Serum ATIC Expression as a Novel Diagnostic and Prognostic Biomarker in Multiple Myeloma Patients

BackgroundHypertension is commonly reported in multiple myeloma (MM) patients and may be associated with older age, disease-related complications and consequences of MM treatments. This study evaluated the incidence rates of and risk factors for hypertension and malignant hypertension in newly-treated MM patients in the United States.MethodsNewly-treated adult MM patients were identified from Truven MarketScan claims database from 1/1/05 to 3/31/14. Inclusion criteria were new diagnosis of MM with start of MM treatment, ≥12 months continuous enrollment prior to diagnosis, ≥30 days of continuous enrollment following initial diagnosis, and prescription drug coverage. Non-MM patients were matched for age (within +/− 5 years), sex and distribution of index dates to MM patients. Baseline cardiovascular (CV) comorbidities, incidence rate of hypertension and malignant hypertension in the follow-up period, and risk of hypertension and malignant hypertension based on existing baseline CV comorbidities were evaluated.ResultsA total of 7895 MM patients (38% with hypertension history) and 23,685 non-MM patients (24% with hypertension history) were included in the study. Twenty-two percent of MM patients versus 3% of non-MM patients had baseline renal failure. A higher percentage of MM versus non-MM patients had baseline hypertension in combination with renal failure, congestive heart failure or both. The incidence rate of hypertension in MM and non-MM patients was 260 and 178 per 1000 person-years, respectively. There was a 30% increase in the risk of hypertension for MM versus non-MM patients: hazard ratio (HR) 1.30 (95% confidence interval [CI] 1.22, 1.37). In MM patients with a history of hypertension, the risk of malignant hypertension was significantly increased with the following comorbid conditions: cardiomyopathy, HR 2.79 (95% CI 1.20, 6.48); renal failure, HR 2.13 (95% CI 1.36, 3.34); and diabetes mellitus, HR 1.59 (95% CI 1.05, 2.39).ConclusionsThis study confirms that the incidence of hypertension and malignant hypertension is significantly higher in newly-treated MM versus non-MM patients. Hypertension is a risk factor for MM patients developing malignant hypertension. Management of CV comorbidities in MM patients is important based on the increased risk of hypertension and malignant hypertension among patients with these comorbidities.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-016-2955-0) contains supplementary material, which is available to authorized users.

Bone marrow‐derived mesenchymal stem cells inhibit NK cell function via Tim‐3/galectin‐9 in multiple myeloma patients

Multiple myeloma (MM) is a hematologic malignancy characterized by clonal proliferation of plasma cells and remains incurable. Patients with primary refractory multiple myeloma (PRMM) show poor response to initial induction therapy. This study aims to develop a machine learning-based model to predict treatment response in newly diagnosed multiple myeloma (NDMM) patients, in order to optimize therapeutic strategies. NDMM and post-treatment MM patients hospitalized in the Department of Hematology, Third Xiangya Hospital, Central South University, between August 2022 and July 2023 were enrolled. Post-treatment MM patients were categorized into PRMM patients and treatment-responsive MM (TRMM) patients based on therapeutic efficacy. Serum metabolites were detected and analyzed via metabolomics. Based on the metabolomics analysis results and combined with transcriptomic sequencing data of NDMM patients from databases, differentially expressed amino acid metabolism-related genes (AAMGs) among post-treatment NDMM patients with varying therapeutic outcomes were screened. Using bioinformatics analyses and machine learning algorithms, a predictive model for treatment response in NDMM was constructed and used to identify patients at risk for PRMM. A total of 61 patients were included: 22 NDMM, 23 TRMM, and 16 PRMM patients. Significant differences in metabolite levels were observed among the 3 groups, with differential metabolites mainly enriched in amino acid metabolism pathways. Follow-up data were available for 16 of the 22 NDMM patients, including 12 treatment responders (ND_TR group) and 4 with PRMM (ND_PR group). A total of 23 differential metabolites were identified between these 2 groups: 6 metabolites (e.g., tryptophan) were upregulated and 17 (e.g., citric acid) were downregulated in the ND_TR group. Transcriptomic data from 108 TRMM and 77 PRMM patients were analyzed to identify differentially expressed AAMGs, which were then used to construct a prediction model. The area under the receiver operating characteristic curve (AUC) for the model exceeded 0.8, and AUC values in 3 external validation cohorts were all above 0.7. This study delineated the metabolic alterations in MM patients with different treatment response, suggesting that dysregulated amino acid metabolism may be associated with poor treatment response in PRMM. By integrating metabolomics and transcriptomics, a machine learning-based predictive model was successfully established to forecast treatment response in NDMM patients.

Background The association between the serum free light chain (sFLC) ratio and the prognosis of multiple myeloma (MM) patients is controversial. Aim The purpose of this study is to explore the relationship between the sFLC ratio and the prognosis of MM patients through meta-analysis. Methods Online public databases were searched to find relevant studies. The retrieval time is limited from the establishment of the database to July 2021. The overall survival (OS) and progression-free survival (PFS) rates were compared. The results were described using hazard ratio (HR) and a 95% confidence interval (CI). Qualitative studies were also included. Results A total of 9 studies involving 2864 participants were included. A pooled analysis based on four studies including newly-diagnosed MM patients, demonstrated that an abnormal sFLC ratio was associated with poor outcomes of OS (HR = 1.82, 95% CI: 1.15–2.90) and PFS (HR = 1.87, 95% CI: 1.20–2.90). Three qualitative studies showed that an abnormal sFLC ratio was related with poor outcomes of OS (studies all included newly diagnosed MM patients) and PFS (two studies included newly-diagnosed MM patients and one study included non-newly-diagnosed MM patients). Two studies stated that the sFLC ratio is not associated with OS (both studies included non-newly-diagnosed MM patients) and one study reported that the sFLC ratio is not associated with PFS (study included non-newly-diagnosed MM patients). Conclusion sFLC ratio could be used to predict adverse outcomes in newly-diagnosed MM patients, but is not suitable for non-newly-diagnosed MM patients.

To analyze the outcomes and adverse effects of bortezomib-based regimen for the treatment of multiple myeloma (MM) patients. A total of 110 MM patients were treated with a bortezomib-based regimen at our hospital from January 2006 to February 2010. The patients over 65 years old received bortezomib-prednisone ± thalidomide (PD±T) regimen or velcade-melphalan-prednisone (VMP) regimen therapy and the patients under 65 years old or resistant to PD±T regimen received bortezomib-doxorubicin-prednisone ± thalidomide (PAD±T) regimen therapy. The outcomes and adverse effects of bortezomib-based regimen were retrospectively evaluated. There were 47 newly-diagnosed MM patients and 63 relapsing/refractory MM patients. The overall remission (OR) rate was 76.4% (84/110) and the OR rate of newly-diagnosed MM patients was statistically higher than that of relapsing/refractory MM patients (83.0% vs 71.4%, P<0.05). The complete remission (CR)+very good partial remission (VGPR) rate in group bortezomib 1.0 mg/m2 was lower than that in group bortezomib 1.3 mg/m2 (newly-diagnosed 53.6% vs 73.7%, relapsing/refractory 28.9% vs 40.0%, both P<0.05). The OR rate of ISS III stage patients was as better as that of ISS I and II stage patients (newly-diagnosed 82.1% vs 83.6%, relapsing/refractory 69.2% vs 72.2%, both P>0.05). Thirteen newly-diagnosed MM patients underwent autologous stem cell transplantation (ASCT) after induced therapy and achieved a VGPR or above. The median follow-up time was 13.0 (6.0-20.0) months. Their conditions were stable except two patients with extramedullary plasmacytoma after ASCT. Thirteen relapsing/refractory MM patients were retreated with a bortezomib-based regimen. The CR rate was 15.4% (2/13), VGPR rate was 23.1% (3/13), partial remission (PR) rate was 23.1% (3/13), OR rate 61.5% (8/13) and the median duration of remission (DOR) was 6.7 (3.0-21.0) months. Six MM patients with extramedullary plasmacytoma were treated with a bortezomib-based regimen and all of them achieved a PR or above. The median DOR was 4.5 (2.0-10.0) months. The main adverse effects were peripheral neuropathy, thrombocytopenia, neutropenia, fatigue, gastrointestinal symptoms, anemia, etc. The bortezomib-based combination regimen is the front-line therapy for newly-diagnosed and relapsing/refractory MM patients.

Multiple Myeloma with a Deletion of Chromosome 17p: TP53 Mutations Are Highly Prevalent and Negatively Affect Prognosis

Use of Anti-Infective Prophylaxis in Newly Diagnosed and Relapsed/Refractory Multiple Myeloma Patients Initiating Treatment with Daratumumab

Kinetics of Myeloid-Derived Suppressor Cells during Stem Cell Mobilization and Autologous Hematopoietic Stem Cell Transplantation in Multiple Myeloma and Lymphoma Patients

AimsTo evaluate abnormal metabolites related to treatment response and prognosis of multiple myeloma (MM) patients through ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS).MethodsForty-six symptomatic MM patients were included in this study who had a prior high level of positive monoclonal proteins before receiving targeted therapy with bortezomib-based regimens. UPLC-MS along with traditional immunofixation was performed on MM diagnostic samples and effective serum samples, and UPLC-MS was used to target valuable metabolic markers related to M protein.MM patients were segregated into pre-therapy (pre-T) and post-therapy (post-T) groups according to the response after chemotherapy. A monoclonal protein could be detected at baseline in 33 newly diagnosed MM (NDMM), 13 refractory and relapsed MM (RRMM) patients and 20 healthy controls (HC) by immunofixation.ResultsBetween pre-T and post-T patients, the data showed that 32, 28 and 3 different metabolites were significantly correlated with M protein in IgG, IgA and light chain-type MM, respectively. These identified metabolites were significantly enriched in arginine and proline metabolism as well as glycerophospholipid metabolism pathways. Among them, PC (19:0/22:2) was displayed to increase significantly and consistently with M protein in each subtype of MM after treatment, which obviously indicated that it was related to the treatment response of MM. Further survival analysis of metabolic markers found that aspartic acid, LysoPE (16:0), SM (d18:1/17:0), PC (18:0/24:1), PC (16:0/16:0), TG (18:1/18:1/22:5) and LysoPE (18:2) reaching a certain cutoff value may be associated with shorter progression free survival (PFS). Finally, Cox multivariate regression analysis identified three factors were independent prognostic factors of MM. Moreover, there were significantly different in PC (19:0/22:2) and in aspartic acid between MM patients and healthy people.ConclusionThis work identified significant metabolic disorders in 46 pairs off pre- and post-therapy MM patients, specifically in arginine, proline and glycerophospholipid pathways. The abnormal metabolites have the potential to serve as new biomarkers for evaluating treatment response and prognosis, as well as early monitoring of disease activity. Therefore, these systematic studies on abnormal metabolites as biomarkers for diagnosis and treatment will provide the evidence for future precise treatment of MM.

CRIP1 Upregulated Along with chr1q-Gain Indicates Immune Dysregulation and Portends Poor Outcomes in Multiple Myeloma

Identification of an Epithelial-to-Mesenchymal Transition (EMT)-like Programme in t(4;14)-Positive Multiple Myeloma Reveals Novel Targets for Therapeutic Intervention

High Hospital-related Costs at the End-of-life in Patients With Multiple Myeloma: A Single-center Study.

Survival of Hemodialysis-Dependent Multiple Myeloma Patients and Factors Associated with Dialysis Independence: A Real-World Study in China

The Low-Bone (LB) Subtype of Multiple Myeloma Exhibits an Inferior Outcome in African Americans

CD31 and JAM-a Expressing Circulating Tumor Plasma Cells As Prognostic Biomarkers for Multiple Myeloma Disease