Evidence map›Paper›PMID 41037139›Full record

ArticleDiscover oncology2025

Identification of key biomarkers and immune microenvironment features in gliomas based on single-cell analysis combined with bioinformatics.

Yang Zhang, Lisha Liu, Chao Peng, Lu Wang, Jun Yang, Yingjiang Gu, Yu Cai

Abstract read
In one paragraph

Article in Discover oncology, 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. Review
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

7 authors.

Yang Zhang *Department of Neurosurgery, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, Sichuan Province, China.
Lisha Liu *Department of Neurosurgery, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, Sichuan Province, China.
Chao PengThe First People Hospital of Guiyang, Guiyang, Guizhou Province, China.
Lu WangBeijing Jishuitan Hospital Guizhou Hospital, Guiyang, Guizhou Province, China.
Jun YangDepartment of Neurosurgery, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, Sichuan Province, China.
Yingjiang GuDepartment of Neurosurgery, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, Sichuan Province, China. 702815989@qq.com.
Yu CaiDepartment of Neurosurgery, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, Sichuan Province, China. cyjlcx0409@swmu.edu.cn.

Funding

Southwest Medical University 2019ZQN147
6 · The paper itself

Abstract

Gliomas are highly invasive and heterogeneous tumors in the central nervous system (CNS), characterized by poor prognosis and significant therapeutic challenges. The comprehensive understanding of their molecular mechanisms remains a critical focus and challenge in current research. This study aims to integrate bioinformatics and single-cell analysis technologies to explore glioma-related cell types and immune cell infiltration features, providing new insights into the molecular pathogenesis of gliomas and identifying potential therapeutic targets. Gene expression profiles were selected from Gene Expression Omnibus (GEO), and a glioma-related gene dataset was obtained from GeneCards. Single-cell analysis was employed to identify cell types, and bioinformatics techniques were applied to identify potential pathogenic targets in gliomas. A protein-protein interaction (PPI) network was constructed, followed by functional enrichment analysis using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Ultimately, drug target prediction and molecular docking analysis revealed the mechanisms of potential drugs. Single-cell analysis identified 10 cell types, with microglial cells and oligodendrocytes playing crucial roles in gliomas. Molecular biological analysis identified 20 key genes. GO and KEGG analyses indicated that these hub genes were primarily enriched in processes such as cellular component organization or biogenesis, cellular processes, cell junctions, and catalytic activity. The main signaling pathways involved include the p53 signaling pathway, cell cycle, and cellular senescence. Furthermore, molecular docking results showed that quercetin effectively binds to four hub targets (DLGAP5, TOP2A, CHEK1, MKI67), suggesting that quercetin may improve glioma-related biological features by acting on these targets. In conclusion, this study not only reveals the significant roles of specific cell types and key genes in gliomas but also preliminarily elucidates the molecular mechanisms of quercetin as a potential therapeutic agent, providing a solid theoretical foundation and new research directions for future glioma intervention strategies.

Indexed as

GliomaImmune cell infiltrationQuercetinSingle-cell analysis

Identifiers

PMID41037139
PMCPMC12491134

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Registered trials

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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.