Evidence map›Paper›PMID 41164132›Full record

ArticleFrontiers in oncology2025

The role of immune- and lipid metabolism-related genes in macrophage polarization and prognosis of glioblastoma.

Yue Zhang, Xin Xu, Shuo Li, Chenlong Liao, Xiaosheng Yang, Wenchuan Zhang

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PubMed Full text at PMC Publisher
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Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

  1. Review
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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

6 authors.

Yue Zhang *Department of Neurosurgery, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Xin Xu *Department of Neurosurgery, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Shuo Li *Department of Neurosurgery, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Chenlong LiaoDepartment of Neurosurgery, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Xiaosheng YangDepartment of Neurosurgery, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Wenchuan ZhangDepartment of Neurosurgery, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the roles of immune- and lipid metabolism-related genes in macrophage polarization and their prognostic and therapeutic implications in glioblastoma (GBM). Methods: A total of 655 GBM samples from The Cancer Genome Atlas (TCGA) were stratified into immune and non-immune groups based on immune scores. Differentially expressed genes (DEGs) were identified, and their intersection with 859 lipid metabolism-related genes yielded 26 candidates. A 10-gene prognostic signature was constructed using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses and validated in both internal (TCGA) and independent (Chinese Glioma Genome Atlas, CGGA) cohorts. Functional enrichment, single-cell transcriptomic analysis, experimental validation, and drug sensitivity profiling were performed to assess the biological and therapeutic relevance of the identified genes. Results: Ten immune- and lipid metabolism-related genes were significantly associated with GBM prognosis. Key genes such as Conclusions: Immune- and lipid metabolism-related genes contribute to macrophage polarization and are closely linked to GBM prognosis. The identified gene signature provides prognostic value and potential therapeutic targets for immunometabolic modulation in GBM.

Indexed as

glioblastomaimmune responselipid metabolismmacrophage polarizationprognostic genes

Identifiers

PMID41164132
PMCPMC12558797

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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.