Lymphokine‐activated killer and dendritic cell carriage enhances oncolytic reovirus therapy for ovarian cancer by overcoming antibody neutralization in ascites
Bibliographic record
Abstract
Reovirus is an oncolytic virus (OV), which acts by both direct tumor cell killing and priming of antitumor immunity. A major obstacle for effective oncolytic virotherapy is effective delivery of OV to tumor cells. Ovarian cancer is often confined to the peritoneal cavity and therefore i.p. delivery of reovirus may provide the ideal locoregional delivery, avoiding systemic dissemination. However, ovarian cancer is associated with an accumulation of ascitic fluid, which may interfere with oncolytic viral therapy. Here, we investigated the effect of ascites on reovirus-induced oncolysis against primary ovarian cancer cells and ovarian cancer cell lines. In the absence of ascites, reovirus was cytotoxic against ovarian cancer cells; however, cytotoxicity was abrogated in the presence of ascitic fluid. Neutralizing antibodies (NAb) were identified as the cause of this inhibition. Loading OV onto cell carriers may facilitate virus delivery in the presence of NAb and immune cells which have their own antitumor effector activity are particularly appealing. Immature dendritic cells (iDC), Lymphokine-activated killer (LAK) cells and LAKDC cocultures were tested as potential carriers for reovirus for tumor cell killing and immune cell priming. Reovirus-loaded LAKDC, and to a lesser degree iDC, were able to: (i) protect from NAb and hand-off reovirus for tumor cell killing; (ii) induce a proinflammatory cytokine milieu (IFNɣ, IL-12, IFNα and TNFα) and (iii) generate an innate and specific antitumor adaptive immune response. Hence, LAKDC pulsed with reovirus represent a novel, clinically practical treatment for ovarian cancer to maximise both direct and innate/adaptive immune-mediated tumor cell killing.
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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".