Evidence map›Paper›PMID 42141926›Full record

ArticleJournal of cellular and molecular medicine2026

Mitophagy-Oxidative Stress Molecular Subtypes Define an Immunosuppressive Ecosystem and Vulnerabilities in Glioblastoma.

Changjiang He, Yang Wang, Hongliang Zhong

Abstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2026. 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
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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

3 authors.

Changjiang HeBeijing Chaoyang Hospital, The Third Clinical Medical College, Capital Medical University, Beijing, China.
Yang WangDepartment of Neurosurgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Hongliang ZhongDepartment of Neurosurgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID 0009-0004-4510-672X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioblastoma (GBM) is an aggressive brain tumour with an immunosuppressive environment and poor prognosis; however, the roles of mitophagy and oxidative stress in its prognosis remain underexplored. This study analysed multi-omics data from TCGA-GBM (n = 168) and two GEO cohorts (GSE43378, n = 50; GSE147352, n = 85), compiling 603 mitophagy and oxidative stress-related genes. Unsupervised consensus clustering identified molecular subtypes, and prognostic genes were found via univariate Cox regression, leading to a refined gene signature using LASSO. The tumour immune microenvironment was characterized with ESTIMATE, CIBERSORT, and ssGSEA, while immunotherapy response was predicted using TIDE and IPS. Drug sensitivity was evaluated with GDSC and CTRP data, and a clinical nomogram integrating the gene signature and clinical variables was constructed and validated. Two molecular subtypes, C1 and C2, showed different prognoses (HR = 0.64, p = 0.011) and immune profiles. A 7-gene signature indicated high-risk patients had worse survival (p < 0.001) and an immunosuppressive environment. The risk score correlated with anti-PD-1 response (p < 0.05) and predicted therapy sensitivity. The signature was an independent prognostic factor (HR = 3.37, p < 0.001), and the nomogram accurately predicted survival at 1, 3, and 5 years. An innovative prognostic signature from mitophagy and oxidative stress genes stratifies GBM patients, characterizes the immunosuppressive microenvironment, and identifies therapeutic vulnerabilities for personalized treatment.

Indexed as

Brain NeoplasmsGlioblastomaMitophagyOxidative StressBiomarkers, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansPrognosisTumor MicroenvironmentBiomarkers, Tumorglioblastomaimmunotherapymitophagy oxidative stressprognostic signaturetumour microenvironment

Identifiers

PMID42141926
PMCPMC13179569

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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.