Neoadjuvant oncolytic virotherapy before surgery sensitizes triple-negative breast cancer to immune checkpoint therapy
Bibliographic record
Abstract
Triple-negative breast cancer (TNBC) is an aggressive disease for which treatment options are limited and associated with severe toxicities. Immunotherapeutic approaches like immune checkpoint inhibitors (ICIs) are a potential strategy, but clinical trials have demonstrated limited success in this patient cohort. Clinical studies using ICIs have revealed that patients with preexisting anticancer immunity are the most responsive. Given that oncolytic viruses (OVs) induce antitumor immunity, we investigated their use as an ICI-sensitizing approach. Using a therapeutic model that mimics the course of treatment for women with newly diagnosed TNBC, we demonstrate that early OV treatment coupled with surgical resection provides long-term benefits. OV therapy sensitizes otherwise refractory TNBC to immune checkpoint blockade, preventing relapse in most of the treated animals. We suggest that OV therapy in combination with immune checkpoint blockade warrants testing as a neoadjuvant treatment option in the window of opportunity between TNBC diagnosis and surgical resection.
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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 | 0.000 | 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 | 0.001 |
| 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".