Protein–protein interaction networks and different clustering analysis in Burkitt’s lymphoma

ABSTRACT

Objective: Burkitt's lymphoma (BL) is a highly aggressive malignant lymphoma, its molecular biological mechanism has not been fully investigated. The construction of protein-protein interaction (PPI) networks and the identification of complexes through a cluster analysis are important research directions in the post-genome era. However, different cluster analysis algorithms have their own characteristics, and a single analysis has some limitations. In this study, we obtained the target and pathway information of BL using different clustering analyses.

Material and Methods: First, we obtained 50 BL genes by screening the Online Mendelian Inheritance in Man (OMIM) database; their related genes were further extracted from the literature. The PPI network was constructed with the Search Tool for Retrieval of Interacting Genes/Proteins (STRING). Afterward, the interaction data were input in Cytoscape3.4.0 software and related plug-ins were used to implement topology analysis and clustering analysis. Functional analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database were used to characterize the biological importance of the clusters.

Results: We constructed a PPI network consisting of 459 nodes (proteins) and 1399 sides (interactions), 12 genes and 8 signaling pathways were found to be closely related to BL.

Conclusion: In this study, the use of combined algorithms to analyse gene interactions provides a new perspective for network-based analysis. The results of this study reveal new insights into the molecular mechanisms underlying BL, which may be novel therapeutic targets for disease management and may provide a bioinformatic basis for the further understanding of BL.

KEYWORDS:

• Burkitt’s lymphoma
• protein–protein interaction network
• clustering analysis
• pathways
• key target

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Cun Liu http://orcid.org/0000-0001-8197-9000

Additional information

Funding

National Natural Science Foundation of China (No. 81673799); National Natural Science Foundation of China (No. 81703915).