1H-NMR Spectroscopy of Blood Plasma for Detection of Changes in Metabolism during the Development of M-1 Sarcoma in Rats

IF 4.033 Q4 Biochemistry, Genetics and Molecular Biology Biophysics Pub Date : 2025-02-26 DOI:10.1134/S0006350924700829

A. Y. Egorov, A. S. Bykov, T. I. Ponomareva, M. V. Molchanov, N. M. Pankratova, A. N. Pankratov, A. G. Arakelyan, S. N. Koryakin, M. A. Timchenko

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Abstract

The effectiveness of ¹H-NMR-based metabolomic analysis for the detection of metabolic changes during carcinogenesis was assessed based on a comparison of the quantitative composition of metabolites in the blood plasma of healthy rats and rats that receiving M-1 sarcoma grafts. Plasma was collected from the rats under study on day 12 and day 36 after sarcoma transplantation to identify metabolites associated with tumor development. Analysis of the NMR spectra using multivariate statistical methods showed differences in the composition of metabolites for the groups of animals under study as soon as on day 12 after sarcoma transplantation; on day 36 the differences were significant. Twenty three metabolites were quantified. On day 12, only the lactate and allantoin levels were significantly different between the groups, while on day 36, the levels of nine metabolites were different between the two groups. All of the identified metabolites are involved in cancer metabolism, which makes ¹H-NMR spectroscopy a promising method for cancer diagnosis.

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血浆1H-NMR检测大鼠M-1肉瘤发生过程中代谢变化

通过比较健康大鼠和接受M-1肉瘤移植的大鼠血浆中代谢物的定量组成，评估基于1h - nmr的代谢组学分析检测癌变过程中代谢变化的有效性。在肉瘤移植后第12天和第36天收集研究大鼠的血浆，以鉴定与肿瘤发展相关的代谢物。利用多元统计方法对核磁共振光谱进行分析，发现在肉瘤移植后第12天，研究动物组的代谢物组成就存在差异；第36天差异显著。对23种代谢物进行了量化。第12天，两组间只有乳酸和尿囊素水平存在显著差异，第36天，9种代谢物水平在两组间存在显著差异。所有鉴定的代谢物都参与了癌症代谢，这使得1H-NMR成为一种很有前途的癌症诊断方法。

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来源期刊

Biophysics Biochemistry, Genetics and Molecular Biology-Biophysics

CiteScore

1.20

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0.00%

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期刊介绍： Biophysics is a multidisciplinary international peer reviewed journal that covers a wide scope of problems related to the main physical mechanisms of processes taking place at different organization levels in biosystems. It includes structure and dynamics of macromolecules, cells and tissues; the influence of environment; energy transformation and transfer; thermodynamics; biological motility; population dynamics and cell differentiation modeling; biomechanics and tissue rheology; nonlinear phenomena, mathematical and cybernetics modeling of complex systems; and computational biology. The journal publishes short communications devoted and review articles.