Cell Fate Control Gene Therapy Based on Engineered Variants of Human Deoxycytidine Kinase
Bibliographic record
Abstract
The safety of cell therapy applications can be enhanced by the introduction of Cell Fate Control (CFC) elements, which encode pharmacologically controlled cellular suicide switches. CFC Gene Therapy (CFCGT) offers the possibility of establishing control over gene-modified cells (GMCs) with regards to their proliferation, differentiation, or function. However, enzymes commonly employed in these approaches often possess poor kinetics and high immunogenicity. We describe a novel CFCGT system based on engineered variants of human deoxyCytidine Kinase (dCK) that overcomes limitations of current modalities. Mutants of dCK with rationally designed active sites that make them thymidine-activating were stably introduced into cells by recombinant lentiviral vectors (LVs). Transduced cells maintained growth kinetics and function. These dCK mutants efficiently activate bromovinyl-deoxyuridine (BVdU), L-deoxythymidine (LdT), and L-deoxyuridine (LdU), which are otherwise not toxic to wild-type cells. We show that mutant dCK-expressing Jurkat, Molt-4, and U87mg cells could be efficiently eliminated in vitro and in xenogeneic leukemia and tumor models in vivo. We also describe a fusion construct of the thymidine-activating dCK to the cytoplasmic tail-truncated LNGFR molecule and applications to in vivo eradication of primary human T cells. This novel CFCGT system offers unique plasticity with respect to the wide range of prodrugs it can potentiate, and can be used as a reliable safety switch in cell and gene therapy.
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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) | 0.000 | 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) | 0.000 | 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".