A computational platform for MALDI-TOF mass spectrometry data: Application to serum and plasma samples

作者：Mantini Dante; Petrucci Francesca; Pieragostino Damiana; Del Boccio Piero; Sacchetta Paolo; Candiano Giovanni; Ghiggeri Gian Marco; Lugaresi Alessandra; Federici Giorgio; Di Ilio Carmine; Urbani Andrea^*

来源：Journal of Proteomics, 2010, 73(3): 562-570.

DOI：10.1016/j.jprot.2009.11.004

• Biomarker discovery
• Graphical tools
• Mass spectrometry
• Proteomics
• Statistical analysis

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.

• 出版日期2010-1-3