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脂质组学作为前列腺癌的诊断工具

Lipidomics as a Diagnostic Tool for Prostate Cancer.

作者信息

Buszewska-Forajta Magdalena, Pomastowski Paweł, Monedeiro Fernanda, Walczak-Skierska Justyna, Markuszewski Marcin, Matuszewski Marcin, Markuszewski Michał J, Buszewski Bogusław

机构信息

Department of Biopharmaceutics and Pharmacodynamics, Faculty of Pharmacy, Medical University of Gdańsk, Aleja Generała Józefa Hallera 107, 80-416 Gdańsk, Poland.

Institute of Veterinary Medicine, Faculty of Biological and Veterinary Sciences, Nicolaus Copernicus University, 87-100 Toruń, Poland.

出版信息

Cancers (Basel). 2021 Apr 21;13(9):2000. doi: 10.3390/cancers13092000.

Abstract

The main goal of this study was to explore the phospholipid alterations associated with the development of prostate cancer (PCa) using two imaging methods: matrix-assisted laser desorption ionization with time-of-flight mass spectrometer (MALDI-TOF/MS), and electrospray ionization with triple quadrupole mass spectrometer (ESI-QqQ/MS). For this purpose, samples of PCa tissue ( = 40) were evaluated in comparison to the controls ( = 40). As a result, few classes of compounds, namely phosphatidylcholines (PCs), lysophosphatidylcholines (LPCs), sphingomyelins (SMs), and phosphatidylethanolamines (PEs), were determined. The obtained results were evaluated by univariate (Mann-Whitney U-test) and multivariate statistical analysis (principal component analysis, correlation analysis, volcano plot, artificial neural network, and random forest algorithm), in order to select the most discriminative features and to search for the relationships between the responses of these groups of substances, also in terms of the used analytical technique. Based on previous literature and our results, it can be assumed that PCa is linked with both the synthesis of fatty acids and lipid oxidation. Among the compounds, phospholipids, namely PC 16:0/16:1, PC 16:0/18:2, PC 18:0/22:5, PC 18:1/18:2, PC 18:1/20:0, PC 18:1/20:4, and SM d18:1/24:0, were assigned as metabolites with the best discriminative power for the tested groups. Based on the results, lipidomics can be found as alternative diagnostic tool for CaP diagnosis.

摘要

本研究的主要目标是使用两种成像方法,即基质辅助激光解吸电离飞行时间质谱仪(MALDI-TOF/MS)和电喷雾电离三重四极杆质谱仪(ESI-QqQ/MS),探索与前列腺癌(PCa)发展相关的磷脂变化。为此,对40份PCa组织样本与40份对照样本进行了评估。结果确定了几类化合物,即磷脂酰胆碱(PCs)、溶血磷脂酰胆碱(LPCs)、鞘磷脂(SMs)和磷脂酰乙醇胺(PEs)。通过单变量(曼-惠特尼U检验)和多变量统计分析(主成分分析、相关性分析、火山图、人工神经网络和随机森林算法)对所得结果进行评估,以便选择最具判别力的特征,并从所用分析技术的角度寻找这些物质组反应之间的关系。根据以往文献和我们的结果,可以假设PCa与脂肪酸合成和脂质氧化均有关联。在这些化合物中,磷脂,即PC 16:0/16:1、PC 16:0/18:2、PC 18:0/22:5、PC 18:1/18:2、PC 18:1/20:0、PC 18:1/20:4和SM d18:1/24:0,被确定为对测试组具有最佳判别力的代谢物。基于这些结果,脂质组学可作为前列腺癌诊断的替代诊断工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2f6/8122642/4c12e9294c17/cancers-13-02000-g001.jpg

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