Progesterone Receptor-B Regulation of Insulin-Like Growth Factor–Stimulated Cell Migration in Breast Cancer Cells via Insulin Receptor Substrate-2
Bibliographic record
Abstract
Progesterone action contributes to the signaling of many growth factor pathways relevant to breast cancer tumor biology, including the insulin-like growth factor (IGF) system. Previous work has shown that insulin receptor substrate-2 (IRS-2) but not IRS-1 levels were regulated by progestin in progesterone receptor-B (PR-B) isoform expressing MCF-7 cells (C4-12 PR-B). Furthermore, type 1 IGF receptor (IGF1R) signaling via IRS-2 correlated with the increased cell migration observed in a number of breast cancer cell lines. Consequently, in this study, we examined whether the elevation of IRS-2 protein induced by progestin was sufficient to promote IGF-I-stimulated cell motility. Treatment of C4-12 PR-B cells with progestin shifted the balance of phosphorylation from IRS-1 to IRS-2 in response to IGF-I. This shift in IRS-2 activation was associated with enhanced migration in C4-12 PR-B cells pretreated with progestin, but had no effect on cell proliferation or survival. Treatment of C4-12 PR-B cells with RU486, an antiprogestin, inhibited IGF-induced cell migration. Attenuation of IRS-2 expression using small interfering RNA resulted in decreased IGF-stimulated motility. In addition, IRS-2 knockdown resulted in an abrogation of PKB/Akt phosphorylation but not mitogen-activated protein kinase. Consequently, LY294002, a phosphoinositide-3-kinase inhibitor, abolished IGF-induced cell motility in progestin-treated C4-12 PR-B cells. These data show a role for the PR in functionally promoting growth factor signaling, showing that levels of IRS proteins can determine IGF-mediated biology, PR-B signaling regulates IRS-2 expression, and that IRS-2 can mediate IGF-induced cell migration via phosphoinositide-3-kinase in breast cancer cells.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".