Gemcitabine-mediated tumour regression and p53-dependent gene expression: implications for colon and pancreatic cancer therapy
Bibliographic record
Abstract
Gemcitabine is a chemotherapeutic that is widely used for the treatment of a variety of haematological malignancies and has become the standard chemotherapy for the treatment of advanced pancreatic cancer. Combinational gemcitabine regimes (e.g.with doxorubicin) are being tested in clinical trials to treat a variety of cancers, including colon cancer. The limited success of these trials has prompted us to pursue a better understanding of gemcitabine's mechanism of cell killing, which could dramatically improve the therapeutic potential of this agent. For comparison, we included gamma irradiation that triggers robust cell cycle arrest and Cr(VI), which is a highly toxic chemical that induces a robust p53-dependent apoptotic response. Gemcitabine induced a potent p53-dependent apoptosis that correlated with the accumulation of pro-apoptotic proteins such as PUMA and Bax. This is accompanied by a drastic reduction in p2l and 14-3-3σ protein levels, thereby significantly sensitizing the cells to apoptosis. In vitro and in vivo studies demonstrated that gemcitabine required PUMA transcription to instigate an apoptotic programme. This was in contrast to Cr(VI)-induced apoptosis that required Bax and was independent of transcription. An examination of clinical colon and pancreatic cancer tissues shows higher p53, p21, 14-3-3σ and Bax expression compared with matched normal tissues, yet there is a near absence of PUMA protein. This may explain why gemcitabine shows only limited efficacy in the treatment of these cancers. Our results raise the possibility that targeting the Bax-dependent cell death pathway, rather than the PUMA pathway, could result in significantly improved patient outcome and prognosis for these cancers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".