Integration of the transcriptome and glycome for identification of glycan cell signatures.

ABSTRACT: Abnormalities in glycan biosynthesis have been conclusively linked to many diseases but the complexity of glycosylation has hindered the analysis of glycan data in order to identify glycoforms contributing to disease. To overcome this limitation, we developed a quantitative N-glycosylation model that interprets and integrates mass spectral and transcriptomic data by incorporating key glycosylation enzyme activities. Using the cancer progression model of androgen-dependent to androgen-independent Lymph Node Carcinoma of the Prostate (LNCaP) cells, the N-glycosylation model identified and quantified glycan structural details not typically derived from single-stage mass spectral or gene expression data. Differences between the cell types uncovered include increases in H(II) and Le(y) epitopes

SUBMITTER: Bennun SV 

PROVIDER: S-EPMC3542073 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature