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Glycan Node Analysis: A Bottom-up Approach to Glycomics
Published on: May 22, 2016
Transcriptomic analysis uncovers dysregulated glycosylation pathways in clear cell renal cell carcinoma
Ru M Wen1, G Edward W Marti2, Rosalie Nolley3
1Department of Urology, Stanford University School of Medicine, Stanford, CA, USA; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
Abstract:
Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer and is characterized by altered metabolism, immune remodeling, and aberrant glycosylation. Although glycosylation regulates tumor-cell signaling, adhesion, angiogenesis, and immune recognition, its relationship with the ccRCC immune microenvironment remains incompletely defined. Here, we analyzed RNA-sequencing profiles from ccRCC tumors and adjacent normal kidney tissues. Glycan-related genes and glycogenes involved in glycan biosynthesis distinguished ccRCC tumors from normal tissues and revealed altered sulfatase, nucleotide sugar, glycosyltransferase, glycosaminoglycan pathways. CIBERSORTx analysis showed distinct immune cell distributions in tumors, and Spearman correlation analysis linked glycosylation pathway activity with immune cell abundance. Glycogene expression further classified ccRCC tumors into two subtypes with different immune signatures, Siglec expression patterns, and overall survival. The transcriptional differences between normal and tumor tissues are dominated by immune/inflammatory activation and ion/membrane transport regulation. Our results underscore the importance of targeting cancer-associated changes in glycosylation machinery using novel strategies to improve the specificity and efficacy of cancer therapeutics in ccRCC.