Evidence map›Paper›PMID 40852729›Full record

ArticleFrontiers in immunology2025

Meta-analysis of multi-center transcriptomic profiles and machine learning reveal phospholipase Cβ4 as a Wnt/Ca²

Zhaoming Song, Fei Wang, Chen Yang, Yanao Guo, Jinfeng Li, Run Huang, Hongyi Ling, Guosheng Cheng, Zhouqing Chen, Zhanchi Zhu and 1 more

Abstract read
In one paragraph

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Genome-Wide Characterization of the wnt Gene Family Reveals aAnimals : an open access journal from MDPI · 2026
    Article
  2. Review
  3. Artificial Intelligence-Driven Multi-Omics Approaches in Glioblastoma.International journal of molecular sciences · 2025
    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.

Zhaoming Song *Department of Neurosurgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Fei Wang *Department of Neurosurgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Chen Yang *Department of Neurosurgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Yanao GuoSuzhou Medical College of Soochow University, Suzhou, Jiangsu, China.
Jinfeng LiSuzhou Medical College of Soochow University, Suzhou, Jiangsu, China.
Run HuangSuzhou Medical College of Soochow University, Suzhou, Jiangsu, China.
Hongyi LingSuzhou Medical College of Soochow University, Suzhou, Jiangsu, China.
Guosheng ChengChinese Academy of Sciences (CAS) Key Laboratory of Nano-Bio Interface, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, Jiangsu, China.
Zhouqing ChenDepartment of Neurosurgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Zhanchi ZhuChinese Academy of Sciences (CAS) Key Laboratory of Nano-Bio Interface, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, Jiangsu, China.
Zhong WangDepartment of Neurosurgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Glioblastoma (GBM) is a highly aggressive brain tumor characterized by pronounced invasiveness, rapid progression, frequent recurrence, and poor clinical prognosis. Current treatment strategies remain inadequate due to the lack of effective molecular targets, underscoring the urgent need to identify novel therapeutic avenues. Methods: In this study, we employed weighted gene co-expression network analysis and meta-analysis, incorporating clinical immunotherapy datasets, to identify ten candidate genes associated with GBM initiation, progression, prognosis, and response to immunotherapy. Multi-omics analyses across glioma and pan-cancer datasets revealed that these genes play pivotal roles in cancer biology. Results: Phospholipase Cb4 (PLCB4) showed a negative correlation with tumor grade in clinical samples, suggesting its potential role as a tumor suppressor. Evidence indicated that PLCB4 expression is modulated by Wnt signaling, and its overexpression may activate the calcium ion signaling pathway. Notably, Discussion: This study's integrative approach-combining target identification, pathway inference, and in silico drug screening-offers a promising framework for rational drug development in GBM. The findings may reduce unnecessary experimental screening and medical costs, and represent a significant step toward improving therapeutic outcomes and prognosis for GBM patients.

Indexed as

Brain NeoplasmsCalcium SignalingGlioblastomaImmunotherapyMachine LearningPhospholipase C betaWnt Signaling PathwayGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansMeta-Analysis as TopicPrognosisTranscriptomePhospholipase C betaglioblastomaimmunotherapymachine learningmulti-omicsPLCB4tumor microenvironment

Identifiers

PMID40852729
PMCPMC12368592

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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.