ArticleJournal of molecular neuroscience : MN2020
Identification of Core Genes and Pathways in Medulloblastoma by Integrated Bioinformatics Analysis.
Article in Journal of molecular neuroscience : MN, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Identification of metabolism-associated molecular classification and prognostic genes for medulloblastoma based on bioinformatics analysis.Clinics (Sao Paulo, Brazil) · 2026Article
- The potential of ribonucleotide reductase M2 as a novel prognostic maker and therapeutic target to inhibit medulloblastoma proliferation, migration, and invasiveness.Pediatric discovery · 2024Article
- Identification and validation of a metabolism-related gene signature for predicting the prognosis of paediatric medulloblastoma.Scientific reports · 2024Article
- Identification of ITPR1 as a Hub Gene of Group 3 Medulloblastoma and Coregulated Genes with Potential Prognostic Values.Journal of molecular neuroscience : MN · 2022Article
- The Predictive Competing Endogenous RNA Regulatory Networks and Potential Prognostic and Immunological Roles of Cyclin A2 in Pan-Cancer Analysis.Frontiers in molecular biosciences · 2022Article
- Identification of Potential Key Genes and Molecular Mechanisms of Medulloblastoma Based on Integrated Bioinformatics Approach.BioMed research international · 2022Article
- Identification of Regeneration and Hub Genes and Pathways at Different Time Points after Spinal Cord Injury.Molecular neurobiology · 2021Article
- Identification of Key Genes Associated With the Process of Hepatitis B Inflammation and Cancer Transformation by Integrated Bioinformatics Analysis.Frontiers in genetics · 2021Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Medulloblastoma (MB) is one of the most common intracranial malignancies in children. The present study applied integrated bioinformatics to identify potential core genes associated with the pathogenesis of MB and reveal potential molecular mechanisms. Through the integrated analysis of multiple data sets from the Gene Expression Omnibus (GEO), 414 differentially expressed genes (DEGs) were identified. Combining the protein-protein interaction (PPI) network analysis with gene set enrichment analysis (GSEA), eight core genes, including CCNA2, CCNB1, CCNB2, AURKA, CDK1, MAD2L1, BUB1B, and RRM2, as well as four core pathways, including "cell cycle", "oocyte meiosis", "p53 pathway" and "DNA replication" were selected. In independent data sets, the core genes showed superior diagnostic values and significant prognostic correlations. Moreover, in the pan-caner data of the cancer genome atlas (TCGA), the core genes were also widely abnormally expressed. In conclusion, this study identified core genes and pathways of MB through integrated analysis to deepen the understanding of the molecular mechanisms underlying the MB and provide potential targets and pathways for diagnosis and treatment of MB.
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Registered trials
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