ArticleMolecular medicine reports2017
Identification of key genes and pathways associated with classical Hodgkin lymphoma by bioinformatics analysis.
Article in Molecular medicine reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- PLCG2 across human disease: genetic variants, signaling mechanisms, and clinical implications.Journal of translational medicine · 2026Review
- BLNK as an important prognostic indicator for survival in pediatric classic hodgkin lymphoma patients: a single-center retrospective study.Annals of hematology · 2025Article
- Insights into the Gene Expression Profile of Classical Hodgkin Lymphoma: A Study towards Discovery of Novel Therapeutic Targets.Molecules (Basel, Switzerland) · 2024Article
- Sequential transcriptome profiling: comparative analysis of normal and canine lymphoma preceding detailed T-cell and B-cell subtype comparison.Frontiers in veterinary science · 2024Article
- Predicting the molecular mechanism-driven progression of breast cancer through comprehensive network pharmacology and molecular docking approach.Scientific reports · 2023Article
- Genomic crossroads between non-Hodgkin's lymphoma and common variable immunodeficiency.Frontiers in immunology · 2022Article
- [Structure and function of B-cell linker and its role in the development of B cell-related diseases].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2019Article
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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 current study aimed to explore the mechanisms associated with classic Hodgkin lymphoma (cHL) to identify novel diagnostic and therapeutic targets. The GES12453 microarray dataset was downloaded from the Gene Expression Omnibus database; the differentially expressed genes (DEGs) between cHL samples and normal B cell samples by were identified using the limma package. Gene ontology (GO) and pathway enrichment analysis of DEGs gene were performed. Furthermore, construction and analysis of protein‑protein interaction (PPI) network was performed, and co‑expression modules of DEGs were produced. A total of 450 DEGs were identified, comprising 216 upregulated and 234 downregulated genes in cHL compared with normal B cell samples. The DEGs were enriched in biological processes associated with immune response. The upregulated genes were mainly associated with the pathway of transcriptional misregulation in cancer, while downregulated genes were associated with B cell receptor signaling. PPI network analysis demonstrated that IL6 had the highest connectivity degree. Interleukin‑6 (IL6) and signal transducer and activator of transcription 1 (STAT1) were demonstrated to be involved with the response to cytokine GO term in co‑expression module 1. Spleen tyrosine kinase (SYK), B‑cell linker protein (BLNK), CD79B, phospholipase C γ2 (PLCG2) were enriched in the B cell receptor signaling pathway in module 2. Matrix metallopeptidase 9 (MMP9), protein tyrosine phosphatase receptor type C had the highest connectivity degrees in module 3 and module 4, respectively. The results suggested that DEGs, including IL6, STAT1, MMP9, SYK, BLNK, PLCG2 and CD79B, and the pathways of B cell receptor signaling, Epstein‑Barr virus infection and transcriptional misregulation in cancer have strong potential to be useful as targets for diagnosis or treatment of cHL.
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