The Hormonal Response of Estrogen Receptor β Is Decreased by the Phosphatidylinositol 3-Kinase/Akt Pathway via a Phosphorylation-dependent Release of CREB-binding Protein
Bibliographic record
Abstract
The hormonal response of estrogen receptors (ER) alpha and ERbeta is controlled by a number of cofactors, including the general transcriptional coactivator CREB-binding protein (CBP). Growing evidence suggests that specific kinase signaling events also modulate the formation and activity of the ER coactivation complex. Here we show that ERbeta activity and target gene expression are decreased upon activation of ErbB2/ErbB3 receptors despite the presence of CBP. This inhibition of ERbeta involved activation of the phosphatidylinositol 3-kinase/Akt pathway, abrogating the potential of CBP to facilitate ERbeta response to estrogen. Such reduced activity was associated with an impaired ability of ERbeta to recruit CBP upon activation of Akt. Mutation of serine 255, an Akt consensus site contained in the hinge region of ERbeta, prevented the release of CBP and rendered ERbeta transcriptionally more responsive to CBP coactivation, suggesting that Ser-255 may serve as a regulatory site to restrain ERbeta activity in Akt-activated cells. In contrast, we found that CBP intrinsic activity was increased by Akt through threonine 1872, a consensus site for Akt in the cysteine- and histidine-rich 3 domain of CBP, indicating that such enhanced transcriptional potential of CBP did not serve to activate ERbeta. Interestingly, nuclear receptors sharing a conserved Akt consensus site with ERbeta also exhibit a reduced ability to be coactivated by CBP, whereas others missing that site were able to benefit from the activation of CBP by Akt. These results therefore outline a regulatory mechanism by which the phosphatidylinositol 3-kinase/Akt pathway may discriminate nuclear receptor response through coactivator transcriptional competence.
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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) | 0.002 | 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".