A computational platform for MALDI-TOF mass spectrometry data: application to serum and plasma samples.
BACKGROUND
Mass spectrometry (MS) is becoming the gold standard for biomarker discovery. Several MS-based bioinformatics methods have been proposed for this application, but the divergence of the findings by different research groups on the same MS data suggests that the definition of a reliable method has not been achieved yet. In this work, we propose an integrated software platform, MASCAP, intended for comparative biomarker detection from MALDI-TOF MS data.


RESULTS
MASCAP integrates denoising and feature extraction algorithms, which have already shown to provide consistent peaks across mass spectra; furthermore, it relies on statistical analysis and graphical tools to compare the results between groups. The effectiveness in mass spectrum processing is demonstrated using MALDI-TOF data, as well as SELDI-TOF data. The usefulness in detecting potential protein biomarkers is shown comparing MALDI-TOF mass spectra collected from serum and plasma samples belonging to the same clinical population.


CONCLUSIONS
The analysis approach implemented in MASCAP may simplify biomarker detection, by assisting the recognition of proteomic expression signatures of the disease. A MATLAB implementation of the software and the data used for its validation are available at http://www.unich.it/proteomica/bioinf.
Mantini
Dante
D
Istituto Tecnologie Avanzate Biomediche (ITAB), Fondazione G. d'Annunzio, Chieti, Italy.
Petrucci
Francesca
F
Pieragostino
Damiana
D
Del Boccio
Piero
P
Sacchetta
Paolo
P
Candiano
Giovanni
G
Ghiggeri
Gian Marco
GM
Lugaresi
Alessandra
A
Federici
Giorgio
G
Di Ilio
Carmine
C
Urbani
Andrea
A
D000465:Algorithms; D001327:Autoimmune Diseases / Q000097:blood / Q000378:metabolism; D015415:Biomarkers / Q000032:analysis / Q000097:blood / Q000378:metabolism; D001774:Blood Chemical Analysis / Q000379:methods / Q000706:statistics & numerical data*; D001798:Blood Proteins / Q000032:analysis / Q000378:metabolism; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D003627:Data Interpretation, Statistical; D006801:Humans; D010949:Plasma / Q000737:chemistry* / Q000378:metabolism; D044967:Serum / Q000737:chemistry* / Q000378:metabolism; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*
D015415:Biomarkers; D001798:Blood Proteins