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健康对照以及晚期前列腺癌和肺癌患者中不同血浆外泌体分离方法可检测到的脂质组和代谢组

Detectable Lipidomes and Metabolomes by Different Plasma Exosome Isolation Methods in Healthy Controls and Patients with Advanced Prostate and Lung Cancer.

作者信息

Soupir Alex C, Tian Yijun, Stewart Paul A, Nunez-Lopez Yury O, Manley Brandon J, Pellini Bruna, Bloomer Amanda M, Zhang Jingsong, Mo Qianxing, Marchion Douglas C, Liu Min, Koomen John M, Siegel Erin M, Wang Liang

机构信息

Department of Tumor Biology, Moffitt Cancer Center, Tampa, FL 33612, USA.

Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL 33612, USA.

出版信息

Int J Mol Sci. 2023 Jan 17;24(3):1830. doi: 10.3390/ijms24031830.

Abstract

Circulating exosomes in the blood are promising tools for biomarker discovery in cancer. Due to their heterogeneity, different isolation methods may enrich distinct exosome cargos generating different omic profiles. In this study, we evaluated the effects of plasma exosome isolation methods on detectable multi-omic profiles in patients with non-small cell lung cancer (NSCLC), castration-resistant prostate cancer (CRPC), and healthy controls, and developed an algorithm to quantify exosome enrichment. Plasma exosomes were isolated from CRPC (n = 10), NSCLC (n = 14), and healthy controls (n = 10) using three different methods: size exclusion chromatography (SEC), lectin binding, and T-cell immunoglobulin domain and mucin domain-containing protein 4 (TIM4) binding. Molecular profiles were determined by mass spectrometry of extracted exosome fractions. Enrichment analysis of uniquely detected molecules was performed for each method with MetaboAnalyst. The exosome enrichment index (EEI) scores methods based on top differential molecules between patient groups. The lipidomic analysis detected 949 lipids using exosomes from SEC, followed by 246 from lectin binding and 226 from TIM4 binding. The detectable metabolites showed SEC identifying 191 while lectin binding and TIM4 binding identified 100 and 107, respectively. When comparing uniquely detected molecules, different methods showed preferential enrichment of different sets of molecules with SEC enriching the greatest diversity. Compared to controls, SEC identified 28 lipids showing significant difference in NSCLC, while only 1 metabolite in NSCLC and 5 metabolites in CRPC were considered statistically significant (FDR < 0.1). Neither lectin-binding- nor TIM4-binding-derived exosome lipids or metabolites demonstrated significant differences between patient groups. We observed the highest EEI from SEC in lipids (NSCLC: 871.33) which was also noted in metabolites. These results support that the size exclusion method of exosome extraction implemented by SBI captures more heterogeneous exosome populations. In contrast, lectin-binding and TIM4-binding methods bind surface glycans or phosphatidylserine moieties of the exosomes. Overall, these findings suggest that specific isolation methods select subpopulations which may significantly impact cancer biomarker discovery.

摘要

血液中循环的外泌体是癌症生物标志物发现中很有前景的工具。由于其异质性,不同的分离方法可能富集不同的外泌体货物,从而产生不同的组学图谱。在本研究中,我们评估了血浆外泌体分离方法对非小细胞肺癌(NSCLC)、去势抵抗性前列腺癌(CRPC)患者及健康对照中可检测的多组学图谱的影响,并开发了一种算法来量化外泌体富集情况。使用三种不同方法从CRPC患者(n = 10)、NSCLC患者(n = 14)和健康对照(n = 10)中分离血浆外泌体:尺寸排阻色谱法(SEC)、凝集素结合法和含T细胞免疫球蛋白结构域和粘蛋白结构域蛋白4(TIM4)结合法。通过对提取的外泌体组分进行质谱分析来确定分子图谱。使用MetaboAnalyst对每种方法独特检测到的分子进行富集分析。外泌体富集指数(EEI)根据患者组之间的顶级差异分子对方法进行评分。脂质组学分析使用SEC法提取的外泌体检测到949种脂质,其次,凝集素结合法检测到246种,TIM4结合法检测到226种。可检测的代谢物显示,SEC法鉴定出191种,而凝集素结合法和TIM4结合法分别鉴定出100种和107种。在比较独特检测到的分子时,不同方法显示出对不同分子集的优先富集,SEC法富集的分子多样性最大。与对照组相比,SEC法鉴定出NSCLC中有28种脂质存在显著差异,而NSCLC中只有1种代谢物以及CRPC中有5种代谢物被认为具有统计学意义(FDR < 0.1)。凝集素结合法或TIM4结合法衍生的外泌体脂质或代谢物在患者组之间均未显示出显著差异。我们观察到SEC法在脂质方面的EEI最高(NSCLC:871.33),在代谢物方面也是如此。这些结果支持SBI实施的外泌体提取尺寸排阻方法捕获了更多异质性的外泌体群体。相比之下,凝集素结合法和TIM4结合法结合外泌体的表面聚糖或磷脂酰丝氨酸部分。总体而言,这些发现表明特定的分离方法选择的亚群可能会对癌症生物标志物的发现产生重大影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fde3/9916336/621a055afe2d/ijms-24-01830-g001.jpg

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