EGF activation of POMC gene transcription is mediated by STAT3
Bibliographic record
Abstract
Classical activation of the hypothalamic-pituitary-adrenal axis is exerted by the stimulation of pituitary POMC gene transcription and ACTH release by the hypothalamic hormone CRH. In parallel, inflammatory cytokines such as IL6 and LIF also stimulate ACTH release and POMC transcription through the JAK/STAT pathway. In recent years, a particular interest in the role of the EGF pathway for POMC activation was sparked by the identification of causative mutations in the USP8 gene that have been implicated in the formation of pituitary corticotroph adenomas that are the hallmark of Cushing's disease. These mutations were associated with the persistent upregulation of the EGF/EGFR pathway and its putative role in ACTH hypersecretion. In the present work, we reassessed the signaling pathways that are activated in response to EGF in pituitary corticotroph cells using the AtT20 cell model. We confirmed the activation of the MAP kinase pathway by EGF and also showed the activation of the AKT/mTOR and JAK/STAT pathways. Whereas activation of all three pathways appears essential for the stimulation of cell proliferation, only the JAK/STAT pathway, and more specifically STAT3, enhances POMC gene transcription. This action is mapped to a single STAT-binding element of the POMC promoter in contrast to the activation by the other STAT-activating cytokines LIF and IL6. Furthermore, EGF signaling is specifically enhanced by STAT3 but not STAT1 in contrast to LIF-dependent activation. All together, the data identified a unique STAT3-dependent target on the POMC promoter that mediates EGF activation of POMC gene transcription.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".