Enhanced susceptibility of cancer cells to oncolytic rhabdo-virotherapy by expression of Nodamura virus protein B2 as a suppressor of RNA interference
Bibliographic record
Abstract
Antiviral responses are barriers that must be overcome for efficacy of oncolytic virotherapy. In mammalian cells, antiviral responses involve the interferon pathway, a protein-signaling cascade that alerts the immune system and limits virus propagation. Tumour-specific defects in interferon signaling enhance viral infection and responses to oncolytic virotherapy, but many human cancers are still refractory to oncolytic viruses. Given that invertebrates, fungi and plants rely on RNA interference pathways for antiviral protection, we investigated the potential involvement of this alternative antiviral mechanism in cancer cells. Here, we detected viral genome-derived small RNAs, indicative of RNAi-mediated antiviral responses, in human cancer cells. As viruses may encode suppressors of the RNA interference pathways, we engineered an oncolytic vesicular stomatitis virus variant to encode the Nodamura virus protein B2, a known inhibitor of RNAi-mediated immune responses. B2-expressing oncolytic virus showed enhanced viral replication and cytotoxicity, impaired viral genome cleavage and altered microRNA processing in cancer cells. Our data establish the improved therapeutic potential of our novel virus which targets the RNAi-mediated antiviral defense of cancer cells.
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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".