Reolysin is a novel reovirus-based agent that induces endoplasmic reticular stress-mediated apoptosis in pancreatic cancer
Bibliographic record
Abstract
Activating mutation of KRas is a genetic alteration that occurs in the majority of pancreatic tumors and is therefore an ideal therapeutic target. The ability of reoviruses to preferentially replicate and induce cell death in transformed cells that express activated Ras prompted the development of a reovirus-based formulation for cancer therapy called Reolysin. We hypothesized that Reolysin exposure would trigger heavy production of viral products leading to endoplasmic reticular (ER) stress-mediated apoptosis. Here, we report that Reolysin treatment stimulated selective reovirus replication and decreased cell viability in KRas-transformed immortalized human pancreatic duct epithelial cells and pancreatic cancer cell lines. These effects were associated with increased expression of ER stress-related genes, ER swelling, cleavage of caspase-4, and splicing of XBP-1. Treatment with ER stress stimuli including tunicamycin, brefeldin A, and bortezomib (BZ) augmented the anticancer activity of Reolysin. Cotreatment with BZ and Reolysin induced the simultaneous accumulation of ubiquitinated and viral proteins, resulting in enhanced levels of ER stress and apoptosis in both in vitro and in vivo models of pancreatic cancer. Our collective results demonstrate that the abnormal protein accumulation induced by the combination of Reolysin and BZ promotes heightened ER stress and apoptosis in pancreatic cancer cells and provides the rationale for a phase I clinical trial further investigating the safety and efficacy of this novel strategy.
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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) | 0.000 | 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".