Identification of drug responsible glycogene signature in liver carcinoma from meta-analysis using RNA-seq data

• Published in: Glycoconjugate journal 2024-04, Vol.41 (2), p.133-149
• Main Authors: Koreeda, Tatsuya, Honda, Hiroshi
• Format: Article
• Language: English
• Subjects: Antineoplastic Agents - pharmacology; Biochemistry; Bioinformatics; Biomedical and Life Sciences; Cancer therapies; Carcinoma, Hepatocellular - drug therapy; Carcinoma, Hepatocellular - genetics; Carcinoma, Hepatocellular - metabolism; Cell Line, Tumor; Cell surface; Ceramide glucosyltransferase; GDP-mannose; Gene Expression Regulation, Neoplastic - drug effects; Glucosyltransferase; Heparan sulfate; Hepatocytes; Humans; Life Sciences; Lipids; Liver cancer; Liver Neoplasms - drug therapy; Liver Neoplasms - genetics; Liver Neoplasms - metabolism; Mannose; Meta-analysis; N-Acetyllactosamine synthase; Pathology; Polysaccharides; Polysaccharides - metabolism; Protein interaction; Protein Interaction Maps; RNA-Seq; Tumor cell lines
• ISSN: 0282-0080; 1573-4986; 1573-4986
• DOI: 10.1007/s10719-024-10153-y

Glycans have attracted much attention in cancer therapeutic strategies, and cell surface proteins and lipids with glycans are known to be altered during the carcinogenic process. However, our understanding of how the glycogenes profile responds to drug stimulation remains incomplete. In this study, we search public databases for Sequence Read Archive data on drug-treated liver cancer cells, with the aim to comprehensively analyze the drug responses of glycogenes via bioinformatic meta-analysis. The study comprised 86 datasets, encompassing eight distinct liver cancer cell lines and 13 different drugs. Differentially expressed genes were quantified, and 399 glycogenes were identified. The glycogenes signature was then analyzed using bioinformatics methodologies. In the Protein-protein interaction network analysis, we identified drug-responsive glycogenes such as Beta-1,4-Galactosyltransferase 1, GDP-Mannose 4,6-Dehydratase, UDP-Glucose Ceramide Glucosyltransferase, and Solute Carrier Family 2 Member 4 as key glycan biomarkers. In the enrichment analysis using the pathway list of glycogenes, the results also demonstrated that drug stimulation resulted in alterations to glycopathway-related genes involved in several processes, namely O-Mannosylation, POMGNT2 Type, Capping, Heparan Sulfate Sulfation, and Glucuronidation pathways. These genes and pathways commonly exhibit variable expression across multiple liver cancer cells in response to the same drug, making them potential targets for new cancer therapies. In addition to their primary roles, drugs may also participate in the regulation of glycans. The insights from this study could pave the way for the development of liver cancer therapies that target the regulation of gene profiles involved in the biosynthesis of glycans.