A Theoretical Model for the Hormetic Dose-response Curve for Anticancer Agents
Tatsuya Yoshimasu1, Takuya Ohashi2, Shoji Oura2
1Department of Thoracic and Cardiovascular Surgery, Wakayama Medical University, Wakayama, Japan yositatu@wakayama-med.ac.jp.
This study quantifies the dose-response of anticancer agents, revealing hormetic effects that can promote cancer cell growth. Gemcitabine and 5-fluorouracil showed the strongest promotive effects in non-small-cell lung cancer cells.
Area of Science:
- Pharmacology
- Cancer Biology
- Biostatistics
Background:
- Anticancer agents can exhibit complex dose-response relationships.
- Hormesis, a biphasic response, is observed with some therapeutic agents.
- Understanding these effects is crucial for optimizing cancer treatment.
Purpose of the Study:
- To quantitatively evaluate the dose-response relationship of hormetic reactions of anticancer agents in vitro.
- To analyze the biphasic dose-response curves of five common anticancer drugs.
- To develop a theoretical model for predicting hormetic effects in cancer treatment.
Main Methods:
- Serial dilutions of gemcitabine, cisplatin, 5-fluorouracil, vinorelbine, and paclitaxel were tested.
- The A549 non-small-cell lung cancer cell line was used for in vitro experiments.
- A novel bi-phasic sigmoidal equation was fitted to the dose-response data using non-linear least square regression.
Main Results:
- The dose-responses of the five anticancer agents were successfully fitted to the proposed bi-phasic sigmoidal equation.
- Gemcitabine and 5-fluorouracil exhibited the most pronounced promotive effects, indicated by the lowest ED50 for hormesis.
- Hormetic reactions showed an exponential progression with increased culturing time.
Conclusions:
- Anticancer agents can induce hormetic reactions, potentially promoting cancer cell growth at low doses.
- A theoretical model was established to describe and predict these hormetic dose-response relationships.
- This model may aid in predicting the impact of hormesis on patients with malignant tumors, informing treatment strategies.
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