Modeling the metabolic response of A2780 ovarian cancer cells to gold-based cytotoxic drugs.

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Walter Vieri, Veronica Ghini, Paola Turano, Lara Massai, Luigi Messori, Marco Fondi
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引用次数: 0

Abstract

Gold compounds are a promising class of experimental anticancer metallodrugs. Unlike platinum-based drugs, their antiproliferative effects are thought to result mainly from modulation of cancer cell metabolism rather than direct interaction with DNA. Previous NMR studies have shown that four cytotoxic gold compounds - auranofin, aurothiomalate and two gold N-heterocyclic carbenes - induce distinct metabolic changes in A2780 ovarian cancer cells, suggesting the occurrence of different mechanisms of action. To better understand these effects, we constructed a genome-scale metabolic model (GEM) of A2780 cells to analyze the NMR-detected metabolomic changes. The model successfully predicts the diverse metabolic responses induced by each gold compound and identifies common metabolic changes. These results confirm the potential of GEMs as a powerful tool for interpreting and predicting cellular responses to gold-based drugs, providing insights into their mechanisms of action and potential therapeutic applications.

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模拟卵巢癌A2780细胞对含金细胞毒性药物的代谢反应。
金化合物是一类很有前途的实验性抗癌金属药物。与铂类药物不同,它们的抗增殖作用被认为主要是通过调节癌细胞代谢而不是直接与DNA相互作用产生的。先前的核磁共振研究表明,四种细胞毒性金化合物-金硫硫酸酯,金硫硫酸酯和两种金n -杂环碳烯-诱导A2780卵巢癌细胞发生不同的代谢变化,提示发生不同的作用机制。为了更好地理解这些影响,我们构建了A2780细胞的基因组尺度代谢模型(GEM)来分析核磁共振检测到的代谢组学变化。该模型成功地预测了每种金化合物引起的不同代谢反应,并识别了常见的代谢变化。这些结果证实了GEMs作为解释和预测细胞对金基药物反应的强大工具的潜力,为其作用机制和潜在的治疗应用提供了见解。
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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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