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 This study aims to construct and identify the chimeric antigen receptor NK92 (CAR-NK92) cells targeting NKG2D ligand (NKG2DL) (secreting IL-15Ra-IL-15) and verify the killing activity of NKG2D CAR-NK92 cells against multiple myeloma cells. Methods The extracellular segment of NKG2D was employed to connect 4-1BB and CD3Z, as well as IL-15Ra-IL-15 sequence to obtain a CAR expression framework. The lentivirus was packaged and transduced into NK92 cells to obtain NKG2D CAR-NK92 cells. The proliferation of NKG2D CAR-NK92 cells was detected by CCK-8 assay, IL-15Ra secretion was detected by ELISA and killing efficiency was detected by lactate dehydrogenase (LDH) assay. The molecular markers of NKp30, NKp44, NKp46, the ratio of apoptotic cell population, CD107a, and the secretion level of granzyme B and perforin were detected using flow cytometry. In addition, the cytotoxic mechanism of NKG2D CAR-NK92 cells on the tumor was verified by measuring the degranulation ability. Moreover, after NKG2D antibody inhibited effector cells and histamine inhibited tumor cells, LDH assay was utilized to detect the effect on cell-killing efficiency. Finally, the multiple myeloma tumor xenograft model was constructed to verify its anti-tumor activity in vivo. Results Lentiviral transduction significantly increased NKG2D expression in NK92 cells. Compared with NK92 cells, the proliferation ability of NKG2D CAR-NK92 cells was weaker. The early apoptotic cell population of NKG2D CAR-NK92 cells was less, and NKG2D CAR-NK92 cells had stronger cytotoxicity to multiple myeloma cells. Additionally, IL-15Ra secretion could be detected in its culture supernatant. NKp44 protein expression in NKG2D CAR-NK92 cells was clearly increased, demonstrating an enhanced activation level. Inhibition test revealed that the cytotoxicity of CAR-NK92 cells to MHC-I chain-related protein A (MICA) and MICB-positive tumor cells was more dependent on the interaction between NKG2D CAR and NKG2DL. After stimulating NKG2D CAR-NK92 cells with tumor cells, granzyme B and perforin expression increased, and NK cells obviously upregulated CD107α. Furthermore, multiple myeloma tumor xenograft model revealed that the tumors of mice treated with NKG2D CAR-NK92 cells were significantly reduced, and the cell therapy did not sensibly affect the weight of the mice. Conclusion A type of CAR-NK92 cell targeting NKG2DL (secreting IL-15Ra-IL-15) is successfully constructed, indicating the effective killing of multiple myeloid cells.
Humans ; Mice ; Animals ; Receptors, Chimeric Antigen/genetics* ; Interleukin-15 ; NK Cell Lectin-Like Receptor Subfamily K/metabolism* ; Granzymes ; Cell Line, Tumor ; Multiple Myeloma/therapy* ; Perforin

OBJECTIVE: To investigate the association between the expression level of platelet-activating factor acetylhydrolase 1B3 (PAFAH1B3 ) gene in bone marrow CD138⁺ cells of patients with multiple myeloma (MM) treated with autologous hematopoietic stem cell transplantation (AHSCT) and the prognosis within 2 years. METHODS: 147 MM patients treated with AHSCT in The First and The Second Affiliated Hospital of Nantong University from May 2014 to May 2019 were included in the study. Expression level of PAFAH1B3 mRNA in bone marrow CD138⁺ cells of the patients was detected. Patients with disease progression or death during 2 years of follow-up were included in progression group, and the rest were included in good prognosis group. After comparing the clinical data and PAFAH1B3 mRNA expression levels of the two groups, the patients were divided into high PAFAH1B3 expression group and low PAFAH1B3 expression group based on the median PAFAH1B3 mRNA expression level of the enrolled patients. Progression-free survival rate (PFSR) between the two groups was compared by the Kaplan-Meier method. The related factors of prognosis within 2 years were analyzed by univariate analysis and multivariate COX regression analysis. RESULTS: At the end of follow-up, there were 13 patients lost to follow-up. Finally, 44 patients were included in the progression group and 90 patients were included in the good prognosis group. Age in the progression group was higher than that in the good prognosis group, the proportion of patients with CR+VGPR after transplantation in the progression group was lower than that in the good prognosis group, and there was a statistical difference between two groups in the cases distribution of ISS stage (all P<0.05). PAFAH1B3 mRNA expression level and the proportion of patients with LDH>250U/L in the progression group were higher than those in the good prognosis group, and platelet count in the progression group was lower than that in the good prognosis group (all P<0.05). Compared with the low PAFAH1B3 expression group, the 2-year PFSR of the high PAFAH1B3 expression group was significantly lower (log-rank χ²=8.167, P=0.004). LDH>250U/L (HR=3.389, P=0.010), PAFAH1B3 mRNA expression (HR=50.561, P=0.001) and ISS stage Ⅲ(HR=1.000, P=0.003) were independent risk factors for prognosis in MM patients, and ISS stage Ⅰ (HR=0.133, P=0.001) was independent protective factor. CONCLUSION The expression level of PAFAH1B3 mRNA in bone marrow CD138⁺ cells is related to the prognosis of MM patients treated with AHSCT, and detecting PAFAH1B3 mRNA expression can bring some information for predicting PFSR and prognostic stratification of patients.
Humans ; Disease Progression ; Hematopoietic Stem Cell Transplantation ; Multiple Myeloma/drug therapy* ; Prognosis ; Retrospective Studies ; Transplantation, Autologous ; 1-Alkyl-2-acetylglycerophosphocholine Esterase/genetics*

Extramedullary plasma cell tumor (EMP) is a kind of plasma cell tumor, and its pathogenesis is not completely clear. According to whether it is independent of myeloma disease, it can be divided into primary and secondary EMP, which have different biological and clinical characteristics. Primary EMP has low invasion, fewer cytogenetic and molecular genetic abnormalities and good prognosis, and surgery and / or radiotherapy are the mainly treatments. Secondary EMP, as the extramedullary invasive progression of multiple myeloma (MM), is often accompanied by high-risk cellular and molecular genetic abnormalities and poor prognosis, chemotherapy, immunotherapy and hematopoietic stem cell transplantation are the mainly treatment. This paper reviews the latest research progress of EMP in the pathogenesis, cytogenetics molecular genetics and treatment, so as to provide reference for clinical work.
Humans ; Plasmacytoma/surgery* ; Prognosis ; Multiple Myeloma/genetics* ; Hematopoietic Stem Cell Transplantation

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

OBJECTIVE: To explore the clinical and laboratory characteristics of hematological tumors with different types of abnormalities in platelet derived growth factor β (PDGFRβ) gene. METHODS: A retrospective analysis was carried out on 141 patients with abnormal long arm of chromosome 5 (5q) and comprehensive medical history data from Changhai Hospital Affiliated to Naval Medical University from 2009 to 2020, and their clinical data were collected. R-banding technique was used for chromosomal karyotyping analysis for the patient's bone marrow, and fluorescence in situ hybridization (FISH) was used to detect the PDGFRβ gene. The results of detection were divided into the amplification group, deletion group, and translocation group based on FISH signals. The three sets of data column crosstabs were statistically analyzed, and if the sample size was n >= 40 and the expected frequency T for each cell was >= 5, a Pearson test was used to compare the three groups of data. If N < 40 and any of the expected frequency T for each cell was < 5, a Fisher's exact test is used. Should there be a difference in the comparison results between the three sets of data, a Bonferroni method was further used to compare the data. RESULTS: In total 98 patients were detected to have PDGFRβ gene abnormalities with the PDGFRβ probe, which yielded a detection rate of 69.50% (98/141). Among these, 38 cases (38.78%) had PDGFRβ gene amplifications, 57 cases (58.16%) had deletions, and 3 (3.06%) had translocations. Among the 98 cases, 93 were found to have complex karyotypes, including 37 cases from the amplification group (97.37%, 37/38), 55 cases from the deletion group (96.49%, 55/57), and 1 case from the translocation group (33.33%, 1/3). Analysis of three sets of clinical data showed no significant gender preponderance in the groups (P > 0.05). The PDGFRβ deletion group was mainly associated with myeloid tumors, such as acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) (P < 0.001). The PDGFRβ amplification group was more common in lymphoid tumors, such as multiple myeloma (MM) (P < 0.001). The PDGFRβ translocation group was also more common in myelodysplastic/myeloproliferative tumors (MDS/MPN). CONCLUSION Tumors with PDGFRβ gene rearrangement may exhibit excessive proliferation of myeloproliferative tumors (MPN) and pathological hematopoietic changes in the MDS, and have typical clinical and hematological characteristics. As a relatively rare type of hematological tumor, in addition to previously described myeloid tumors such as MPN or MDS/MPN, it may also cover lymphoid/plasma cell tumors such as multiple myeloma and non-Hodgkin's lymphoma.
Humans ; Clinical Relevance ; Hematologic Neoplasms/genetics* ; In Situ Hybridization, Fluorescence ; Multiple Myeloma ; Myelodysplastic Syndromes ; Retrospective Studies ; Translocation, Genetic