Functional Characterization of the Kinase Activation Loop in Nucleophosmin (NPM)-Anaplastic Lymphoma Kinase (ALK) Using Tandem Affinity Purification and Liquid Chromatography-Mass Spectrometry
Bibliographic record
Abstract
Previous studies have shown that the kinase activation loop (KAL) of the oncogenic fusion protein NPM-ALK regulates its overall tyrosine phosphorylation status and tumorigenicity. Using tandem affinity purification-mass spectrometry, we assessed how the KAL of NPM-ALK regulates the phosphorylation status of its individual tyrosines. Using the lysates of GP293 cells transfected with NPM-ALK, our highly reproducible results showed evidence of phosphorylation in all 3 tyrosines in KAL and 8 tyrosines outside KAL. We created 7 KAL mutants, each of which carried a Tyr-to-Phe mutation of >or=1 of the 3 tyrosines in KAL. A complete loss of the 8 phosphotyrosines outside KAL was found in 3 KAL mutants, and their oncogenicity (assessed by cell viability, colony formation, and the ability to phosphorylate effector proteins) was abrogated. A partial loss of the 8 phosphotyrosines was found in 4 KAL mutants, but their oncogenicity did not show simple correlation with the number of residual phosphotyrosines. Tyr-to-Phe mutations of each of the 8 phosphotyrosines outside KAL did not result in a significant decrease in the oncogenicity. In conclusion, we have provided details of how the KAL in NPM-ALK regulates its tyrosine phosphorylation pattern. Our results challenge some of the current concepts regarding the relationship between the tyrosine phosphorylation and oncogenicity of NPM-ALK.
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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) | 0.000 | 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".