Influence of the prodrugs 5‐fluorocytosine and CPT‐11 on ovarian cancer cells using genetically engineered stem cells: tumor‐tropic potential and inhibition of ovarian cancer cell growth
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recent studies have shown that genetically engineered stem cells (GESTECs) to produce suicide enzymes that convert non-toxic prodrugs to toxic metabolites selectively migrate toward tumor sites and reduce tumor growth. In the present study, we evaluated whether these GESTECs were capable of migrating to human ovarian cancer cells and examined the potential therapeutic efficacy of the gene-directed enzyme prodrug therapy against ovarian cancer cells in vitro. The expression of cytosine deaminase (CD) or carboxyl esterase (CE) mRNA of GESTECs was confirmed by RT-PCR. A modified transwell migration assay was performed to determine the migratory capacity of GESTECs to ovarian cancer cells. GESTECs (HB1.F3.CD or HB1.F3.CE cells) engineered to express a suicide gene (CD or CE) selectively migrated toward ovarian cancer cells. A [(3)H] thymidine incorporation assay was conducted to measure the proliferative index. Treatment of human epithelial ovarian cancer cell line (SKOV-3, an ovarian adenocarcinoma derived from the ascites of an ovarian cancer patient) with the prodrugs 5-fluorocytosine (5-FC) or camptothecin-11 (CPT-11) in the presence of HB1.F3.CD or HB1.F3.CE cells resulted in the inhibition of ovarian cancer cell growth. Based on the data presented herein, we suggest that GESTECs expressing CD/CE may have a potent advantage to selectively treat ovarian cancers.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it