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Cited by 11Lymphoma Diagnosis and TreatmentBioinformatics and Genomic NetworksBreast Cancer Treatment Studies

Identification of key genes and pathways associated with classical Hodgkin lymphoma by bioinformatics analysis

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Kuang, Zhixing, Guo, Li, Li, Xun·2017·Molecular Medicine Reports
DOI 10.3892/mmr.2017.7158PMC PMC5647037
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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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  • Downregulation of PLCγ2 gene pathways, and other BCR-related genes, along with EBV infection, is associated with Hodgkin's lymphoma.

    “Downregulation of PLCγ2 gene pathways, and other BCR-related genes, along with EBV infection, is also associated with Hodgkin’s lymphoma (137).”

    From The role of PLCγ2 in immunological disorders, cancer, and neurodegeneration (2021) · cites this paper as [137]

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Cited by

Sorted by citations

Authors
Kuang, Z., Guo, L., & Li, X.
Affiliations
Xinjiang Medical University (CN)
Corresponding author
Li, Xun
ORCID
Venue
Molecular Medicine Reports
Publisher
Spandidos Publications
Published
2017-08-03
Volume
16
Issue
4
Pages
4685-4693
ISSN
  • 1791-2997 (ISSN-L)
  • 1791-3004
DOI
10.3892/mmr.2017.7158
PMC
PMC5647037
OpenAlex
W2743751021
Cited by
11
References
1
Citations by year
2026: 1 · 2025: 2 · 2024: 1 · 2023: 1 · 2022: 2 · 2021: 2 · 2019: 1 · 2018: 1
FWCI
0.43
Type
journal article
Language
en
Open access
Licence
cc-by-nc-nd
Locations
  • Molecular Medicine Reports (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Pathology and Forensic Medicine › Lymphoma Diagnosis and Treatment
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
Keywords
classical Hodgkin lymphoma, differentially expressed genes, B cell receptor signaling, interleukin-6, STAT1, Syk, BLNK, CD79b, PLCγ2, MMP-9, Epstein-Barr virus infection, diagnostic and therapeutic targets, protein-protein interaction network
MeSH terms
Hodgkin Disease, Humans, Biomarkers, Tumor, Signal Transduction, Oncogene Proteins, Gene Expression Regulation, Neoplastic, Computational Biology, Protein Interaction Mapping, Databases, Genetic, Gene Regulatory Networks, Molecular Sequence Annotation, Protein Interaction Maps, Gene Ontology

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