Gly l of cob na io r lo u g o y Bennun et al., J Glycobiol 2013, S1 J Journal of Glycobiology DOI: 10.4172/2168-958X.S1-004 ISSN: 2168-958X

Research Article Open Access Towards Integrative for Based Biomarker Cancer Research and Discovery Sandra V Bennun1*, Deniz Baycin Hizal2, René Ranzinger3 and Michael J Betenbaugh2 1Nanobiology Department, Sandia National Laboratories, Albuquerque, NM 87185, USA 2Department of Chemical and Biomolecular Engineering, Johns Hopkins University 3400 North Charles Street- Baltimore, Maryland 21218, USA 3Complex Research Center, University of Georgia, Athens, GA 30602, USA

Abstract Despite some recent successes in deciphering new cancer molecular makers, there is still a clear and continual need to develop new technologies that help characterizing existing biomarkers or facilitate discovery of new biomarkers. An important systems biology opportunity on this respect is provided by understanding the changes associated with cancer. Indeed, interest in cancer glycosylation has expanded over the past decade and large amount of data relevant to cancer glycosylation has been accumulating rapidly. Furthermore, new and improved sophisticated glycoinformatics tools, methods and for glycan analysis now offer the opportunity to investigate this data for understanding the role that play in cancer glycosylation. Here we summarize developments of glycoinformatics tools to support analysis of cancer glycosylation and experimental glycoproteomics approaches. In addition, we discuss challenges faced by glycoinformatics for the integration and interrogation of disparate high-throughput glycan data sets in order to assimilate technologies and better address cancer glycosylation. We also provide examples of integrative glycoinformatics approaches that lead to a better understanding of cancer glycosylation as a complex cellular process.

Keywords: Cancer; Biomarkers; Glycobiology; Glycans; Integrative diagnostics of clinical utility. Improved integrative glycoinformatics glycoinformatics; Glycoproteomics; Automatic glycan annotation; tools will likely play an important role in addressing these challenges. High-throughput; Technologies; Mass spectrum spectrum; ; Databases; Mathematical modeling; Monocytic leukemia; Experimental Glycoproteomic Approaches Prostate cancer; Lncap cells Aberrant glycosylation has been associated with cancer, and several that are biomarkers and targets for cancer have Introduction been found to be glycosylated. There are many US Food and Drug Glycans are structurally complex carbohydrate chains found on Administration (FDA) approved biomarkers and targets such as proteins, to form glycoproteins, and on lipids, to form glycolipids. epidermal growth factor receptor, which is used for therapy selection Abnormalities in glycosylation are linked to cancer and many other and α-fetoprotein and human chorionic gonadotropin-β which diseases [1-4]. The glycosylation of healthy and diseased cells often are currently used for diagnosis [34]. Rather than just studying the diverges resulting in glycan changes that may contribute to pathological glycan structures, glycoproteomics evaluates the glycosylated proteins progression [5,6]. Thus changes in glycosylation provide promise for and their glycosylation sites [35]. Glycoprotein enrichment can be the diagnosis and therapeutics of a wide variety of cancers [7-10]. To coupled with comparative proteomics methods and advanced mass give but one of many examples, antibodies that recognize the sialyl spectrometry techniques to find the differentially expressed proteins Lewisa/x carbohydrate determinants prov