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ZHAO Ming-yue, HOU Yu-zhu, LIU Xin, WANG Yang, SUN Kai-ju, PANG Bo, LIU Shu-ying, LI Dan, SU Rui. Metabolomics of Mice Serum Analysis to Assess the Effects of Saikosaponin D on Breast Cancer[J]. Journal of Chinese Mass Spectrometry Society, 2022, 43(2): 142-154. DOI: 10.7538/zpxb.2021.0084
Citation: ZHAO Ming-yue, HOU Yu-zhu, LIU Xin, WANG Yang, SUN Kai-ju, PANG Bo, LIU Shu-ying, LI Dan, SU Rui. Metabolomics of Mice Serum Analysis to Assess the Effects of Saikosaponin D on Breast Cancer[J]. Journal of Chinese Mass Spectrometry Society, 2022, 43(2): 142-154. DOI: 10.7538/zpxb.2021.0084
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Metabolomics of Mice Serum Analysis to Assess the Effects of Saikosaponin D on Breast Cancer

  • 1.

    Changchun University of Chinese Medicine, Changchun 130117, China

  • 2.

    Department of Cardiology, the First Hospital of Jilin University, Changchun 130021, China

  • 3.

    State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, Jilin University, Changchun 130012, China

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    • Abstract
  • The implementation of targeted therapies for breast cancer has been a challenge. Saikosaponin D (SsD), a triterpene saponin derived from Bupleurum, exhibits potential therapeutic properties for cancer therapy. Here, the role of SsD in broad anti-proliferation effects in breast cancer was investigated, and the SsD pharmaceutical efficacy was evaluated by metabolomics analysis. Low (0.4 mg/kg) and high (2.0 mg/kg) concentrations of SsDs were used to treat breast cancer tumors in mice by intraperitoneal injection. Blood samples of mice were collected and the serum samples were extracted after SsD administration for different days. Subsequently, the serum samples were analyzed by ultra-high performance liquid chromatography tandem Orbitrap mass spectrometry (UPLC-Orbitrap MS). According to the “80% rule”, UPLC-Orbitrap MS data were processed and proper ions were screened out for further analysis. Statistical methods including one-way analysis of variance (One-way ANOVA), principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed to cross validate the reasonable and accuracy of the models. Representational metabolite ions present significant differences acquired by comparison within/between control group, SsD low concentration group and SsD high concentration group. The results of animal survival experiments demonstrated that SsD had obvious therapeutic effect on tumor. Mice treated with low and high concentrations of SsD showed 60% and 80% survival rate, respectively, with a significant increase in survival compared to untreated control mice. Metabonomic results showed that 12 target metabolite ions including pipecolic acid, N-acryloylglycine, 3-methyleneindolenine, L-kynurenine, phenylethylamine, DL-2-aminooctanoic acid, N (6)-methyllysine, indoleacetaldehyde, 3-methylhistamine, hexanoylglycine, hypoxanthine and hexanoylcarnitine were obtained by intra-group (in control group) screening. The signal intensities of these 12 ions changed significantly in the process of tumor growth, which provided theoretical basis for the study of tumor development and evolution. Meanwhile, 7 important metabolite ions including 3-methylene-indolenine, phenylethylamine, pipecolic acid, L-kynurenine, indoleacetaldehyde, 5-acetylamino-6-formylamino-3-methyluracil and proline betaine were obtained by analyzing inter-group data (compared among three groups), and the first 5 metabolite ions were overlapped with the ions in the list of intra-group screening. Moreover, the biological significances of the selected ions with significant difference were investigated, and two highly correlated manifested metabolic pathways including amino acid metabolism and nucleotide metabolism were discussed. Overall, the results derived from intra-group metabolomic analysis were highly correlated with the inter-group results, and the metabolites along the relevant pathways deserve further attention. This study provides a practical strategy for targeting metabolic analysis using natural product to improve the survival of patients with breast cancer.
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