Poor Prognosis In Multiple Myeloma Research Articles

Cytidine triphosphate synthase 1-mediated metabolic reprogramming promotes proliferation and drug resistance in multiple myeloma

Upregulation of metabolism-related gene cytidine triphosphate synthase 1 (CTPS1) is associated with poor prognosis in multiple myeloma (MM). However, its role in MM remains unclear. In this study, bioinformatics analysis revealed significant differences in CTPS1 expression levels among various plasma cell malignancies. The patients with high CTPS1 expression had poor overall survival, progression-free survival, and event-free survival. CTPS1 was significantly correlated with sex, albumin, β2 microglobulin, lactate dehydrogenase, and advanced disease. In vitro experiments demonstrated that CTPS1-overexpressing (CTPS1-OE) cells proliferated faster than CTPS1-short hairpin RNA (CTPS1-sh) cells. NRG-SGM3 mice showed significantly accelerated tumor growth in the CTPS1-OE group. CTPS1-OE decreased sensitivity to bortezomib, whereas CTPS1-sh increased sensitivity to bortezomib in MM cell lines. Mechanistically, CTPS1 was primarily involved in metabolism processes. Additionally, CTPS1 was closely related to several co-expressed genes such as MYC and the bone marrow immune microenvironment. In conclusion, CTPS1 is a significant prognostic biomarker for patients with MM, suggesting a potential therapeutic target.

NK cells with adhesion defects and reduced cytotoxic functions are associated with a poor prognosis in multiple myeloma

AbstractThe promising results obtained with immunotherapeutic approaches for multiple myeloma (MM) call for a better stratification of patients based on immune components. The most pressing being cytotoxic lymphocytes such as natural killer (NK) cells that are mandatory for MM surveillance and therapy. Here, we performed a single-cell RNA sequencing analysis of NK cells from 10 patients with MM and 10 age/sex–matched healthy donors that revealed important transcriptomic changes in the NK cell landscape affecting both the bone marrow (BM) and peripheral blood compartment. The frequency of mature cytotoxic CD56dim NK cell subsets was reduced in patients with MM at the advantage of late-stage NK cell subsets expressing NF-κB and interferon-I inflammatory signatures. These NK cell subsets accumulating in patients with MM were characterized by low CD16 and CD226 expression and poor cytotoxic functions. MM CD16/CD226Lo NK cells also had adhesion defects with reduced lymphocyte function-associated antigen 1 (LFA-1) integrin activation and actin polymerization that may account for their limited effector functions in vitro. Finally, analysis of BM-infiltrating NK cells in a retrospective cohort of 177 patients with MM from the Intergroupe Francophone du Myélome (IFM) 2009 trial demonstrated that a high frequency of NK cells and their low CD16 and CD226 expression were associated with a shorter overall survival. Thus, CD16/CD226Lo NK cells with reduced effector functions accumulate along MM development and negatively affect patients’ clinical outcomes. Given the growing interest in harnessing NK cells to treat myeloma, this improved knowledge around MM–associated NK cell dysfunction will stimulate the development of more efficient immunotherapeutic drugs against MM.

Predicting cytogenetic risk in multiple myeloma using conventional whole-body MRI, spinal dynamic contrast-enhanced MRI, and spinal diffusion-weighted imaging

ObjectivesCytogenetic abnormalities are predictors of poor prognosis in multiple myeloma (MM). This paper aims to build and validate a multiparametric conventional and functional whole-body MRI-based prediction model for cytogenetic risk classification in newly diagnosed MM.MethodsPatients with newly diagnosed MM who underwent multiparametric conventional whole-body MRI, spinal dynamic contrast-enhanced (DCE-)MRI, spinal diffusion-weighted MRI (DWI) and had genetic analysis were retrospectively included (2011–2020/Ghent University Hospital/Belgium). Patients were stratified into standard versus intermediate/high cytogenetic risk groups. After segmentation, 303 MRI features were extracted. Univariate and model-based methods were evaluated for feature and model selection. Testing was performed using receiver operating characteristic (ROC) and precision-recall curves. Models comparing the performance for genetic risk classification of the entire MRI protocol and of all MRI sequences separately were evaluated, including all features. Four final models, including only the top three most predictive features, were evaluated.ResultsThirty-one patients were enrolled (mean age 66 ± 7 years, 15 men, 13 intermediate-/high-risk genetics). None of the univariate models and none of the models with all features included achieved good performance. The best performing model with only the three most predictive features and including all MRI sequences reached a ROC-area-under-the-curve of 0.80 and precision-recall-area-under-the-curve of 0.79. The highest statistical performance was reached when all three MRI sequences were combined (conventional whole-body MRI + DCE-MRI + DWI). Conventional MRI always outperformed the other sequences. DCE-MRI always outperformed DWI, except for specificity.ConclusionsA multiparametric MRI-based model has a better performance in the noninvasive prediction of high-risk cytogenetics in newly diagnosed MM than conventional MRI alone.Critical relevance statementAn elaborate multiparametric MRI-based model performs better than conventional MRI alone for the noninvasive prediction of high-risk cytogenetics in newly diagnosed multiple myeloma; this opens opportunities to assess genetic heterogeneity thus overcoming sampling bias.Key points• Standard genetic techniques in multiple myeloma patients suffer from sampling bias due to tumoral heterogeneity.• Multiparametric MRI noninvasively predicts genetic risk in multiple myeloma.• Combined conventional anatomical MRI, DCE-MRI, and DWI had the highest statistical performance to predict genetic risk.• Conventional MRI alone always outperformed DCE-MRI and DWI separately to predict genetic risk. DCE-MRI alone always outperformed DWI separately, except for the parameter specificity to predict genetic risk.• This multiparametric MRI-based genetic risk prediction model opens opportunities to noninvasively assess genetic heterogeneity thereby overcoming sampling bias in predicting genetic risk in multiple myeloma.Graphical

ARK5 enhances cell survival associated with mitochondrial morphological dynamics from fusion to fission in human multiple myeloma cells

5′ adenosine monophosphate–activated protein kinase–related kinase 5 (ARK5) is involved in mitochondrial ATP production and associated with poor prognosis of multiple myeloma (MM). However, the molecular mechanisms of ARK5 in MM remain largely unknown. This study examined the pathogenic role of ARK5 in mitochondria by using genetically modified isogenic cell clones with or without ARK5 in human myeloma cell lines, KMS-11 and Sachi, which overexpress ARK5. The biallelic knockout of ARK5 (ARK5-KO) inhibited cell proliferation, colony formation, and migration with increased apoptosis. Mitochondrial fusion was enhanced in ARK5-KO cells, unlike in ARK5 wild-type (ARK5-WT) cells, which exhibited increased mitochondrial fission. Furthermore, ARK5-KO cells demonstrated a lower phosphorylated dynamin–related protein 1 at serine 616, higher protein expression of mitofusin-1 (MFN1) and MFN2, optic atrophy 1 with a lower level of ATP, and higher levels of lactate and reactive oxygen species than ARK5-WT cells. Our findings suggest that ARK5-enhanced myeloma cells can survive associated mitochondrial fission and activity. This study first revealed the relationship between ARK5 and mitochondrial morphological dynamics. Thus, our outcomes show novel aspects of mitochondrial biology of ARK5, which can afford a more advanced treatment approach for unfavorable MM expressing ARK5.

Complex karyotype determined using conventional cytogenetic analysis is a poor prognostic factor in patients with multiple myeloma.

High-risk cytogenetic abnormalities (HRCAs) influence the prognosis of multiple myeloma (MM). However, additional cytogenetic aberrations can lead to poor outcomes. This study aimed to clarify whether HRCAs and additional chromosomal abnormalities affect MM prognosis. Patients with newly diagnosed MM who were treated with novel agents were retrospectively evaluated. The primary objective was to assess the difference in progression-free survival (PFS) and overall survival (OS) between patients with/without HRCAs and between patients with/without complex karyotype (CK). The secondary objectives were to identify factors affecting PFS/OS and factors related to CK. HRCAs were defined as del(17p), t(4;14), t(14;16), and gain/amplification(1q) assessed using fluorescence in situ hybridization. CK was defined as ≥3 chromosomal abnormalities on G-banding. Among 110 patients, 40 had HRCAs and 15 had CK. In this study, survival durations between patients with/without HRCAs were similar, while the CK group had significantly poorer PFS/OS than the no-CK group (median PFS: 9 vs. 24 months and median OS: 29 vs. 97 months, respectively), and a poor prognostic impact of CK was maintained in patients with HRCAs. In multivariate analysis, CK was correlated with poor PFS/OS (hazard ratio [HR]: 2.39, 95% confidence interval [95% CI]: 1.22-4.66 and HR: 2.66, 95% CI: 1.10-6.45, respectively). Bone marrow plasma cell (BMPC) ≥60% (odds ratio [OR] = 6.40, 95% CI: 1.50-27.2) and Revised International Staging System III (OR = 7.53, 95% CI: 2.09-27.1) were associated with CK. Our study suggests that CK may contribute to the poor prognosis of MM. Aggressive disease status including high BMPC proliferation could be relevant to CK.

Suppression of TRIP13 Induces Metabolic Changes and Potentiates Ferroptosis in Multiple Myeloma

Introduction Despite the remarkable success of combination treatments, multiple myeloma (MM) still poses significant challenges, with a high percentage of patients experiencing relapse over time. Additional metabolic alterations are found in relapsed and refractory MM; however, their impacts have not been fully elucidated. Expression of thyroid hormone receptor interactor 13 (TRIP13) has been identified by Gene Expression Profile (GEP)-70 to correlate with poor prognosis in MM. TRIP13 is an AAA ATPase that regulates the spindle assembly checkpoint in mitosis. Based on GEP data from 34 paired baseline and relapse samples, TRIP13 continuously increased from baseline to first and to second relapse. Overexpression of TRIP13 induces bortezomib resistance. In this study, we aimed to investigate how TRIP13 might regulate MM cell metabolism and to use this information to develop a novel combination strategy to overcome MM resistance. Methods Knockout (KO) of TRIP13 in OPM2 and MM1.S cells was generated by dual gRNAs CRISPR-Cas9 editing deleting a fragment between exon 4 and exon 5. Cell growth curves and response to bortezomib were recorded in the control and TRIP13-KO cells. Metabolomics was performed to reveal cellular metabolic alterations. Seahorse analysis was used to test the mitochondrial stress and glycolysis stress. To investigate whether TRIP13 KO promotes ferroptosis, an intracellular iron-dependent cell death characterized by the accumulation of lipid peroxides, we applied C11-BODIY staining after treatment with Erastin, a ferroptosis-inducer. Expression levels of cyclooxygenase 2 (encoded by PTGS2, a hallmark of ferroptosis), cystine transporter (xCT), and intracellular glutathione peroxidase 4 (GPX4) were analyzed. In addition, the protein levels of iron metabolic molecules, including iron importer transferrin receptor protein 1 (TFRC), iron exporter ferroportin 1 (FPN1), ferritin heavy chain 1 (FTH1), and nuclear receptor coactivator 4 (NCOA4) were assessed. To study whether TRIP13 KO delays MM progression in an immune-competent MM mouse model, Vκ12653 murine MM cells were genetically modified by CRISPR-mediated TRIP13-KO and then injected into C57BL/6 mice. Mouse survival was monitored. Results The cell-doubling rate of TRIP13-KO cells was decreased by 50% compared to control cells. After 24 hours of treatment with 5 nM bortezomib, cell viability of TRIP13-KO cells decreased by 31% compared with control cells. The metabolomic studies revealed that TRIP13-KO OPM2 and MM1.S cells both had significantly decreased intracellular L-serine (FC = 0.57) but increased pyruvate (FC = 1.79), citric acid (FC = 1.76), and isocitric acid (FC = 1.64), indicating TRIP13 may regulate serine metabolism, mitochondrial function, and cellular redox balance. Seahorse analysis indicated that TRIP13-KO MM cells showed decreased glycolysis (decreased by 30%, p < 0.001) and glycolytic capacity (decreased by 33%, p < 0.001) while oxidative phosphorylation showed little change. Moreover, lipid peroxidation and PTGS2 were increased in TRIP13-KO cells after Erastin treatment, indicating that these cells were more vulnerable to ferroptosis. Mechanistically, inhibition of TRIP13 decreased GPX4, FPN1, FTH1, and increased NCOA4, while overexpression of TRIP13 showed the opposite changes, suggesting that targeting TRIP13 sensitizes MM cells to ferroptosis by impairing cellular redox balance and increasing the labile-iron pool. Lastly, TRIP13-KO significantly prolonged mouse survival in the Vκ12653 mouse model (median survival: TRIP13-KO 93 days vs. Control 60.5 days, p < 0.001). Conclusion Our study revealed that TRIP13 plays a critical role in regulating MM cell metabolism. By suppressing TRIP13, we observed increased sensitivity of MM cells to bortezomib, leading to enhanced ferroptosis-mediated cell death and prolonged mouse survival. These findings strongly suggest that targeting TRIP13 could be a promising approach in MM therapy. Moving forward, our future investigations will concentrate on unraveling the precise molecular mechanisms underlying TRIP13-mediated alterations in cell metabolism. Additionally, we plan to explore the potential synergistic effects of TRIP13 inhibition in combination with metabolic targeted treatments, such as venetoclax, to further enhance therapeutic outcomes in MM.

Potential Significance of CTPS1 in Multiple Myeloma

Introduction With the increasing interest to the metabolism of multiple myeloma (MM), a number of metabolic genes and their associated regulatory networks are essential for MM progression. Our team's prior work indicated that high expression of metabolism-related gene CTPS1 (CTP synthase 1) correlated with poor prognosis of MM. However, the mechanism of CTPS1 in MM is unknown. Methods The difference in CTPS1 expression level in patients with plasma cell malignancies, various stages, and drug-resistant recurrence was examined using publicly available data. MM cell lines were engineered to overexpress or knockdown CTPS1. RNA-seq was used to unbiased interrogate the downstream effector genes modulated by CTPS1. Severe immunodeficient NRG-SGM mice expressing humanized myeloid cytokines were used to determine the effect of CTPS1 on MM proliferation in vivo. Results CTPS1 expression levels varied substantially in various plasma cell malignancies. High CTPS1 expression was associated with shorter overall survival and progression-free survival in newly diagnosed MM patients. Moreover, there was a strong correlation between CTPS1 and sex, albumin, β2 microglobulin, lactate dehydrogenase, and ISS/R-ISS stage. In vitro, CTPS1 overexpressing cells proliferated more quickly than CTPS1 knockdown cells. NRG-SGM3 mouse experiments demonstrated that tumor growth was significantly accelerated in vivo in the CTPS1 overexpression group. In the pharmacological experiment, CTPS1 overexpression group's sensitivity to 20 nM bortezomib reduced, but CTPS1 down-knocked group's sensitivity to 20 nM bortezomib rose. CTPS1 was also shown to be involved in metabolism and synthesis, notably mRNA metabolism, DNA metabolism, chromosomal combination, cell cycle, spliceosome, and cellular senescence. Furthermore, Myc was found to be tightly connected to CTPS1 in both MM cell lines and newly diagnosed MM. Conclusions This study found that increased CTPS1 expression is associated with a poor prognosis and reduced sensitivity to bortezomib in MM. Additionally, CTPS1 upregulated Myc-signaling genes, which promoted progression of MM.

TI17, a novel compound, exerts anti-MM activity by impairing Trip13 function of DSBs repair and enhancing DNA damage.

Thyroid hormone receptor interacting protein 13 (Trip13) is an AAA-ATPase that regulates the assembly or disassembly protein complexes and mediates Double-strand breaks (DSBs) repair. Overexpression of Trip13 has been detected in many cancers and is associated with myeloma progression, disease relapse and poor prognosis inmultiple myeloma (MM). We have identified a small molecular, TI17, through a parallel compound-centric approach, which specifically targets Trip13. To identify whether TI17 targeted Trip13, pull-down and nuclear magnetic resonance spectroscopy (NMR) assays were performed. Cell counting kit-8, clone formation, apoptosis and cell cycle assays were applied to investigate the effects of TI17. We also utilized a mouse model to investigate the effects of TI17 in vivo. TI17 effectively inhibited the proliferation of MM cells, and induced the cycle arrest and apoptosis of MM cells. Furthermore, treatment with TI17 abrogates tumor growth and has no apparent side effects in mouse xenograft models. TI17 specifically impaired Trip13 function of DSBs repair and enhanced DNA damage responses in MM. Combining with melphalan or HDAC inhibitor panobinostat triggers synergistic anti-MM effect. Our study suggests that TI17 could be acted as a specific inhibitor of Trip13 and supports a preclinical proof of concept for therapeutic targeting of Trip13 in MM.

Network Modeling of Apoptosis-Related Genes Reveal a High-Risk Cluster in Multiple Myeloma

The plasma cell cancer multiple myeloma (MM) varies significantly in genomic characteristics, response to therapy, and long-term prognosis. Recent studies have shown the complexity of biological systems associated with poor outcomes in MM. One hallmark of cancer pathogenesis, applicable to MM, is the dysregulation of apoptotic cell death. Understanding the relationship between known drivers of MM and critical pathways in the apoptosis gene network is key towards identifying novel therapeutic targets. Recently, there has been a surge of interest in developing network-based approaches to study gene interactions and use machine learning tools to further elucidate useful biological factors. It is well-known that genes operate as network systems; however, interpretable computational methods are still limited. In this work, we combine a set of network analysis tools to provide novel biological insights into how the apoptosis network is dysregulated in MM. We identify a set of genes associated with poor outcomes in MM using both univariate and network-based approaches. Genomic and clinical data, including RNA-sequencing (RNA-seq) and copy number alteration (CNA), for 659 subjects were obtained from the Multiple Myeloma Research Foundation's CoMMpass (IA19) database. The apoptosis gene set is defined using the apoptosis hallmark pathway provided by the gene set enrichment analysis tool. The interactions between the given list of genes are provided via MetaCore. Univariate gene modeling is done using a Cox proportional hazards model. To determine the relationship between genes, we used Ollivier-Ricci curvature (ORC), a measure of network robustness. The ORC value between two genes incorporates information about both the two genes in question and their local neighborhoods, a concept critical for understanding the role a neighborhood of genes has on a given connection. Once edge information is computed, we used a uniform manifold approximation and projection (UMAP) to reduce the complexity of the dataset. The resulting projection is clustered using k-means clustering, and survival analysis of the given clusters is done using the Kaplan-Meier (KM) method. To understand which features are most informative, we used a random forest to predict the cluster labels using the RNA-seq data. After five-fold cross-validation, feature importance was computed using random forest's permutation importance methodology. All statistical significance testing was corrected for multiple comparisons via the Benjamini-Hochberg false discovery rate method with an alpha set to 0.05. Using RNA-seq data of genes associated with apoptosis, we identified nineteen apoptosis genes associated with poor prognosis in MM. Some of these genes, such as ANXA1 and WEE1 are known to have an effect in MM, while others, such as AVPR1A have yet to be studied extensively for their role in MM. When examining CNA data associated with apoptosis, a similar pattern emerged - nineteen genes were associated with poor prognosis. However, between the two key gene sets found by RNA-seq and CNA, only FAS appeared in both lists. FAS, Fas Cell Surface Death Receptor, is critical for triggering apoptosis. Half of the 37 genes identified using RNA-seq and CNA data are directly connected to the TP53 gene. While TP53 mutations are not a marker of the presence of MM itself, TP53 mutations have been shown to be associated with poorer outcomes. After reducing the complexity of the Ollivier-Ricci curvature analysis of the RNA-seq apoptosis network using UMAPs, the data revealed five clusters with KM curves for progression-free survival were significant (p<0.001). To identify the genes most impactful for separating these clusters, we trained a random forest model on the RNA-seq - note, it was the edge robustness values that were clustered - and evaluated its performance for predicted class membership. The model had an overall accuracy of approximately 78% with F1 scores for each class ranging from 61% to 87%. The top three features associated with the model include CTNNB1, RELA, and LEF1. Of note, CTNNB1 and RELA are directly interacted with the TP53 gene. Because these three genes discriminate between all five clusters, their expression levels may play a mediating effect on MM outcomes. Further investigation with external datasets is needed to validate these results.

P-339 Longitudinal genetically detectable minimal residual disease by interphase fluorescence in situ hybridization confers a poor prognosis in multiple myeloma

P-339 Longitudinal genetically detectable minimal residual disease by interphase fluorescence in situ hybridization confers a poor prognosis in multiple myeloma

Identification of mutation gene prognostic biomarker in multiple myeloma through gene panel exome sequencing and transcriptome analysis in Chinese population

BackgroundThe 5-year survival rate of multiple myeloma (MM) in China is less than 40%, with considerable individual heterogeneity. Gene mutations are important predictive biomarkers that influence MM treatment decision. The aim of our study was to uncover the clinical significance of mutated genes in MM in the Chinese population. MethodsTargeted exon panel sequencing was performed of 400 genes to detect the gene mutation status in plasma cells from 50 patients with MM. DAVID was used to explore the functions and pathways of mutated genes. Detection of mutant gene expression, prognosis and immune cell infiltration with GSE6477. GEO2R was utilized to identify differentially expressed genes (DEGs). Kaplan-Meier and CIBERSORT were applied to compare survival distributions and evaluate the gene expression associated with immune cell infiltration, respectively. ResultsMutations of 337 genes were identified in MM. The mutation types included SNP, INS, and DEL, but the dominant mutation type was SNP. Function and pathway analysis of mutant genes were performed to elucidate DNA modifications. We identified a total number of 660 downregulated and 587 upregulated genes from the GSE6477 dataset. Thirty-three common genes were present in both the mutant genes and DEGs. The functions and pathways of the mutated genes were enriched in myeloid cell differentiation, regulation of hemopoiesis, etc. Moreover, we found that the low expression of BCL6, BIRC3, HLA-DQA1, and VCAN was correlated with poor prognosis in MM. ConclusionsThe mutations and low expression of BCL6, BIRC3, HLA-DQA1, and VCAN were correlated with poor prognosis and immune cell infiltration in MM. This study is the first to reveal the spectrum of mutations in the Chinese population by the use of an NGS panel.

Identification of evolutionary mechanisms of myelomatous effusion by single-cell RNA sequencing

AbstractMyelomatous effusion (ME) is a rare manifestation of extramedullary multiple myeloma (MM) with limited therapeutic options and poor outcomes. The molecular mechanisms underlying ME are incompletely understood. We profiled transcriptomes of bone marrow, peripheral blood (PB), and pleural effusion/ascites from 3 patients with ME using single-cell RNA sequencing analysis. We found that ME contained a higher percentage of cytotoxic T cells, whereas PB contained a higher proportion of naive T cells. Malignant cells varied within and between sites and patients in their expression of signatures. We identified a gene module highly expressed in intramedullary and extramedullary plasma cell clusters and defined cell clusters expressing this gene set as extramedullary-initiating cells (EMICs). This gene set was associated with increased cellular proliferation, involved in p53 signaling, and related to poor prognosis in MM. The transcriptional regulators E2F1, YY1, and SMAD1 were activated in EMICs. Leukocyte immunoglobulin–like receptor subfamily B4 (LILRB4) was upregulated in extramedullary EMICs. We confirmed that LILRB4 promoted MM cell migration in vitro. This study provided insight into the evolutionary mechanisms of ME and defined EMICs and LILRB4 associated with extramedullary development.

Increased Expression of SRSF1 Predicts Poor Prognosis in Multiple Myeloma.

Multiple myeloma (MM) is a clonal plasma cell disorder which still lacks sufficient prognostic factors. The serine/arginine-rich splicing factor (SRSF) family serves as an important splicing regulator in organ development. Among all members, SRSF1 plays an important role in cell proliferation and renewal. However, the role of SRSF1 in MM is still unknown. SRSF1 was selected from the primary bioinformatics analysis of SRSF family members, and then we integrated 11 independent datasets and analyzed the relationship between SRSF1 expression and MM clinical characteristics. Gene set enrichment analysis (GSEA) was conducted to explore the potential mechanism of SRSF1 in MM progression. ImmuCellAI was used to estimate the abundance of immune infiltrating cells between the SRSF1high and SRSF1low groups. The ESTIMATE algorithm was used to evaluate the tumor microenvironment in MM. The expression of immune-related genes was compared between the groups. Additionally, SRSF1 expression was validated in clinical samples. SRSF1 knockdown was conducted to explore the role of SRSF1 in MM development. SRSF1 expression showed an increasing trend with the progression of myeloma. Besides, SRSF1 expression increased as the age, ISS stage, 1q21 amplification level, and relapse times increased. MM patients with higher SRSF1 expression had worse clinical features and poorer outcomes. Univariate and multivariate analysis indicated that upregulated SRSF1 expression was an independent poor prognostic factor for MM. Enrichment pathway analysis confirmed that SRSF1 takes part in the myeloma progression via tumor-associated and immune-related pathways. Several checkpoints and immune-activating genes were significantly downregulated in the SRSF1high groups. Furthermore, we detected that SRSF1 expression was significantly higher in MM patients than that in control donors. SRSF1 knockdown resulted in proliferation arrest in MM cell lines. The expression value of SRSF1 is positively associated with myeloma progression, and high SRSF1 expression might be a poor prognostic biomarker in MM patients.

Excessive serine from the bone marrow microenvironment impairs megakaryopoiesis and thrombopoiesis in Multiple Myeloma

Thrombocytopenia is a major complication in a subset of patients with multiple myeloma (MM). However, little is known about its development and significance during MM. Here, we show thrombocytopenia is linked to poor prognosis in MM. In addition, we identify serine, which is released from MM cells into the bone marrow microenvironment, as a key metabolic factor that suppresses megakaryopoiesis and thrombopoiesis. The impact of excessive serine on thrombocytopenia is mainly mediated through the suppression of megakaryocyte (MK) differentiation. Extrinsic serine is transported into MKs through SLC38A1 and downregulates SVIL via SAM-mediated tri-methylation of H3K9, ultimately leading to the impairment of megakaryopoiesis. Inhibition of serine utilization or treatment with TPO enhances megakaryopoiesis and thrombopoiesis and suppresses MM progression. Together, we identify serine as a key metabolic regulator of thrombocytopenia, unveil molecular mechanisms governing MM progression, and provide potential therapeutic strategies for treating MM patients by targeting thrombocytopenia.

The ubiquitin ligase HERC4 suppresses MafA transcriptional activity triggered by GSK3β in myeloma by atypical K63-linked polyubiquitination

MafA and c-Maf are close members of the Maf transcription factor family and indicators of poor prognosis of multiple myeloma (MM). Our previous study finds that the ubiquitin ligase HERC4 induces c-Maf degradation but stabilizes MafA, and the mechanism is elusive. In the present study we find that HERC4 interacts with MafA and mediates its K63-linked polyubiquitination at K33. Moreover, HERC4 inhibits MafA phosphorylation and its transcriptional activity triggered by glycogen synthase kinase 3β (GSK3β). The K33R MafA variant prevents HERC4 from inhibiting MafA phosphorylation and increases MafA transcriptional activity. Further analyses reveal that MafA can also activate the STAT3 signaling but it is suppressed by HERC4. Lastly, we demonstrate that lithium chloride, a GSK3β inhibitor, can upregulate HERC4 and synergizes dexamethasone, a typical anti-MM drug, in inhibiting MM cell proliferation and xenograft growth in nude mice. These findings thus highlight a novel regulation of MafA oncogenic activity in MM and provide the rationale by targeting HERC4/GSK3β/MafA for the treatment of MM.

The TT Genotype of the KIAA1524 rs2278911 Polymorphism Is Associated with Poor Prognosis in Multiple Myeloma

The KIAA1524 gene encodes an oncoprotein, CIP2A, which inhibits the phosphorylation of the Akt kinase B, stabilizes the c-Myc protein, and, through that, promotes cancerogenesis. An increase in CIP2A expression has been observed in numerous solid tumors and hematologic malignancies, including multiple myeloma (MM). The aim of our study was to evaluate the clinical impact of the functional single nucleotide polymorphisms (SNP) of the KIAA1524 gene (rs2278911, 686C > T) in MM patients. The study group consisted of 128 patients with de novo MM. EDTA venous blood samples were collected prior to the treatment. The SNPs were analyzed by Real-Time PCR with the use of specific Taqman probes. Multivariable analysis revealed that variables independently associated with shorter progression-free survival (PFS) included thrombocytopenia, delTP53 and IGH/CCND1 translocation and the TT genotype of the KIAA1524 gene (686C > T) (median PFS: 6 vs. 25 months; HR = 7.18). On the other hand, autologous haematopoietic stem cell transplantation (AHSCT) was related to a lower risk of early disease progression. Moreover, light chain disease, International Staging System (ISS) 3, poor performance status, hypoalbuminemia, IGH/FGFR3 translocation and the TT genotype of the KIAA1524 gene (686C > T) were independent prognostic factors associated with shorter overall survival (OS) (median OS: 8 vs. 45 months; HR = 7.08). The evaluation of the SNP 686C > T of the KIAA1524 gene could be used as a diagnostic tool in MM patients at risk of early disease progression and death.

EMD originates from hyaluronan-induced homophilic interactions of CD44 variant-expressing MM cells under shear stress.

Extramedullary disease (EMD) is known to be associated with chemoresistance and poor prognosis in multiple myeloma (MM); however, the mechanisms of its development are not fully understood. Elucidating the mechanism of EMD development and its therapeutic targeting would greatly contribute to further improvement of treatment outcome in patients with MM. Here, we show that bone marrow stroma cell-derived hyaluronan (HA) elicits homophilic interactions of MM cells by binding to surface CD44, especially long-stretch variants, under physiological shear stress and generates cell clusters that might develop into EMD. We recapitulated the development of EMD via administration of HA in a syngeneic murine MM model in a CD44-dependent manner. HA-induced MM cell clusters exhibited the specific resistance to proteasome inhibitors (PIs) invitro and in murine models via γ-secretase-mediated cleavage of the intracellular domains of CD44, which in turn transactivated PI resistance-inducible genes. Treatment of HA-injected mice with anti-CD44 antibody or γ-secretase inhibitors readily suppressed the development of EMD from transplanted MM cells and significantly prolonged the survival of recipients by overcoming PI resistance. The HA-CD44 axis represents a novel pathway to trigger EMD development and could be a target of the prediction, prevention, and treatment of EMD in patients with MM.

Increased expression of CEP72 predicts poor prognosis in multiple myeloma.

Multiple myeloma (MM) is a fatal hematological malignancy and does not have adequate prognostic indicators. Previous studies indicate that CEP72 is closely related to tumorigenesis and tumor progression. However, the expression and function of CEP72 in multiple myeloma have yet to be elucidated. In this study, we explored the correlation between CEP72 expression and clinicopathological characteristics as well as the impacts of CEP72 expression on the survival of MM patients. In addition, PPI, GSEA and Chemotherapy drug resistance analysis identified the possible mechanism. CEP72 is overexpressed in both MM patients and MM cell lines. Clinically, patients in the CEP72high subgroup were significantly older than those in the CEP72low subgroup (p=0.003). Up-regulation of CEP72 was related to poor overall survival and event-free survival. PPI network showed that CEP72 was related to PCM1, KIZ, OFD1, etc. GSEA analysis showed that CEP72 was enriched in cell cycle, oocyte meiosis, protein export, lysosome and N-glycan biosynthesis pathways. Drug resistance analysis indicated that there was a positive correlation between the CEP72 expression and the IC50 values of 6-mercaptopurine, 8-chloro-adenosine, clofarabine, fludarabine and allopurinol. High CEP72 expression was a poor prognostic factor in patients diagnosed with multiple myeloma.

Proline promotes proliferation and drug resistance of multiple myeloma by downregulation of proline dehydrogenase.

Amino acids in the bone marrow microenvironment (BMME) are a critical factor for multiple myeloma (MM) progression. Here, we have determined that proline is elevated in BMME of MM patients and links to poor prognosis in MM. Moreover, exogenous proline regulates MM cell proliferation and drug resistance. Elevated proline in BMME is due to bone collagen degradation and abnormal expression of the key enzyme of proline catabolism, proline dehydrogenase (PRODH). PRODH is downregulated in MM patients, mainly as a result of promoter hypermethylation with high expression of DNMT3b. Thus, overexpression of PRODH suppresses cell proliferation and drug resistance of MM and exhibits therapeutic potential for treatment of MM. Altogether, we identify proline as a key metabolic regulator of MM, unveil PRODH governing MM progression and provide a promising therapeutic strategy for MM treatment.

Survival analysis of transplant-eligible newly-diagnosed multiple myeloma patients harboring t(4;14), t(14;16), and/or del(17p) in the real-world setting

Cytogenetic abnormalities (CA) such as t(4;14), t(14;16), and del(17p), are associated with a poor prognosis in Multiple Myeloma (MM) patients. However, there is scarce information regarding the Latin-American population. This study aims to analyze the impact of t(4;14), t(14;16), and del(17p) on the progression-free survival (PFS) and overall survival (OS) of transplant-eligible newly-diagnosed MM (NDMM) patients in Latin America. Retrospective survival analysis based on the Grupo de Estudio Latinoamericano de MM (GELAMM) registry, including all adult patients with NDMM harboring CA t(4;14), t(14;16), and/or del(17p). Fifty-nine patients were included; the median age was 57 years, 55.9% males, 22% ISS-I, 25.4% ISS-II, and 47.5% ISS-III. The majority (89.8%) had one alteration, whereas 10.2% had del(17p) and t(4;14). The frequencies of CA were del(17p) in 61.0%, t(4;14) in 25.4%, and t(14;16) in 3,4%. Autologous stem cell transplantation was performed in 36 cases, 20 patients did not use this consolidative strategy, and this data was missed in three cases.Five-year OS for the entire cohort was 60.8% and 5-year PFS was 28.1%. Bortezomib-based induction regimen (BBR) (p=0.029), consolidation with ASCT (p<0.001), and maintenance therapy (p=0.004) were associated with an improved 5-year OS. In the multivariate analysis, ASCT was the only variable with a positive impact on OS (HR 0.11, 95% CI 0.033 to 0.34, p<0.001). The median PFS presented a non-statistically significant benefit in BBR, ASCT, and maintenance therapy groups. BBR induction, ASCT, and maintenance therapy were associated with improved OS in high-risk NDMM patients.