Evidence map›Paper›PMID 35347632›Full record

ArticleJournal of molecular neuroscience : MN2022

Clinical and Epidemiological Study of Intracranial Tumors in Children and Identification of Diagnostic Biomarkers for the Most Common Tumor Subtype and Their Relationship with the Immune Microenvironment Through Bioinformatics Analysis.

Guanyi Wang, Yibin Jia, Yuqin Ye, Enming Kang, Huijun Chen, Jiayou Wang, Xiaosheng He

Abstract read
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In one paragraph

Article in Journal of molecular neuroscience : MN, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 52% of its field
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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

7 authors at 2 institutions in 1 country.

Guanyi Wang *Department of Neurosurgery, Xijing Hospital, Airforce Military Medical University (Fourth Military Medical University), Xi'an, 710032, China.
Yibin Jia *Department of Neurosurgery, Xijing Hospital, Airforce Military Medical University (Fourth Military Medical University), Xi'an, 710032, China.
Yuqin Ye *Department of Neurosurgery, Xijing Hospital, Airforce Military Medical University (Fourth Military Medical University), Xi'an, 710032, China.
Enming KangDepartment of Neurosurgery, Xijing Hospital, Airforce Military Medical University (Fourth Military Medical University), Xi'an, 710032, China.
Huijun ChenDepartment of Neurosurgery, Xijing Hospital, Airforce Military Medical University (Fourth Military Medical University), Xi'an, 710032, China.
Jiayou WangDepartment of Neurosurgery, Xijing Hospital, Airforce Military Medical University (Fourth Military Medical University), Xi'an, 710032, China.
Xiaosheng HeDepartment of Neurosurgery, Xijing Hospital, Airforce Military Medical University (Fourth Military Medical University), Xi'an, 710032, China. hexiaos@fmmu.edu.cn.ORCID http://orcid.org/0000-0002-6581-4043
Xijing Hospital · CNHunan Normal University · CN

Funding

Natural Science Foundation of China 2020XC015Natural Science Foundation of China Nos. 81971156
6 · The paper itself

Abstract

Brain tumors are the second most common pediatric malignancy and have poor prognosis. Understanding the pathogenesis of tumors at the molecular level is essential for clinical treatment. We conducted a retrospective study on the epidemiology of brain tumors in children based on clinical data obtained from a neurosurgical center. After identifying the most prevalent tumor subtype, we identified new potential diagnostic biomarkers through bioinformatics analysis of the public database. All children (0-15 years) with brain tumors diagnosed histopathologically between 2010 and 2020 at the Department of Neurosurgery, Xijing Hospital, were reviewed retrospectively for age distribution, sex predilection, native location, tumor location, symptoms, and histological grade, and identified the most common tumor subtypes. Two datasets (GSE44971 and GSE44684) were downloaded from the Gene Expression Omnibus database, whereas the GSE44971 dataset was used to screen the differentially expressed genes between normal and tumor samples. Gene ontology, disease ontology, and gene set enrichment analysis enrichment analyses were performed to investigate the underlying mechanisms of differentially expressed genes in the tumor. Combined with methylation data in the GSE44684 dataset, we further analyzed the correlation between methylation and gene expression levels. Two algorithms, LASSO and SVM-RFE, were used to select the hub genes of the tumor. The diagnostic value of the hub genes was assessed using the receiver operating characteristic (ROC) curve. Finally, we further evaluated the relationship between the hub gene and the tumor microenvironment and immune gene sets. Overall, 650 children from 18 provinces in China were included in this study. The male-to-female ratio was 1.41:1, and the number of patients reached a peak in the 10-15-year-old group (41.4%).The most common symptoms we encountered in our institute were headache and dizziness 250 (28.2%), and nausea and vomiting 228 (25.7%). The predominant location is supratentorial, with a supratentorial to infratentorial ratio of 1.74:1. Low-grade tumors (WHO I/II) constituted 60.9% of all cases and were predominant in every age group. According to basic classification, the most common tumor subtype is pilocytic astrocytoma (PA). A total of 3264 differentially expressed genes were identified in the GSE44971 dataset, which are mainly involved in the process of neural signal transduction, immunity, and some diseases. Correlation analysis indicated that the expression of 45 differentially expressed genes was negatively correlated with promoter DNA methylation. Next, we acquired five hub genes (NCKAP1L, GPR37L1, CSPG4, PPFIA4, and C8orf46) from the 45 differentially expressed genes by intersecting the LASSO and SVM-RFE models. The ROC analysis revealed that the five hub genes had good diagnostic value for patients with PA (AUC > 0.99). Furthermore, the expression of NCKAP1L was negatively correlated with immune, stromal, and estimated scores, and positively correlated with immune gene sets. This study, based on the data analysis of intracranial tumors in children in a single center over the past 10 years, reflected the clinical and epidemiological characteristics of intracranial tumors in children in Northwest China to a certain extent. PA is considered the most common subtype of intracranial tumors in children. Through bioinformatics analysis, we suggested that NCKAP1L, GPR37L1, CSPG4, PPFIA4, and C8orf46 are potential biomarkers for the diagnosis of PA.

Indexed as

AstrocytomaBrain NeoplasmsAdolescentBiomarkersBiomarkers, TumorChildComputational BiologyFemaleGene Expression ProfilingHumansMaleMembrane ProteinsReceptors, G-Protein-CoupledRetrospective StudiesTumor MicroenvironmentBiomarkersBiomarkers, TumorGPR37L1 protein, humanMembrane ProteinsNCKAP1L protein, humanReceptors, G-Protein-CoupledBiomarkerBrain tumorChildhoodPilocytic astrocytoma (PA)Tumor microenvironment (TME)

Identifiers

PMID35347632
OpenAlexW4225985815

What Socratic holds

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Registered trials

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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 Socratic graph.