MicroRNA Modification of Coxsackievirus B3 Decreases Its Toxicity, while Retaining Oncolytic Potency against Lung Cancer
Bibliographic record
Abstract
We recently discovered that coxsackievirus B3 (CVB3) is a potent oncolytic virus against KRAS mutant lung adenocarcinoma. Nevertheless, the evident toxicity restricts the use of wild-type (WT)-CVB3 for cancer therapy. The current study aims to engineer the CVB3 to decrease its toxicity and to extend our previous research to determine its safety and efficacy in treating TP53 / RB1 mutant small-cell lung cancer (SCLC). A microRNA-modified CVB3 (miR-CVB3) was generated via inserting multiple copies of tumor-suppressive miR-145/miR-143 target sequences into the viral genome. In vitro experiments revealed that miR-CVB3 retained the ability to infect and lyse KRAS mutant lung adenocarcinoma and TP53 / RB1- mutant SCLC cells, but with a markedly reduced cytotoxicity toward cardiomyocytes. In vivo study using a TP53 / RB1- mutant SCLC xenograft model demonstrated that a single dose of miR-CVB3 via systemic administration resulted in a significant tumor regression. Most strikingly, mice treated with miR-CVB3 exhibited greatly attenuated cardiotoxicities and decreased viral titers compared to WT-CVB3-treated mice. Collectively, we generated a recombinant CVB3 that is powerful in destroying both KRAS mutant lung adenocarcinoma and TP53 / RB1- mutant SCLC, with a negligible toxicity toward normal tissues. Future investigation is needed to address the issue of genome instability of miR-CVB3, which was observed in ~40% of mice after a prolonged 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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".