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低级别与高级别神经胶质瘤的代谢差异:基于~1H NMR 波谱分析。

Metabolic Variations between Low-Grade and High-Grade Gliomas-Profiling by H NMR Spectroscopy.

机构信息

Department of Biochemistry, University of Madras, Chennai 600025, Tamilnadu, India.

Department of Neuropathology, Madras Medical College and Government General Hospital, Chennai 600003, Tamilnadu, India.

出版信息

J Proteome Res. 2020 Jun 5;19(6):2483-2490. doi: 10.1021/acs.jproteome.0c00243. Epub 2020 May 22.

Abstract

Altered cellular metabolism is one of the crucial hallmarks of glioma that deserves exploration, as the metabolites act as direct indicators of protein function and genetic variations. The current study focused on the metabolomic profiling of patients from whom glioma specimens were obtained for the identification of specific metabolites that could distinguish the low grade and high grade. In the current study, H NMR spectroscopy was carried out and the data were analyzed by partial least-squares discriminant analysis (PLS-DA) and orthogonal projection to latent structure with discriminant analysis (OPLS-DA). Pathway analysis was done to associate characteristic metabolites with the grades of sample using MetaboAnalyst 4.0 software based on the KEGG metabolic pathways database. Distinctive metabolic profiles among low- and high-grade gliomas with top 15 characteristic metabolites that could discriminate these grades were identified on the basis of their VIP scores from the OPLS-DA model. The major altered metabolic pathways include choline, taurine and hypotaurine, glutamate/glutamine, glutathione, and phenyl alanine/tyrosine, which were found to be consistent with the particular grade of a sample. Our study clearly demonstrated a characteristic metabolic profile of individual grades of glioma, suggesting that an altered metabolism is consistent with the specific grades of glioma appreciation and could lead to the development novel treatment strategies.

摘要

细胞代谢改变是神经胶质瘤的重要特征之一,值得深入研究,因为代谢物可直接反映蛋白质功能和基因变异。本研究专注于对神经胶质瘤患者的代谢组学分析,以确定可区分低级别和高级别神经胶质瘤的特定代谢物。本研究采用核磁共振波谱法(1H NMR)进行代谢组学分析,并用偏最小二乘判别分析(PLS-DA)和正交偏最小二乘判别分析(OPLS-DA)对数据进行分析。采用 MetaboAnalyst 4.0 软件对特征代谢物进行通路分析,该软件基于KEGG 代谢途径数据库,将特征代谢物与样本的分级相关联。根据 OPLS-DA 模型的 VIP 得分,确定了低级别和高级别神经胶质瘤之间存在显著差异的代谢谱,并鉴定出可区分这些级别的 15 种特征代谢物。主要改变的代谢途径包括胆碱、牛磺酸和次牛磺酸、谷氨酸/谷氨酰胺、谷胱甘肽和苯丙氨酸/酪氨酸,这些代谢途径与样本的特定分级一致。本研究清楚地显示了神经胶质瘤各分级的特征代谢谱,表明代谢改变与神经胶质瘤的特定分级一致,可能为开发新的治疗策略提供依据。

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