β-catenin turnover is regulated by Nek10-mediated tyrosine phosphorylation in A549 lung adenocarcinoma cells
Bibliographic record
Abstract
β-catenin has influential roles affecting embryonic development, tissue homeostasis, and human diseases including cancer. Cellular β-catenin levels are exquisitely controlled by a variety of regulatory mechanisms. In the course of exploring the functions of the Nek10 tyrosine kinase, we observed that deletion of Nek10 in lung adenocarcinoma cells resulted in dramatic stabilization of β-catenin, suggestive of a Nek10 role in the control of β-catenin turnover. Nek10-deficient cells exhibited diminished ability to form tumorspheres in suspension, grow in soft agar, and colonize mouse lung tissue following tail vein injection. Mechanistically, Nek10 associates with the Axin complex, responsible for β-catenin degradation, 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, is impaired. This represents a divergent function within the Nek family, whose other members are serine-threonine kinases involved in different elements of the centrosomal cycle, primary cilia function, and DNA damage responses.
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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".