The spectraplakin Dystonin antagonizes YAP activity and suppresses tumourigenesis
Bibliographic record
Abstract
Aberrant expression of the Spectraplakin Dystonin (DST) has been observed in various cancers, including those of the breast. However, little is known about its role in carcinogenesis. In this report, we demonstrate that Dystonin is a candidate tumour suppressor in breast cancer and provide an underlying molecular mechanism. We show that in MCF10A cells, Dystonin is necessary to restrain cell growth, anchorage-independent growth, self-renewal properties and resistance to doxorubicin. Strikingly, while Dystonin maintains focal adhesion integrity, promotes cell spreading and cell-substratum adhesion, it prevents Zyxin accumulation, stabilizes LATS and restricts YAP activation. Moreover, treating DST-depleted MCF10A cells with the YAP inhibitor Verteporfin prevents their growth. In vivo, the Drosophila Dystonin Short stop also restricts tissue growth by limiting Yorkie activity. As the two Dystonin isoforms BPAG1eA and BPAG1e are necessary to inhibit the acquisition of transformed features and are both downregulated in breast tumour samples and in MCF10A cells with conditional induction of the Src proto-oncogene, they could function as the predominant Dystonin tumour suppressor variants in breast epithelial cells. Thus, their loss could deem as promising prognostic biomarkers for breast 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 | 0.000 |
| 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".