MicroRNA-182 drives metastasis of primary sarcomas by targeting multiple genes
Bibliographic record
Abstract
Metastasis causes most cancer deaths, but is incompletely understood. MicroRNAs can regulate metastasis, but it is not known whether a single miRNA can regulate metastasis in primary cancer models in vivo. We compared the expression of miRNAs in metastatic and nonmetastatic primary mouse sarcomas and found that microRNA-182 (miR-182) was markedly overexpressed in some tumors that metastasized to the lungs. By utilizing genetically engineered mice with either deletion of or overexpression of miR-182 in primary sarcomas, we discovered that deletion of miR-182 substantially decreased, while overexpression of miR-182 considerably increased, the rate of lung metastasis after amputation of the tumor-bearing limb. Additionally, deletion of miR-182 decreased circulating tumor cells (CTCs), while overexpression of miR-182 increased CTCs, suggesting that miR-182 regulates intravasation of cancer cells into the circulation. We identified 4 miR-182 targets that inhibit either the migration of tumor cells or the degradation of the extracellular matrix. Notably, restoration of any of these targets in isolation did not alter the metastatic potential of sarcoma cells injected orthotopically, but the simultaneous restoration of all 4 targets together substantially decreased the number of metastases. These results demonstrate that a single miRNA can regulate metastasis of primary tumors in vivo by coordinated regulation of multiple genes.
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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 | 0.002 | 0.003 |
| 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) | 0.000 | 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 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".