miR-200b induces cell cycle arrest and represses cell growth in esophageal squamous cell carcinoma
Bibliographic record
Abstract
miR-200b is a pleiotropically acting microRNA in cancer progression, representing an attractive therapeutic target. We previously identified miR-200b as an invasiveness repressor in esophageal squamous cell carcinoma (ESCC), whereas further understanding is warranted to establish it as a therapeutic target. Here, we show that miR-200b mitigates ESCC cell growth by inducing G2-phase cell cycle arrest and apoptosis. The expression/activation of multiple key cell cycle regulators such as CDK1, CDK2, CDK4 and Cyclin B, and the Wnt/β-Catenin signaling are modulated by miR-200b. We identified CDK2 and PAF (PCNA-associated factor), two important tumor-promoting factors, as direct miR-200b targets in ESCC. Correlating with the frequent loss of miR-200b in ESCC, both CDK2 and PAF levels are significantly increased in ESCC tumors compared to case-matched normal tissues (n = 119, both P < 0.0001), and correlate with markedly reduced survival (P = 0.007 and P = 0.041, respectively). Furthermore, CDK2 and PAF are also associated with poor prognosis in certain subtypes of breast cancer (n = 1802) and gastric cancer (n = 233). Although CDK2 could not significantly mediate the biological function of miR-200b, PAF siRNA knockdown phenocopied while restored expression of PAF abrogated the biological effects of miR-200b on ESCC cells. Moreover, PAF was revealed to mediate the inhibitory effects of miR-200b on Wnt/β-Catenin signaling. Collectively, the pleiotropic effects of miR-200b in ESCC highlight its potential for therapeutic intervention in this aggressive disease.
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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 | 0.001 |
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 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".