Whole Genome Expression Profiling of Glucose-Dependent Insulinotropic Peptide (GIP)- and Adrenocorticotropin-Dependent Adrenal Hyperplasias Reveals Novel Targets for the Study of GIP-Dependent Cushing’s Syndrome
Bibliographic record
Abstract
CONTEXT: The mechanisms responsible for the ectopic adrenal expression of glucose-dependent insulinotropic peptide (GIP) receptor (GIPR) in GIP-dependent Cushing's syndrome (CS) are unknown. Chronic adrenal stimulation by ACTH in Cushing's disease or GIP in GIP-dependent ACTH-independent macronodular adrenal hyperplasia both lead to the induction of genes implicated in adrenal proliferation and steroidogenesis. OBJECTIVE: The objective of the study was to identify genes differentially expressed specifically in GIP-dependent CS that could be implicated in the ectopic expression of GIPR. METHODS: We used the Affymetrix U133 plus 2.0 microarray oligochips to compare the whole genome expression profile of adrenal tissues from five cases of GIP-dependent bilateral ACTH-independent macronodular adrenal hyperplasia with CS, one case of GIP-dependent unilateral adenoma with CS, five cases of ACTH-dependent hyperplasias, and a pool of adrenals from 62 normal individuals. RESULTS: After data normalization and statistical filtering, 723 genes with differential expression were identified, including 461 genes or sequences with a known functional implication, classified in eight dominant functional classes. Specific findings include repression of perilipin, the overexpression of 13 G protein-coupled receptors, and the potential involvement of Rho-GTPases. We also isolated 94 probe sets potentially linked to the formation of GIP-dependent nodules adjacent to the diffuse hyperplasia. These included probe sets related to the linker histone H1 and repression of RXRa and CCND2. The expression profiles for eight genes were confirmed by real-time RT-PCR. CONCLUSION: This study identified an extensive series of potentially novel target candidate genes that could be implicated in the molecular mechanisms of ectopic expression of the GIPR as well as in the multistep progression of GIP-dependent CS.
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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".