Bone Morphogenetic Proteins 2 and 5 Are Down-regulated in Adrenocortical Carcinoma and Modulate Adrenal Cell Proliferation and Steroidogenesis
Bibliographic record
Abstract
Bone morphogenetic proteins (BMP) have been shown to affect tumorigenesis in a variety of tumors. Quantitative PCR analysis revealed down-regulation of BMP2 and BMP5 in tissue samples from adrenocortical carcinoma and adrenocortical tumor cell lines compared with normal adrenal glands. Integrity of BMP-dependent pathways in these cell lines could be shown by activation of the Smad1/5/8 pathway with subsequent increase of ID protein expression upon incubation with BMP2 or BMP5. On a functional level, BMP treatment resulted in inhibition of cell proliferation and viability in a dose- and time-dependent manner. This growth inhibitory effect was associated with BMP-dependent reduction of AKT phosphorylation under baseline conditions and under insulin-like growth factor costimulation. Furthermore, steroidogenic function, including melanocortin-2 receptor and steroidogenic enzyme expressions, was profoundly reduced. In vitro demethylation treatment and overexpression of GATA6 resulted in reactivation of BMP-dependent pathways with concomitant modulation of steroidogenesis. Taken together, we show that loss of expression of members of the BMP family of ligands is a common finding in adrenocortical tumors and we provide evidence that BMP-dependent pathways are likely to be involved in the modulation of the malignant and functional phenotype of adrenocortical cancer cells.
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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".