miR-200b suppresses invasiveness and modulates the cytoskeletal and adhesive machinery in esophageal squamous cell carcinoma cells via targeting Kindlin-2
Bibliographic record
Abstract
To further our understanding of the pathobiology of esophageal squamous cell carcinoma (ESCC), we previously performed microRNA profiling that revealed downregulation of miR-200b in ESCC. Using quantitative real-time PCR applied to 88 patient samples, we confirmed that ESCC tumors expressed significantly lower levels of miR-200b compared with the respective adjacent benign tissues (P = 0.003). Importantly, downregulation of miR-200b significantly correlated with shortened survival (P = 0.025), lymph node metastasis (P = 0.002) and advanced clinical stage (P = 0.020) in ESCC patients. Quantitative mass spectrometry identified 57 putative miR-200b targets, including Kindlin-2, previously implicated in the regulation of tumor invasiveness and actin cytoskeleton in other cell types. Enforced expression of miR-200b mimic in ESCC cells led to a decrease of Kindlin-2 expression, whereas transfection of miR-200b inhibitor induced Kindlin-2 expression. Furthermore, transfection of miR-200b mimic or knockdown of Kindlin-2 in ESCC cells decreased cell protrusion and focal adhesion (FA) formation, reduced cell spreading and invasiveness/migration. Enforced expression of Kindlin-2 largely abrogated the inhibitory effects of miR-200b on ESCC cell invasiveness. Mechanistic studies revealed that Rho-family guanosine triphosphatases and FA kinase mediated the biological effects of the miR-200b-Kindlin-2 axis in ESCC cells. To conclude, loss of miR-200b, a frequent biochemical defect in ESCC, correlates with aggressive clinical features. The tumor suppressor effects of miR-200b may be due to its suppression of Kindlin-2, a novel target of miR-200b that modulates actin cytoskeleton, FA formation and the migratory/invasiveness properties of ESCC.
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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".