The pathobiology of the oncogenic tyrosine kinase NPM-ALK: a brief update
Bibliographic record
Abstract
Extensive research has been carried out in the past two decades to study the pathobiology of nucleophosmin-anaplastic lymphoma kinase (NPM-ALK), which is an oncogenic fusion protein found exclusively in a specific type of T-cell lymphoid malignancy, namely ALK-positive anaplastic large cell lymphoma. Results from these studies have provided highly useful insights into the mechanisms by which a constitutively tyrosine kinase, such as NPM-ALK, promotes tumorigenesis. Several previous publications have comprehensively summarized the advances in this field. In this review, we provide readers with a brief update on specific areas of NPM-ALK pathobiology. In the first part, the NPM-ALK/signal transducer and activator of transcription 3 (STAT3) signaling axis is discussed, with an emphasis on the existence of multiple biochemical defects that have been shown to amplify the oncogenic effects of this signaling axis. Specifically, findings regarding JAK3, SHP1 and the stimulatory effects of several cytokines including interleukin (IL)-9, IL-21 and IL-22 are summarized. New concepts stemming from recent observations regarding the functional interactions among the NPM-ALK/STAT3 axis, β catenin and glycogen synthase kinase 3β will be postulated. Lastly, new mechanisms by which the NPM-ALK/STAT3 axis promotes tumorigenesis, such as its modulations of Twist1, hypoxia-induced factor 1α, CD274, will be described. In the second part, we summarize recent data generated by mass spectrometry studies of NPM-ALK, and use MSH2 and heat shock proteins as examples to illustrate the use of mass spectrometry data in stimulating new research in this field. In the third part, the evolving field of microRNA in the context of NPM-ALK biology is discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".