Pre-surgical neoadjuvant oncolytic virotherapy confers protection against rechallenge in a murine model of breast cancer
Bibliographic record
Abstract
The use of oncolytic viruses (OVs) for cancer treatment is emerging as a successful strategy that combines the direct, targeted killing of the cancer with the induction of a long-lasting anti-tumor immune response. Using multiple aggressive murine models of triple-negative breast cancer, we have recently demonstrated that the early administration of oncolytic Maraba virus (MRB) prior to surgical resection of the primary tumor is sufficient to minimize the metastatic burden, protect against tumor rechallenge, cure a fraction of the mice and sensitize refractory tumors to immune checkpoint blockade without the need for further treatment. Here, we apply our surgical model to other OVs: Vesicular stomatitis virus (VSV), Adenovirus (Ad), Reovirus (Reo) and Herpes simplex virus (HSV) and show that all of the tested OVs could positively change the outcome of the treated animals. The growth of the primary and secondary tumors was differently affected by the various OVs and most of the viruses conferred survival benefits in this neoadjuvant setting despite the absence of direct treatment following rechallenge. This study establishes that OV-therapy confers long-term protection when administered in the pre-operative window of opportunity.
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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".