Enhanced gene transfer and cell death following p53 gene transfer using photochemical internalisation of glucosylated PEI‐DNA complexes
Bibliographic record
Abstract
BACKGROUND: p53 is frequently mutated in many cancers including human head and neck squamous cell carcinoma and pancreatic cancer. In tumor models, wild-type (wt) p53 gene transfer induces apoptosis and tumor regression in vivo, justifying the extensive clinical investigation of p53 gene therapy. METHODS: p53 nonviral-mediated gene transfer was achieved using glucosylated polyethylenimine (PEI) in conjunction with photochemical internalisation (PCI). Experimental conditions were optimised using the green fluorescent protein (GFP) as a reporter. p53 gene transfer was then evaluated using semi-quantitative RT-PCR in p53-deleted PANC3 and p53-mutated FaDu cell lines. Following gene transfer, induction of apoptosis was investigated using phosphatidylserine externalisation and nuclear fragmentation assays. Induction of long-term cell death was analysed using colony-forming assays. RESULTS: PCI was found to enhance GFP gene transfer after 48 h in both cell lines. Whether using glucosylated-PEI alone or associated with PCI, p53 gene transfer was achieved with subsequent recovery of p53 mRNA expression in PANC3 cells and a significant 4-fold increase in p53 mRNA expression in FaDu cells. PCI was found to further enhance p53 mRNA expression by 2.3-fold in PANC3 cells. Spontaneous induction of apoptosis following wt-p53 gene transfer was achieved in both cell lines. PCI was found to enhance apoptosis up to levels similar to those achieved with chemotherapy. As a consequence, long-term cell death was significantly enhanced after wt-p53 gene transfer when PCI was used in both cell lines, yielding up to 60% cell death. CONCLUSIONS: PCI increases glucosylated-PEI-mediated p53 gene transfer, apoptosis as well as cell death in mutant p53 human cancer cells.
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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".