Objective: To explore the relationship between Monoclonal Gammopathy of undetermined significance (MGUS) and Multiple Myeloma (MM) based on bioinformatics methods.
Methods: In this study, we conducted bioinformatics to identify genes associated with MGUS and MM using the PubMed pubmed2ensemble (http://pubmed2ensembl.ls.manchester. ac.uk/) until 2021. Gene ontology function was used to label overlapping genes, and Kyoto Encyclopedia of Genes and Genomes analysis was used to identify enriched pathways. The cluster-1 genes obtained from Cytoscape were analyzed by Comparative Toxicogenomics Database (CTD, http://ctdbase.org/) and then used to screen candidate drugs using the DSigDB database (https://amp.pharm.mssm.edu/Enrichr/).
Results: In total, 227 genes were common to both MGUS and MM. These genes were significantly associated with cytokine-cytokine receptor interaction and the PI3K-Akt signaling pathway. The protein-protein interaction network revealed that TNF, IL-1B, IL-6, CSF2, CXCL8, and IL-10 were among the core genes of MM. Finally, eight candidate drugs showed maximum interaction with core genes, which could potentially prevent MGUS from progressing to MM.
Conclusion: The progression of MGUS to MM is driven by aberrant cytokine secretion, which leads to inflammation immune dysfunction, and dysregulation of the PI3K/AKT/mTOR signaling pathway.
Keywords: Bioinformatics; Immune dysfunction; Inflammation; Monoclonal Gammopathy of Undetermined Significance; Multiple Myeloma; PI3K/AKT/mTOR.
Copyright: © Pakistan Journal of Medical Sciences.