Proteomic-based biomarker discovery with emphasis on cerebrospinal fluid and multiple sclerosis

被引:16
作者
Berven, F. S. [1 ]
Flikka, K.
Berle, M.
Vedeler, C.
Ulvik, R. J.
机构
[1] Haukeland Hosp, Lab Clin Biochem, N-5021 Bergen, Norway
[2] Univ Bergen, Inst Med, Bergen, Norway
[3] Bergen Ctr Compuatat Sci, Computat Biol Unit, Bergen, Norway
[4] Univ Bergen, PROBE, Proteom Unit, Bergen, Norway
[5] Univ Bergen, Dept Informat, Bergen, Norway
[6] Univ Bergen, Dept Clin Med, Bergen, Norway
[7] Haukeland Hosp, Dept Neurol, N-5021 Bergen, Norway
关键词
biomarker; multiple sclerosis; proteomics; bioinformatics; mass spectrometry;
D O I
10.2174/138920106777549713
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Discovery of disease specific biomarkers in human body fluids has become an important challenge in clinical proteomics. Facing the increasing threat of degenerative and disabling diseases like cancer, cardiovascular, neurological and inflammatory diseases in large parts of the world's population, there is an urgent need to improve early diagnostics. In this review we discuss possibilities and limitations connected to using mass spectrometry based proteomics in the search for novel biomarkers, with focus on multiple sclerosis as a typical representative for the large group of non-curable degenerative and disabling disease with the lack of specific tests for early diagnosis. Careful control of the pre-analytical phase including sampling, storage and fractionation of samples, in addition to a thoroughly considered patient selection, is important in order to avoid false biomarkers to appear in the resulting mass spectra. Furthermore, advanced computational tools are needed in order to discover potential biomarkers from the enormous data amounts generated by the mass spectrometers. The development of such computer tools is a research field currently in the start phase and could prove to be a bottle neck in the biomarker discovery the next years. Therefore, a rather detailed review of the most used computational and pre-analytical methods is given in this review. Mass spectrometry based biomarker discovery is undoubtedly still in its early infancy. However, in light of the potential of this technology to provide deep coverage of the body fluid proteomes, it will certainly consolidate its role in developing molecular medicine into clinical practice.
引用
收藏
页码:147 / 158
页数:12
相关论文
共 93 条
[1]  
ABRAHAMSON M, 1987, J BIOL CHEM, V262, P9688
[2]  
ABRAHAMSON M, 1986, J BIOL CHEM, V261, P1282
[3]   Proteomic characterization of the human centrosome by protein correlation profiling [J].
Andersen, JS ;
Wilkinson, CJ ;
Mayor, T ;
Mortensen, P ;
Nigg, EA ;
Mann, M .
NATURE, 2003, 426 (6966) :570-574
[4]   A distinctive molecular signature of multiple sclerosis derived from MALDI-TOF/MS and serum proteomic pattern analysis - Detection of three biomarkers [J].
Avasarala, LR ;
Wall, MR ;
Wolfe, GM .
JOURNAL OF MOLECULAR NEUROSCIENCE, 2005, 25 (01) :119-125
[5]   A comprehensive approach to the analysis of matrix-assisted laser desorption/ionization-time of flight proteomics spectra from serum samples [J].
Baggerly, KA ;
Morris, JS ;
Wang, J ;
Gold, D ;
Xiao, LC ;
Coombes, KR .
PROTEOMICS, 2003, 3 (09) :1667-1672
[6]   THE PLACE OF HUMAN GAMMA-TRACE (CYSTATIN-C) AMONGST THE CYSTEINE PROTEINASE-INHIBITORS [J].
BARRETT, AJ ;
DAVIES, ME ;
GRUBB, A .
BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS, 1984, 120 (02) :631-636
[7]   Multiple polypeptide forms observed in two-dimensional gels of Methylococcus capsulatus (Bath) polypeptides are generated during the separation procedure [J].
Berven, FS ;
Karlsen, OA ;
Murrell, JC ;
Jensen, HB .
ELECTROPHORESIS, 2003, 24 (04) :757-761
[8]   A robust meta-classification strategy for cancer detection from MS data [J].
Bhanot, G ;
Alexe, G ;
Venkataraghavan, B ;
Levine, AJ .
PROTEOMICS, 2006, 6 (02) :592-604
[9]   Diagnosis of pancreatic cancer using serum proteomic profiling [J].
Bhattacharyya, S ;
Siegel, ER ;
Petersen, GM ;
Chari, ST ;
Suva, LJ ;
Haun, RS .
NEOPLASIA, 2004, 6 (05) :674-686
[10]   Peptidomics biomarker discovery in mouse models of obesity and type 2 diabetes [J].
Budde, P ;
Schulte, L ;
Appel, A ;
Neitz, S ;
Kellmann, M ;
Tammen, H ;
Hess, R ;
Rose, H .
COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING, 2005, 8 (08) :775-781