Reovirus Oncolysis of Human Breast Cancer
Bibliographic record
Abstract
We have previously shown that human reovirus replication is restricted to cells with an activated Ras pathway, and that reovirus could be used as an effective oncolytic agent against human glioblastoma xenografts. This study examines in more detail the feasibility of reovirus as a therapeutic for breast cancer, a subset of cancer in which direct activating mutations in the ras proto-oncogene are rare, and yet where unregulated stimulation of Ras signaling pathways is important in the pathogenesis of the disease. We demonstrate herein the efficient lysis of breast tumor-derived cell lines by the virus, whereas normal breast cells resist infection in vitro. In vivo studies of reovirus breast cancer therapy reveal that viral administration could cause tumor regression in an MDA-MB-435S mammary fat pad model in severe combined immunodeficient mice. Reovirus could also effect regression of tumors remote from the injection site in an MDA-MB-468 bilateral tumor model, raising the possibility of systemic therapy of breast cancer by the oncolytic agent. Finally, the ability of reovirus to act against primary breast tumor samples not propagated as cell lines was evaluated; we found that reovirus could indeed replicate in ex vivo surgical specimens. Overall, reovirus shows promise as a potential breast cancer therapeutic.
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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 | 0.000 |
| 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".