<i>O</i> -GlcNAcylation is essential for rapid <i>Pomc</i> expression and cell proliferation in corticotropic tumor cells
Bibliographic record
Abstract
ABSTRACT Pituitary adenomas have a staggering 16.7% lifetime prevalence and can be devastating in many patients due to profound endocrine and neurologic dysfunction. To date, no clear genomic or epigenomic markers correlates with their onset or severity. Herein, we investigate the impact of the O -GlcNAc post-translational modification in their etiology. Found in over 5000 human proteins to date, O -GlcNAcylation dynamically regulates proteins in critical signaling pathways, and its deregulation is involved in cancers progression and endocrine diseases such as diabetes. In this study, we demonstrate that O -GlcNAcylation enzymes were upregulated, particularly in aggressive ACTH-secreting tumors, suggesting a role for O -GlcNAcylation in pituitary adenoma etiology. In addition to the demonstration that O -GlcNAcylation was essential for their proliferation, we show that the endocrine function of pituitary adenoma is also dependent on O -GlcNAcylation. In corticotropic tumors, hyper-secretion of the proopiomelanocortin (POMC)-derived hormone ACTH leads to Cushing’s disease, materialized by severe endocrine disruption and increased mortality. We demonstrate that Pomc mRNA is stabilized in an O -GlcNAc-dependent manner in response to corticotropic-stimulating hormone (CRH). By impacting Pomc mRNA splicing and stability, O -GlcNAcylation contributes to this new mechanism of fast hormonal response in corticotropes. Thus, this study stresses the essential role of O -GlcNAcylation in ACTH-secreting adenomas’ pathophysiology, including cellular proliferation and hypersecretion.
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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".