Engulfment Protein GULP Is Regulator of Transforming Growth Factor-β Response in Ovarian Cells
Bibliographic record
Abstract
Transforming growth factor β (TGF-β) is a key regulatory molecule with pleiotropic effects on cell growth, migration, and invasion. As a result, impairment of proper TGF-β signaling is central to tumorigenesis and metastasis. The TGF-β receptor V (TGFBRV or LRP1) has been shown to be responsible for TGF-β-mediated cell growth inhibition in Chinese hamster ovary (CHO) cells. The LRP1 adapter protein GULP mediates internalization of the various LRP1-specific ligands, and we hypothesize that GULP acts as a novel regulator of TGF-β signaling in ovarian cells. CHO cells that overexpress exogenous GULP (FL) demonstrate enhancement in growth inhibition, migration, and invasion from TGF-β treatment, whereas cells that lack GULP (AS) show impairment of growth inhibition and decreased migration and invasion. The enhanced TGF-β response in FL cells was confirmed by a prolonged TGF-β-induced SMAD3 phosphorylation, whereas a shortening of the phosphorylation event is observed in AS cells. Mechanistically, the presence of GULP retains the TGF-β in a signaling-competent early endosome for enhanced signaling. To address this mechanism in a physiological setting, TGF-β insensitive ovarian adenocarcinoma cells (HEY) have a very low GULP expression level, similar to the observation made in a wide selection of human ovarian adenocarcinomas. Transfection of GULP into the HEY cells restored the TGF-β responsiveness, as measured by SMAD3 phosphorylation and impairment of cell growth. Because GULP expression positively regulates TGF-β signaling leading to growth inhibition, this may represent an attractive target to achieve TGF-β responsiveness in ovarian 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 | 0.001 |
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".