Evidence map›Paper›PMID 40963614›Full record

ArticleFrontiers in immunology2025

Prognostic value of metal-based ferroptosis and cuproptosis genes and score in lower grade gliomas.

Umair Ali Khan Saddozai, Zhendong Lu, Shuangshuang Dong, Muhammad Babar Khawar, Zhehao Fan, Liangliang Cai, Xiaohui Guo, Muhammad Usman Akbar, Saadullah Khattak, Haibo Sun and 1 more

Abstract read
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Article in Frontiers in immunology, 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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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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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

11 authors.

Umair Ali Khan Saddozai *Institute of Translational Medicine, Medical College, Yangzhou University, Yangzhou, Jiangsu, China.
Zhendong Lu *Department of Medical Oncology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Shuangshuang Dong *Department of Pathology, Northern Jiangsu People's Hospital Affiliated to Yangzhou, Yangzhou, Jiangsu, China.
Muhammad Babar KhawarInstitute of Translational Medicine, Medical College, Yangzhou University, Yangzhou, Jiangsu, China.
Zhehao FanInstitute of Translational Medicine, Medical College, Yangzhou University, Yangzhou, Jiangsu, China.
Liangliang CaiSchool of Basic Medical Sciences, Faculty of Medicine, Yangzhou University, Yangzhou, Jiangsu, China.
Xiaohui GuoInstitute of Translational Medicine, Medical College, Yangzhou University, Yangzhou, Jiangsu, China.
Muhammad Usman AkbarOujiang Laboratory; Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Saadullah KhattakDepartment of Preventive Medicine, Institute of Biomedical Informatics, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Henan University, Kaifeng, Henan, China.
Haibo SunInstitute of Translational Medicine, Medical College, Yangzhou University, Yangzhou, Jiangsu, China.
Yajun WangDepartment of Oncology, Haian Hospital of Traditional Chinese Medicine, Haian, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Ferroptosis and Cuproptosis are newly defined forms of cell death. Despite distinct mechanisms, both involve metabolic processes in the TCA cycle and downstream pathways, crucial for anticancer immunity. Methods: We evaluated Iron (Fe) and Copper-induced cell death in lower-grade gliomas (LGG) using The Cancer Genome Atlas (TCGA) data by developing a metal-based ferroptosis and cuproptosis genes score (MBFCGs) risk model. Lasso regression and survival analyses assessed MBFCGs' significance. An MBFCGs-based nomogram was created and its predictive performance verified. Signaling pathways, immune checkpoints, chemokines, and therapeutic response indicators were quantified using R/oncoPredict and Tidepay. Immunohistochemistry (IHC) examined candidate gene expression. Results: The MBFCGs risk model, based on BACH1, CDCA3, and TIMP1, predicts LGG prognosis. High MBFCGs were associated with poor clinical outcomes. Functional enrichment analysis showed upregulation in neurotransmitter receptor regulation, KRAS signaling, and hedgehog signaling pathways in the high-risk group. High-risk LGG patients exhibited higher tumor mutation burden (TMB) and lower IDH1 mutation incidence. These patients also had increased stromal and immune scores, with elevated levels of T helper cells, B cells, macrophages, neutrophils, and NK cells. Immune checkpoint analysis indicated higher expression of CD274, PDCD1, and other inhibitory molecules, suggesting potential for targeted cancer immunotherapy. Conclusion: The MBFCGs risk model is a promising prognostic tool for LGG, offering insights into underlying mechanisms and new directions for immunotherapy strategies. Assessment of MBFCGs for individual LGG patients may provide clues for developing new immunotherapy strategies.

Indexed as

Biomarkers, TumorBrain NeoplasmsFerroptosisGliomaFemaleGene Expression Regulation, NeoplasticHumansIronMaleMiddle AgedNeoplasm GradingNomogramsPrognosisTumor MicroenvironmentBiomarkers, TumorIroncell deathcuproptosisferroptosisimmune checkpoint blockadeimmunotherapylow-grade gliomatumor microenvironment

Identifiers

PMID40963614
PMCPMC12436455

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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.