Impaired MicroRNA Processing Facilitates Breast Cancer Cell Invasion by Upregulating Urokinase-Type Plasminogen Activator Expression
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Bibliographic record
Abstract
Global mature microRNA (miRNA) expression is downregulated in cancers, and impaired miRNA processing enhances cancer cell proliferation. These findings indicate that the miRNA system generally serves as a negative regulator during cancer progression. In this study, we investigated the role of the miRNA system in cancer cell invasion by determining the effect of damaging miRNA processing on invasion-essential urokinase-type plasminogen activator (uPA) expression in breast cancer cells. Short hairpin RNAs specific for Drosha, DGCR8, and Dicer, key components of miRNA processing machinery, were introduced into 2 breast cancer cell lines with high uPA expression and 2 lines with poor uPA expression. Knockdown of Drosha, DGCR8, or Dicer led to even higher uPA expression in cells with high uPA expression, while it was unable to increase uPA level in cells with poor uPA expression, suggesting that the miRNA system most likely impacts uPA expression as a facilitator. In cells with high uPA expression, knockdown of Drosha, DGCR8, or Dicer substantially increased in vitro invasion, and depleting uPA abrogated enhanced invasion. These results thus link the augmented invasion conferred by impaired miRNA processing to upregulated uPA expression. uPA mRNA was a direct target of miR-193a/b and miR-181a, and a higher uPA level in cells with impaired miRNA processing resulted from less mature miR-193a/b and miR-181a processed from their respective primary miRNAs. Importantly, the levels of mature miR-193a, miR-193b, and miR-181a, but not their respective primary miRNAs, were lower in high uPA-expressing cells compared to cells with low uPA expression, and this apparently attributed to lower Drosha/DGCR8 expression in high uPA-expressing cells. This study suggests that less efficient miRNA processing can be a mechanism responsible for reduced levels of mature forms of tumor-suppressive miRNAs frequently detected in cancers.
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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) | 0.000 | 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 it