Efficacy and Safety/Toxicity Study of Recombinant Vaccinia Virus JX-594 in Two Immunocompetent Animal Models of Glioma
Bibliographic record
Abstract
The purpose of this study was to investigate the oncolytic potential of the recombinant, granulocyte macrophage colony-stimulating factor (GM-CSF)-expressing vaccinia virus (VV) JX-594 in experimental malignant glioma (MGs) in vitro and in immunocompetent rodent models. We have found that JX-594 killed all MG cell lines tested in vitro. Intratumoral (i.t.) administration of JX-594 significantly inhibited tumor growth and prolonged survival in rats-bearing RG2 intracranial (i.c.) tumors and mice-bearing GL261 brain tumors. Combination therapy with JX-594 and rapamycin significantly increased viral replication and further prolonged survival in both immunocompetent i.c. MG models with several animals considered "cured" (three out of seven rats >120 days, terminated experiment). JX-594 infected and killed brain tumor-initiating cells (BTICs) from patient samples grown ex vivo, and did so more efficiently than other oncolytic viruses MYXV, Reovirus type-3, and VSV(ΔM51). Additional safety/toxicity studies in nontumor-bearing rodents treated with a supratherapeutic dose of JX-594 demonstrated GM-CSF-dependent inflammation and necrosis. These results suggest that i.c. administered JX-594 triggers a predictable GM-CSF-mediated inflammation in murine models. Before proceeding to clinical trials, JX-594 should be evaluated in the brains of nonhuman primates and optimized for the viral doses, delivery routes as well as the combination agents (e.g., mTOR inhibitors).
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".