A Growth Hormone Receptor Mutation Impairs Growth Hormone Autofeedback Signaling in Pituitary Tumors
Bibliographic record
Abstract
Pituitary tumors are a diverse group of neoplasms that are classified based on clinical manifestations, hormone excess, and histomorphologic features. Those that cause growth hormone (GH) excess and acromegaly are subdivided into morphologic variants that have not yet been shown to have pathogenetic significance or predictive value for therapy and outcome. Here, we identify a selective somatic histidine-to-leucine substitution in codon 49 of the extracellular domain of the GH receptor (GHR) in a morphologic subtype of human GH-producing pituitary tumors that is characterized by the presence of cytoskeletal aggresomes. This GHR mutation significantly impairs glycosylation-mediated receptor processing, maturation, ligand binding, and signaling. Pharmacologic GH antagonism recapitulates the morphologic phenotype of pituitary tumors from which this mutation was identified, inducing the formation of cytoskeletal keratin aggresomes. This novel GHR mutation provides evidence for impaired hormone autofeedback in the pathogenesis of these pituitary tumors. It explains the lack of responsiveness to somatostatin analogue therapy of this tumor type, in contrast to the exquisite sensitivity of tumors that lack aggresomes, and has therapeutic implications for the safety of GH antagonism as a therapeutic modality in acromegaly.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".