Snail Induction of Epithelial to Mesenchymal Transition in Tumor Cells Is Accompanied by MUC1 Repression andZEB1 Expression
Bibliographic record
Abstract
E-cadherin protein plays a key role in the establishment and maintenance of adherent junctions. Recent evidence implicates the transcription factor Snail in the blockage of E-cadherin expression in fibroblasts and some epithelial tumor cells through direct binding to three E-boxes in the E-cadherin promoter. Transfection of Snail into epithelial cells leads to a more fibroblastic phenotype. Cells expressing Snail presented a scattered flattened phenotype with low intercellular contacts. Other epithelial markers like Cytokeratin 18 or MUC1 were also repressed. The effects of Snail on MUC1 transcription were mediated by two E-boxes present in the proximal promoter. Snail also induced expression of the mesenchymal markers fibronectin and LEF1 and the transcription repressor ZEB1. ZEB1 and Snail had a similar pattern of expression in epithelial cell lines, and both were induced by overexpression of ILK1, a kinase that causes the loss of E-cadherin and the acquisition of a fibroblastic phenotype. Snail overexpression in several cell lines raised ZEB1 RNA levels and increased the activity of ZEB1 promoter. ZEB1 could also repress E-cadherin and MUC1 promoters but less strongly than Snail. However, since ZEB1 expression persisted after Snail was down-regulated, ZEB1 may regulate epithelial genes in several tumor cell 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".