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Genome-Wide RNA-Seq Analyses of O-Glycan Glycosyltransferases for Molecular Prognostic Markers in Non-Small Cell Lung Cancer

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A7087 - Genome-Wide RNA-Seq Analyses of O-Glycan Glycosyltransferases for Molecular Prognostic Markers in Non-Small Cell Lung Cancer
Author Block: S. Lin1, Y. Chen2, T. Yang2, Y. Wu3, G. A. Oswita3, H. Lu4, C. Yu5, H. Tsai6; 1Internal medicine, National Taiwan University Hospital Jin-Shan Branch, New Tapei City, Taiwan, 2Graduate Institute of Toxicology, National Taiwan University, College of Medicine, Taipei, Taiwan, 3Graduate Institute of Toxicology, National Taiwan University, College of Medicine, Tapei, Taiwan, 4Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan, 5Internal medicine, National Taiwan University Hospital, Taipei, Taiwan, 6Internal medicine, National Taiwan University Hospital, Tapei, Taiwan.
Background:Aberrant O-glycosylation represents a common feature during oncogenesis in various tumor types. A number of glycosyltransferases are involved in the formation of complex structures of O-glycans. However, their prognostic relevance and the corresponding molecular alterations in cancer are mostly unknown. By utilizing genome-wide RNA-seq analysis, we aim to reveal the comprehensive picture of altered O-glycosyltransferases, their prognostic impact, and molecular signaling pathways in lung cancer patients. Methods:Eighty-one (adenocarcinoma n=44, squamous cell carcinoma n=37) archived non-small cell lung cancer surgical samples and 19 adjacent normal tissues from 1996 to 2008 underwent genome-wide RNA-seq analysis. We queried a total of 44 O-glycosyltransferases, including core forming, branching, terminal sialyation and fucosylation enzymes. Principle component analysis (PCA) were performed to visualize global changes in tumors and normal tissues. Differentially-expressed O-glycosyltransferases between tumors and normal tissues were statistically derived, and correlated with clinicopathological features and overall survivals. Finally, we performed co-expression analysis, gene ontology enrichment and pathway identification on these gene-sets for functional classification. Results:The unsupervised hierarchical cluster analysis of the O-glycosyltransferases and PCA analysis showed distinct expression patterns between lung cancer and normal adjacent tissues. Core 1-3 forming enzymes showed statistically significant up-regulation, while terminal sialyation enzymes showed down-regulation in lung cancer tissues. Decreased expression of ST6GALNAC3 (ST6 GalNAc α-2,6-Sialyltransferase 3) was associated with positive nodal status. ST6GALNAC6 and ST3GAL3 (ST3 β-Galactoside Alpha-2,3-Sialyltransferase 3), two terminal sialyltransferases were negatively associated with overall survival. Co-expression analysis showed distinct pathways involved in each glycosyltransferase. Notably, immune process-related pathways were negatively correlated with ST3GAL3, while cellular movement pathways were positively correlated with ST6GALNAC3. Conclusions:We have unraveled the complex alterations of O-glycosyltransferases in non-small cell lung cancer, which favored the formation of core structures and suppressed terminal sialyation. In addition, the decreased activity of terminal sialyltransferases were associated with nodal stage and poor survival.
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