Oncolytic Reovirus and Immune Checkpoint Inhibition as a Novel Immunotherapeutic Strategy for Breast Cancer
Bibliographic record
Abstract
As the current efficacy of oncolytic viruses (OVs) as monotherapy is limited, exploration of OVs as part of a broader immunotherapeutic treatment strategy for cancer is necessary. Here, we investigated the ability for immune checkpoint blockade to enhance the efficacy of oncolytic reovirus (RV) for the treatment of breast cancer (BrCa). In vitro, oncolysis and cytokine production were assessed in human and murine BrCa cell lines following RV exposure. Furthermore, RV-induced upregulation of tumor cell PD-L1 was evaluated. In vivo, the immunocompetent, syngeneic EMT6 murine model of BrCa was employed to determine therapeutic and tumor-specific immune responses following treatment with RV, anti-PD-1 antibodies or in combination. RV-mediated oncolysis and cytokine production were observed following BrCa cell infection and RV upregulated tumor cell expression of PD-L1. In vivo, RV monotherapy significantly reduced disease burden and enhanced survival in treated mice, and was further enhanced by PD-1 blockade. RV therapy increased the number of intratumoral regulatory T cells, which was reversed by the addition of PD-1 blockade. Finally, dual treatment led to the generation of a systemic adaptive anti-tumor immune response evidenced by an increase in tumor-specific IFN-γ producing CD8⁺ T cells, and immunity from tumor re-challenge. The combination of PD-1 blockade and RV appears to be an efficacious immunotherapeutic strategy for the treatment of BrCa, and warrants further investigation in early-phase clinical trials.
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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 | 0.000 | 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 | 0.000 |
| 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".