ArticleScientific reports2024
Predictive potentials of glycosylation-related genes in glioma prognosis and their correlation with immune infiltration.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 17 citations in OpenAlex.
- An externally validated lactylation-associated prognostic signature for overall survival prediction in lung adenocarcinoma identifiesTranslational cancer research · 2026Article
- Glycosylation-related gene risk model and functional validation of OSTC and TUBA1C in lung adenocarcinoma.Respiratory research · 2026Article
- Multi-Omics Integration for Advancing Glioma Precision Medicine.Annals of clinical and translational neurology · 2026Review
- Machine-Learning-Based Prediction of Clinical Outcomes in Gliomas Using Glycomic Features.Computational and structural biotechnology journal · 2026Article
- P4HB regulates tumor-associated macrophage polarization and chemotaxis by enhancing IL-6 cytokine secretion in glioblastoma.Annals of medicine and surgery (2012) · 2025Article
- SERPINA1 gene regulates the tumorigenesis and progression of breast cancer through PI3K/AKT signaling pathway and tumor immune microenvironment.Scientific reports · 2025Article
- Article
- Identification and Validation of Glycosylation‑Related Genes in Ischemic Stroke Based on Bioinformatics and Machine Learning.Journal of molecular neuroscience : MN · 2025Article
- Serum N-Glycomics with Nano-LC-QToF LC-MS/MS Reveals N-Glycan Biomarkers for Glioblastoma, Meningioma, and High-Grade Meningioma.Journal of proteome research · 2025Article
- Review
- A multi-cohort validated OXPHOS signature predicts survival and immune profiles in grade II/III glioma patients.Frontiers in immunology · 2025Article
- Effect of Different Glucose Levels and Glycation on Meningioma Cell Migration and Invasion.International journal of molecular sciences · 2024Article
- Application of a risk score model based on glycosylation-related genes in the prognosis and treatment of patients with low-grade glioma.Frontiers in immunology · 2024Article
- When a negative (charge) is not a positive: sialylation and its role in cancer mechanics and progression.Frontiers in oncology · 2024Review
- Targeting the Siglec/sialic-acid axis in glioblastoma: Glycome-mediated immune evasion and emerging therapeutic platforms.Neuro-oncology advancesReview
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
Glycosylation is currently considered to be an important hallmark of cancer. However, the characterization of glycosylation-related gene sets has not been comprehensively analyzed in glioma, and the relationship between glycosylation-related genes and glioma prognosis has not been elucidated. Here, we firstly found that the glycosylation-related differentially expressed genes in glioma patients were engaged in biological functions related to glioma progression revealed by enrichment analysis. Then seven glycosylation genes (BGN, C1GALT1C1L, GALNT13, SDC1, SERPINA1, SPTBN5 and TUBA1C) associated with glioma prognosis were screened out by consensus clustering, principal component analysis, Lasso regression, and univariate and multivariate Cox regression analysis using the TCGA-GTEx database. A glycosylation-related prognostic signature was developed and validated using CGGA database data with significantly accurate prediction on glioma prognosis, which showed better capacity to predict the prognosis of glioma patients than clinicopathological factors do. GSEA enrichment analysis based on the risk score further revealed that patients in the high-risk group were involved in immune-related pathways such as cytokine signaling, inflammatory responses, and immune regulation, as well as glycan synthesis and metabolic function. Immuno-correlation analysis revealed that a variety of immune cell infiltrations, such as Macrophage, activated dendritic cell, Regulatory T cell (Treg), and Natural killer cell, were increased in the high-risk group. Moreover, functional experiments were performed to evaluate the roles of risk genes in the cell viability and cell number of glioma U87 and U251 cells, which demonstrated that silencing BGN, SDC1, SERPINA1, TUBA1C, C1GALT1C1L and SPTBN5 could inhibit the growth and viability of glioma cells. These findings strengthened the prognostic potentials of our predictive signature in glioma. In conclusion, this prognostic model composed of 7 glycosylation-related genes distinguishes well the high-risk glioma patients, which might potentially serve as caner biomarkers for disease diagnosis and treatment.
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