Efficacy of targeted FasL in nasopharyngeal carcinoma
Bibliographic record
Abstract
We have successfully achieved selective gene expression in human nasopharyngeal carcinoma (NPC) by exploiting the presence of the Epstein-Barr virus (EBV), utilizing a transcriptional targeting strategy (J. H. Li et al., 2002, Cancer Res. 62: 171). Building on this platform, we have generated a novel DeltaE1 adenoviral vector mediating the expression of a mutant noncleavable form of the FasL gene (HUGO-approved symbol TNFSF6) (ad5oriP.ncFasL). We observe that this therapy induces significant cytotoxicity in the EBV-positive NPC cell line C666-1, mediated by the induction of caspase-dependent apoptosis. The addition of ionizing radiation therapy (RT) causes additional cytotoxicity. Ex vivo infection of C666-1 cells with adv.oriP.ncFasL completely prevents tumor formation in SCID mice followed for up to 100 days. The combination of intratumoral adv.oriP.ncFasL with RT causes regression of established nasopharyngeal xenograft tumors for 2 weeks' duration. Systemic delivery of this targeted strategy achieves 50-fold higher gene expression in nasopharyngeal tumors than in normal organs. Intravenously injected adv.oriP.ncFasL results in mild perturbation of liver function that returns to normal 2 weeks after initial therapy. These results demonstrate the efficacy of our EBV-specific targeting strategy, which allows the potentially safe and effective utilization of a highly potent membrane-based apoptotic gene.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".