Oncolytic and Immunotherapeutic Vaccinia Induces Antibody-Mediated Complement-Dependent Cancer Cell Lysis in Humans
Bibliographic record
Abstract
Oncolytic viruses cause direct cytolysis and cancer-specific immunity in preclinical models. The goal of this study was to demonstrate induction of functional anticancer immunity that can lyse target cancer cells in humans. Pexa-Vec (pexastimogene devacirepvec; JX-594) is a targeted oncolytic and immunotherapeutic vaccinia virus engineered to express human granulocyte-macrophage colony-stimulating factor (GM-CSF). Pexa-Vec demonstrated replication, GM-CSF expression, and tumor responses in previous phase 1 trials. We now evaluated whether Pexa-Vec induced functional anticancer immunity both in the rabbit VX2 tumor model and in patients with diverse solid tumor types in phase 1. Antibody-mediated complement-dependent cancer cell cytotoxicity (CDC) was induced by intravenous Pexa-Vec in rabbits; transfer of serum from Pexa-Vec-treated animals to tumor-bearing animals resulted in tumor necrosis and improved survival. In patients with diverse tumor types treated on a phase 1 trial, CDC developed within 4 to 8 weeks in most patients; normal cells were resistant to the cytotoxic effects. T lymphocyte activation in patients was evidenced by antibody class switching. We determined that patients with the longest survival duration had the highest CDC activity, and identified candidate target tumor cell antigens. Thus, we demonstrated that Pexa-Vec induced polyclonal antibody-mediated CDC against multiple tumor antigens both in rabbits and in patients with diverse solid tumor types.
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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".