FOXC1 Regulates FGFR1 Isoform Switching to Promote Invasion Following TGFβ-Induced EMT
Bibliographic record
Abstract
Abstract Epithelial-to-mesenchymal transition (EMT) is an important physiologic process that drives tissue formation during development, but also contributes to disease pathogenesis, including fibrosis and cancer metastasis. Elevated expression of the FOXC1 transcription factor has been detected in several metastatic cancers that have undergone EMT. Therefore, mechanistic insight into the role of FOXC1 in the initiation of the EMT process was sought. It was determined that although Foxc1 transcript expression was elevated following TGFβ1-induced EMT of NMuMG cells, FOXC1 was not required for this induction. RNA sequencing revealed that the mRNA levels of FGF receptor 1-isoform IIIc (Fgfr1-IIIc), normally activated upon TGFβ1 treatment, were reduced in Foxc1 knockdown cells, and overexpression of Foxc1 was sufficient to induce Fgfr1-IIIc expression, but not EMT. Chromatin immunoprecipitation experiments demonstrated that FOXC1 binds to an Fgfr1 upstream regulatory region and that FOXC1 activates an Fgfr1 promoter element. Furthermore, elevated expression of Foxc1 led to increased Fgfr1-IIIc transcript. Foxc1 knockdown impaired the FGF2-mediated three-dimensional migratory ability of NMuMG cells, which was rescued by expression of FGFR1. In addition, elevated expression of FOXC1 and FGFR1 was also observed in migratory mesenchymal MDA-MB-231 breast cancer cells. Together, these results define a role for FOXC1 in specifying an invasive mesenchymal cell type by promoting FGFR1 isoform switching following induction of TGFβ1-mediated EMT. Mol Cancer Res; 15(10); 1341–53. ©2017 AACR.
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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".