Targeted and Armed Oncolytic Poxviruses for Cancer: the Lead Example of JX-594
Bibliographic record
Abstract
Oncolytic viruses (OVs) are designed to replicate in, and subsequently lyse cancer cells. Numerous oncolytic virus platforms are currently in development. Here we review preclinical and clinical experience with JX-594, the lead candidate from the targeted and armed oncolytic poxvirus class. JX-594 is derived from a vaccinia vaccine strain that has been engineered for 1) enhanced cancer targeting and 2) has been "armed" with the therapeutic transgene granulocytemacrophage colony stimulating factor (GM-CSF) to stimulate anti-tumoral immunity. Poxviruses have many ideal features for use as oncolytic agents. The development of oncolytic vaccinia viruses is supported by a large safety database accumulated in the smallpox eradication program. In addition, poxviruses have evolved unique capabilities for systemic spread through the blood that can be harnessed for the treatment of metastatic disease. JX-594 demonstrates a high degree of cancer selectivity and systemic efficacy by multiple mechanisms-of-action (MOAs) in preclinical testing. Data from Phase 1 and 2 clinical trials has confirmed that these features result in potent and systemic efficacy in patients with treatment refractory metastatic cancers.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".