Sequential Therapy With JX-594, A Targeted Oncolytic Poxvirus, Followed by Sorafenib in Hepatocellular Carcinoma: Preclinical and Clinical Demonstration of Combination Efficacy
Bibliographic record
Abstract
JX-594 is a targeted and granulocyte-macrophage colony stimulating factor (GM-CSF) expressing oncolytic poxvirus designed to selectively replicate in and destroy cancer cells through viral oncolysis and tumor-specific immunity. In a phase 1 trial, JX-594 injection into hepatocellular carcinoma (HCC) was well-tolerated and associated with viral replication, decreased tumor perfusion, and tumor necrosis. We hypothesized that JX-594 and sorafenib, a small molecule inhibitor of B-raf and vascular endothelial growth factor receptor (VEGFR) approved for HCC, would have clinical benefit in combination given their demonstrated efficacy in HCC patients and their complementary mechanisms-of-action. HCC cell lines were uniformly sensitive to JX-594. Anti-raf kinase effects of concurrent sorafenib inhibited JX-594 replication in vitro, whereas sequential therapy was superior to either agent alone in murine tumor models. We therefore explored pilot safety and efficacy of JX-594 followed by sorafenib in three HCC patients. In all three patients, sequential treatment was (i) well-tolerated, (ii) associated with significantly decreased tumor perfusion, and (iii) associated with objective tumor responses (Choi criteria; up to 100% necrosis). HCC historical control patients on sorafenib alone at the same institutions had no objective tumor responses (0 of 15). Treatment of HCC with JX-594 followed by sorafenib has antitumoral activity, and JX-594 may sensitize tumors to subsequent therapy with VEGF/VEGFR 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".