Loss of SHP1 enhances JAK3/STAT3 signaling and decreases proteosome degradation of JAK3 and NPM-ALK in ALK+ anaplastic large-cell lymphoma
Why this work is in the frame
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Bibliographic record
Abstract
Previous studies showed that most cases of ALK(+) anaplastic large-cell lymphoma (ALK(+)ALCL) do not express SHP1, a tyrosine phosphatase and an important negative regulator for cellular signaling pathways such as that of JAK/STAT. To fully assess the biologic significance of loss of SHP1 in ALK(+)ALCL, we transfected SHP1 plasmids into 2 SHP1(-), ALK(+)ALCL cell lines, Karpas 299 and SU-DHL-1. After 24 hours of transfection, pJAK3 and pSTAT3 were decreased, and these changes correlated with down-regulation of STAT3 downstream targets including cyclin D3, mcl-1, and bcl-2. Expression of SHP1 in these 2 cell lines also resulted in marked decreases in the protein levels of JAK3 and NPM-ALK, and these effects were reversible by proteosome inhibitor MG132. Conversely, when SHP1 expression in SUP-M2 (a SHP1(+) ALK(+)ALCL cell line) was inhibited using siRNA, pSTAT3, pJAK3, JAK3, and NPM-ALK were all up-regulated. Coimmunoprecipitation studies showed that SHP1 was physically associated with JAK3 and NPM-ALK. SHP1 expression in Karpas 299 and SU-DHL-1 led to significant G(1) cell cycle arrest but not apoptosis. To conclude, loss of SHP1 contributes to the pathogenesis of ALK(+)ALCL by 2 mechanisms: (1) it leaves the tyrosine phosphorylation and activation of JAK3/STAT3 unchecked and (2) it decreases proteosome degradation of JAK3 and NPM-ALK.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it