A Conditionally Replicating Adenovirus for Nasopharyngeal Carcinoma Gene Therapy
Bibliographic record
Abstract
Successful attainment of tumor-specific gene expression was achieved in nasopharyngeal carcinoma (NPC) by exploiting the exclusive presence of the Epstein-Barr virus (EBV) genome in the cancer cells. In the current study, we have utilized an EBV-dependent transcriptional targeting strategy to construct a novel conditionally replicating adenovirus, adv.oriP.E1A. After treatment with adv.oriP.E1A, we observed extensive cell death in the EBV-positive NPC cell line C666-1. In contrast, no cytotoxicity was observed in a panel of other human EBV-negative cell lines, including fibroblasts from the nasopharynx. In vitro adenoviral replication was confirmed by the time-dependent increase in the expression of adenoviral capsid fiber protein and adenoviral DNA after C666-1 cells were infected with adv.oriP.E1A. Tumor formation was inhibited for more than 100 days after ex vivo infection of C666-1 cells with adv.oriP.E1A. Combination of local tumor radiation and adv.oriP.E1A caused complete disappearance of established tumors for at least 2 weeks in two distinct EBV-positive NPC xenograft models. Safety of this treatment was determined through the systemic delivery of adv.oriP.E1A in vivo, whereby minimal temporary perturbation of liver function was observed. We have successfully established a conditionally replicating adenovirus for EBV-positive NPC, which is both safe and efficacious, indicating a strategy that may be therapeutically applicable.
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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 | 0.000 | 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 | 0.001 |
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".