The RET receptor tyrosine kinase causes activation of the β-catenin pathway
Bibliographic record
Abstract
341 The RET proto-oncogene encodes a receptor tyrosine kinase required for development of the kidney and neural crest derived cell types. Gain-of-function mutations in RET have been implicated in over 50% of sporadic Medullary thyroid carcinoma (MTC) and 90% of families with Multiple Endocrine Neoplasia type 2 (MEN 2). MEN 2 is associated with MTC as well as the adrenal tumour pheochromocytoma (PC), with or without hyperparathyroidism. The biochemical mechanisms by which the potent transforming and mitogenic signals of RET are transduced are still not clear. Here, we report a novel mechanism of RET-mediated signalling, through the activation of the β-catenin pathway. We show that the oncogenic form of the RET receptor, and its wildtype form upon activation, tyrosine phosphorylate β-catenin, resulting in the altered sub-cellular localization of β-catenin. Using a kinase dead mutant for RET, we also show that β-catenin is tyrosine phosphorylated in a RET kinase dependent manner. However, we also show that the association of RET and β-catenin is constitutive and is not dependent on tyrosine phosphorylation of either RET or β-catenin. We also demonstrate that the interaction between RET and β-catenin can be direct and can be independent of cytoplasmic kinase, SRC. Our biochemical data shows that RET can phosphorylate β-catenin at Y654, which is predicted to cause it’s dissociation from the E-cadherin complex, leading to accumulation of cytosolic and nuclear localization of β-catenin. Consistently with this, we show altered cellular localization of β-catenin was associated with the activation of TCF dependent transcription activity, using a TOPFLASH reporter. Recent studies have shown the aberrant expression of E-cadherin/ s-catenin levels in thyroid tumors. Our data suggest that the RET-induced activation of the β-catenin pathway may contribute to cellular transformation and driving malignant tumour progression in thyroid cancer.
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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".