miR-137 Modulates a Tumor Suppressor Network-Inducing Senescence in Pancreatic Cancer Cells
Bibliographic record
Abstract
Activating K-Ras mutations occurs frequently in pancreatic cancers and is implicated in their development. Cancer-initiating events, such as oncogenic Ras activation, lead to the induction of cellular senescence, a tumor suppressor response. During senescence, the decreased levels of KDM4A lysine demethylase contribute to p53 activation, however, the mechanism by which KDM4A is downregulated is unknown. We show that miR-137 targets KDM4A mRNA during Ras-induced senescence and activates both p53 and retinoblastoma (pRb) tumor suppressor pathways. Restoring the KDM4A expression contributed to bypass of miR-137-induced senescence and inhibition of endogenous miR-137 with an miRNA sponge-compromised Ras-induced senescence. miR-137 levels are significantly reduced in human pancreatic tumors, consistent with previous studies revealing a defective senescence response in this cancer type. Restoration of miR-137 expression inhibited proliferation and promoted senescence of pancreatic cancer cells. These results suggest that modulating levels of miR-137 may be important for triggering tumor suppressor networks in pancreatic cancer.
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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".