OBJECTIVE: To screen novel diagnostic marker or therapeutic target for multiple myeloma (MM). METHODS: Sel1L, SPAG4, KCNN3 and PARM1 were identified by bioinformatics method based on GEO database as high expression genes in MM. Their RNA and protein expression levels in bone marrow mononuclear cells from myeloma cell lines U266, NCI-H929, MM.1s, RPMI8226 and leukemia cell line THP1, as well as 31 MM patients were evaluated by RT-PCR and Western blot, respectively. Meanwhile, 5 samples of bone marrow from healthy donors for allogeneic hematopoietic stem cell transplantation were employed as controls. RESULTS: Compared with leukemia cell line THP1, the expression levels of KCNN3, PARM1 and Sel1L mRNA were significantly increased in myeloma cell lines U266, NCI-H929 and MM.1s, while PARM1 was further increased in myeloma cell lines 8226. Western blot showed that the 4 genes were all expressed in the 4 myeloma cell lines. Compared with healthy controls, the expression levels of Sel1L, SPAG4, KCNN3 and PARM1 mRNA were significantly higher in MM patients (all P < 0.05). Western blot showed that the 4 genes were all expressed in MM patients, and the protein expression level of Sel1L and KCNN3 were significantly different compared with healthy donors (all P < 0.01). CONCLUSION Sel1L, SPAG4, KCNN3 and PARM1 may be potential diagnostic markers and therapeutic targets for MM.
Humans ; Multiple Myeloma/genetics* ; Cell Line, Tumor ; Proteins/metabolism* ; Computational Biology ; RNA, Messenger/genetics*

OBJECTIVE: To explore the clinical significance of 26 circulating tumor DNA (ctDNA) associated with multiple myeloma (MM) in peripheral blood of new diagnosed patients. METHODS: We conducted a study to detect 26 ctDNA mutations in the peripheral blood of 31 newly diagnosed multiple myeloma (NDMM) patients. RESULTS: Among the 31 NDMM patients, the ctDNA detection rate was 93.55%, significantly higher than that of FISH and chromosome screening methods. The most frequently mutated genes in NDMM were ACTG1 and GNAS. Notably, ACTG1 mutations were exclusive to NDMM patients, furthermore, resulted from the missense mutation of the exon 4. ACTG1 was the gene most frequently co-mutated with others. All patients with ACTG1 mutations were surviving, and there was a positive correlation between ACTG1 mutation and the survival of patients. GNAS mutations were confined to exon 1. CONCLUSION The detection rate of ctDNA sequencing in peripheral blood of NDMM patients was higher than that in bone marrow. ACTG1 and GNAS genes have a guiding role in the prognosis of newly diagnosed patients.
Humans ; Multiple Myeloma/blood* ; Circulating Tumor DNA/genetics* ; Mutation ; Prognosis ; GTP-Binding Protein alpha Subunits, Gs/genetics* ; Chromogranins ; Male ; Female ; Middle Aged

OBJECTIVES: Multiple myeloma (MM) is a highly heterogeneous hematologic malignancy, with disease progression driven by cytogenetic abnormalities and a complex bone marrow microenvironment. This study aims to construct a prognostic model for MM based on transcriptomic data and lipid metabolism related genes (LRGs), and to identify potential drug targets for high-risk patients to support clinical decision-making. METHODS: In this study, 2 transcriptomic datasets covering 985 newly diagnosed MM patients were retrieved from the Gene Expression Omnibus (GEO) database. Univariate Cox regression and 101 machine learning algorithms were used for gene selection. An LRG-based prognostic model was constructed using Stepwise Cox (both directions) and random survival forest (RSF) algorithms. The association between the prognostic score and clinical events was evaluated, and model performance was assessed using time-dependent receiver operating characteristic (ROC) curves and the C-index. The added predictive value of combining prognostic scores with clinical variables and staging systems was also analyzed. Differentially expressed genes between high- and low-risk groups were identified using limma and clusterProfiler and subjected to pathway enrichment analysis. Drug sensitivity analysis was conducted using the Genomics of Drug Sensitivity in Cancer (GDSC) database and oncoPredict to identify potential therapeutic targets for high-risk patients. The functional role of key LRGs in the model was validated via in vitro cell experiments. RESULTS: An LRG-based prognostic model (LRG17) was successfully developed using transcriptomic data and machine learning. The model demonstrated robust predictive performance, with area under the curve (AUC) values of 0.962, 0.912, and 0.842 for 3-, 5-, and 7-year survival, respectively. Patients were stratified into high- and low-risk groups, with high-risk patients showing significantly shorter overall survival (OS) and event-free survival (EFS) (both P<0.001) and worse clinical profiles (e.g., lower albumin, higher β2-microglobulin and lactate dehydrogenase levels). Enrichment analysis revealed that high-risk patients were significantly enriched for pathways related to chromosome segregation and mitosis, whereas low-risk patients were enriched for immune response and immune cell activation pathways. Drug screening suggested that AURKA inhibitor BMS-754807 and FGFR3 inhibitor I-BET-762 may be more effective in high-risk patients. Functional assays demonstrated that silencing of key LRG PLA2G4A significantly inhibited cell viability and induced apoptosis. CONCLUSIONS LRGs serve as promising biomarkers for prognosis prediction and risk stratification in MM. The overexpression of chromosomal instability-related and high-risk genetic event-associated genes in high-risk patients may explain their poorer outcomes. Given the observed resistance to bortezomib and lenalidomide in high-risk patients, combination therapies involving BMS-754807 or I-BET-762 may represent effective alternatives.
Humans ; Multiple Myeloma/mortality* ; Prognosis ; Lipid Metabolism/genetics* ; Transcriptome ; Machine Learning ; Male ; Female ; Gene Expression Profiling ; Algorithms

Multiple myeloma (MM) is a common hematologic malignancy that originates from precursor conditions such as monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). Identifying its risk factors is crucial for early intervention. The etiology of MM is multifactorial, involving race, familial clustering, gender, age, obesity, cytogenetic abnormalities, and environmental exposures. Among these, cytogenetic abnormalities and modifiable factors play pivotal roles in MM pathogenesis and progression. 1) cytogenetic abnormalities. Primary abnormalities [e.g., hyperdiploidy, t(11;14), t(14;16)] emerge at the MGUS stage, while secondary abnormalities [e.g., 1q+, del(17p)] drive disease progression. The accumulation of 1q+ promotes clonal evolution, and del(17p) is associated with significantly reduced survival. 2) modifiable risk factors. Obesity promotes MM via the acetyl-CoA synthetase 2 (ACSS2)-interferon regulatory factor 4 (IRF4) pathway. Vitamin D deficiency weakens immune surveillance. Exposure to herbicides such as Agent Orange and glyphosate increases MGUS incidence. Insufficient UV exposure, by reducing vitamin D synthesis, elevates MM risk. Gut microbiota dysbiosis (enrichment of nitrogen-cycle bacteria and depletion of short-chain fatty acids producers) induces chromosomal instability through the ammonium ion-solute carrier family 12 member 22 (SLC12A2)-NEK2 axis. Therefore, risk-based screening among high-risk populations (e.g., those who are obese, elderly, or chemically exposed), along with early interventions targeting cytogenetic abnormalities [e.g., B cell lymphoma 2 (Bcl-2) inhibitors for t(11;14), ferroptosis inducers for t(4;14)] and modifiable factors (e.g., vitamin D supplementation, gut microbiota modulation), may effectively delay disease progression and improve prognosis.
Humans ; Multiple Myeloma/epidemiology* ; Risk Factors ; Obesity/complications* ; Chromosome Aberrations ; Monoclonal Gammopathy of Undetermined Significance/etiology* ; Gastrointestinal Microbiome ; Vitamin D Deficiency/complications* ; Precancerous Conditions/genetics*

OBJECTIVE: To investigate the effect of adipocytes in the bone marrow microenvironment of patients with multiple myeloma (MM) on the pathogenesis of MM. METHODS: Bone marrow adipocytes (BMA) in bone marrow smears of health donors (HD) and newly diagnosed MM (ND-MM) patients were evaluated with oil red O staining. The mesenchymal stem cells (MSC) from HD and ND-MM patients were isolated, and in vitro co-culture assay was used to explore the effects of MM cells on the adipogenic differentiation of MSC and the role of BMA in the survival and drug resistance of MM cells. The expression of adipogenic/osteogenic differentiation-related genes PPAR-γ, DLK1, DGAT1, FABP4, FASN and ALP both in MSC and MSC-derived adipocytes was determined with real-time quantitative PCR. The Western blot was employed to detect the expression levels of IL-6, IL-10, SDF-1α, TNF-α and IGF-1 in the supernatant with or without PPAR-γ inhibitor. RESULTS: The results of oil red O staining of bone marrow smears showed that BMA increased significantly in patients of ND-MM compared with the normal control group, and the BMA content was related to the disease status. The content of BMA decreased in the patients with effective chemotherapy. MM cells up-regulated the expression of MSC adipogenic differentiation-related genes PPAR-γ, DLK1, DGAT1, FABP4 and FASN, but the expression of osteogenic differentiation-related gene ALP was significantly down-regulated. This means that the direct consequence of the interaction between MM cells and MSC in the bone marrow microenvironment is to promote the differentiation of MSC into adipocytes at the expense of osteoblasts, and the cytokines detected in supernatant changed. PPAR-γ inhibitor G3335 could partially reverse the release of cytokines by BMA. Those results confirmed that BMA regulated the release of cytokines via PPAR-γ signal, and PPAR-γ inhibitor G3335 could distort PPAR-γ mediated BMA maturation and cytokines release. The increased BMA and related cytokines effectively promoted the proliferation, migration and drug resistance of MM cells. CONCLUSION The BMA and its associated cytokines are the promoting factors in the survival, proliferation and migration of MM cells. BMA can protect MM cells from drug-induced apoptosis and plays an important role in MM treatment failure and disease progression.
Humans ; Osteogenesis/genetics* ; Bone Marrow/metabolism* ; Multiple Myeloma/metabolism* ; Drug Resistance, Neoplasm ; Peroxisome Proliferator-Activated Receptors/pharmacology* ; Cell Differentiation ; Adipogenesis ; Cytokines/metabolism* ; Adipocytes/metabolism* ; Bone Marrow Cells/metabolism* ; Cells, Cultured ; PPAR gamma/pharmacology* ; Tumor Microenvironment

OBJECTIVE: To screen the prognostic biomarkers of metabolic genes in patients with multiple myeloma (MM), and construct a prognostic model of metabolic genes. METHODS: The histological database related to MM patients was searched. Data from MM patients and healthy controls with complete clinical information were selected for analysis.The second generation sequencing data and clinical information of bone marrow tissue of MM patients and healthy controls were collected from human protein atlas (HPA) and multiple myeloma research foundation (MMRF) databases. The gene set of metabolism-related pathways was extracted from Molecular Signatures Database (MSigDB) by Perl language. The biomarkers related to MM metabolism were screened by difference analysis, univariate Cox risk regression analysis and LASSO regression analysis, and the risk prognostic model and Nomogram were constructed. Risk curve and survival curve were used to verify the grouping effect of the model. Gene set enrichment analysis (GSEA) was used to study the difference of biological pathway enrichment between high risk group and low risk group. Multivariate Cox risk regression analysis was used to verify the independent prognostic ability of risk score. RESULTS: A total of 8 mRNAs which were significantly related to the survival and prognosis of MM patients were obtained (P<0.01). As molecular markers, MM patients could be divided into high-risk group and low-risk group. Survival curve and risk curve showed that the overall survival time of patients in the low-risk group was significantly better than that in the high risk group (P<0.001). GSEA results showed that signal pathways related to basic metabolism, cell differentiation and cell cycle were significantly enriched in the high-risk group, while ribosome and N polysaccharide biosynthesis signaling pathway were more enriched in the low-risk group. Multivariate Cox regression analysis showed that the risk score composed of the eight metabolism-related genes could be used as an independent risk factor for the prognosis of MM patients, and receiver operating characteristic curve (ROC) showed that the molecular signatures of metabolism-related genes had the best predictive effect. CONCLUSION Metabolism-related pathways play an important role in the pathogenesis and prognosis of patients with MM. The clinical significance of the risk assessment model for patients with MM constructed based on eight metabolism-related core genes needs to be confirmed by further clinical studies.
Humans ; Cell Cycle ; Multiple Myeloma/genetics* ; Prognosis ; Risk Factors

OBJECTIVE: To investigate the expression of pyruvate kinase M2 (PKM2) in bone marrow mesenchymal stem cells (BMSCs) in myeloma bone disease (MBD) and its effect on osteogenic and adipogenic differentiation of BMSCs. METHODS: BMSCs were isolated from bone marrow of five patients with multiple myeloma (MM) (MM group) and five with iron deficiency anemia (control group) for culture and identification. The expression of PKM2 protein were compared between the two groups. The differences between osteogenic and adipogenic differentiation of BMSCs were assessed by using alkaline phosphatase (ALP) and oil red O staining, and detecting marker genes of osteogenesis and adipogenesis. The effect of MM cell line (RPMI-8226) and BMSCs co-culture on the expression of PKM2 was explored. Functional analysis was performed to investigate the correlations of PKM2 expression of MM-derived BMSCs with osteogenic and adipogenic differentiation by employing PKM2 activator and inhibitor. The role of orlistat was explored in regulating PKM2 expression, osteogenic and adipogenic differentiation of MM-derived BMSCs. RESULTS: Compared with control, MM-originated BMSCs possessed the ability of increased adipogenic and decreased osteogenic differentiation, and higher level of PKM2 protein. Co-culture of MM cells with BMSCs markedly up-regulated the expression of PKM2 of BMSCs. Up-regulation of PKM2 expression could promote adipogenic differentiation and inhibit osteogenic differentiation of MM-derived BMSCs, while down-regulation of PKM2 showed opposite effect. Orlistat significantly promoted osteogenic differentiation in MM-derived BMSCs via inhibiting the expression of PKM2. CONCLUSION The overexpression of PKM2 can induce the inhibition of osteogenic differentiation of BMSCs in MBD. Orlistat can promote the osteogenic differentiation of BMSCs via inhibiting the expression of PKM2, indicating a potential novel agent of anti-MBD therapy.
Humans ; Adipogenesis ; Bone Diseases/metabolism* ; Bone Marrow Cells ; Cell Differentiation ; Cells, Cultured ; Mesenchymal Stem Cells/physiology* ; Multiple Myeloma/metabolism* ; Orlistat/pharmacology* ; Osteogenesis/genetics*

Humans ; Multiple Myeloma/genetics* ; Karyotyping ; Translocation, Genetic/genetics*

OBJECTIVE: To explore the biological function of LINC00174 in multiple myeloma (MM). METHODS: Real-time quantitative polymerase chain reaction (RT-qPCR) was used to detect the expressions of LINC00174 and miR-150 in peripheral blood of MM patients and MM cell lines. EdU staining and flow cytometry were used to detect the effects of LINC00174 and miR-150 on the proliferation and apoptosis of MM cells. Western blot was used to detect the expressions of proliferation marker nuclear-related antigen Ki67, apoptosis-related protein cleaved caspase-3 and transcription factor forkhead box protein P1 (FOXP1). Bioinformatics and dual-luciferase reporter assay were used to verify the targeting relationship between LINC00174 and miR-150 and the targeting relationship between miR-150 and FOXP1. RESULTS: The level of LINC00174 was significantly increased in peripheral blood of MM patients and MM cell lines (P <0.05). Compared with NC-siRNA group, the expression of LINC00174 was significantly reduced in LINC00174-siRNA group, the proliferation of U266 cells was reduced, the apoptosis rate was significantly increased, the level of Ki67 protein was reduced, and the level of cleaved caspase-3 protein was increased (all P <0.05). LINC00174 targeted regulation of the expression of miR-150. Compared with LINC00174-siRNA+NC inhibitor group, the expression of miR-150 in U266 cells in LINC00174-siRNA+miR-150 inhibitor group was significantly reduced, the cell proliferation was enhanced, the apoptosis rate was reduced, the level of Ki67 protein was increased, and the level of cleaved caspase-3 was decreased (all P <0.05). FOXP1 is the target gene of miR-150. Compared with NC mimic group, the expression of FOXP1 protein in miR-150 mimic group was significantly reduced, the cell proliferation was reduced, the apoptosis rate was significantly increased, Ki67 protein level was decreased, and the level of cleaved caspase-3 was increased. Compared with miR-150 mimic + vector group, the expression of FOXP1 protein in miR-150 mimic + pcDNA-FOXP1 group was significantly increased, the cell proliferation was enhanced, the apoptosis rate was reduced, the level of Ki67 protein was increased, and the level of cleaved caspase-3 was decreased (all P <0.05). CONCLUSION LINC00174 promotes the proliferation of MM cells and inhibits cell apoptosis by regulating the miR-150/ FOXP1 axis.
Humans ; Apoptosis ; Caspase 3 ; Cell Line, Tumor ; Cell Proliferation ; Forkhead Transcription Factors ; Ki-67 Antigen ; MicroRNAs/genetics* ; Multiple Myeloma/pathology* ; Repressor Proteins ; RNA, Small Interfering ; RNA, Long Noncoding/genetics*

OBJECTIVE: To investigate the effect of resveratrol (RSV) on the proliferation of multiple myeloma (MM) cells and its molecular mechanism. METHODS: MM cells (MM1.S, RPMI-8226 and U266) were treated with different concentrations of RSV for 24-72 h. The effect of RSV on the proliferation of MM cells was detected by CCK-8 (cell counting kit-8) assay. RPMI-8226 cells were divided into RSV, miR-21 mimic, RSV+miR-21 mimic, miR-21 inhibitor and RSV+miR-21 inhibitor groups, and transfected with corresponding plasmids. The cell cycle distribution of each group was detected by flow cytometry with propidium iodide (PI) single staining. The cell apoptosis of each group was detected by AnnexinV-FITC/PE-PI double staining. The expression of miR-21 in MM cells treated with RSV and the expression of KLF5 mRNA in each group were detected by qRT-PCR. The expression of KLF5 protein in each group was detected by Western blot. RESULTS: RSV inhibited the proliferation and induced apoptosis of MM cells in a time- and dose-dependent manner. After the MM cells were treated with RSV, the number of cells in sub-G₁ phase was increased, and that in G₂/M phase was decreased. Moreover, RSV significantly downregulated the expression of miR-21 in MM cells, and the inhibitory effect of miR-21 mimic on KLF5 expression in MM cells was counteracted by RSV. CONCLUSION RSV may inhibit the proliferation and induce apoptosis of MM cells by inhibiting miR-21 and up-regulating KLF5 expression.
Humans ; Resveratrol/pharmacology* ; Multiple Myeloma/metabolism* ; Cell Proliferation ; Cell Line, Tumor ; Apoptosis ; MicroRNAs/genetics*