Functional Analysis of FOXC1 in TGF‐β Mediated Epithelial to Mesenchymal Transition
Bibliographic record
Abstract
Elevated expression of FOXC1 has been detected in many metastatic cancers characterised by mesenchymal characteristics. Furthermore in development FOXC1 functions in the formation mesenchymal derived tissues including the axial skeleton and eye that are derived through transforming growth factor beta (TGFβ) signalling pathways. However it is not known whether FOXC1 functions in initiation of EMT by TGFβ signalling. We utilized the mouse mammary epithelial cell line NMUMG, to test what role FOXC1 plays in EMT. Treatment of NMUMG cells with 5 ng/ml of TGFβ induced EMT and was accompanied by a down regulation of the epithelial marker E‐cadherin and an upregulation of mesenchymal markers N‐cadherin and Vimentin and Snail1. Elevated levels of Foxc1 mRNA were detected at 24 and 48 hours of treatment. To test whether this upregulation of Foxc1 was necessary for initiation of EMT we used RNA interference to reduce levels of by 60‐85%. When treated with TGFβ, knock down of Foxc1 had no effect on EMT progression based on morphological assessment, and through changes in gene expression monitored by quantitative PCR and immunofluorescence assays. Elevated N‐cadherin mRNA expression was detected in Foxc1 knock down cells prior to the initiation of EMT. In wound closure assays Foxc1 knock down cells demonstrated an increase in cell migration compared to control cells. We next created an NMUMG cell line expressing Foxc1 under the control of a tetracycline inducible system. When Foxc1 levels were elevated in the absence of TGFβ, NMUMG cells continued to express epithelial markers and an induction in the expression mesenchymal markers (N‐cadherin, Vimentin, Snail1) was not observed. Our data suggest that Foxc1 is not necessary or sufficient for the initiation of EMT by TGFβ in murine cells lines.
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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) | 0.002 | 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".