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基于质谱的血浆代谢物全景分析揭示了胰腺癌有潜力的强判别分类器。

Comprehensive mass spectrometry based metabolic profiling of blood plasma reveals potent discriminatory classifiers of pancreatic cancer.

机构信息

Division of Gastroenterology and Hepatology, Department of Internal Medicine, University of California, Davis, CA 95817, USA.

出版信息

Rapid Commun Mass Spectrom. 2010 Mar 15;24(5):613-20. doi: 10.1002/rcm.4420.

DOI:10.1002/rcm.4420
PMID:20143319
Abstract

Poor outcome of pancreatic cancer necessitates development of an early diagnostic method to reduce mortality. No reliable early diagnostic test for pancreatic cancer detection has been developed and validated to date. In the current study, metabolic profiling of plasma samples from selected cancer patients and noncancerous controls was performed to seek novel metabolic biomarkers of pancreatic cancer. A comprehensive mass spectrometry based analytical platform established at the Metabolomics Core of the UC Davis Genome Center allowed detection of multiple compounds previously unreported in plasma from pancreatic cancer patients. It was found that selective amino acids, bile acids, and polar lipids were detected with increased or decreased levels in pancreatic cancer samples compared to controls. These findings on blood plasma levels of the relevant metabolites might be very useful clinical parameters for early diagnosis of pancreatic cancer.

摘要

胰腺癌预后不良,因此需要开发一种早期诊断方法以降低死亡率。目前尚未开发出可靠的胰腺癌早期诊断检测方法。在本研究中,对选定的癌症患者和非癌症对照者的血浆样本进行代谢组学分析,以寻找胰腺癌的新型代谢生物标志物。在加利福尼亚大学戴维斯分校基因组中心的代谢组学核心建立的基于全面质谱的分析平台,可检测到之前在胰腺癌患者血浆中未报告的多种化合物。结果发现,与对照相比,胰腺癌样本中选择性氨基酸、胆汁酸和极性脂质的水平升高或降低。这些关于相关代谢物血液水平的发现可能是用于胰腺癌早期诊断的非常有用的临床参数。

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