Sorafenib inhibits cAMP-dependent ERK activation, cell proliferation, and in vitro cyst growth of human ADPKD cyst epithelial cells
Bibliographic record
Abstract
In autosomal dominant polycystic kidney disease (ADPKD), aberrant proliferation of the renal epithelial cells is responsible for the formation of numerable fluid-filled cysts, massively enlarged kidneys, and progressive loss of renal function. cAMP agonists, including arginine vasopressin, accelerate cyst epithelial cell proliferation through protein kinase A activation of the B-Raf/MEK/extracellular signal-regulated kinase (ERK) signaling pathway. The mitogenic effect of cAMP is equally potent and additive to growth factor stimulation. Here, we determined whether Sorafenib (BAY 43-9006), a small molecule Raf inhibitor, inhibits proliferation of cells derived from the cysts of human ADPKD kidneys. We found that nanomolar concentrations of Sorafenib reduced the basal activity of ERK, inhibited cAMP-dependent activation of B-Raf and MEK/ERK signaling, and caused a concentration-dependent inhibition of cell proliferation induced by cAMP, epidermal growth factor, or the combination of the two agonists. Sorafenib completely blocked in vitro cyst growth of human ADPKD cystic cells cultured within a three-dimensional collagen gel. These data demonstrate that cAMP-dependent proliferation of human ADPKD cyst epithelial cells is blocked by Sorafenib and suggest that small molecule B-Raf inhibitors may be a therapeutic option to reduce the mitogenic effects of cAMP on cyst expansion.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".