Synergistic Effect of Anethole and Platinum Drug Cisplatin against Oral Cancer Cell Growth and Migration by Inhibiting MAPKase, Beta-Catenin, and NF-κB Pathways
Bibliographic record
Abstract
Cisplatin is a common drug used to treat patients with oral squamous cell carcinoma. However, cisplatin-induced chemoresistance poses a major challenge to its clinical application. Our recent study has shown that anethole possesses an anti-oral cancer effect. In this study, we examined the combined effect of anethole and cisplatin on oral cancer therapy. Gingival cancer cells Ca9-22 were cultured in the presence of various concentrations of cisplatin with or without anethole. The cell viability/proliferation and cytotoxicity were evaluated, respectively, by MTT, Hoechst staining, and LDH assay, while colony formation was measured by crystal violet. Oral cancer cell migration was evaluated by the scratch method. Apoptosis, caspase activity, oxidative stress, MitoSOX, and mitochondrial membrane potential (ΔΨm) levels were evaluated by flow cytometry, and the inhibition of signaling pathways was investigated by Western blot. Our results show that anethole (3 µM) potentiates cisplatin-induced inhibition of cell proliferation and decreases the ΔΨm on Ca9-22 cells. Furthermore, drug combination was found to inhibit cell migration and enhanced cisplatin cytotoxicity. The combination of anethole and cisplatin potentiates cisplatin-induced oral cancer cell apoptosis through the activation of caspase, while we also found anethole and cisplatin to enhance the cisplatin-induced generation of reactive oxygen species (ROS) and mitochondrial stress. In addition, major cancer signaling pathways were inhibited by the combination of anethole and cisplatin such as MAPKase, beta-catenin, and NF-κB pathways. This study reports that the combination of anethole and cisplatin might provide a beneficial effect in enhancing the cisplatin cancer cell-killing effect, thus lowering the associated side effects.
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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) | 0.000 | 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 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".