Abstract 2651: Cucurbitacin I (JSI-124) activates the JNK signaling pathway leading to transcriptional up-regulation of vascular endothelial growth factor in B leukemia cells
Bibliographic record
Abstract
Abstract JSI-124 (Cucurbitain I) is a biochemical compound isolated from the herbal plant families, which have been used as folk medicines for centuries in Asian countries. The molecular mechanisms for this inhibitor acts primarily through STAT3 inhibition in many tumors, including chronic lymphocytic leukemia. However, other molecular targets of JSI-124 are not fully understood. The objective of this study was to determine the molecular targets of JSI-124 beyond STAT3. Chemotherapeutic drugs often induce a stress response in cancer cells. One of early stress response pathways is the c-Jun N-terminal kinase (JNK) pathway. Herein, we show that JSI-124 activates JNK and increased the expression of c-Jun protein in the B leukemia cell lines BJAB, I-83 and NALM-6. Interestingly, the inhibition of the JNK signaling pathway failed to effect JSI-124 induced cell cycle arrest or apoptosis in these leukemia cells but repressed c-Jun level. Furthermore, JNK activation also failed to effect JSI-124 inhibition of STAT3 phosphorylation in these cells. It is known that one of the important factors involved in JNK signaling is Vascular Endothelial Growth Factor (VEGF). We found that JSI-124 treated BJAB cells showed an increased in mRNA and protein level in VEGF in BJAB, I-83 and NALM-6 cells. Knockdown of c-Jun expression and inhibition of JNK activation significantly blocked JSI-124 induced VEGF expression. Taken together, our data demonstrate that JSI-124 activates JNK signaling pathway leading to VEGF expression independent of inhibition of STAT3 activation. This could lead to increased angiogenesis in B leukemia cells treated with JSI-124. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2651. doi:10.1158/1538-7445.AM2011-2651
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".