Evidence map›Paper›PMID 40548122›Full record

ArticleFrontiers in oncology2025

Interrogation of macrophage-related prognostic signatures reveals a potential immune-mediated therapy strategy by histone deacetylase inhibition in glioma.

Xisen Wang, Xuya Wang, Lei Chen, Haozhe Ding, Jikang Fan, Jianshen Liang, Yu Zhang, Yiming Li, Yiming Zhang, Shengping Yu and 4 more

Abstract read
In one paragraph

Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Xisen Wang *Department of Neurosurgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.
Xuya Wang *Department of Neurosurgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.
Lei Chen *Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Haozhe DingDepartment of Neurosurgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.
Jikang FanDepartment of Neurosurgery, Tianjin Huanhu Hospital, Tianjin, China.
Jianshen LiangDepartment of Neurosurgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.
Yu ZhangDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Yiming LiDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Yiming ZhangDepartment of Neurosurgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.
Shengping YuDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Chen ZhangDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Yaohua LiDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Tao LiDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Xuejun YangDepartment of Neurosurgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Glioma-associated macrophages (GAMs) originate from intracranially resident microglia and myeloid-derived macrophages. In the glioma microenvironment, these two types of macrophages tend to adopt a specialized activation state known as type 2 or M2 macrophages and play crucial roles in the progression of glioma. Methods: To identify genes associated with GAMs, we intersected genes identified from single-cell RNA sequencing (scRNA-seq) data (specific to GAMs) with M2 macrophage module genes derived from weighted gene coexpression network analysis (WGCNA). Prognostic genes were screened using univariate Cox regression, multivariate Cox regression, and least absolute shrinkage and selection operator (LASSO) regression analysis. These genes were used to construct and validate prognostic signatures and to delineate the immune landscape. During drug screening, Vorinostat exhibited the highest risk score and the lowest half-maximal inhibitory concentration (IC Results: Fourteen prognostic genes (TREM2, GAL3ST4, AP1B1, SLA, CYBB, CD53, SLC37A2, ABI3, RIN3, SCIN, SIGLEC10, C3, PLEKHO2, and PLXDC2) were identified. The prognostic model constructed from these genes demonstrated robust predictive efficacy. Based on this model, Vorinostat was prioritized as a candidate therapeutic agent, and subsequent validation confirmed its significant inhibitory effects on the glioma microenvironment. Conclusion: These findings elucidate the molecular mechanisms of GAMs in glioma, uncover the immunological landscape of the tumor microenvironment, and identify potential therapeutic targets and drug action mechanisms.

Indexed as

gliomaglioma-associated macrophageshistone deacetylase inhibitorsimmune microenvironmentprognostic signaturevorinostat

Identifiers

PMID40548122
PMCPMC12179195

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