NEK10 tyrosine phosphorylates β-catenin to regulate its cytoplasmic turnover
Bibliographic record
Abstract
Abstract Nek kinases are involved in regulating several different elements of the centrosomal cycle, primary cilia function, and DNA damage responses. Unlike the other members of the Nek family, which are serine-threonine kinases, Nek10 preferentially targets tyrosines. Nek10 appears to have a broad role in DNA damage responses, regulating a MAPK-activated G2/M checkpoint following UV irradiation and influencing the p53-mediated activation induced by genotoxicity. In an attempt to identify additional Nek10 functions, we characterized the effect of Nek10 deletion in lung cancer cells, where it is relatively highly expressed. Nek10 absence led to an increase in both the signaling and adherens junctions pools of β-catenin. Mechanistically, Nek10 associates with the Axin complex where it phosphorylates β-catenin at Tyr30, located within the regulatory region governing β-catenin turnover. In the absence of Nek10 phosphorylation, GSK3-mediated phosphorylation of β-catenin, a prerequisite for its turnover, was significantly impaired. Stabilization of β-catenin driven by Nek10 loss diminished the ability of cells to form tumorspheres in suspension, grow in soft agar, and colonize mouse lung tissue following tail vein injections.
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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) | 0.003 | 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".