NIC/CSL TRANSCRIPTIONAL ACTIVITY IS REGULATED BY THE MEK/ERK PATHWAY IN HUMAN PANCREATIC CANCER CELLS
Bibliographic record
Abstract
Background: Notch are transmembrane receptors which, upon ligand binding, are cleaved thus releasing a Notch intracellular domain (NIC). NIC then translocates into the nucleus where it binds the DNA-binding protein CSL to induce expression of target genes. The Notch pathway is normally inactive in the adult pancreas. However, recent findings revealed that this pathway is reactivated during pancreatic carcinogenesis. The mechanisms by which Notch activity is regulated are still unknown. Aim: To investigate the role of the Mek/Erk pathway in Notch activity regulation. Methods: The MIA PaCa-2 human pancreatic cancer cell line was used. The specific Mek inhibitor U0126 was used while the phorbol-ester PMA was used to stimulate the Mek/Erk pathway. NIC/CSL transcriptional activity was measured by luciferase assays using the CSL-luciferase reporter gene. Overexpression of Notch1 and NIC cDNAs were used to up-regulate NIC/CSL transcriptional activity. Results: 1-Inhibition of the Mek/Erk pathway down-regulated equally (by 50%) the basal and the Notch- and NIC-induced NIC/CSL transcriptional activity. 2-Conversely, strong and sustained activation of the Mek/Erk pathway by PMA increased by 3-fold the basal and Notch- and NIC-induced NIC/CSL transcriptional activity, 3-an effect that was completely blocked by addition of U0126. 4-No modulation in NIC expression was observed following U0126 or PMA treatment. Conclusion: Taking together, these results suggest that the Mek/Erk pathway can directly affects NIC/CSL transcriptional activity independently of an impact on NIC expression.
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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".