Multiple Myeloma Patients Research Articles

Impaired acute-phase humoral immunity is the major factor predicting unfavorable outcomes in multiple myeloma patients with SARS-CoV-2 Omicron variants outbreak infection.

At the end of 2022, a huge tide of SARS-CoV-2 infection mainly Omicron BA.4/5 developed in China. Multiple myeloma (MM) patients suffered cancer deterioration and mortality from COVID-19, yet profound analyses of Omicron variants-induced immunity function are scarce. We presented a longitudinal study in 218 MM patients and 73 healthy controls (HCs), reporting the prognostic factors and dynamic humoral and cellular immune responses. Neutralizing antibody and interferon γ ELISpot assay of SARS-CoV-2 was tested at three time points: 2-4, 8-10, and 14-16 weeks after infections. Our data showed older age, active MM, relapsed/refractory MM (R/RMM), immunotherapy, comorbidity, and non-vaccination were risk factors associated with hospitalization. Severe humoral immunity impairment within 2-4 weeks was especially seen in patients with unvaccinated, older age, immunotherapy, R/RMM and comorbidities, while T-cell response was relatively intact. Although antibodies of Omicron variants reached positive levels in MM patients at 8-10 weeks, half lost effective antibody protection at 14-16 weeks. However, most seronegative patients (76.2% at 2-4 weeks, 83.3% at 8-10 weeks) could develop effective T-cell response. Notably, the inactivated wild-type vaccinated patients exhibited weaker humoral and cellular immunity only at 2-4 weeks, escalating to similar levels as those in HCs later. Our findings indicate impairment of humoral immunity at acute-phase after infection is the major factor correlated with hospitalization. One-month suspension of immune therapy is suggested to prevent serious infection. These results confirm the value of inactivated vaccine, but indicate the need for additional booster at 14-16 weeks after infection for high-risk MM population.

Identification of lipid metabolism-related gene signature in the bone marrow microenvironment of multiple myelomas through deep analysis of transcriptomic data

Dysregulated lipid metabolism in the bone marrow microenvironment (BMM) plays a vital role in multiple myeloma (MM) development, progression, and drug resistance. However, the exact mechanism by which lipid metabolism impacts the BMM, promotes tumorigenesis, and triggers drug resistance remains to be fully elucidated.By analyzing the bulk sequencing and single-cell sequencing data of MM patients, we identified lipid metabolism-related genes differential expression significantly associated with MM prognosis, referred to as LMRPgenes. Using a cohort of ten machine learning algorithms and 117 combinations, LMRPgenes predictive models were constructed. Further exploration of the effects of the model risk score (RS) on the survival status, immune status of patients with BMM, and response to immunotherapy was conducted. The study also facilitated the identification of personalized therapeutic strategies targeting specified risk categories within patient cohorts.Analysis of the scRNA-seq data revealed increased lipid metabolism-related gene enrichment scores (LMESs) in erythroblasts and progenitor, malignant, and Tprolif cells but decreased LMESs in lymphocytes. LMESs were also strongly correlated with most of the 50 hallmark pathways within these cell populations. An elevated malignant cell ratio and reduced lymphocytes were observed in the high LMES group. Moreover, the LMRPgenes predictive model, consisting of 14 genes, showed great predictive power. The risk score emerged as an independent indicator of poor outcomes. Inverse relationships between the RS and immune status were noted, and a high RS was associated with impaired immunotherapy responses. Drug sensitivity assays indicated the effectiveness of bortezomib, buparlisib, dinaciclib, staurosporine, rapamycin, and MST-312 in the high-RS group, suggesting their potential for treating patients with high-RS values and poor response to immunotherapy. Ultimately, upon verification via qRT-PCR, we observed a significant upregulation of ACBD6 in NDMM group compared to the control group.Our research enhances the knowledge base regarding the association between lipid metabolism-related genes (LMRGs) and the BMM in MM patients, offering substantive insights into the mechanistic effects of the BMM mediated by LMRGs.Graphical abstract

Which factors are associated with adverse prognosis in multiple myeloma patients after surgery? - preliminary establishment and validation of the nomogram

BackgroundTo investigate the prognosis of patients with Multiple Myeloma (MM) after surgery, analyze the risk factors leading to adverse postoperative outcomes, and establish a nomogram.MethodsClinical data from 154 patients with MM who underwent surgery at our institution between 2007 and 2019 were retrospectively analyzed. Assessing and comparing patients’ pain levels, quality of life, and functional status before and after surgery (P < 0.05) were considered statistically significant. The Kaplan-Meier survival curve was used to estimate the median survival time. Adverse postoperative outcomes were defined as worsened symptoms, lesion recurrence, complication grade ≥ 2, or a postoperative survival period < 1 year. Logistic regression analysis was used to determine the prognostic factors. Based on the logistic regression results, a nomogram predictive model was developed and calibrated.ResultsPostoperative pain was significantly alleviated in patients with MM, and there were significant improvements in the quality of life and functional status (P < 0.05). The median postoperative survival was 41 months. Forty-nine patients (31.8%) experienced adverse postoperative outcomes. Multivariate logistic regression analysis identified patient age, duration of MM, International Staging System, preoperative Karnofsky Performance Status, and Hb < 90 g/L as independent factors influencing patient prognosis. Based on these results, a nomogram was constructed, with a C-index of 0.812. The calibration curve demonstrated similarity between the predicted and actual survival curves. Decision curve analysis favored the predictive value of the model at high-risk thresholds from 10% to-69%.ConclusionThis study developed a nomogram risk prediction model to assist in providing quantifiable assessment indicators for preoperative evaluation of surgical risk.

Monoclonal whole IgG impairs both fibrin and thrombin formation: hemostasis and surface plasmon resonance studies.

Monoclonal gammopathies frequently associate with hemostatic alterations. Thrombotic events occur with high incidence particularly upon treatment, while in rarer cases hemorrhagic diathesis can be observed. Thepathology of these tendencies could be caused by thrombocytopenia or hyperviscosity burden of circulating monoclonal antibodies. Studies also suggest interference ofmonoclonal antibodies with primary hemostasis. We isolated monoclonal whole IgG paraproteins from two myeloma patients to observe their effect on thrombin formation and fibrin polymerization. Monoclonal whole IgG was prepared from sera of two newly diagnosed untreated multiple myeloma patients and control normal plasma samples. Fibrin formation was measured using thrombin time and dilute prothrombin time tests and thrombin formation was detected with a fluorimetric thrombin generation assay. In addition, molecular interactions were investigated by surface plasmon resonance (SPR). Thrombin time was prolonged upon addition of monoclonal IgG even at 30 g/L by 12 %, increasing up to 36 % at 60 g/L concentration. Dilute prothrombin time was prolonged by 20 % even at 30 g/L. Thrombin generation assay indicated an impairment in thrombin formation at the presence of monoclonal IgG compared to polyclonal at equivalent concentration. By an SPR assay we determined that both clonality IgG preparations interacted with fibrinogen, however interaction with human thrombin was only detected with monoclonal immunoglobulins (KD=1.03×10-7 M). Here we provide evidence that isolated monoclonal whole IgG from myeloma patients can impair both fibrin and thrombin formation and we demonstrate by SPR assay that it interacts with components of the final phase of the coagulation system.

The comparative efficacy and safety of factor Xa inhibitors and warfarin for primary thromboprophylaxis in multiple myeloma patients undergoing immunomodulatory therapy.

There are limited data on the optimal choice of anticoagulation in multiple myeloma (MM) patients receiving immunomodulatory drugs (IMiDs). We conducted a propensity score-matched cohort study using the TriNetX database to compare the efficacy and safety of factor Xa inhibitors and warfarin in this patient population. Compared to warfarin, factor Xa inhibitors had a similar risk of deep vein thrombosis (hazard ratio [HR]: 1.11 [95% CI: 0.50-2.46]) or pulmonary embolism (HR: 1.08 [95% CI: 0.59-2.00]). There were no differences in the risk of gastrointestinal or intracranial bleeding. Factor Xa inhibitor-treated patients had lower all-cause mortality (HR: 0.56 [95% CI: 0.36-0.86]) compared with warfarin. These data suggest that factor Xa inhibitors had similar safety and efficacy compared with warfarin for MM patients on IMiDs.

IRF4 requires ARID1A to establish plasma cell identity in multiple myeloma

Multiple myeloma (MM) is an incurable plasma cell malignancy that exploits transcriptional networks driven by IRF4. We employ a multi-omics approach to discover IRF4 vulnerabilities, integrating functional genomics screening, spatial proteomics, and global chromatin mapping. ARID1A, a member of the SWI/SNF chromatin remodeling complex, is required for IRF4 expression and functionally associates with IRF4 protein on chromatin. Deleting Arid1a in activated murine B cells disrupts IRF4-dependent transcriptional networks and blocks plasma cell differentiation. Targeting SWI/SNF activity leads to rapid loss of IRF4-target gene expression and quenches global amplification of oncogenic gene expression by MYC, resulting in profound toxicity to MM cells. Notably, MM patients with aggressive disease bear the signature of SWI/SNF activity, and SMARCA2/4 inhibitors remain effective in immunomodulatory drug (IMiD)-resistant MM cells. Moreover, combinations of SWI/SNF and MEK inhibitors demonstrate synergistic toxicity to MM cells, providing a promising strategy for relapsed/refractory disease.

Identification of Therapy-Induced Clonal Evolution and Resistance Pathways in Minimal Residual Clones in Multiple Myeloma through Single-Cell Sequencing.

In multiple myeloma (MM), therapy-induced clonal evolution is associated with treatment resistance and is one of the most important hindrances toward a cure for MM. To further understand the molecular mechanisms controlling the clonal evolution of MM, we applied single-cell RNA sequencing (scRNA-seq) to paired diagnostic and posttreatment bone marrow (BM) samples. scRNA-seq was performed on 38 BM samples from patients with monoclonal gammopathy of undetermined significance (n = 1), MM patients at diagnosis (n = 19), MM posttreatment (n = 17), and one healthy donor (HD). The single-cell transcriptome data of malignant plasma cells (PC) and the surrounding immune microenvironment were analyzed. Profiling by scRNA-seq data revealed three primary trajectories of transcriptional evolution after treatment: clonal elimination in patients with undetectable minimal residual disease (MRD-) and clonal stabilization and clonal selection in detectable MRD (MRD+) patients. We noted a metabolic shift toward fatty acid oxidation in cycling-resistant PCs, whereas selective PCs favored the NF-κB pathway. Intriguingly, when comparing the genetic and transcriptional dynamics, we found a significant correlation between genetic and nongenetic factors in driving the clonal evolution. Furthermore, we identified variations in cellular interactions between malignant PCs and the tumor microenvironment. Selective PCs showed the most robust cellular interactions with the tumor microenvironment. These data suggest that MM cells could rapidly adapt to induction treatment through transcriptional adaptation, metabolic adaptation, and specialized immune evasion. Targeting therapy-induced resistance mechanisms may help to avert refractory disease in MM.

CREB1 promotes expression of immune checkpoint HLA-E leading to immune escape in multiple myeloma

Multiple myeloma (MM) cells effectively escape anti-tumoral immunity to survive in the tumor microenvironment (TME). Herein, we identify non-classical major histocompatibility complex (MHC) class I molecule HLA-E as a major contributing factor in immune escape. Clinically, HLA-E expression correlates with aggressive disease features such as t(4;14) and CD56 expression and is induced by IFN-gamma (IFN-γ) in the TME. We discovered that HLA-E is regulated by cAMP responsive element binding protein 1 (CREB1) transcription factor by direct promoter binding; genomic and pharmacological inhibition of CREB1 reduced HLA-E levels even in the presence of IFN-γ or IFN-γ activating agents, such as immunomodulatory drugs and panobinostat. HLA-E binds to natural killer group 2A (NKG2A), delivering an inhibitor signal to natural killer (NK) cells. Treatment with a CREB1 inhibitor was able to restore NK cell-mediated cytotoxicity against MM cell lines and patient samples. In conclusion, our results strongly demonstrate that CREB1 inhibition promotes anti-tumoral immunity in MM by limiting HLA-E expression and enhancing the activity of NK cells.

The prognostic significance of ubiquitination-related genes in multiple myeloma by bioinformatics analysis

BackgroundImmunoregulatory drugs regulate the ubiquitin-proteasome system, which is the main treatment for multiple myeloma (MM) at present. In this study, bioinformatics analysis was used to construct the risk model and evaluate the prognostic value of ubiquitination-related genes in MM.Methods and resultsThe data on ubiquitination-related genes and MM samples were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The consistent cluster analysis and ESTIMATE algorithm were used to create distinct clusters. The MM prognostic risk model was constructed through single-factor and multiple-factor analysis. The ROC curve was plotted to compare the survival difference between high- and low-risk groups. The nomogram was used to validate the predictive capability of the risk model. A total of 87 ubiquitination-related genes were obtained, with 47 genes showing high expression in the MM group. According to the consistent cluster analysis, 4 clusters were determined. The immune infiltration, survival, and prognosis differed significantly among the 4 clusters. The tumor purity was higher in clusters 1 and 3 than in clusters 2 and 4, while the immune score and stromal score were lower in clusters 1 and 3. The proportion of B cells memory, plasma cells, and T cells CD4 naïve was the lowest in cluster 4. The model genes KLHL24, HERC6, USP3, TNIP1, and CISH were highly expressed in the high-risk group. AICAr and BMS.754,807 exhibited higher drug sensitivity in the low-risk group, whereas Bleomycin showed higher drug sensitivity in the high-risk group. The nomogram of the risk model demonstrated good efficacy in predicting the survival of MM patients using TCGA and GEO datasets.ConclusionsThe risk model constructed by ubiquitination-related genes can be effectively used to predict the prognosis of MM patients. KLHL24, HERC6, USP3, TNIP1, and CISH genes in MM warrant further investigation as therapeutic targets and to combat drug resistance.

Intensive salvage chemotherapy with VDTPACE or mCBAD followed by hematopoietic stem-cell support for refractory/relapsed multiple myeloma.

Triple- and quad-refractory multiple myeloma patients usually have an aggressive course and a poor prognosis. Available therapeutic options are scarce. The objective of the current study was to evaluate responses and toxicities of VDTPACE or mCBAD with hematopoietic stem-cell support as a bridge to subsequent therapies in patients with refractory/relapsed multiple myeloma. Thirteen patients were included (11 mCBAD, 2 VDTPACE), and 21 cycles of chemotherapy with hematopoietic stem-cell support were delivered. Mean number of previous therapies was 4.8. Stem cells were infused on a median day 9.9 after chemotherapy. Mean time to neutrophil recovery was 18.2 days in patients receiving the first cycle and 15.9 following subsequent cycles. Before therapy, most patients were in PD (77%), PR (15%), or VGPR (8%). Following treatment, the best responses achieved were PR (46%), VGPR (46%), and CR (8%). Median overall and progression-free survivals were 17 and 9 months. There has been no case of non-relapse mortality. In the 21 cycles, the main complications were infectious. Intensive chemotherapy can decrease disease burden in patients with relapsed/refractory MM, and stem-cell support can successfully decrease toxicities and treatment-related mortality associated with these regimens and may be a good bridging option.

An automated workflow based on data independent acquisition for practical and high-throughput personalized assay development and minimal residual disease monitoring in multiple myeloma patients.

Minimal residual disease (MRD) status in multiple myeloma (MM) is an important prognostic biomarker. Personalized blood-based targeted mass spectrometry detecting M-proteins (MS-MRD) was shown to provide a sensitive and minimally invasive alternative to MRD-assessment in bone marrow. However, MS-MRD still comprises of manual steps that hamper upscaling of MS-MRD testing. Here, we introduce a proof-of-concept for a novel workflow using data independent acquisition-parallel accumulation and serial fragmentation (dia-PASEF) and automated data processing. Using automated data processing of dia-PASEF measurements, we developed a workflow that identified unique targets from MM patient sera and personalized protein sequence databases. We generated patient-specific libraries linked to dia-PASEF methods and subsequently quantitated and reported M-protein concentrations in MM patient follow-up samples. Assay performance of parallel reaction monitoring (prm)-PASEF and dia-PASEF workflows were compared and we tested mixing patient intake sera for multiplexed target selection. No significant differences were observed in lowest detectable concentration, linearity, and slope coefficient when comparing prm-PASEF and dia-PASEF measurements of serial dilutions of patient sera. To improve assay development times, we tested multiplexing patient intake sera for target selection which resulted in the selection of identical clonotypic peptides for both simplex and multiplex dia-PASEF. Furthermore, assay development times improved up to 25× when measuring multiplexed samples for peptide selection compared to simplex. Dia-PASEF technology combined with automated data processing and multiplexed target selection facilitated the development of a faster MS-MRD workflow which benefits upscaling and is an important step towards the clinical implementation of MS-MRD.

Identification of clinical-biological features of newly diagnosed early relapse multiple myeloma patients eligible for autologous stem cell transplantation.

A portion of multiple myeloma (MM) patients relapse early or do not respond to first line treatment. Identification of possible clinical and or biological features of these patients remains an unmet medical need. In this study we assesed the predictive markers for early relapse MM, defined as a progressive disease that occurred within 18 months, from autologoust stem cell transplantation (ASCT) in MM patients who did not have primary refractory disease. 74 consecutive MM patients were included in the study that received intensive therapy with ASCT. The study was able to identify the main features of newly diagnosed ER MM patients eligible for ASCT identifying the IgA isotype and the R2-ISS score system as the main predictive prognostic factors for ER in this cohort of MM patients.

Prevalence, outcomes, and complications of vitamin D deficiency among patients with multiple myeloma: Nationwide burden of disease.

Multiple myeloma (MM), constituting 10% of hematological malignancies, poses significant morbidity and mortality, especially with skeletal involvement. Bisphosphonate use in MM may lead to severe hypocalcemia due to vitamin D deficiency (VDD), exacerbating bone-marrow plasma cell burden. We aimed to assess VDD prevalence and its impact on outcomes in MM patients. A retrospective cross-sectional analysis (2008-2018) of nationwide inpatient data identified adult MM hospitalizations with VDD using ICD-10-CM codes. Univariate and multivariate analyses were conducted to evaluate prevalence, demographics, and outcomes, with significance set at p < 0.05. Among 330,175 MM hospitalizations, 3.48% had VDD. VDD was more prevalent among 50-75 year olds (61.72% vs 59.74%), females (53.36% vs 44.34%), Blacks (23.34% vs 22.94%), Whites (65.84% vs 65.79%), higher income brackets (26.13% vs 23.85%), and those with comorbidities like hypertension (71.12% vs 69.89%), dyslipidemia (42.47% vs 34.98%), obesity (13.63% vs 10.19%), and alcohol abuse (1.61% vs 1.34%). In regression analysis, VDD in MM patients correlated with higher morbidity (adjusted odds ratio (aOR): 1.24, 95% confidence interval (95% CI): 1.14-1.36) and major disability (aOR: 1.26, 95% CI: 1.20-1.30). MM patients with VDD exhibit worse outcomes, underscoring the importance of recognizing and managing VDD promptly. Further prospective studies are needed to validate our findings and explore the impact of vitamin D supplementation on MM patient outcomes.

Denosumab-Induced Maxillary Osteonecrosis: A Case Study on Long-Term Complications in Multiple Myeloma Treatment.

Background: Targeted therapies like denosumab have revolutionized multiple myeloma (MM) treatment, improved patient outcomes while introducing long-term complications. This study explores a rare instance of delayed maxillary osteonecrosis post-denosumab therapy, delving into its pathophysiology and management. Methods: A 40-year-old male MM patient who developed a painful palatal lesion post denosumab treatment and diagnosed of maxillary osteonecrosis by computed tomography scan and surgical biopsy is presented. Treatment history, symptom progression, and response to the PENTOCLO protocol were analyzed. Results: Post-denosumab discontinuation osteonecrosis highlights its prolonged impact on bone metabolism. PENTOCLO treatment protocol led to significant improvement. Genetic factors influencing osteonecrosis susceptibility have been discussed and considered. Conclusions: This case underscores the need for vigilance regarding long-term complications in MM survivors, preventive strategies, including regular dental evaluations and reducing invasive dental procedures, are crucial. We advocate for an interdisciplinary approach and further research into tailored prevention and management of osteonecrosis in cancer survivors.

Radiomic nomogram for predicting high-risk cytogenetic status in multiple myeloma based on fat-suppressed T2-weighted magnetic resonance imaging

Rationale and ObjectivesRadiomics has demonstrated potential in predicting the cytogenetic status of multiple myeloma (MM). However, the role of single-sequence radiomic nomograms in predicting the high-risk cytogenetic (HRC) status of MM remains underexplored. This study aims to develop and validate radiomic nomograms based on fat-suppressed T2-weighted images (T2WI-FS) for predicting MM’s HRC status, facilitating pre-treatment decision-making and prognostic assessment. Materials and methodsA cohort of 159 MM patients was included, comprising 71 HRC and 88 non-HRC cases. Regions of interest within the most significant tumor lesions on T2WI-FS images were manually delineated, yielding 1688 features. Fourteen radiomic features were selected using 10-fold cross-validation, employing methods such as variance thresholds, Student’s t-test, redundancy analysis, and least absolute shrinkage and selection operator (LASSO). Logistic regression was utilized to develop three prediction models: a clinical model (model 1), a T2WI-FS radiomic model (model 2), and a combined clinical-radiomic model (model 3). Receiver operating characteristic (ROC) curves evaluated and compared the diagnostic performance of these models. Kaplan-Meier survival analysis and log-rank tests assessed the prognostic value of the radiomic nomograms. ResultsModels 2 and 3 demonstrated significantly greater diagnostic efficacy compared to model 1 (p < 0.05). The areas under the ROC curve for models 1, 2, and 3 were as follows: training set—0.650, 0.832, and 0.846; validation set—0.702, 0.730, and 0.757, respectively. Kaplan-Meier survival analysis indicated comparable prognostic values between the radiomic nomogram and MM cytogenetic status, with log-rank test results (p < 0.05) and concordance indices of 0.651 and 0.659, respectively; z-score test results were not statistically significant (p = 0.153). Additionally, Kaplan-Meier analysis revealed that patients in the non-HRC group, low-RS group, and aged ≤ 60 years exhibited the longest overall survival, while those in the HRC group, high-RS group, and aged > 60 years demonstrated the shortest overall survival (p = 0.004, Log-rank test). ConclusionsRadiomic nomograms are capable of predicting the HRC status in MM. The cytogenetic status, radiomics model Rad score, and age collectively influence the overall survival of MM patients. These factors potentially contribute to pre-treatment clinical decision-making and prognostic assessment.

EE148 The Institutional Level Impact of Additional Apheresis Days for Multiple Myeloma Patients Undergoing Autologous Stem Cell Transplantation on Costs and Healthcare Resource Utilization

EE148 The Institutional Level Impact of Additional Apheresis Days for Multiple Myeloma Patients Undergoing Autologous Stem Cell Transplantation on Costs and Healthcare Resource Utilization

Cytoplasmic light-chain immunofluorescence combined with FISH in bone marrow smears to detect cytogenetic abnormalities in multiple myeloma

Objective: To analyze the sensitivity of cytoplasmic light-chain immunofluorescence with fluorescence in situ hybridization in bone marrow smears (new FISH) for detecting cytogenetic abnormalities in multiple myeloma (MM) . Methods: 42 MM patients admitted to the First Affiliated Hospital of Nanjing Medical University from April 2022 to October 2023 were enrolled. The patients with MM were detected by new FISH and CD138 immunomagnetic bead sorting technology combined with FISH (MACS-FISH) or cytoplasmic immunoglobulin FISH (cIg-FISH) to analyze cytogenetic detection results using combination probes which included 1q21/1p32, p53, IgH, IgH/FGFR3 [t (4;14) ], and IgH/MAF [t (14;16) ]. Results: In 23 patients with MM, the abnormality detection rates of cIg-FISH and new FISH were 95.7% and 100.0%, respectively (P>0.05). The detection rates of 1q21+, 1p32-, p53 deletion, and IgH abnormalities by cIg-FISH and new FISH were consistent, which were 52.2%, 8.7%, 17.4%, and 65.2%, respectively. The results of the two methods further performed with t (4;14) and t (14;16) in patients with IgH abnormalities were identical. The positive rate of t (4;14) was 26.7%, whereas t (14;16) was not detected. In 19 patients with MM, the abnormality detection rates of MACS-FISH and new FISH were 73.7% and 63.2%, respectively (P>0.05). The positivity rate of 1q21+, 1p32- and IgH abnormalities detected by MACS-FISH were slightly higher than those detected by new FISH; however, the differences were not statistically significant (all P values >0.05) . Conclusion: The new FISH method has a higher detection rate of cytogenetic abnormalities in patients with MM and has good consistency with MACS-FISH and cIg-FISH.

The implication of serum HLA-G in angiogenesis of multiple myeloma

BackgroundDespite the advances of therapies, multiple myeloma (MM) remains an incurable hematological cancer that most patients experience relapse. Tumor angiogenesis is strongly correlated with cancer relapse. Human leukocyte antigen G (HLA-G) has been known as a molecule to suppress angiogenesis. We aimed to investigate whether soluble HLA-G (sHLA-G) was involved in the relapse of MM.MethodsWe first investigated the dynamics of serum sHLA-G, vascular endothelial growth factor (VEGF) and interleukin 6 (IL-6) in 57 successfully treated MM patients undergoing remission and relapse. The interactions among these angiogenesis-related targets (sHLA-G, VEGF and IL-6) were examined in vitro. Their expression at different oxygen concentrations was investigated using a xenograft animal model by intra-bone marrow and skin grafts with myeloma cells.ResultsWe found that HLA-G protein degradation augmented angiogenesis. Soluble HLA-G directly inhibited vasculature formation in vitro. Mechanistically, HLA-G expression was regulated by hypoxia-inducible factor-1α (HIF-1α) in MM cells under hypoxia. We thus developed two mouse models of myeloma xenografts in intra-bone marrow (BM) and underneath the skin, and found a strong correlation between HLA-G and HIF-1α expressions in hypoxic BM, but not in oxygenated tissues. Yet when stimulated with IL-6, both HLA-G and HIF-1α could be targeted to ubiquitin-mediated degradation via PARKIN.ConclusionThese results highlight the importance of sHLA-G in angiogenesis at different phases of multiple myeloma. The experimental evidence that sHLA-G as an angiogenesis suppressor in MM may be useful for future development of novel therapies to prevent relapse.

Identifying high-risk multiple myeloma patients: A novel approach using a clonal gene signature.

Multiple myeloma (MM) is a heterogeneous disease with a small subset of high-risk patients having poor prognoses. Identifying these patients is crucial for treatment management and strategic decisions. In this study, we developed a novel computational framework to define prognostic gene signatures by selecting genes with expression driven by clonal copy number alterations. We applied this framework to MM and developed a clonal gene signature (CGS) consisting of 22 genes and evaluated in five independent datasets. The CGS provided significant prognostic values after adjusting for well-established factors including cytogenetic abnormalities, International Staging System (ISS), and Revised ISS (R-ISS). Importantly, CGS demonstrated higher performance in identifying high-risk patients compared to the GEP70 and SKY92 signatures recommended for prognostic stratification of MM. CGS can further stratify patients into subgroups with significantly differential prognoses when applied to the high- and low-risk groups identified by GEP70 and SKY92. Additionally, CGS scores are significantly associated with patient response to dexamethasone, a commonly used treatment for MM. In summary, we proposed a computational framework that requires only gene expression data to identify CGSs for prognosis prediction. CGS provides a useful biomarker for improving prognostic stratification in MM, especially for identifying the highest-risk patients.

Treatment Efficacy and Safety of Bortezomib Combined with Dexamethasone and Lenalidomide Chemotherapy Regimen for Multiple Myeloma

Objective: To analyze the effect of bortezomib combined with dexamethasone and lenalidomide in the treatment of multiple myeloma. Methods: 60 cases of multiple myeloma patients admitted to our hospital from January 2022 to December 2023 were selected randomly, with 30 cases in each group. Bortezomib combined with dexamethasone was administered in the control group, and bortezomib combined with dexamethasone and lenalidomide was given to the observation group, and the treatment effect was analyzed. Results: After treatment, CD3+ and CD4+ of the observation group were higher than that of the control group, CD8+ was lower than that of the control group, and the total treatment efficiency was higher, which was statistically significant (P &lt; 0.05), and there was no difference in the total incidence of adverse reactions between the two groups (P &gt; 0.05). Conclusion: Bortezomib combined with dexamethasone and lenalidomide is effective in the treatment of multiple myeloma as it regulates the immune function and is safe, thus it can be promoted in clinical practice.