Enhanced <i>In vitro</i> and <i>In vivo</i> Cytotoxicity of Combined Reovirus and Radiotherapy
Bibliographic record
Abstract
PURPOSE: To test combination treatment schedules of reovirus and radiation in human and murine tumor cells in vitro and in vivo. EXPERIMENTAL DESIGN: In vitro cytotoxicity and cell cycle effects of reovirus given alone and combined with radiotherapy were assessed by colorimetric, tissue culture infectious dose 50, and fluorescence-activated cell sorting-based assays. Interactions between the agents were evaluated using combination index analysis. The effect of different schedules of reovirus and radiotherapy on viral replication and cytotoxicity was tested in vitro and the combination was assessed in three tumor models in vivo. RESULTS: Characterization of reovirus cytotoxicity in a panel of cell lines yielded a range of sensitivities. Combined reovirus and radiotherapy yielded statistically significantly increased cytotoxicity, particularly in cell lines with moderate susceptibility to reovirus alone. The enhanced cytotoxicity of the combination occurred independently of treatment sequence or schedule. Radiation did not affect viral replication and only reduced reoviral cytotoxicity after clinically irrelevant single doses (>50 Gy). Combination index analysis revealed synergy between radiation (3-10 Gy) and reovirus at multiplicities of infection between 0.001 and 1. Combination treatment significantly increased apoptosis in tumor cells relative to either single-agent treatment. In vivo studies using xenograft and syngeneic tumors showed enhanced activity of the combination relative to reovirus or radiation alone (P < 0.001). CONCLUSIONS: Combining reovirus and radiotherapy synergistically enhances cytotoxicity in a variety of tumor cells in vitro and in vivo. These results offer strong support for translational clinical trials of reovirus plus radiotherapy that have been initiated in the clinic.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".