Objective: To uncover the potential regulatory mechanisms of the relevant genes that contribute to the prognosis and prevention of multiple myeloma (MM).
Methods: Microarray data (GSE13591) were downloaded, including five plasma cell samples from normal donors and 133 plasma cell samples from MM patients. Differentially expressed genes (DEGs) were identified by Student’s t -test. Functional enrichment analysis was performed for DEGs using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Transcription factors and tumor-associated genes were also explored by mapping genes in the TRANSFAC, the tumor suppressor gene (TSGene), and tumor-associated gene (TAG) databases. A protein–protein interaction (PPI) network and PPI subnetworks were constructed by Cytoscape software using the Search Tool for the Retrieval of Interacting Genes (STRING) database.
Results: A total of 63 DEGs (42 downregulated, 21 upregulated) were identified. Functional enrichment analysis showed that HLA-DRB1 and VCAM1 might be involved in the positive regulation of immune system processes, and HLA-DRB1 might be related to the intestinal immune network for IgA production pathway. The genes CEBPD , JUND , and ATF3  were identified as transcription factors. The top ten nodal genes in the PPI network were revealed including HLA-DRB1 , VCAM1 , and TFRC . In addition, genes in the PPI subnetwork, such as HLA-DRB1 and VCAM1 , were enriched in the cell adhesion molecules pathway, whereas CD4 and TFRC were both enriched in the hematopoietic cell pathway.
Conclusion: Several crucial genes correlated to MM were identified, including CD4 , HLA-DRB1 , TFRC , and VCAM1 , which might exert their roles in MM progression via immune-mediated pathways. There might be certain regulatory correlations between HLA-DRB1 , CD4 , and TFRC .
Keywords: multiple myeloma, functional enrichment, transcription factor analysis, PPI network, pathway enrichment