Ginkgolic Acid C 17:1, Derived from Ginkgo biloba Leaves, Suppresses Constitutive and Inducible STAT3 Activation through Induction of PTEN and SHP-1 Tyrosine Phosphatase
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Bibliographic record
Abstract
Ginkgolic acid C 17:1 (GAC 17:1) extracted from Ginkgo biloba leaves, has been previously reported to exhibit diverse antitumor effect(s) through modulation of several molecular targets in tumor cells, however the detailed mechanism(s) of its actions still remains to be elucidated. Signal transducer and activator of transcription 3 (STAT3) is an oncogenic transcription factor that regulates various critical functions involved in progression of diverse hematological malignancies, including multiple myeloma, therefore attenuating STAT3 activation may have a potential in cancer therapy. We determined the anti-tumor mechanism of GAC 17:1 with respect to its effect on STAT3 signaling pathway in multiple myeloma cell lines. We found that GAC 17:1 can inhibit constitutive activation of STAT3 through the abrogation of upstream JAK2, Src but not of JAK1 kinases in U266 cells and also found that GAC can suppress IL-6-induced STAT3 phosphorylation in MM.1S cells. Treatment of protein tyrosine phosphatase (PTP) inhibitor blocked suppression of STAT3 phosphorylation by GAC 17:1, thereby indicating a critical role for a PTP. We also demonstrate that GAC 17:1 can induce the substantial expression of PTEN and SHP-1 at both protein and mRNA level. Further, deletion of PTEN and SHP-1 genes by siRNA can repress the induction of PTEN and SHP-1, as well as abolished the inhibitory effect of drug on STAT3 phosphorylation. GAC 17:1 down-regulated the expression of STAT3 regulated gene products and induced apoptosis of tumor cells. Overall, GAC 17:1 was found to abrogate STAT3 signaling pathway and thus exert its anticancer effects against multiple myeloma cells.
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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