ArticleFrontiers in pharmacology2023
A glycosylation-related gene signature predicts prognosis, immune microenvironment infiltration, and drug sensitivity in glioma.
Article in Frontiers in pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Integrative Analysis of Glycosylation-Related Genes Reveals Prognostic Subtypes, Immune Evasion, and Therapeutic Vulnerabilities in Lung Adenocarcinoma.Oncology research · 2026Article
- Post-Translational Modification-Driven Metabolic Reprogramming Shapes Melanoma Progression and Immune Microenvironment.Clinical, cosmetic and investigational dermatology · 2026Article
- Multi-Omics and Single-Cell Dissection of Exostosin Glycosyltransferases (EXT1/EXT2) Reveals Divergent Oncogenic Roles and Therapeutic Vulnerabilities in Gliomas.Journal of Cancer · 2026Article
- CT-based intratumoral and peritumoral radiomics to predict the treatment response to hepatic arterial infusion chemotherapy plus lenvatinib and PD-1 in high-risk hepatocellular carcinoma cases: a multi-center study.Hepatology international · 2025Article
- The role of glycan-lectin interactions in the tumor microenvironment: immunosuppression regulators of colorectal cancer.American journal of cancer research · 2025Review
- Review
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Authors and funding
11 authors.
Funding
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Abstract
Glioma represents the most common primary cancer of the central nervous system in adults. Glycosylation is a prevalent post-translational modification that occurs in eukaryotic cells, leading to a wide array of modifications on proteins. We obtained the clinical information, bulk RNA-seq data, and single-cell RNA sequencing (scRNA-seq) from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Gene Expression Omnibus (GEO), and Repository of Molecular Brain Neoplasia Data (Rembrandt) databases. RNA sequencing data for normal brain tissues were accessed from the Genotype-Tissue Expression (GTEx) database. Then, the glycosylation genes that were differentially expressed were identified and further subjected to variable selection using a least absolute shrinkage and selection operator (LASSO)-regularized Cox model. We further conducted enrichment analysis, qPCR, nomogram, and single-cell transcriptome to detect the glycosylation signature. Drug sensitivity analysis was also conducted. A five-gene glycosylation signature (
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