Evidence map›Paper›PMID 40386998›Full record

ArticleAnnals of clinical and translational neurology2025

Glycosylation Gene Signatures as Prognostic Biomarkers in Glioblastoma.

Tong Zhao, Hongliang Ge, Chenchao Lin, Xiyue Wu, Jianwu Chen

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PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of clinical and translational neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Tong ZhaoDepartment of Neurosurgery, Neurosurgery Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Hongliang GeDepartment of Neurosurgery, Neurosurgery Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Chenchao LinDepartment of Neurosurgery, Neurosurgery Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Xiyue WuDepartment of Neurosurgery, Neurosurgery Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Jianwu ChenDepartment of Neurosurgery, Neurosurgery Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.ORCID 0009-0003-5201-9598

Funding

Fujian Provincial Science and Technology Innovation Joint Fund Project 2021Y9149Joint Funds for the Innovation of Science and Technology, Fujian Province 2024Y9123Leading Project Foundation of Science and Technology, Fujian Province 2021Y0013National Natural Science Foundation of China 82301543
6 · The paper itself

Abstract

objectiveGlioblastoma (GBM) is an aggressive brain tumor characterized by significant heterogeneity. This study investigates the role of glycosylation-related genes in GBM subtyping, prognosis, and response to therapy.

methodsWe analyzed mRNA expression data and clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Glycosylation-related genes were selected for differential expression analysis, sample clustering, and survival analysis. Immune cell infiltration and drug sensitivity were evaluated using CIBERSORT and oncoPredict, respectively. A prognostic model was constructed with Lasso regression.

resultsGBM samples were stratified into two glycosylation-related subtypes, showing distinct survival outcomes, with higher glycosylation expression correlating with poorer prognosis. Immune microenvironment analysis revealed differences in T-cell infiltration and immune checkpoint expression between subtypes, indicating variable immunotherapy responses. The prognostic model based on glycosylation genes demonstrated significant predictive value for patient survival.

conclusionGlycosylation-related gene expression contributes to GBM heterogeneity and is a valuable biomarker for prognosis and treatment stratification. This study provides insights into personalized treatment approaches for GBM based on glycosylation-related molecular subtypes.

Indexed as

Biomarkers, TumorBrain NeoplasmsGlioblastomaGene Expression Regulation, NeoplasticGlycosylationHumansPrognosisTranscriptomeTumor MicroenvironmentBiomarkers, Tumorglioblastomaglycosylation genesimmune microenvironmentLasso regressionprognostic modelsurvival analysis

Identifiers

PMID40386998
PMCPMC12257128

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.