TY - JOUR T1 - Integration of the Transcriptome and Glycome for Identification of Glycan Cell Signatures A1 - Bennun, Sandra V. A1 - Yarema, Kevin J. A1 - Betenbaugh, Michael J. A1 - Krambeck, Frederick J. Y1 - 2013/01/10 N2 - Author Summary Glycans are the sugar attachments that are found on proteins and lipids. These highly variable and structurally diverse sugar chains confer distinctive characteristics to the cell surface. Recent research has revealed that these glycan profiles can represent important signatures of disease states and thus understanding glycan processing and structures in cells is an important systems biology goal. Glycan structures are often characterized through mass spectral analysis while their glycosylation processing enzymes are characterized using gene expression profiling. Unfortunately, due to the complexity of glycosylational processing, it has been difficult to relate these disparate data sets until now. In this paper we demonstrate for the first time the ability of a systems glycobiology model to link glycan structural data obtained from mass spectral analysis with mRNA expression data in terms of enzyme activities catalyzing the glycosylation reactions in the cells. We show that such a systems biology model enables identification of distinctive and subtle glycan fingerprints differences between prostate cancer cell stages (androgen-dependent and more metastatic androgen independent). This systems approach will enable us to use high throughput glycomics and gene expression data sets in order to specify glycan-based signatures as important diagnostic markers of disease and potential therapeutic targets. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 9 IS - 1 UR - https://doi.org/10.1371/journal.pcbi.1002813 SP - e1002813 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1002813 ER -