Mass spectrometric and linear discriminant analysis of N-glycans of human serum alpha-1-acid glycoprotein in cancer patients and healthy individuals

被引:63
作者
Imre, Timea [1 ]
Kremmer, Tibor [2 ]
Heberger, Karoly [2 ]
Molnar-Szollosi, Eva [3 ]
Ludanyi, Krisztina [1 ]
Pocsfalvi, Gabriella [4 ]
Malorni, Antonio [4 ]
Drahos, Laszlo [1 ]
Vekey, Karoly [1 ]
机构
[1] Hungarian Acad Sci, Chem Res Ctr, Inst Struct Chem, H-1525 Budapest, Hungary
[2] Hungarian Acad Sci, Chem Res Ctr, Inst Biomol Chem, H-1525 Budapest, Hungary
[3] Natl Inst Oncol, Dept Biochem, H-1122 Budapest, Hungary
[4] CNR, Ist Sci Alimentaz, I-83100 Avellino, Italy
关键词
Alpha-1-acid glycoprotein (AGP); Glycosylation; MALDI-TOF; Mass spectrometry; Linear discriminant analysis (LDA); Cancer; Lymphoma; Ovarian tumor; Biomarker;
D O I
10.1016/j.jprot.2008.04.005
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
N-glycan oligosaccharides of human serum a(1)-acid glycoprotein (AGP) samples isolated from 43 individuals (healthy individuals and patients with lymphoma and with ovarian tumor) were analyzed by MALDI-TOF mass spectrometry and a multivariate statistical method (linear discriminant analysis, LDA). 34 different glycan structures have been identified. From the glycosylation pattern determined by mass spectrometry fucosylation and branching indices have been calculated. These parameters show only small differences between the patient groups studied, but these differences are not sufficiently large to use as a potential biomarker. LDA analysis, on the other hand shows a very good separation between the three groups (with a classification of 88%). Cross-validation indicates that the method has predictive power: Identifying cancerous vs. healthy individuals shows 96% selectivity and 93% specificity; identification of lymphoma vs. the mixed group of healthy and ovarian tumor cases is also promising (72% selectivity and 84% specificity). The pilot study presented here demonstrates that mass spectrometry combined with linear discriminant analysis (LDA) may provide valuable data for identifying and studying the pathophysiology of malignant diseases. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:186 / 197
页数:12
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