Integrative analysis of LC-MS based glycomic and proteomic data

Studies associating changes in the levels of glycans and proteins with the onset of cancer have been widely investigated to identify clinically relevant diagnostic biomarkers. Advances in liquid chromatography mass spectrometry (LC-MS) have enabled high-throughput identification and quantitative analysis of these biomolecules. While results from separate analyses of glycans and proteins have been reported widely, the mutual information obtained by combining the two has been relatively unexplored. In this study, we investigate integrative analysis of glycans and proteins to take advantage complementary information to improve the ability to distinguish cancer cases from controls. Specifically, SVM-RFE algorithm is utilized to select a panel of N-glycans and proteins from LC-MS data previously acquired by analysis of sera from two cohorts in a liver cancer study. Improved performances are observed by integrative analysis compared to separate glycomic and proteomic studies in distinguishing liver cancer cases from patients with liver cirrhosis.