The Quantitative Analysis of Dynamic Mechanisms Impacting Gastric Cancer Cell Proliferation via Serine/glycine Conversion
10.16476/j.pibb.2023.0127
- VernacularTitle:定量分析丝氨酸/甘氨酸转换影响胃癌细胞增殖的动力学机制
- Author:
Jun-Wu FAN
1
;
Xiao-Mei ZHU
2
;
Zhi-Yuan FAN
3
;
Bing-Ya LIU
4
;
Ping AO
5
;
Yong-Cong CHEN
1
Author Information
1. Department of Physics, Shanghai University, Shanghai 200444, China
2. Shanghai Key Lab of Modern Optical System, School of Optical-Electrical Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
3. Department of Breast Surgery, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai 200092, China
4. Department of Surgery, Shanghai Institute of Digestive Surgery, Shanghai Key Laboratory of Gastric Neoplasms, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
5. College of Biomedical Engineering, Sichuan University, Chengdu 610065, China
- Publication Type:Journal Article
- Keywords:
gastric cancer;
serine/glycine metabolism;
cell proliferation;
stochastic dynamic decomposition;
Lyapunov function;
S-adenosylmethionine;
methylation
- From:
Progress in Biochemistry and Biophysics
2024;51(3):658-672
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveGastric cancer (GC) seriously affects human health and life, and research has shown that it is closely related to the serine/glycine metabolism. The proliferation ability of tumor cells is greatly influenced by the metabolism of serine and glycine. The aim of this study was to investigate the molecular mechanism of serine/glycine metabolism can affect the proliferation of gastric cancer cells. MethodsIn this work, a stable metabolic dynamic model of gastric cancer cells was established via a large-scale metabolic network dynamic modeling method in terms of a potential landscape description of stochastic and non-gradient systems. Based on the regulation of the model, a quantitative analysis was conducted to investigate the dynamic mechanism of serine/glycine metabolism affecting the proliferation of gastric cancer cells. We introduced random noise to the kinetic equations of the general metabolic network, and applied stochastic kinetic decomposition to obtain the Lyapunov function of the metabolic network parameter space. A stable metabolic network was achieved by further reducing the change in the Lyapunov function tied to the stochastic fluctuations. ResultsDespite the unavailability of a large number of dynamic parameters, we were able to successfully construct a dynamic model for the metabolic network in gastric cancer cells. When extracellular serine is available, the model preferentially consumes serine. In addition, when the conversion rate of glycine to serine increases, the model significantly upregulates the steady-state fluxes of S-adenosylmethionine (SAM) and S-adenosyl homocysteine (SAH). ConclusionIn this paper, we provide evidence supporting the preferential uptake of serine by gastric cancer cells and the important role of serine/glycine conversion rate in SAM generation, which may affect the proliferation ability of gastric cancer cells by regulating the cellular methylation process. This provides a new idea and direction for targeted cancer therapy based on serine/glycine metabolism.
