Regulation of <i>Her2/neu</i> promoter activity by the ETS transcription factor, ER81
Bibliographic record
Abstract
Overexpression of the HER2/Neu receptor is correlated to a poor prognosis in tumor patients and leads to stimulation of mitogen-activated protein kinase (MAPK) signaling pathways, which in turn activate transcription factors, such as the ETS protein ER81. Here, we have analyzed whether, on the other hand, ER81 may regulate the Her2/neu gene. Indeed, ER81, together with its co-activators, p300 and CBP, activates the Her2/neu promoter, and this activation is enhanced upon stimulation of MAPK pathways as well as by oncogenic HER2/Neu protein. Furthermore, ER81 interacts with one ETS binding site in the Her2/neu promoter, whose mutation decreases ER81-mediated transcription. Activation of the Her2/neu promoter is also diminished upon mutation of MAPK-dependent phosphorylation sites in ER81 or upon deletion of ER81 transactivation domains. In addition, the ER81 DNA-binding domain on its own functions as a dominant-negative molecule, effectively repressing any stimulation of the Her2/neu promoter. Altogether, our results show that ER81 is a component of a positive regulatory feedback loop, in which the HER2/Neu protein activates ER81, as well as p300/CBP via MAPKs causing the upregulation of the Her2/neu gene.
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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".