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使用基于质谱的代谢组学分析鉴定乳腺癌中的代谢改变

Identification of Metabolic Alterations in Breast Cancer Using Mass Spectrometry-Based Metabolomic Analysis.

作者信息

Fan Sili, Shahid Muhammad, Jin Peng, Asher Arash, Kim Jayoung

机构信息

West Coast Metabolomics Center, University of California, Davis, CA 95616, USA.

Departments of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.

出版信息

Metabolites. 2020 Apr 24;10(4):170. doi: 10.3390/metabo10040170.

Abstract

Breast cancer (BC) is a major global health issue and remains the second leading cause of cancer-related death in women, contributing to approximately 41,760 deaths annually. BC is caused by a combination of genetic and environmental factors. Although various molecular diagnostic tools have been developed to improve diagnosis of BC in the clinical setting, better detection tools for earlier diagnosis can improve survival rates. Given that altered metabolism is a characteristic feature of BC, we aimed to understand the comparative metabolic differences between BC and healthy controls. Metabolomics, the study of metabolism, can provide incredible insight and create useful tools for identifying potential BC biomarkers. In this study, we applied two analytical mass spectrometry (MS) platforms, including hydrophilic interaction chromatography (HILIC) and gas chromatography (GC), to generate BC-associated metabolic profiles using breast tissue from BC patients. These metabolites were further analyzed to identify differentially expressed metabolites in BC and their associated metabolic networks. Additionally, Chemical Similarity Enrichment Analysis (ChemRICH), MetaMapp, and Metabolite Set Enrichment Analysis (MSEA) identified significantly enriched clusters and networks in BC tissues. Since metabolomic signatures hold significant promise in the clinical setting, more effort should be placed on validating potential BC biomarkers based on identifying altered metabolomes.

摘要

乳腺癌(BC)是一个重大的全球健康问题,仍然是女性癌症相关死亡的第二大主要原因,每年导致约41,760人死亡。乳腺癌由遗传和环境因素共同引起。尽管已经开发了各种分子诊断工具以改善临床环境中乳腺癌的诊断,但更好的早期诊断检测工具可以提高生存率。鉴于代谢改变是乳腺癌的一个特征,我们旨在了解乳腺癌与健康对照之间的比较代谢差异。代谢组学,即对代谢的研究,可以提供令人难以置信的见解,并为识别潜在的乳腺癌生物标志物创造有用的工具。在本研究中,我们应用了两种分析质谱(MS)平台,包括亲水相互作用色谱(HILIC)和气相色谱(GC),以使用乳腺癌患者的乳腺组织生成与乳腺癌相关的代谢谱。对这些代谢物进行进一步分析,以识别乳腺癌中差异表达的代谢物及其相关的代谢网络。此外,化学相似性富集分析(ChemRICH)、MetaMapp和代谢物集富集分析(MSEA)确定了乳腺癌组织中显著富集的簇和网络。由于代谢组学特征在临床环境中有很大前景,因此应更加努力基于识别改变的代谢组来验证潜在的乳腺癌生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2b4/7241246/30a133b83af9/metabolites-10-00170-g001.jpg

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