JSI‐124 (cucurbitacin I) inhibits Janus kinase‐3/signal transducer and activator of transcription‐3 signalling, downregulates nucleophosmin‐anaplastic lymphoma kinase (ALK), and induces apoptosis in ALK‐positive anaplastic large cell lymphoma cells
Bibliographic record
Abstract
JSI-124 (cucurbitacin I) has been recently described as a specific inhibitor of signal transducer and activator of transcription-3 (STAT3). As STAT3 activation is pathogenetically important in anaplastic lymphoma kinase-positive anaplastic large cell lymphoma (ALK+ ALCL), we investigated whether JSI-124 can mediate significant inhibitory effects in this cell type. In two ALK+ ALCL cell lines (Karpas 299 and SU-DHL-1), JSI-124 significantly reduced the number of viable cells to 50% of that of negative controls at a dose of 5-10 micromol/l at 24 h and 1-1.25 micromol/l at 48 h. This decrease in viability was associated with apoptosis, as confirmed by the increase in the subG(0/1) fraction, poly(ADP-ribose)polymerase cleavage and expression of active caspase 3. JSI-124 decreased the phosphorylated-STAT3 and -Janus kinase-3 (JAK3) levels in a dose-dependent fashion, and these changes were coupled with significant decreases in several STAT3 downstream targets, including mcl-1, bcl-2, bcl-xL and cyclin D3. Interestingly, JSI-124 also dramatically decreased the protein levels of JAK3 and nucleophosmin (NPM)-ALK, and these effects were reversible by MG132. Our data support that JSI-124 is a potentially useful therapeutic agent for ALK+ ALCL. In addition to its role as a tyrosine kinase inhibitor, JSI-124 appears to be involved in regulating proteosome degradation for proteins such as JAK3 and 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) | 0.001 | 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) | 0.001 | 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".