EAG K+ channel joins the p53&x2212;miR-34&x2212;E2F1 signaling pathway as a terminal effecter component for its oncogenic overexpression and action
Bibliographic record
Abstract
Abstract The human ether-&x00E0;-go-go-1 (h-eag1) voltage-dependent K+ channel is necessary for cell cycle progression and its overexpression stimulates tumorigenesis; specific inhibition of h-eag1 expression leads to a reduction in tumor cell proliferation in vitro and in vivo. On the other hand, the tumor-suppressor gene p53 and its downstream genes consist of a complex molecular signaling network and p53 is at the center of this network regulating diverse physiological responses to cancer-related stresses. We report here that h-eag1 expression is controlled by the p53&x2212;miR-34&x2212;E2F1 pathway through a negative feed-forward mechanism. We first established E2F1 as a transactivator of h-eag1 gene. We then revealed that miR-34, a known transcriptional target of p53, is an important negative regulator of h-eag1 through dual mechanisms by directly repressing h-eag1 at the post-transcriptional level and indirectly silencing h-eag1 at the transcriptional level via repressing E2F1. The antisense against h-eag1 antagonized the growth-stimulating effects and the upregulation of h-eag1 expression in SHSY5Y cells, induced by E2F1 overexpression, inhibition of p53 activity, or knockdown of miR-34. Thus, negative regulation of p53 causes oncogenic overexpression of h-eag1 by relieving the negative feed-forward regulation of the p53&x2212;miR-34&x2212;E2F1 pathway or overexpression of h-eag1 fulfills the oncogenic cell growth-stimulating effect of p53 inactivation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".