Telomerase‐specific oncolytic adenoviral therapy for orthotopic hepatocellular carcinoma in HBx transgenic mice
Bibliographic record
Abstract
The telomerase-specific replication-competent oncolytic adenovirus, Telomelysin, was developed for virus-mediated preferential lysis of tumor cells. Its selectivity is derived from a human telomerase reverse transcriptase (hTERT) promoter-driven active viral replication, which occurs in cancer cells with high telomerase activity but not in normal cells lacking such activity. Because the TERT activity is elevated in most cases of hepatocellular carcinoma (HCC), the current study aims to investigate whether Telomelysin can be used for treatment of HCC. The oncolytic effect of Telomelysin has been investigated both in vitro using cell culture and in vivo using an immunocompetent in situ orthotopic HCC model. In this model, HCC developed spontaneously in the liver of HBx transgenic mice, which is pathologically and genetically similar to human HCC. In cell culture assay, Telomelysin lyses HCC cell lines at a low multiplicity of infection (MOI), ranging 0.77-6.35 (MOI [PFU/cell]). In the orthotopic HCC model, Telomelysin showed a potent oncolytic effect on HCC but spared normal liver tissue. Dose escalation analysis identified a safety dose of 1.25 × 10(8) PFU for this model. The effect of multiple injections of Telomelysin was also evaluated in this immunocompetent HCC model. We found that the virus replicates in HCC after a second intratumoral injection despite an immune response induced by the previous injection. This preclinical study shows that Telomelysin can be used for treatment of human HCC at an appropriate dosage and that its tumor-killing activity persists after multiple injections.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".