NPM-ALK: The Prototypic Member of a Family of Oncogenic Fusion Tyrosine Kinases
Bibliographic record
Abstract
Anaplastic lymphoma kinase (ALK) was first identified in 1994 with the discovery that the gene encoding for this kinase was involved in the t(2;5)(p23;q35) chromosomal translocation observed in a subset of anaplastic large cell lymphoma (ALCL). The NPM-ALK fusion protein generated by this translocation is a constitutively active tyrosine kinase, and much research has focused on characterizing the signalling pathways and cellular activities this oncoprotein regulates in ALCL. We now know about the existence of nearly 20 distinct ALK translocation partners, and the fusion proteins resulting from these translocations play a critical role in the pathogenesis of a variety of cancers including subsets of large B-cell lymphomas, nonsmall cell lung carcinomas, and inflammatory myofibroblastic tumours. Moreover, the inhibition of ALK has been shown to be an effective treatment strategy in some of these malignancies. In this paper we will highlight malignancies where ALK translocations have been identified and discuss why ALK fusion proteins are constitutively active tyrosine kinases. Finally, using ALCL as an example, we will examine three key signalling pathways activated by NPM-ALK that contribute to proliferation and survival in ALCL.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".