Statins downregulate<scp>YAP</scp>and<scp>TAZ</scp>and exert anti‐cancer effects in canine mammary tumour cells
Bibliographic record
Abstract
Canine mammary tumours (CMTs) are the most common neoplasms in intact bitches, and few chemotherapeutic options are available for highly invasive and metastatic tumours. Recent studies have shown the potential involvement of dysregulated Hippo signalling in CMT development and progression. Statins can activate the Hippo pathway by blocking protein geranylgeranylation (GGylation), resulting in decreased expression and activity of the transcriptional co-activators YAP and TAZ. In this study, we therefore sought to determine if statins could exert anti-cancer effects in CMT cells. Our results demonstrate that Atorvastatin and Fluvastatin are cytotoxic to two CMT cell lines (CMT9 and CMT47), with ED50 values ranging from 0.95 to 23.5 μM. Both statins acted to increase apoptosis and promote cell cycle arrest. Both statins also decreased YAP and TAZ expression and reduced the mRNA levels of key Hippo transcriptional target genes known to be involved in breast cancer progression and chemoresistance (CYR61, CTGF and RHAMM). Moreover, both statins effectively inhibited cell migration and anchorage independent growth, but did not influence matrix invasion. Taken together, our results demonstrate for the first time that statins act upon the Hippo pathway in CMT cells to counteract several molecular and cellular hallmarks of cancer. These findings suggest that targeting the Hippo pathway with statins represents a novel and promising approach for the treatment canine mammary gland cancers.
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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 | 0.001 |
| 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".