Evidence map›Paper›PMID 41485080›Full record

ArticleNeuro-oncology2026

Metabolic profiling defines glioblastoma subtypes with distinct prognoses and therapeutic vulnerabilities.

Fan Wu, Yi-Yun Yin, Di Wang, Chang-Qing Pan, You Zhai, Ming-Chen Yu, Zhi-Liang Wang, Wen-Hua Fan, Zheng Zhao, Guan-Zhang Li and 2 more

Abstract read
In one paragraph

Article in Neuro-oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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

12 authors.

Fan WuDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Yi-Yun YinDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Di WangDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Chang-Qing PanDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
You ZhaiDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Ming-Chen YuDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Zhi-Liang WangDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Wen-Hua FanDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Zheng ZhaoDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Guan-Zhang LiDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Tao JiangDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.ORCID 0000-0002-7008-6351
Wei ZhangDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.ORCID 0000-0001-7800-3189

Funding

National Natural Science Foundation of China 81672479National Natural Science Foundation of China 82002994National Natural Science Foundation of China 82261160578National Natural Science Foundation of China 82525053Youth Beijing Scholar 055
6 · The paper itself

Abstract

backgroundGlioblastoma (GBM) is a highly aggressive brain tumor with profound metabolic heterogeneity. However, a clinically actionable classification based on metabolic gene expression remains undefined.

methodsWe conducted a comprehensive multi-omics analysis of IDH-wildtype GBMs from three publicly available datasets. Prognostic metabolism-related genes were used to define transcriptional subtypes, which were validated in independent datasets and patient-derived cell (PDC) models. Functional assays and drug sensitivity studies were performed to explore therapeutic relevance.

resultsWe identified three distinct metabolic subtypes: M1, enriched for synaptic signaling and amino acid metabolism, exhibited leading-edge anatomical features; M2, characterized by mitochondrial metabolism and cell cycle activity, was associated with favorable survival; and M3, marked by hypoxia, immune activation and suppression, and broad metabolic pathway engagement, correlated with poor prognosis. These subtypes were reproducible across cohorts and faithfully recapitulated in PDC models. Metabolomic profiling confirmed distinct subtype-specific metabolic signatures. Notably, M3 cells showed high sensitivity to inhibitors targeting glycosaminoglycan degradation, nicotinamide metabolism, and retinoic acid pathways in both in vitro and in vivo models.

conclusionOur study defines three biologically and clinically relevant metabolic subtypes of IDH-wildtype GBM. This classification reveals distinct metabolic programs and therapeutic vulnerabilities, providing a framework for precision metabolism-targeted strategies in GBM.

Indexed as

Biomarkers, TumorBrain NeoplasmsGlioblastomaMetabolomeMetabolomicsAnimalsHumansIsocitrate DehydrogenaseMicePrognosisSurvival RateTumor Cells, CulturedBiomarkers, TumorIsocitrate Dehydrogenaseglioblastomametabolic profilingmolecular subtypemulti-omicsprognosis

Identifiers

PMID41485080
PMCPMC13128474

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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.