β-Catenin Inhibitor ICAT Modulates the Invasive Motility of Melanoma Cells
Bibliographic record
Abstract
Inhibitor of β-catenin and TCF (ICAT) inhibits β-catenin transcriptional activity by competing with T-cell factor/lymphoid enhancer factor. We documented high ICAT levels in human melanoma cells, in which β-catenin signaling is frequently deregulated, finding a correlation with the capacity to form metastases in nude mice. Ectopic expression of ICAT in melanoma cells did not affect their proliferation but increased cell motility and Matrigel invasion of metastatic cells in a manner relying upon stable ICAT-β-catenin interaction. This effect was associated with conversion of an elongated/mesenchymal phenotype to a round/amoeboid phenotype in the absence of similar effects on elongated morphology of nonmetastatic melanoma cells. Transition from mesenchymal to amoeboid movement was associated with decreased levels of NEDD9 and activated Rac1, a positive regulator of mesenchymal movement. Ectopic ICAT promoted colonization of melanoma cells in the lungs of nude mice, suggesting an increase in metastatic potential. Together, our results showed that by downregulating Rac signaling in metastatic melanoma cells, ICAT increased their invasive motility by promoting a morphologic variation that facilitates a favorable adaptation to their microenvironment.
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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".