Evidence map›Paper›PMID 41849028›Full record

ArticleFASEB journal : official publication of the Federation of American Societies for Experimental Biology2026

Lactate Metabolism-Immune Regulation-Related Gene Signature in Lower-Grade Gliomas: Prognostic Model Development and Immune Characterization.

Enhao Zhang, Liangzhe Wei, He Ren, Jianfei Zhang, Hongqiao Yang, Meng Sun, Xiang Gao, Yi Huang

Abstract read
In one paragraph

Article in FASEB journal : official publication of the Federation of American Societies for Experimental Biology, 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
–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

8 authors.

Enhao ZhangNingbo Key Laboratory of Nervous System and Brain Function, Department of Neurosurgery, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.ORCID https://orcid.org/0009-0004-2168-519X
Liangzhe WeiNingbo Key Laboratory of Nervous System and Brain Function, Department of Neurosurgery, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
He RenNingbo Key Laboratory of Nervous System and Brain Function, Department of Neurosurgery, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
Jianfei ZhangNingbo Key Laboratory of Nervous System and Brain Function, Department of Neurosurgery, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
Hongqiao YangNingbo Key Laboratory of Nervous System and Brain Function, Department of Neurosurgery, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
Meng SunNingbo Key Laboratory of Nervous System and Brain Function, Department of Neurosurgery, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
Xiang GaoNingbo Key Laboratory of Nervous System and Brain Function, Department of Neurosurgery, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
Yi HuangNingbo Key Laboratory of Nervous System and Brain Function, Department of Neurosurgery, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.ORCID https://orcid.org/0000-0003-3598-9747

Funding

Ningbo Municipal Youth Science and Technology Innovation Leading Talent Project 2025QL015Ningbo Natural Science Foundation 2023J135Ningbo Top Medical and Health Research Program 2022020304
6 · The paper itself

Abstract

Low-grade gliomas represent a diverse category of central nervous system tumors, characterized by considerable variability in prognosis. Metabolic reprogramming, particularly lactate metabolism, has been associated with the tumor immune microenvironment; however, the prognostic significance of the related genes in LGG is still not well understood. This study used TCGA and CGGA cohorts to perform consensus clustering based on genes involved in lactate metabolism. A predictive model was constructed using differential analysis, Cox regression, and LASSO methods. The model's association with immune cell infiltration, TMB, and drug responsiveness was also evaluated. The function of the key gene PLA2G2A was validated using RT-qPCR, Western blot, immunofluorescence, ELISA, CCK-8, Transwell assays, and mouse tumorigenesis experiments. Consensus clustering classified LGG into two distinct subtypes, each showing significant variations in survival and immune profiles. The three-gene signature (VAV3, TNFRSF12A, PLA2G2A) effectively distinguished high-risk from low-risk patients, demonstrating high predictive accuracy in both TCGA and CGGA datasets. Patients categorized as high-risk showed reduced immune infiltration, increased TMB, and a worse prognosis. Additionally, they showed increased sensitivity to tyrosine kinase inhibitors and platinum-based therapies. Functional experiments showed that PLA2G2A was highly expressed in gliomas, and its downregulation notably reduced tumor cell proliferation, migration, invasion, and growth in vivo, while reversing the epithelial-mesenchymal transition. This study proposes and validates a novel three-gene prognostic model that reflects the metabolic-immune interactions in LGG, predicts patient prognosis, and suggests potential therapeutic targets. The functional validation of PLA2G2A further underscores its potential as a therapeutic biomarker.

Indexed as

Brain NeoplasmsGene Expression Regulation, NeoplasticGliomaLactic AcidAnimalsBiomarkers, TumorCell Line, TumorFemaleHumansMicePrognosisTumor MicroenvironmentBiomarkers, TumorLactic Acidimmune microenvironmentlactate metabolism‐immune regulation‐related geneslow‐grade gliomaPLA2G2Aprognostic modeltumor mutation burden

Identifiers

PMID41849028
PMCPMC12998596

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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.