학술논문

OncoDB. Glycogene: An integrated cancer genomic database for glycosylation-related genes
Document Type
Conference
Source
2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Intelligent Informatics and Biomedical Sciences (ICIIBMS), 2017 International Conference on. :301-301 Nov, 2017
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
General Topics for Engineers
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Cancer
Tumors
Bioinformatics
Biomedical imaging
Genomics
Databases
Neuroscience
glycosylation
tumor progression
omics
integration
Language
ISSN
2189-8723
Abstract
Glycosylation by classic définition is a serial biochemical and enzymatic addition that a glycosyl donor attached to the hydroxyl or functional group of glycosyl acceptor, such as protein or lipid, to form a branch structure. Emerging evidences that aberrant expression of glycosylation-related genes (glycogenes) resulting in altered glycosylation targets have been identified its importance in tumor progression including invasion, migration, proliferation, angiogenesis, and metastasis, while all these components are highly correlated with clinical diagnosis and treatment. To facilitate our understanding of such genes participated in tumor progression, we construct a database OncoDB.Glycogene for developing new theranostic targets of cancers and demonstrate our text-mining based glycogene corpus with the combination of The Cancer Genome Atlas (TCGA) data to draw the interaction between abnormal glycosylation with tumor from integrated genomic viewpoints. We first showed that the coverage of 3026 glycogenes from OncoDB.Glycogene are more comprehensive and unique than other public glycogene resources with inclusion of biosynthesis, metabolism and functional participation of glycosylation such as nucleotide sugar transporter, precursors, or surveillance chaperon, from the aspects of pathway or either Gene Ontology similarity. And to comprehensively reveal glycogenes participated in cancers, we integrated cancer omics data such as copy number, methylation, gene expression with clinical features, i.e. patient survival information, from TCGA with user friendly webpage interfaces for graphic and pathway network displays. With our integrative effort we should improve our knowledge how glycosylation engage in tumor progression and facilitate development of theranostic biomarkers of cancers.