Activation of p53 by Chemotherapeutic Agents Enhances Reovirus Oncolysis
Bibliographic record
Abstract
Mammalian reovirus is a benign virus that possesses the natural ability to preferentially infect and kill cancer cells (reovirus oncolysis). Reovirus exploits aberrant Ras signalling in many human cancers to promote its own replication and spread. In vitro and in vivo studies using reovirus either singly or in combination with anti-cancer drugs have shown very encouraging results. Presently, a number of reovirus combination therapies are undergoing clinical trials for a variety of cancers. Previously we showed that accumulation of the tumor suppressor protein p53 by Nutlin-3a (a specific p53 stabilizer) enhanced reovirus-induced apoptosis, and resulted in significantly higher levels of reovirus dissemination. In this study, we examined the role of p53 in combination therapies involving reovirus and chemotherapeutic drugs. We showed that sub-lethal concentrations of traditional chemotherapy drugs actinomycin D or etoposide, but not doxorubicin, enhanced reovirus-induced apoptosis in a p53-dependent manner. Furthermore, NF-κB activation and expression of p53-target genes (p21 and bax) were important for the p53-dependent enhancement of cell death. Our results show that p53 status affects the efficacy of combination therapy involving reovirus. Choosing the right combination partner for reovirus and a low dosage of the drug may help to both enhance reovirus-induced cancer elimination and reduce drug toxicity.
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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) | 0.001 | 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 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".