Comprehensive Analysis of Glycosyltransferases in Cancer Identified from a Multifaceted Genomics Approach

Abstract

Despite accumulating evidence supporting a role for glycosylation in cancer progression and prognosis, the complexity of the human glycome and study thereof poses many challenges to gaining a comprehensive understanding of glycosylation-related events in cancer. In this study, a multifaceted genomics approach was applied to analyze potential impact of differential expression of glycosyltransferases responsible involved in various glycosylation pathways. An enzyme list was first compiled and curated from numerous resources to create a consensus list of glycosyltransferases. These enzymes were then analyzed for differential expression in cancer and examined for enrichment among cancer samples. Finally, these results were integrated with experimental evidence from other types of analyses including similarity of expression patterns across orthologous genes in mice, miRNA expression of miRNAs expected to target these genes, scRNA expression of the same genes, and automatically mined literature relationships for these genes in human disease. Top genes identified by cross-referencing analyses were examined with respect to functional impact, and high-value glycan residues were identified. Relevant findings have been made publicly available through OncoMX at data.oncomx.org, developed in part within the scope of this project. Scripts (available in GitHub) and the overarching pipeline defined herein can be used as a framework for similarly analyzing other groups of enzymes for impact across diverse evidence types in cancer. This work is expected to improve the overall understanding of the role of glycosylation in cancer by transparently defining the space of glycosyltransferase enzymes, and by harmonizing variable experimental data to enable improved generation of data-driven cancer biomarker hypotheses