Oncolytic reovirus therapy: Pilot study in dogs with spontaneously occurring tumours
Bibliographic record
Abstract
Oncolytic virotherapy is a novel treatment involving replication‐competent virus in the elimination of cancer. We have previously reported the oncolytic effects of reovirus in various canine cancer cell lines. This study aims to establish the safety profile of reovirus in dogs with spontaneously occurring tumours and to determine a recommended dosing regimen. Nineteen dogs with various tumours, mostly of advanced stages, were treated with reovirus, ranging from 1.0 × 108 to 5.0 × 109 TCID50 given as intratumour injection (IT) or intravenous infusion (IV) daily for up to 5 consecutive days in 1 or multiple treatment cycles. Adverse events (AEs) were graded according to the Veterinary Cooperative Oncology Group‐ Common Terminology Criteria for Adverse Events (VCOG‐CTCAE) v1.1 guidelines. Viral shedding, neutralizing anti‐reovirus antibody (NARA) production and immunohistochemical (IHC) detection of reovirus protein in the tumours were also assessed. AE was not observed in most dogs and events were limited to Grade I or II fever, vomiting, diarrhoea and inflammation of the injected tumour. No infectious virus was shed and all dogs had elevated NARA levels post‐treatment. Although IHC results were only available in 6 dogs, 4 were detected positive for reovirus protein. In conclusion, reovirus is well‐tolerated and can be given safely to tumour‐bearing dogs according to the dosing regimen used in this study without significant concerns of viral shedding. Reovirus is also potentially effective in various types of canine tumours.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".