Increased Efficacy and Safety in the Treatment of Experimental Liver Cancer with a Novel Adenovirus-Alphavirus Hybrid Vector
Bibliographic record
Abstract
An improved viral vector for cancer gene therapy should be capable of infecting tumors with high efficiency, inducing specific and high-level expression of transgene in the tumor and selectively destroying tumor cells. In the design of such a vector to treat hepatocellular carcinoma, we took advantage of (a) the high infectivity of adenoviruses for hepatic cells, (b) the high level of protein expression and proapoptotic properties that characterize Semliki Forest virus (SFV) replicon, and (c) tumor selectivity provided by alpha-fetoprotein (AFP) promoter. We constructed a hybrid viral vector composed of a helper-dependent adenovirus containing an SFV replicon under the transcriptional control of AFP promoter and a transgene driven by SFV subgenomic promoter. Hybrid vectors containing murine interleukin-12 (mIL-12) genes or reporter gene LacZ showed very specific and high-level expression of transgenes in AFP-expressing hepatocellular carcinoma cells, both in vitro and in an in vivo hepatocellular carcinoma animal model. Infected hepatocellular carcinoma cells were selectively eliminated due to the induction of apoptosis by SFV replication. In a rat orthotopic liver tumor model, treatment of established tumors with a hybrid vector carrying mIL-12 gene resulted in strong antitumoral activity without accompanying toxicity. This new type of hybrid vectors may provide a potent and safe tool for cancer gene therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".