Epidermal Growth Factor–Induced Signaling in Breast Cancer Cells Results in Selective Target Gene Activation by Orphan Nuclear Receptor Estrogen-Related Receptor α
Bibliographic record
Abstract
The orphan nuclear hormone receptor estrogen-related receptor alpha (ERRalpha, NR3B1) is a constitutive transcription factor that is structurally and functionally related to the classic estrogen receptors. ERRalpha can recognize both the estrogen response element and its own binding site (ERRE) in either dimeric or monomeric forms. ERRalpha is also a phosphoprotein whose expression in human breast tumors correlates with that of the receptor tyrosine kinase ErbB2, suggesting that its transcriptional activity could be regulated by signaling cascades. Here, we investigated growth factor regulation of ERRalpha function and found that it is phosphorylated in MCF-7 breast cancer cells in response to epidermal growth factor (EGF), an event that enhances its DNA binding. Interestingly, treatment with alkaline phosphatase shifts ERRalpha from a dimeric to a monomeric DNA-binding factor, and only the dimeric form interacts with the coactivator PGC-1alpha. In vitro, the DNA-binding domain of ERRalpha is selectively phosphorylated by protein kinase Cdelta (PKCdelta), which increases its DNA-binding activity, whereas expression of constitutively active PKCdelta enhances TFF1 promoter activity via the ERRE. However, whereas treatment of MCF-7 cells with the phorbol ester phorbol-12-myristate 13-acetate also enhances ERRalpha activation of the TFF1 promoter reporter, it does not affect ERRalpha activity on its own promoter. In agreement, chromatin immunoprecipitation analysis shows that ERRalpha and RNA polymerase II are preferentially recruited to the TFF1 promoter after EGF treatment, whereas recruitment of these factors to its own promoter is not affected. These results reveal a mechanism through which growth factor signaling can selectively activate ERRalpha target genes in breast cancer cells.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".