ArticleOncoTargets and therapy2018
Identification of driver genes associated with chemotherapy resistance of Ewing's sarcoma.
Article in OncoTargets and therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 7 citations in OpenAlex.
- Single-Cell Transcriptome Reveals Cell Type-Specific Molecular Pathology in a 2VO Cerebral Ischemic Mouse Model.Molecular neurobiology · 2024Article
- Unlocking epigenetics for precision treatment of Ewing's sarcoma.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2024Article
- Histone Methyltransferases G9a/International journal of molecular sciences · 2023Article
- Drugging Hijacked Kinase Pathways in Pediatric Oncology: Opportunities and Current Scenario.Pharmaceutics · 2023Review
- Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe aim of this study was to identify the driver genes associated with chemotherapy resistance of Ewing's sarcoma and potential targets for Ewing's sarcoma treatment.
methodsTwo mRNA microarray datasets, GSE12102 and GSE17679, were downloaded from the Gene Expression Omnibus database, which contain 94 human Ewing's sarcoma samples, including 65 from those who experienced a relapse and 29 from those with no evidence of disease. The differen tially expressed genes (DEGs) were identified using LIMMA package R. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed for DEGs using Database for Annotation, Visualization and Integrated Analysis. The protein-protein interaction network was constructed using Cytoscape software, and module analysis was performed using Molecular Complex Detection.
resultsA total of 206 upregulated DEGs and 141 downregulated DEGs were identified. Upregulated DEGs were primarily enriched in DNA replication, nucleoplasm and protein kinase binding for biological processes, cellular component and molecular functions, respectively. Downregulated DEGs were predominantly involved in receptor clustering, membrane raft, and ligand-dependent nuclear receptor binding. The protein-protein interaction network of DEGs consisted of 150 nodes and 304 interactions. Thirteen hub genes were identified, and biological analysis revealed that these genes were primarily enriched in cell division, cell cycle, and mitosis. Furthermore, based on closeness centrality, betweenness centrality, and degree centrality, the three most significant genes were identified as
conclusionThese hub genes, especially
Indexed as
Identifiers
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Registered trials
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.