Wnt/PCP signaling mediates breast cancer metastasis by promoting pro-invasive protrusion formation in collectively motile leader cells
Bibliographic record
Abstract
Abstract As evidence supporting essential roles for collective cell migration in carcinoma metastasis continues to accumulate, a better understanding of the underlying cellular and molecular mechanisms will be critical to translating these findings to the treatment of advanced cancers. Here we report that Wnt/PCP, a non-canonical Wnt signaling pathway, mediates breast cancer collective migration and metastasis. We observe that mammary gland-specific knockout of Vangl2 , a tetraspanin-like scaffolding protein required for Wnt5a-induced signaling and motility in cultured breast cancer cell lines, results in a striking decrease in metastatic efficiency but not primary tumor growth in the MMTV-NDL transgenic mouse model of HER2-positive breast cancer. We also observe that expression levels of core Wnt/PCP components Wnt5a , Vangl1 and Vangl2 are selectively elevated in K14-positive leader cells relative to follower cells within a collectively migrating cohort, and that Vangl2 expression selectively promotes RhoA activation in leading edge cells. Moreover, Vangl expression drives collective migration in three-dimensional ex vivo tumor organoids, and Vangl protein specifically accumulates within pro-migratory filamentous actin-rich protrusions of leader cells. Together, our observations point to a model whereby Wnt/PCP upregulation facilitates breast tumor collective cell motility by selectively augmenting the formation pro-migratory protrusions within leader 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".