MiR‐128 up‐regulation inhibits Reelin and DCX expression and reduces neuroblastoma cell motility and invasiveness
Bibliographic record
Abstract
ABSTRACT MicroRNAs are a class of sophisticated regulators of gene expression, acting as post‐transcriptional inhibitors that recognize their target mRNAs through base pairing with short regions along the 3'UTRs. Several microRNAs are tissue specific, suggesting a specialized role in tissue differentiation or maintenance, and quite a few are critically involved in tumorigenesis. We studied miR‐128, a brain‐enriched microRNA, in retinoic acid‐differentiated neuroblastoma cells, and we found that this microRNA is up‐regulated in treated cells, where it down‐modulates the expression of two proteins involved in the migratory potential of neural cells: Reelin and DCX. Consistently, miR‐128 ectopic overexpression suppressed Reelin and DCX, whereas the LNA antisensemediated miR‐128 knockdown caused the two proteins to increase. Ectopic miR‐128 overexpression reduced neuroblastoma cell motility and invasiveness, and impaired cell growth. Finally, the analysis of a small series of primary human neuroblastomas showed an association between high levels of miR‐128 expression and favorable features, such as favorable Shimada category or very young age at diagnosis. Thus, we provide evidence for a role for miR‐128 in the molecular events modulating neuroblastoma progression and aggressiveness.—Evangelisti, C., Florian, M. C., Massimi, I., Dominici, C., Giannini, G., Galardi, S., Buè, M. C., Massalini, S., McDowell, H. P., Messi, E., Gulino, A., Farace, M. G., Ciafrè, S. A. MiR‐128 up‐regulation inhibits Reelin and DCX expression and reduces neuroblastoma cell motility and invasiveness. FASEBJ. 23, 4276‐4287 (2009). www.fasebj.org
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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".