Engineered Human tmpk/AZT As a Novel Enzyme/Prodrug Axis for Suicide Gene Therapy
Bibliographic record
Abstract
Gene therapy and stem cell transplantation safety could be enhanced by control over the fate of therapeutic cells. Suicide gene therapy uses enzymes that convert prodrugs to cytotoxic entities; however, heterologous moieties with poor kinetics are employed. We describe a novel enzyme/prodrug combination for selectively inducing apoptosis in lentiviral vector-transduced cells. Rationally designed variants of human thymidylate kinase (tmpk) that effectively phosphorylate 3'-azido-3'-deoxythymidine (AZT) were efficiently delivered. Transduced Jurkat cell lines were eliminated by AZT. We demonstrate that this schema targeted both dividing and non-dividing cells, with a novel killing mechanism involving apoptosis induction via disruption of the mitochondrial inner membrane potential and activation of caspase-3. Primary murine and human T cells were also transduced and responded to AZT. Furthermore, low-dose AZT administration to non-obese diabetic/severe combined immunodeficiency (NOD/SCID) mice injected with transduced K562 cells suppressed tumor growth. This novel suicide gene therapy approach can thus be integrated as a safety switch into therapeutic vectors.
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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".