EGF-Induced ERK Activation Promotes CK2-Mediated Disassociation of α-Catenin from β-Catenin and Transactivation of β-Catenin
Bibliographic record
Abstract
Increased transcriptional activity of beta-catenin resulting from Wnt/Wingless-dependent or -independent signaling has been detected in many types of human cancer, but the underlying mechanism of Wnt-independent regulation remains unclear. We demonstrate here that EGFR activation results in disruption of the complex of beta-catenin and alpha-catenin, thereby abrogating the inhibitory effect of alpha-catenin on beta-catenin transactivation via CK2alpha-dependent phosphorylation of alpha-catenin at S641. ERK2, which is activated by EGFR signaling, directly binds to CK2alpha via the ERK2 docking groove and phosphorylates CK2alpha primarily at T360/S362, subsequently enhancing CK2alpha activity toward alpha-catenin phosphorylation. In addition, levels of alpha-catenin S641 phosphorylation correlate with levels of ERK1/2 activity in human glioblastoma specimens and with grades of glioma malignancy. This EGFR-ERK-CK2-mediated phosphorylation of alpha-catenin promotes beta-catenin transactivation and tumor cell invasion. These findings highlight the importance of the crosstalk between EGFR and Wnt pathways in tumor development.
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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) | 0.002 | 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".