Cucurbitacin-I (JSI-124) activates the JNK/c-Jun signaling pathway independent of apoptosis and cell cycle arrest in B Leukemic Cells
Bibliographic record
Abstract
BACKGROUND: Cucurbitacin-I (JSI-124) is potent inhibitor of JAK/STAT3 signaling pathway and has anti-tumor activity in a variety of cancer including B cell leukemia. However, other molecular targets of JSI-124 beyond the JAK/STAT3 pathway are not fully understood. METHODS: BJAB, I-83, NALM-6 and primary CLL cells were treated with JSI-124 as indicated. Apoptosis was measured using flow cytometry for accumulation of sub-G1 phase cells (indicator of apoptosis) and Annexin V/PI staining. Cell cycle was analyzed by FACS for DNA content of G1 and G2 phases. Changes in phosphorylation and protein expression of p38, Erk1/2, JNK, c-Jun, and XIAP were detected by Western blot analysis. STAT3 and c-Jun genes were knocked out using siRNA transfection. VEGF expression was determined by mRNA and protein levels by RT-PCR and western blotting. Streptavidin Pull-Down Assay was used to determine c-Jun binding to the AP-1 DNA binding site. RESULTS: Herein, we show that JSI-124 activates c-Jun N-terminal kinase (JNK) and increases both the expression and serine phosphorylation of c-Jun protein in the B leukemic cell lines BJAB, I-83 and NALM-6. JSI-124 also activated MAPK p38 and MAPK Erk1/2 albeit at lower levels than JNK activation. Inhibition of the JNK signaling pathway failed to effect cell cycle arrest or apoptosis induced by JSI-124 but repressed JSI-124 induced c-Jun expression in these leukemia cells. The JNK pathway activation c-Jun leads to transcriptional activation of many genes. Treatment of BJAB, I-83, and NALM-6 cells with JSI-124 lead to an increase of Vascular Endothelial Growth Factor (VEGF) at both the mRNA and protein level. Knockdown of c-Jun expression and inhibition of JNK activation significantly blocked JSI-124 induced VEGF expression. Pretreatment with recombinant VEGF reduced JSI-124 induced apoptosis. CONCLUSIONS: Taken together, our data demonstrates that JSI-124 activates the JNK signaling pathway independent of apoptosis and cell cycle arrest, leading to increased VEGF expression.
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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) | 0.001 | 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".