Diagnosis of liver cancer using HPLC-based metabonomics avoiding false-positive result from hepatitis and hepatocirrhosis diseases

被引:181
作者
Yang, J
Xu, GW [1 ]
Zheng, YF
Kong, HW
Pang, T
Lv, S
Yang, Q
机构
[1] Chinese Acad Sci, Dalian Inst Chem Phys, Natl Chromatog R&A Ctr, Dalian 116011, Peoples R China
[2] Dalian Med Univ, Dept Pathol, Dalian 116023, Peoples R China
来源
JOURNAL OF CHROMATOGRAPHY B-ANALYTICAL TECHNOLOGIES IN THE BIOMEDICAL AND LIFE SCIENCES | 2004年 / 813卷 / 1-2期
关键词
metabonomics; HPLC; nucleosides; methodological studies; molecular diagnosis and prognosis;
D O I
10.1016/j.jchromb.2004.09.032
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Metabonomics, the study of metabolites and their roles in various disease states, is a novel methodology arising from the post-genomics era. This methodology has been applied in many fields. Current metabonomics practice has relied on mass spectrometry (MS), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) to analyze metabolites. In this study, a novel approach of using high-performance liquid chromatography (HPLC) in conjunction with developed software was employed. Using the principal components analysis method (PCA), all (113) peaks of urinary metabolites with a cis-diol structure from patients with hepatitis and hepatocirrhosis were compared to those from liver cancer patients. The results showed that the metabonomics-PCA method might be useful to differentiate between patients with hepatocirrhosis and hepatitis from patients with liver cancer while lowering false-positive rate. These findings also suggest that a subset of the urinary nucleosides identified with metabonomics correlate better with cancer diagnosis than the traditional single tumor marker alpha-fetoprotein (AFP). (C) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码:59 / 65
页数:7
相关论文
共 38 条
[1]   Automated mode-of-action detection by metabolic profiling [J].
Aranìbar, N ;
Singh, BK ;
Stockton, GW ;
Ott, KH .
BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS, 2001, 286 (01) :150-155
[2]  
BOREK E, 1971, CANCER RES, V31, P596
[3]  
BOREK E, 1977, CANCER RES, V37, P3362
[4]  
Brindle JT, 2002, NAT MED, V8, P1439, DOI 10.1038/nm802
[5]  
DAVID AF, 2001, TRENDS GENET, V17, P680
[6]   Metabolomics - the link between genotypes and phenotypes [J].
Fiehn, O .
PLANT MOLECULAR BIOLOGY, 2002, 48 (1-2) :155-171
[7]   Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks [J].
Fiehn, O .
COMPARATIVE AND FUNCTIONAL GENOMICS, 2001, 2 (03) :155-168
[8]  
Gehrke C.W., 1990, CHROMATOGRAPHY MODIF
[9]   Chemometric contributions to the evolution of metabonomics: mathematical solutions to characterising and interpreting complex biological NMR spectra [J].
Holmes, E ;
Antti, H .
ANALYST, 2002, 127 (12) :1549-1557
[10]   Metabonomic characterization of genetic variations in toxicological and metabolic responses using probabilistic neural networks [J].
Holmes, E ;
Nicholson, JK ;
Tranter, G .
CHEMICAL RESEARCH IN TOXICOLOGY, 2001, 14 (02) :182-191