Ras Transformation Mediates Reovirus Oncolysis by Enhancing Virus Uncoating, Particle Infectivity, and Apoptosis-dependent Release
Bibliographic record
Abstract
Reovirus, a potential cancer therapy, replicates more efficiently in Ras-transformed cells than in non-transformed cells. It was presumed that increased translation was the mechanistic basis of reovirus oncolysis. Analyses of each step of the reovirus life cycle now show that cellular processes deregulated by Ras transformation promote not one but three viral replication steps. First, in Ras-transformed cells, proteolytic disassembly (uncoating) of the incoming virions, required for onset of infection, occurs more efficiently. Consequently, threefold more Ras-transformed cells become productively infected with reovirus than non-transformed cells, which accounts for the observed increase of reovirus proteins in Ras-transformed cells. Second, Ras transformation increases the infectious-to-noninfectious virus particle ratio, as virions purified from Ras-transformed cells are fourfold more infectious than those purified from non-transformed cells. Progeny assembled in non- and Ras-transformed cells appear similar by electron microscopy and sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) analysis, suggesting that Ras transformation introduces a subtle change necessary for virus infectivity. Finally, reovirus release, mediated by caspase-induced apoptosis, is ninefold more efficient in Ras-transformed cells. The combined effects of enhanced virus uncoating, infectivity, and release result in >100-fold differences in virus titers within one round of replication. Our analysis reveals previously unrecognized mechanisms by which Ras transformation mediates selective viral oncolysis.
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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) | 0.000 | 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 | 0.001 |
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".