A novel curcumin-like dienone induces apoptosis in triple-negative breast cancer cells
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: According to the World Health Organization (WHO), breast cancer is the most common cancer affecting women worldwide. In the USA ~12.3 % of all women are expected to be diagnosed with various types of breast cancer, exhibiting varying degrees of therapeutic response rates. Therefore, the identification of novel anti-breast cancer drugs is of paramount importance. METHODS: The 1,5-diaryl-3-oxo-1,4-pentadienyl pharmacophore was incorporated into a number of cytotoxins. Three of the resulting dienones, 2a, 2b and 2c, were tested for their anti-neoplastic potencies in a variety of human breast cancer-derived cell lines, including the triple negative MDA-MB-231 cell line and its metastatic variant, using a live-cell bio-imaging method. Special emphasis was put on dienone 2c, since its anti-cancer activity and its mode of inflicting cell death have so far not been reported. RESULTS: We found that all three dienones exhibited potent cytotoxicities towards the breast cancer-derived cell lines tested, whereas significantly lower toxicities were observed towards the non-cancerous human breast cell line MCF-10A. The dienones 2b and 2c exhibited the greatest selective cytotoxicity at submicromolar concentration levels. We found that these two dienones induced phosphatidylserine externalization in MDA-MB-231 cells in a concentration-dependent manner, suggesting that their cytotoxic effect might be mediated by apoptosis. This possibility was confirmed by our observation that the dienone 2c can induce mitochondrial depolarization, caspase-3 activation, cell cycle disruption and DNA fragmentation in MDA-MB-231 cells. CONCLUSION: Our findings indicate that dienone 2c uses the mitochondrial/intrinsic pathway to inflict apoptosis in triple negative MDA-MB-231 breast cancer-derived cells. This observation warrants further assessment of dienone 2c as a potential anti-breast cancer drug.
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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