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. 2024 Jan 9;29(2):334.
doi: 10.3390/molecules29020334.

Using Pharmacokinetic-Pharmacodynamic Modeling to Study the Main Active Substances of the Anticancer Effect in Mice from Panax ginseng- Ophiopogon japonicus

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Using Pharmacokinetic-Pharmacodynamic Modeling to Study the Main Active Substances of the Anticancer Effect in Mice from Panax ginseng- Ophiopogon japonicus

Lu Liu et al. Molecules. .

Abstract

Ginseng Radix et Rhizoma Rubra (Panax ginseng C.A. Mey, Hongshen, in Chinese) and Ophiopogonis Radix (Ophiopogon japonicus (L.f) Ker-Gawl., Maidong, in Chinese) are traditional Chinese herbal pairs, which were clinically employed to enhance the immune system of cancer patients. This study employed the pharmacokinetic and pharmacodynamic (PK-PD) spectrum-effect association model to investigate the antitumor active substances of P. ginseng and O. japonicus (PG-OJ). The metabolic processes of 20 major bioactive components were analyzed using Ultra-Performance Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (UPLC-MS/MS) in the lung tissue of tumor-bearing mice treated with PG-OJ. The ELISA method was employed to detect the levels of TGF-β1, TNF-α, and IFN-γ in the lung tissue of mice at various time points, and to analyze their changes after drug administration. The results showed that all components presented a multiple peaks absorption pattern within 0.083 to 24 h post-drug administration. The tumor inhibition rate of tumor and repair rate of IFN-γ, TNF-α, and TGF-β1 all increased, indicating a positive therapeutic effect of PG-OJ on A549 tumor-bearing mice. Finally, a PK-PD model based on the GBDT algorithm was developed for the first time to speculate that Methylophiopogonanone A, Methylophiopogonanone B, Ginsenoside Rb1, and Notoginsenoside R1 are the main active components in PG-OJ for lung cancer treatment.

Keywords: PK–PD modeling; Panax ginseng–Ophiopogon japonicus; UPLC–MS/MS; lung cancer; main active substances.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Extracted ion chromatogram of the 20 compounds. (A) Blank lung tissue samples; (B) lung tissue samples collected at 0.083 h after administration of PG–OJ; (C) blank lung tissue spiked with analytes. (1: Notoginsenoside R1, 2: Ginsenoside Re, 3: Ginsenoside Rg1, 4: 24(R)-pseudoginsenoside F11, 5: Ginsenoside Rb1, 6: Ginsenoside Rc, 7: Ginsenoside Rf, 8: Ginsenoside Rb2, 9: Ginsenoside Rb3, 10: Pseudoginsenoside RT5, 11: Ginsenoside Ro, 12: Ginsenoside Rg2, 13: Ginsenoside F1, 14: Ginsenoside Rd, 15: Ginsenoside Rh1, 16: Ginsenoside Rg5, 17: Ginsenoside Rg3, 18: Ginsenoside F2, 19: Methylophiopogon flavanone A, 20: Methylophiopogon flavanone B).
Figure 2
Figure 2
The profiles of mean lung tissue concentration; time of twenty target constituents after oral administration of PG–OJ extract to tumor-bearing mice. The main figure displays the average content changes of components in the lung tissue of six mice in the PG–OJ group within 24 h, while the secondary figure shows the average content changes within 2 h. The error lines represent the mean ± SD.
Figure 3
Figure 3
Pharmacodynamic indicator for changes in tumor-bearing mice after oral administration of PG–OJ extract at different time points. Main (AC) present the average repair-rate changes of three cytokines (TNF-α, IFN-γ and TGF-β1) in the lung tissue of six mice in the PG–OJ group within 24 h, while the secondary figure shows the average changes within 2 h. (D) primarily illustrates the average tumor-growth-inhibition-rate changes within 24 h and 2 h for the same group of six mice in the PG–OJ group.
Figure 4
Figure 4
Feature-importance ranking of LightGBM model based on SHAP value. (A) Feature-importance ranking in the training set; (B) SHAP plot in the training set; (C) features-importance ranking in the test set; and (D) SHAP plot in the test set.

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