therapy
Bibliographic record
Abstract
Vaccinia virus (VACV) possesses a great safety record as a smallpox vaccine and has been intensively used as an oncolytic virus against various types of cancer over the past decade. Different strategies were developed to make VACV safe and selective to cancer cells. Leading clinical candidates, such as Pexa-Vec, are attenuated through deletion of the viral thymidine kinase (TK) gene, which limits virus growth to replicate in cancer tissue. However, tumors are not the only tissues whose metabolic activity can overcome the lack of viral TK. In this study, we sought to further increase the tumor-specific replication and oncolytic potential of Copenhagen strain VACV ΔTK. We show that deletion of the anti-apoptosis viral gene F1L not only increases the safety of the Copenhagen ΔTK virus but also improves its oncolytic activity in an aggressive glioblastoma model. The additional loss of F1L does not affect VACV replication capacity, yet its ability to induce cancer cell death is significantly increased. Our results also indicate that cell death induced by the Copenhagen ΔTK/F1L mutant releases more immunogenic signals, as indicated by increased levels of IL-1β production. A cytotoxicity screen in an NCI-60 panel shows that the ΔTK/F1L virus induces faster tumor cell death in different cancer types. Most importantly, we show that, compared to the TK-deleted virus, the ΔTK/F1L virus is attenuated in human normal cells and causes fewer pox lesions in murine models. Collectively, our findings describe a new oncolytic vaccinia deletion strain that improves safety and increases tumor cell killing.
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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".