Excellent <b> <i>In vivo</i> </b> Bystander Activity of Fludarabine Phosphate against Human Glioma Xenografts that Express the <b> <i>Escherichia coli</i> </b> Purine Nucleoside Phosphorylase Gene
Bibliographic record
Abstract
Escherichia coli purine nucleoside phosphorylase (PNP) expressed in tumors converts relatively nontoxic prodrugs into membrane-permeant cytotoxic compounds with high bystander activity. In the present study, we examined tumor regressions resulting from treatment with E. coli PNP and fludarabine phosphate (F-araAMP), a clinically approved compound used in the treatment of hematologic malignancies. We tested bystander killing with an adenoviral construct expressing E. coli PNP and then more formally examined thresholds for the bystander effect, using both MuLv and lentiviral vectoring. Because of the importance of understanding the mechanism of bystander action and the limits to this anticancer strategy, we also evaluated in vivo variables related to the expression of E. coli PNP (level of E. coli PNP activity in tumors, ectopic expression in liver, percentage of tumor cells transduced in situ, and accumulation of active metabolites in tumors). Our results indicate that F-araAMP confers excellent in vivo dose-dependent inhibition of bystander tumor cells, including strong responses in subcutaneous human glioma xenografts when 95 to 97.5% of the tumor mass is composed of bystander cells. These findings define levels of E. coli PNP expression necessary for antitumor activity with F-araAMP and demonstrate new potential for a clinically approved compound in solid tumor 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".