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Mass Spectrometry Data



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Identification of N Glycan Serum Markers Associated with Hepatocellular Carcinoma from Mass Spectrometry Data Zhiqun Tang Rency S Varghese Slavka Bekesova Christopher A Loffredo Mohamed Abdul Hamid Zuzana Kyselova Yehia Mechref Milos V Novotny Radoslav Goldman and Habtom W Ressom Department of Oncology Lombardi Comprehensive Cancer Center Georgetown University Washington D C 20057 Minia University and Viral Hepatitis Research Laboratory NHTMRI Cairo Egypt and National Center for Glycomics and Glycoproteomics Department of Chemistry Bloomington Indiana Received May 5 2009 Glycocylation represents the most complex and widespread post translational modifications in human proteins The variation of glycosylation is closely related to oncogenic transformation Therefore profiling of glycans detached from proteins is a promising strategy to identify biomarkers for cancer detection This study identified candidate glycan biomarkers associated with hepatocellular carcinoma by mass spectrometry Specifically mass spectrometry data were analyzed with a peak selection procedure which incorporates multiple random sampling strategies with recursive feature selection based on support vector machines Ten peak sets were obtained from different combinations of samples Seven peaks were shared by each of the 10 peaksets in which 7 12 peaks were selected indicating 58 100 of peaks were shared by the 10 peaksets Support vector machines and hierarchical clustering method were used to evaluate the performance of the peaksets The predictive performance of the seven peaks was further evaluated by using 19 newly generated MALDI TOF spectra Glycan structures for four glycans of the seven peaks were determined Literature search indicated that the structures of the four glycans could be found in some cancer related glycoproteins The method of this study is significant in deriving consistent accurate and biological significant glycan marker candidates for hepatocellular carcinoma diagnosis Keywords



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