The chimeric protein tyrosine kinase ETV6-NTRK3 requires both Ras-Erk1/2 and PI3-kinase-Akt signaling for fibroblast transformation.
Bibliographic record
Abstract
There is increasing interest in the potential role of the NTRK family of neurotrophin receptors in human neoplasia. These receptor protein tyrosine kinases (PTKs) are well-known mediators of neuronal cell survival and differentiation, but altered NTRK signaling has also been implicated in mesenchymal, hematopoietic, and epithelial malignancies. We recently identified a novel gene fusion involving one of the neurotrophin receptor genes, NTRK3, in the pediatric solid tumor, congenital fibrosarcoma. In these tumors (and subsequently demonstrated in several other human malignancies), a t(12;15)(p13;q25) rearrangement fuses the 3' portion of the ETV6 gene with exons encoding the PTK domain of NTRK3. The resulting ETV6-NTRK3 fusion protein functions as a chimeric PTK with potent transforming activity. However, previous studies failed to detect interactions between ETV6-NTRK3 and molecules known to link wild-type NTRK3 to its two major effector pathways, namely the Ras-Raf1-Mek1-Erk1/2 mitogenic pathway or the phosphatidylinositol 3'-kinase pathway leading to activation of the AKT survival factor. Therefore, it remains unknown whether ETV6-NTRK3 transformation involves altered NTRK3 signaling. We now report that ETV6-NTRK3 expression in NIH3T3 cells leads to constitutive activation of Mek1 and Akt, as well as to constitutively high expression of cyclin D1. ETV6-NTRK3-induced soft agar colony formation was almost completely abolished by inhibition of either the Ras-Raf1-Mek1-Erk1/2 or the phosphatidylinositol 3'-kinase-Akt pathway. Moreover, this inhibition dramatically reduced expression of cyclin D1. Our results indicate that ETV6-NTRK3 transformation involves a link between known NTRK3 signaling pathways and aberrant cell cycle progression and that Mek1 and Akt activation act synergistically to mediate these effects.
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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) | 0.002 | 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".