A Phase II Study of Pelareorep (REOLYSIN®) in Combination with Gemcitabine for Patients with Advanced Pancreatic Adenocarcinoma
Bibliographic record
Abstract
Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with 1 and 5-year survival rates of ~18% and 7% respectively. FOLFIRINOX or gemcitabine in combination with nab-paclitaxel are standard treatment options for metastatic disease. However, both regimens are more toxic than gemcitabine alone. Pelareorep (REOLYSIN®), a proprietary isolate of reovirus Type 3 Dearing, has shown antitumor activity in clinical and preclinical models. In addition to direct cytotoxic effects, pelareorep can trigger antitumor immune responses. Due to the high frequency of RAS mutations in PDAC, we hypothesized that pelareorep would promote selective reovirus replication in pancreatic tumors and enhance the anticancer activity of gemcitabine. Chemotherapy-naïve patients with advanced PDAC were eligible for the study. The primary objective was Clinical Benefit Rate (complete response (CR) + partial response (PR) + stable disease (SD) ≥ 12 weeks) and secondary objectives include overall survival (OS), toxicity, and pharmacodynamics (PD) analysis. The study enrolled 34 patients; results included one partial response, 23 stable disease, and 5 progressive disease. The median OS was 10.2 months, with a 1- and 2-year survival rate of 45% and 24%, respectively. The treatment was well tolerated with manageable nonhematological toxicities. PD analysis revealed reovirus replication within pancreatic tumor and associated apoptosis. Upregulation of immune checkpoint marker PD-L1 suggests future consideration of combining oncolytic virus therapy with anti-PD-L1 inhibitors. We conclude that pelareorep complements single agent gemcitabine in PDAC.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".