Oncolytic Virotherapy Synergism with Signaling Inhibitors: Rapamycin Increases Myxoma Virus Tropism for Human Tumor Cells
Bibliographic record
Abstract
Myxoma virus is a rabbit-specific poxvirus pathogen that also exhibits a unique tropism for human tumor cells and is dramatically oncolytic for human cancer xenografts. Most tumor cell lines tested are permissive for myxoma infection in a fashion intimately tied to the activation state of Akt kinase. A host range factor of myxoma virus, M-T5, directly interacts with Akt and mediates myxoma virus tumor cell tropism. mTOR is a regulator of cell growth and metabolism downstream of Akt and is specifically inhibited by rapamycin. We report that treatment of nonpermissive human tumor cell lines, which normally restrict myxoma virus replication, with rapamycin dramatically increased virus tropism and spread in vitro. This increased myxoma replication is concomitant with global effects on mTOR signaling, specifically, an increase in Akt kinase. In contrast to the effects on human cancer cells, rapamycin does not increase myxoma virus replication in rabbit cell lines or permissive human tumor cell lines with constitutively active Akt. This indicates that rapamycin increases the oncolytic capacity of myxoma virus for human cancer cells by reconfiguring the internal cell signaling environment to one that is optimal for productive virus replication and suggests the possibility of a potentially therapeutic synergism between kinase signaling inhibitors and oncolytic poxviruses for cancer treatment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".