Identification of key candidate genes and pathways in multiple myeloma by integrated bioinformatics analysis

Abstract

Multiple myeloma (MM) is a common hematologic malignancy for which the underlying molecular mechanisms remain largely unclear. This study aimed to elucidate key candidate genes and pathways in MM by integrated bioinformatics analysis. Expression profiles GSE6477 and GSE47552 were obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) with p < .05 and [logFC] > 1 were identified. Functional enrichment, protein-protein interaction network construction and survival analyses were then performed. First, 51 upregulated and 78 downregulated DEGs shared between the two GSE datasets were identified. Second, functional enrichment analysis showed that these DEGs are mainly involved in the B cell receptor signaling pathway, hematopoietic cell lineage, and NF-kappa B pathway. Moreover, interrelation analysis of immune system processes showed enrichment of the downregulated DEGs mainly in B cell differentiation, positive regulation of monocyte chemotaxis and positive regulation of T cell proliferation. Finally, the correlation between DEG expression and survival in MM was evaluated using the PrognoScan database. In conclusion, we identified key candidate genes that affect the outcomes of patients with MM, and these genes might serve as potential therapeutic targets.

Keywords: bioinformatics analysis; immune-associated genes; multiple myeloma; prognosis.

Figure 1

Identification of differentially expressed genes in two cohort profile datasets (GSE6477 and GSE47552). (a) Respective volcano plot of the two datasets. Red plots represent genes with [logFC] > 1 and p < .05. Blue plots represent the remaining genes with no significant difference. (b) Heatmap of the top 100 DEGs (100 up‐ and 100 downregulated genes). (c) Commonly changed DEGs in the two datasets (51 up‐ and 78 downregulated genes). DEGs, differentially expressed genes [Color figure can be viewed at wileyonlinelibrary.com]

Figure 2

Gene Ontology (GO) term enrichment analysis of all DEGs. (a) GO analysis of DEGs consisting of three subontologies (biological process, molecular function and cellular component). (b) Significantly enriched GO terms for all DEGs. DEGs, differentially expressed genes [Color figure can be viewed at wileyonlinelibrary.com]

Figure 3

Signaling pathway enrichment analysis of DEGs. (a) KEGG and REACTOME pathway enrichment of up‐ and downregulated DEGs. (b) Interrelation analysis of pathways via assessment of KEGG processes in ClueGO. DEGs, differentially expressed genes [Color figure can be viewed at wileyonlinelibrary.com]

Figure 4

Interrelation analysis between pathways (immune system process) of downregulated DEGs. (a) The interrelation between immune system pathways. (b) Numbers of genes enriched in the identified pathways. DEGs, differentially expressed genes [Color figure can be viewed at wileyonlinelibrary.com]

Figure 5

Interrelation analysis between pathways (biological process) of downregulated DEGs. (a) Interrelation between biological process pathways. (b) Numbers of genes enriched in the identified pathways. DEGs, differentially expressed genes [Color figure can be viewed at wileyonlinelibrary.com]

Figure 6

Protein–protein interaction (PPI) network of DEGs and module analysis. (a) Based on the STRING online database, a DEG PPI network was constructed containing 94 DEGs (41 upregulated DEGs labeled in red and 53 downregulated DEGs labeled in blue). (b) Identification of two significant modules based on the degree of importance. Module 1 contains 8 nodes and 27 edges. (c) Module 2 contains 5 nodes and 7 edges. DEGs, differentially expressed genes; PPI, protein–protein interaction [Color figure can be viewed at wileyonlinelibrary.com]

Figure 7

Correlation between individual DEG expression and MM disease‐specific survival. Kaplan–Meier survival curves comparing high and low expression of DEGs in MM in PrognoScan, as based on the GSE2658 data set (n = 559). DEGs, differentially expressed genes; MM, multiple myeloma [Color figure can be viewed at wileyonlinelibrary.com]