ArticleMolecular medicine reports2015
Functional analysis of the nasopharyngeal carcinoma primary tumor‑associated gene interaction network.
Article in Molecular medicine reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Identification and validation of anoikis-related differentially expressed genes in nasopharyngeal carcinoma.Translational cancer research · 2025Article
- Establishment of a patient-derived organoid model and living biobank for nasopharyngeal carcinoma.Annals of translational medicine · 2022Article
- The CRL4DTL E3 ligase induces degradation of the DNA replication initiation factor TICRR/TRESLIN specifically during S phase.Nucleic acids research · 2021Article
- Review
- High Centromere Protein-A (CENP-A) Expression Correlates with Progression and Prognosis in Gastric Cancer.OncoTargets and therapy · 2020Article
- Novel significant stage-specific differentially expressed genes in hepatocellular carcinoma.BMC cancer · 2019Article
- Bioinformatic identification of candidate biomarkers and related transcription factors in nasopharyngeal carcinoma.World journal of surgical oncology · 2019Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of the present study was to investigate the molecular mechanism of nasopharyngeal carcinoma (NPC) primary tumor development through the identification of key genes using bioinformatics approaches. Using the GSE53819 microarray dataset, acquired from the Gene Expression Omnibus database, differentially expressed genes (DEGs) were screened out between NPC primary tumor and control samples, followed by hierarchical clustering analysis. The Search Tool for the Retrieval of Interacting Genes database was utilized to build a protein‑protein interaction network to identify key node proteins. In total, 1,067 DEGs, including 326 upregulated genes and 741 downregulated genes, were identified between the NPC and control samples. The results of the hierarchical clustering analysis demonstrated that 95% of the DEGs were sample‑specific. Furthermore, PDZ binding kinase (PBK), centromere protein F (CENPF), actin‑binding protein anillin (ANLN), exonuclease 1 (EXO1) and chromosome 15 open reading frame 42 (C15ORF42) were included in the obtained network module, which was closely associated with the cell cycle and nucleic acid metabolic process GO functions. The results of the present study revealed that EXO1, CENPF, ANLN, PBK and C15ORF42 may be involved in the mechanism of NPC via modulating the cell cycle and nucleic acid metabolic processes, and may serve as molecular biomarkers for the diagnosis of this disease.
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