Expression of a non‐functional p53 affects the sensitivity of cancer cells to gemcitabine
Bibliographic record
Abstract
Gemcitabine is a relatively new agent with promising activity in solid tumors. Few data are available regarding mechanisms of resistance to gemcitabine downstream from the drug-target interaction. The present study was performed to gain insight into the role of p53 status on the cytotoxicity of gemcitabine on cancer cells. Drug sensitivity, drug metabolism, cell kinetics and drug-induced apoptosis were compared in 2 lines derived from the mammary adenocarcinoma MCF-7: the wildtype p53 (wt-p53) containing MN-1 cell line and, the MDD2 line containing a dominant negative variant of the p53 protein (mut-p53). The MDD2 cell line was significantly more resistant to gemcitabine cytotoxicity than the MN-1 cell line. The resistant phenotype could not be attributed to a defective gemcitabine activation/degradation pathway or altered levels of expression of intracellular targets. Although both cell lines exhibited p53 accumulation, MN-1 but not MDD2 cells, displayed p21(WAF1) induction after exposure to gemcitabine. Gemcitabine induced an S-phase arrest in both cell lines. A more pronounced block in G1 phase, however, was observed in MN1 cells. Exposure to gemcitabine induced a higher degree of apoptosis in MN-1 than in MDD2 cells. This corresponded with suppression of Bcl-2 and Bcl-X/L expression in wt-p53 cells exposed to gemcitabine whereas Bcl-2 levels remained stable and Bcl-X/L levels increased in mut-p53 cells exposed to gemcitabine. We conclude that the p53 status of cancer cells influences their sensitivity to gemcitabine cytotoxicity. Our evidence suggests that loss of p53 function leads to loss of cell cycle control and alterations in the apoptotic cascade, conferring resistance to gemcitabine in cancer cell lines displaying a mut-p53.
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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".