Evidence map›Paper›PMID 41026376›Full record

ArticleDiscover oncology2025

Integrative multi-omics analysis identifies AEBP1 and EFEMP2 as key regulators of immune heterogeneity and therapeutic response in glioblastoma.

Yi Yin, Xingyu Fu, Shuhua Gong, Yutong Xie, Wenyu Wu, Zhenzhou Li, Shuo Wu, Zhengliang Gao, Ke Hu, Chun Luo and 1 more

Abstract read
PubMed Full text at PMC Publisher
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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Multi-Omics Integration for Advancing Glioma Precision Medicine.Annals of clinical and translational neurology · 2026
    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

11 authors.

Yi YinShanghai Baoshan Luodian Hospital, School of Medicine, Shanghai University, Shanghai, 201908, China.
Xingyu FuShanghai Baoshan Luodian Hospital, School of Medicine, Shanghai University, Shanghai, 201908, China.
Shuhua GongShanghai Baoshan Luodian Hospital, School of Medicine, Shanghai University, Shanghai, 201908, China.
Yutong XieDepartment of Neurosurgery, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, China.
Wenyu WuShanghai Baoshan Luodian Hospital, School of Medicine, Shanghai University, Shanghai, 201908, China.
Zhenzhou LiDepartment of Anesthesiology and Perioperative Medicine, General Hospital of Ningxia Medical University, Ningxia, 750004, China.
Shuo WuShanghai Baoshan Luodian Hospital, School of Medicine, Shanghai University, Shanghai, 201908, China.
Zhengliang GaoShanghai Baoshan Luodian Hospital, School of Medicine, Shanghai University, Shanghai, 201908, China.
Ke HuShanghai Baoshan Luodian Hospital, School of Medicine, Shanghai University, Shanghai, 201908, China. spike@shu.edu.cn.
Chun LuoDepartment of Neurosurgery, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, China. boyluochun@126.com.
Huan WangDepartment of Anesthesiology, Gongli Hospital of Shanghai Pudong New Area, Shanghai, China. Cheery_Wang@usst.edu.cn.

Funding

National Natural Science Foundation of China 32370895National Natural Science Foundation of China 82371839Natural Science Foundation of Ningxia 2024AAC05084Special project for clinical research of Shanghai Municipal Health Commission 202140403
6 · The paper itself

Abstract

objectiveGlioblastoma (GBM) is a highly aggressive brain tumor with complex immune microenvironment and molecular heterogeneity. This study aimed to characterize immune infiltration patterns and identify prognostic biomarkers in GBM.

methodsWe classified GBM samples using immune-related gene sets and correlated subtypes with molecular features. Key genes were identified through Cox and LASSO regression analyses. Multi-omics approaches including single-cell RNA sequencing, transcriptional network analysis, and molecular docking were employed to investigate therapeutic targets.

resultsTwo immune subtypes (c1/c2) were identified, with c2 showing mesenchymal features and poorer prognosis. Four immune-related genes (RPL39L, AEBP1, EFEMP2, GALNT12) were prognostic markers, with AEBP1 and EFEMP2 overexpressed in GBM. Single-cell analysis revealed five tumor subtypes, with MES-like being most malignant. NFIA and BATF3 were key regulators. Seven potential drugs (e.g., Bosutinib) were identified with stable target binding.

conclusionsThis study reveals immune-molecular interactions in GBM, identifies AEBP1/EFEMP2 as prognostic markers, and proposes targeted therapies for personalized treatment.

Indexed as

Drug predictionGlioblastomaImmune infiltrationscRNA-seqSubtype

Identifiers

PMID41026376
PMCPMC12484469

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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.