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. 2021 Jul 23:11:684232.
doi: 10.3389/fonc.2021.684232. eCollection 2021.

PSMB7 Is a Key Gene Involved in the Development of Multiple Myeloma and Resistance to Bortezomib

Dong Wu  1 , Jiyu Miao  1 , Jinsong Hu  2 , Fangmei Li  1 , Dandan Gao  1 , Hongli Chen  1 , Yuandong Feng  1 , Ying Shen  1 , Aili He  1
Affiliations

PSMB7 Is a Key Gene Involved in the Development of Multiple Myeloma and Resistance to Bortezomib

Dong Wu et al. Front Oncol. .

Abstract

Multiple myeloma (MM), the second most commonly diagnosed hematologic neoplasm, is the most significant clinical manifestation in a series of plasma cell (PC) dyscrasia. Monoclonal gammopathy of undetermined significance (MGUS) and smoldering MM (SMM), approximately 1% or 10% of which, respectively, can progress to MM per year, are the premalignant stages of MM. The overall survival (OS) of MM is significantly improved by the introduction of proteasome inhibitors (PIs), but almost all MM patients eventually relapse and resist anti-MM drugs. Therefore, it is crucial to explore the progression of MM and the mechanisms related to MM drug resistance. In this study, we used weighted gene co-expression network analysis (WGCNA) to analyze the gene expression of the dynamic process from normal plasma cells (NPC) to malignant profiling PC, and found that the abnormal gene expression was mainly concentrated in the proteasome. We also found that the expression of one of the proteasomal subunits PSMB7 was capable of distinguishing the different stages of PC dyscrasia and was the highest in ISS III. In the bortezomib (BTZ) treated NDMM patients, higher PSMB7 expression was associated with shorter survival time, and the expression of PSMB7 in the BTZ treatment group was significantly higher than in the thalidomide (Thai) treatment group. In summary, we found that PSMB7 is the key gene associated with MM disease progression and drug resistance.

Keywords: PSMB7; WGCNA; drug resistance; multiple myeloma; proteasome inhibitor.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
WGCNA on the dynamic progression of MM. (A) Analysis of network topology for various soft threshold powers (β). (B) Mean connectivity with various soft threshold power. (C) Clustering dendrogram of all differentially expressed genes with assigned module colors. Each color block represented a module of highly co-expressed genes.
Figure 2
Figure 2
The relationship between modules and PC dyscrasia. (A) Module-trait associations. Each row corresponds to a ME, each column to a stage of PC dyscrasias. The table is color-coded by the corresponding correlation according to the color legend. (B) A scatterplot of GS for weight vs. module membership in the ME pink.
Figure 3
Figure 3
Functional enrichment analysis of hub genes. (A) KEGG pathway enrichment analysis. (B) MF enrichment analysis. (C) BP enrichment analysis. (D) CC enrichment analysis.
Figure 4
Figure 4
The expression of PSMB7. (A) The expression of PSMB7 from HC to NDMM in GSE6477. (B) The expression of PSMB7 in different ISS status in E-MTAB-4032. ns, not significant, *P < 0.05, ***P < 0.001, and ****P < 0.0001.
Figure 5
Figure 5
Mutation analysis of PSMB7 in NDMM. There were 0% genomic alterations of PSMB7 in MM.
Figure 6
Figure 6
Receiver operating characteristic curve analysis in MGUS, SMM, and NDMM. (A) ROC of PSMB7 in MGUS, (B) ROC of PSMB7 in SMM, (C) ROC of PSMB7 in NDMM.
Figure 7
Figure 7
Kaplan-Meier survival curves of NDMM patients. (A) Overall survival of PSMB7 in the TT2 group. (B) Overall survival of PSMB7 in the TT3 group. (C) Expression of PSMB7 in the TT2 and the TT3 group, ****P < 0.001.
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