YAP promotes the proliferation of neuroblastoma cells through decreasing the nuclear location of p27<sup>Kip1</sup> mediated by Akt
Bibliographic record
Abstract
Abstract Objective We aimed to investigate the roles and underlying mechanisms of YAP in the proliferation of neuroblastoma cells. Methods The expression level of YAP was evaluated by Western blotting and immunocytochemistry. Cell viability, cell proliferation and growth were detected by CCK‐8, PH3 and Ki67 immunostaining, and the real‐time cell analyser system. The nuclear and cytoplasmic proteins of p27Kip1 were dissociated by the nuclear‐cytosol extraction kit and were detected by Western blotting and immunocytochemistry. mRNA levels of Akt, CDK5 and CRM1 were determined by qRT‐PCR. Results YAP was enriched in SH‐SY5Y cells (a human neuroblastoma cell line). Knock‐down of YAP in SH‐SY5Y cells or SK‐N‐SH cell line (another human neuroblastoma cell line) significantly decreased cell viability, inhibited cell proliferation and growth. Mechanistically, knock‐down of YAP increased the nuclear location of p27Kip1, whereas serum‐induced YAP activation decreased the nuclear location of p27Kip1 and was required for cell proliferation. Meanwhile, overexpression of YAP in these serum‐starved SH‐SY5Y cells decreased the nuclear location of p27Kip1, promoted cell proliferation and overexpression of p27Kip1 in YAP‐activated cells inhibited cell proliferation. Furthermore, knock‐down of YAP reduced Akt mRNA and protein levels. Overexpression of Akt in YAP‐downregulated cells decreased the nuclear location of p27Kip1 and accelerated the proliferation of SH‐SY5Y cells. Conclusions Our studies suggest that YAP promotes the proliferation of neuroblastoma cells through negatively controlling the nuclear location of p27Kip1 mediated by Akt.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".