Role of Glycogen Synthase Kinase-3 in Cell Fate and Epithelial-Mesenchymal Transitions
Bibliographic record
Abstract
Epithelial cells usually exist as sheets of immotile, tightly packed, well-coupled, polarized cells with distinct apical, basal and lateral surfaces. Remarkably, these cells can dramatically alter their morphology to become motile, fibroblast-like mesenchymal cells in a process of epithelial-mesenchymal transition (EMT). This process and the reverse, mesenchymal-epithelial transition, occur repeatedly during normal embryonic development. A phenomenon similar to physiological EMT occurs during the pathophysiological progression of some cancers. Tumours of epithelial origin, as they transform to malignancy, appear to exploit the innate plasticity of epithelial cells, with EMT conferring increased invasiveness and metastatic potential. Key to the maintenance of epithelial cell identity is the expression of E-cadherin, a protein that is required for tight intercellular adhesion along the lateral surfaces of adjacent epithelial cells. Loss of functional E-cadherin is a critical event in EMT. An important regulator of E-cadherin expression is the protein Snail, a zinc-finger transcriptional repressor. Snail contains several consensus sites for the kinase, glycogen synthase kinase-3 (GSK-3), and accumulating evidence indicates that it is a GSK-3 substrate. Phosphorylation of Snail by GSK-3 facilitates its proteasomal degradation. Conversely, inhibition of GSK-3 leads to Snail accumulation, E-cadherin downregulation, and development of EMT in cultured epithelial cells. Several signalling pathways implicated in the progression of EMT, including the Wnt and phosphoinositide 3-kinase pathways, use GSK-3 to mediate their responses. In these pathways, GSK-3's regulation of other transcriptional effectors like beta-catenin works in concert with changes in Snail to orchestrate the EMT process. This review focuses on the emerging role of GSK-3 as a modulator of cell fate and EMT in the contexts of development, in vitro cell culture and cancer.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".