The therapeutic potential of attenuated diphtheria toxin delivered by an adenovirus vector with survivin promoter on human lung cancer cells
Bibliographic record
Abstract
Adenoviral vectors are superior to plasmid vectors in their gene transport efficiency. The A subunit of the diphtheria toxin (DTA) gene is a popular suicide gene in cancer gene therapy. However, DTA is seldom used in adenoviral therapy due to its great toxicity. The toxicity of DTA is so great that even a single molecule of DTA is enough to kill one cell. To avoid this highly toxic effect on normal cells, DTA should be controlled by tumor-specific promoters. The survivin promoter is a widely used tumor-specific promoter. But genes driven by the survivin promoter show a low level of basal gene expression in non-cancer cells. DTA driven by the survivin promoter in adenoviral vectors may be highly toxic not only to cancer cells but also to normal cells. Therefore, DTA should be attenuated when it is used in adenoviral vectors driven by the survivin promoter. In this study, we compared the three kinds of recombinant adenoviruses that carry DTA or its attenuated forms (DTA176 and DTA197) in the treatment of human lung cancer. The results showed that in comparison with both DTA and DTA176, DTA197 is more suitable for adenoviral cancer therapy controlled by the survivin promoter. In addition, Adsur-DTA197 (DTA197 delivered by an adenoviral vector with the survivin promoter) sensitized human lung cancer cells to cisplatin both in vitro and in vivo. These results indicated that Adsur-DTA197 may be a potential chemosensitizer in cancer therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".