Amyloid aggregates accumulate in melanoma metastasis driving YAP mediated tumor progression
Bibliographic record
Abstract
Abstract Melanoma progression is generally associated to increased Yes-associated protein (YAP) mediated transcription. Actually, mechanical signals from the extracellular matrix are sensed by YAP, which activates proliferative genes expression, promoting melanoma progression and drug resistance. Which and how extracellular signals induce mechanotransduction is not completely understood. Herein, by secretome studies, we revealed an extracellular accumulation of amyloidogenic proteins, i.e. premelanosome protein (PMEL), together with proteins that assist amyloids maturation into fibrils. Indeed, we confirmed the presence of amyloid-like aggregates similar to those detected in Alzheimer disease. These aggregates were enriched in metastatic cell lines as well as in human melanoma biopsies, compared to their primitive counterpart. Mechanistically, we proved that beta-secretase (BACE) regulates the maturation of these aggregates and that its inhibition hampers YAP activity. Moreover, recombinant PMEL fibrils induce per se mechanotransduction promoting YAP activation. Finally, BACE inhibition affects cell proliferation and increases drug sensitivity. These results highlight the importance of amyloids for melanoma survival and the potential of beta-secretase inhibitors as new therapeutic approach to metastatic melanoma.
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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".