Insulin-like growth factor 1 receptor stabilizes the ETV6–NTRK3 chimeric oncoprotein by blocking its KPC1/Rnf123-mediated proteasomal degradation
Bibliographic record
Abstract
Many oncogenes, including chimeric oncoproteins, require insulin-like growth factor 1 receptor (IGF1R) for promoting cell transformation. The ETS variant 6 (ETV6)–neurotrophic receptor tyrosine kinase 3 (NTRK3) (EN) chimeric tyrosine kinase is expressed in mesenchymal, epithelial, and hematopoietic cancers and requires the IGF1R axis for transformation. However, current models of IGF1R-mediated EN activation are lacking mechanistic detail. We demonstrate here that IGF-mediated IGF1R stimulation enhances EN tyrosine phosphorylation and that blocking IGF1R activity or decreasing protein levels of the adaptor protein insulin receptor substrate 1/2 (IRS1/2) results in rapid EN degradation. This was observed both in vitro and in vivo in fibroblast and breast epithelial cell line models and in MO91, an EN-expressing human leukemia cell line. Stable isotope labeling with amino acids in cell culture (SILAC)–based MS analysis identified the E3 ligase RING-finger protein 123 (Rnf123, more commonly known as KPC1) as an EN interactor upon IGF1R/insulin receptor (INSR) inhibitor treatment. KPC1/Rnf123 ubiquitylated EN in vitro , and its overexpression decreased EN protein levels. In contrast, KPC1/Rnf123 knockdown rendered EN resistant to IGF1R inhibitor–mediated degradation. These results support a critical function for IGF1R in protecting EN from KPC1/Rnf123-mediated proteasomal degradation. Attempts to therapeutically target oncogenic chimeric tyrosine kinases have traditionally focused on blocking kinase activity to restrict downstream activation of essential signaling pathways. In this study, we demonstrate that IGF1R inhibition results in rapid ubiquitylation and degradation of the EN oncoprotein through a proteasome-dependent mechanism that is reversible, highlighting a potential strategy for targeting chimeric tyrosine kinases in 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 | 0.001 |
| 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".