MiR-181a-driven downregulation of cholesterol biosynthesis through SREBP2 inhibition suppresses uveal melanoma metastasis
Bibliographic record
Abstract
Abstract Background uveal melanoma (UM) is the most common primary intraocular tumor in adults, with metastasis being the leading cause of death. However, effective treatments for metastatic UM remain limited. Emerging evidence suggests that cholesterol metabolism plays a role in cancer progression, but its impact on UM metastasis is not well understood. Methods we investigated the effects of miR-181a on UM metastasis using multiple UM cell lines and a suprachoroidal injection mouse model. Functional assays, including migration, invasion, and cancer stem-like cell (CSC) formation, were performed. The target of miR-181a was identified through bioinformatics, luciferase assays, and western blotting. Cholesterol levels were measured, and in vitro and in vivo studies assessed the therapeutic potential of combining miR-181a with crizotinib. Results miR-181a significantly decreases UM cell migration, invasion, and metastasis. Mechanistically, miR-181a was found to target sterol regulatory element-binding protein 2 (SREBP2), thereby inhibiting cholesterol biosynthesis. This decrease in cholesterol levels hindered reduced epithelial-to-mesenchymal transition (EMT) and led to a decline in cancer stem-like cell (CSC) populations in UM. Furthermore, elevated cholesterol or overexpression of SREBP2 abrogated the anti-metastatic effects of miR-181a. Additionally, a combination of miR-181a and crizotinib significantly inhibited metastasis, both in vitro and in vivo. Conclusions miR-181a inhibits UM metastasis by targeting SREBP2 and reducing cholesterol biosynthesis. Its combination with crizotinib may provide a promising therapeutic strategy for metastatic UM.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.434 | 0.001 |
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 teacher head, 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".