Nimbolide-Induced Oxidative Stress Abrogates STAT3 Signaling Cascade and Inhibits Tumor Growth in Transgenic Adenocarcinoma of Mouse Prostate Model
Why this work is in the frame
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Bibliographic record
Abstract
AIMS: Prostate cancer (PCa) is one of the most commonly diagnosed cancers worldwide. Currently available therapies for metastatic PCa are only marginally effective, hence novel treatment modalities are urgently required. Considerable evidence(s) suggest that deregulated activation of oncogenic transcription factor, signal transducer and activator of transcription 3 (STAT3) plays a pivotal role in the development and progression of PCa. Thus, agents that can abrogate STAT3 activation could form the basis of novel therapy for PCa patients. In the present study, we analyzed whether the potential anticancer effects of nimbolide (NL), a limonoid triterpene derived from Azadirachta indica, against PCa cell lines and transgenic adenocarcinoma of mouse prostate (TRAMP) model are mediated through the negative regulation of STAT3 pathway. RESULTS: Data from the in vitro studies indicated that NL could significantly inhibit cell viability, induce apoptosis, and suppress cellular invasion and migration. Interestingly, NL also abrogated STAT3 activation and this effect was found to be mediated via an increased production of reactive oxygen species (ROS) due to GSH/GSSG imbalance. Oral administration of NL significantly suppressed the tumor growth and metastasis in TRAMP mouse model without exhibiting any significant adverse effects. INNOVATION: The present study demonstrates the critical role of GSH/GSSG imbalance-mediated ROS production contributing to the STAT3 inhibitory and tumor-suppressive effect of NL in PCa. CONCLUSION: Overall, our findings indicate that NL exhibits significant anticancer effects in PCa that may be primarily mediated through the ROS-regulated inhibition of STAT3 signaling cascade.
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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