Addition of Gallic Acid Overcomes Resistance to Cisplatin in Ovarian Cancer Cell Lines
Bibliographic record
Abstract
OBJECTIVE: Ovarian cancer is one of the leading causes of cancer-related mortality in women, and is often associated with drug resistance. Therefore, finding effective drugs, including naturally derived compounds, is urgently needed. Herein, we aimed to test the anti-cancer potential of gallic acid monohydrate (GA) and its congeners on cisplatin-sensitive (A2780S), and resistant (A2780CP) ovarian cancer and normal ovarian (HOSE6-3) cell lines. METHODS: Cytotoxicity was assessed by AlamarBlue and CCK08 assays by exposing cells to different concentrations of cisplatin (0-21µg/mL), GA and its congeners (0-100µg/mL), and a combination of GA and cisplatin. Apoptosis was estimated by Hoechst stain and monitoring the relative RNA expression of the apoptotic effector caspase-3 using qRT-PCR. RESULTS: GA decreased cell viability in a concentration-dependent manner in all cell lines, with an IC50 of 19.39µg/mL (A2780S), 35.59 µg/mL (A2780CP), and 49.32µg/mL (HOSE6-3). GA displayed higher cytotoxicity than its congeners. An apoptotic rate estimation of approximately 20% and 30% was obtained in A2780S and A2780CP. While the cytotoxicity observed with cisplatin and GA was comparable, combining the two enhanced the cytotoxicity significantly, especially in the A2780CP cell line (p<0.05). CONCLUSION: These data suggest that GA may help overcome the resistance. Hence, the cytotoxic effects of GA, especially on chemo-resistant ovarian cancer cells merit further investigation.<br />.
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How this classification was reachedexpand
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) | 0.003 | 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 teacher head, 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".