Deciphering the Mechanotransduction Symphony: Stiffness-Dependent Interplay of YAP and β-Catenin in Breast Cancer Metastasis
Bibliographic record
Abstract
Metastatic breast cancer poses a formidable clinical challenge, demanding a comprehensive understanding of the intricate signaling networks orchestrating disease progression. Herein, our findings revealed a pronounced increase in the nuclear translocation of both YAP and β-catenin in MDA-MB-231 cells exposed to a stiff substrate (32 kPa). Intriguingly, YAP knockdown resulted in elevated β-catenin nuclear translocation on soft substrates (2 kPa), while no significant change was observed on stiff substrates. Concurrently, the expression of Wnt/β-catenin downstream genes ( CCND1 and AXIN2 ) and cell migration were downregulated in MDA-MB-231 cells on stiff substrates following YAP knockdown. Conversely, on soft substrates, β-catenin nuclear localization, downstream gene expression, and cell migration remained unaltered unless both YAP and β-catenin were concurrently silenced, highlighting the compensatory role of β-catenin in response to YAP depletion in the cellular context of mechanotransduction within metastatic breast cancer cells. Moreover, our investigation revealed the significant impact of myosin-II and cell confluency on the interplay between YAP and β-catenin. Thus, we elucidated a paradigm in which β-catenin assumes a compensatory role in response to YAP knockdown, particularly under distinct mechanical conditions. The interplay is finely tuned to the mechanical microenvironment, highlighting the mechanosensitivity of this compensatory mechanism.
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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".