Stem cells with fused gene expression of cytosine deaminase and interferon-β migrate to human gastric cancer cells and result in synergistic growth inhibition for potential therapeutic use
Bibliographic record
Abstract
Genetically engineered stem cells (GESTECs) producing suicide enzymes and immunotherapeutic cytokines have therapeutic effects on tumors, and may possibly reduce the side effects of toxic drugs used for treatments. Suicide enzymes can convert non-toxic pro-drugs to toxic metabolites that can reduce tumor growth. Cytosine deaminase (CD) is a suicide enzyme that metabolizes a non-toxic pro-drug, 5-fluorocytosine (5-FC), into the cytotoxic agent, 5-fluorouracil (5-FU). As an immunotherapeutic agent, human interferon-β (IFN-β) has anticancer effects. In this study, we used modified human neural stem cells (HB1.F3) expressing the Escherichia coli (E. coli) CD gene (HB1.F3.CD) or both the CD and human IFN-β genes (HB1.F3.CD.IFN-β) and evaluated their effectiveness on gastric carcinoma cells (AGS); migration of GESTECs to AGS was analyzed as well as formation of 5-FU and IFN-β. Reverse transcription-polymerase chain reaction (RT-PCR) was used to confirm the expression of CD and IFN-β genes in GESTECs along with confirming the production of chemoattractant molecules such as stem cell factor (SCF), CXCR4, c-Kit, vascular endothelial growth factor (VEGF) and VEGF receptor 2 (VEGFR2). In addition, by co-culturing GESTECs with AGS in the presence of 5-FC, we were able to confirm that cancer growth was inhibited, along with a synergistic effect when the CD and IFN-β genes (HB1.F3.CD.IFN-β) were co-expressed. Indeed a marked anticancer effect was demonstrated when the CD and IFN-β genes were expressed together compared to expression of the CD gene alone (HB1.F3.CD). According to a modified transwell migration assay, the migration of GESTECs toward AGS was confirmed. In conclusion, these data suggest potential application of GESTECs to gastric cancer therapy, due to a remarkable synergistic effect of CD and IFN-β genes in the presence of 5-FC. Additionally, the tumor-selective migration capability in vitro suggests that GESTECs are a potential anticancer therapy candidate that may result in minimal side effects compared to the conventional chemotherapy.
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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".