Slug-upregulated miR-221 promotes breast cancer progression through suppressing E-cadherin expression
Bibliographic record
Abstract
It is generally regarded that E-cadherin is downregulated during tumorigenesis via Snail/Slug-mediated E-cadherin transcriptional reduction. However, this transcriptional suppressive mechanism cannot explain the failure of producing E-cadherin protein in metastatic breast cancer cells after overexpressing E-cadherin mRNA. Here we reveal a novel mechanism that E-cadherin is post-transcriptionally regulated by Slug-promoted miR-221, which serves as an additional blocker for E-cadherin expression in metastatic tumor cells. Profiling the predicted E-cadherin-targeting miRNAs in breast cancer tissues and cells showed that miR-221 was abundantly expressed in breast tumor and metastatic MDA-MB-231 cells and its level was significantly higher in breast tumor or MDA-MB-231 cells than in distal non-tumor tissue and low-metastatic MCF-7 cells, respectively. MiR-221, which level inversely correlated with E-cadherin level in breast cancer cells, targeted E-cadherin mRNA open reading frame (ORF) and suppressed E-cadherin protein expression. Depleting or increasing miR-221 level in breast cancer cells induced or decreased E-cadherin protein level, leading to suppressing or promoting tumor cell progression, respectively. Moreover, miR-221 was specifically upregulated by Slug but not Snail. TGF-β treatment enhanced Slug activity and thus increased miR-221 level in MCF-7 cells. In summary, our results provide the first evidence that Slug-upregulated miR-221 promotes breast cancer progression via reducing E-cadherin expression.
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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".