A Potential Therapy Using Engineered Stem Cells Prevented Malignant Melanoma in Cellular and Xenograft Mouse Models
Bibliographic record
Abstract
PURPOSE: In the present study, human neural stem cells (hNSCs) with tumor-tropic behavior were used as drug delivery vehicle to selectively target melanoma. A hNSC line (HB1.F3) was transduced into two types: one expressed only the cytosine deaminase (CD) gene (HB1.F3. CD) and the other expressed both CD and human interferon-β (IFN-β) genes (HB1.F3.CD. IFN-β). MATERIALS AND METHODS: This study verified the tumor-tropic migratory competence of engineered hNSCs on melanoma (A375SM) using a modified Boyden chamber assay in vitro and CM-DiI staining in vivo. The antitumor effect of HB1.F3.CD and HB1.F3.CD.IFN-β on melanoma was also confirmed using an MTT assay in vitro and xenograft mouse models. RESULTS: A secreted form of IFN-β from the HB1.F3.CD.IFN-β cells modified the epithelial-mesenchymal transition (EMT) process and metastasis of melanoma. 5-Fluorouracil treatment also accelerated the expression of the pro-apoptotic protein BAX and decelerated the expression of the anti-apoptotic protein Bcl-xL on melanoma cell line. CONCLUSION: Our results illustrate that engineered hNSCs prevented malignant melanoma cells from proliferating in the presence of the prodrug, and the form that secreted IFN-β intervened in the EMT process and melanoma metastasis. Hence, neural stem cell-directed enzyme/prodrug therapy is a plausible treatment for malignant melanoma.
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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 | 0.000 |
| 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 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".