Actin Cytoskeleton Regulation of Epithelial Mesenchymal Transition in Metastatic Cancer Cells
Bibliographic record
Abstract
Epithelial-mesenchymal transition (EMT) is associated with loss of the cell-cell adhesion molecule E-cadherin and disruption of cell-cell junctions as well as with acquisition of migratory properties including reorganization of the actin cytoskeleton and activation of the RhoA GTPase. Here we show that depolymerization of the actin cytoskeleton of various metastatic cancer cell lines with Cytochalasin D (Cyt D) reduces cell size and F-actin levels and induces E-cadherin expression at both the protein and mRNA level. Induction of E-cadherin was dose dependent and paralleled loss of the mesenchymal markers N-cadherin and vimentin. E-cadherin levels increased 2 hours after addition of Cyt D in cells showing an E-cadherin mRNA response but only after 10-12 hours in HT-1080 fibrosarcoma and MDA-MB-231 cells in which E-cadherin mRNA level were only minimally affected by Cyt D. Cyt D treatment induced the nuclear-cytoplasmic translocation of EMT-associated SNAI 1 and SMAD1/2/3 transcription factors. In non-metastatic MCF-7 breast cancer cells, that express E-cadherin and represent a cancer cell model for EMT, actin depolymerization with Cyt D induced elevated E-cadherin while actin stabilization with Jasplakinolide reduced E-cadherin levels. Elevated E-cadherin levels due to Cyt D were associated with reduced activation of Rho A. Expression of dominant-negative Rho A mutant increased and dominant-active Rho A mutant decreased E-cadherin levels and also prevented Cyt D induction of E-cadherin. Reduced Rho A activation downstream of actin remodelling therefore induces E-cadherin and reverses EMT in cancer cells. Cyt D treatment inhibited migration and, at higher concentrations, induced cytotoxicity of both HT-1080 fibrosarcoma cells and normal Hs27 fibroblasts, but only induced mesenchymal-epithelial transition in HT-1080 cancer cells. Our studies suggest that actin remodelling is an upstream regulator of EMT in metastatic cancer cells.
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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".