Multiple myeloma is a plasma cell malignancy characterized by an abnormal increase in monoclonal immunoglobulins. Despite significant advances in treatment, some patients progress to more aggressive forms of multiple myeloma, including extramedullary disease or plasma cell leukemia. Although the exact molecular mechanisms are not known, several studies have confirmed the involvement of small extracellular vesicle-enriched microRNAs in multiple myeloma progression. Therefore, we performed expression profiling of these molecules in bone marrow plasma of multiple myeloma, extramedullary disease, and plasma cell leukemia patients using small RNA sequencing to identify novel molecules involved in disease pathogenesis. In total, 42 microRNAs were significantly dysregulated among analyzed subgroups. Independent validation by RT-qPCR confirmed elevated levels of miR-140-3p, miR-584-5p, miR-191-5p, and miR-143-3p in multiple myeloma patients compared to extramedullary disease and plasma cell leukemia patients. Subsequent statistical analysis revealed significant correlations between patient clinical characteristics or flow cytometry parameters and microRNA expression. These results indicate that dysregulation of microRNAs could contribute to multiple myeloma progression.

• Keywords
• extramedullary disease, microRNAs, multiple myeloma, plasma cell leukemia, small RNA sequencing, small extracellular vesicles,
• MeSH
• Adult MeSH
• Extracellular Vesicles * metabolism   genetics   pathology   MeSH
• Bone Marrow * pathology   metabolism   MeSH
• Middle Aged MeSH
• Humans MeSH
• MicroRNAs * genetics   MeSH
• Multiple Myeloma * genetics   pathology   metabolism   MeSH
• Biomarkers, Tumor genetics   MeSH
• Plasma Cells metabolism   MeSH
• Leukemia, Plasma Cell * genetics   pathology   metabolism   MeSH
• Aged MeSH
• Gene Expression Profiling MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• MicroRNAs * MeSH
• Biomarkers, Tumor MeSH

Multiple myeloma (MM) is the second most prevalent hematological malignancy, characterized by infiltration of the bone marrow by malignant plasma cells. Extramedullary disease (EMD) represents a more aggressive condition involving the migration of a subclone of plasma cells to paraskeletal or extraskeletal sites. Liquid biopsies could improve and speed diagnosis, as they can better capture the disease heterogeneity while lowering patients' discomfort due to minimal invasiveness. Recent studies have confirmed alterations in the proteome across various malignancies, suggesting specific changes in protein classes. In this study, we show that MALDI-TOF mass spectrometry fingerprinting of peripheral blood can differentiate between MM and primary EMD patients. We constructed a predictive model using a supervised learning method, partial least squares-discriminant analysis (PLS-DA) and evaluated its generalization performance on a test dataset. The outcome of this analysis is a method that predicts specifically primary EMD with high sensitivity (86.4%), accuracy (78.4%), and specificity (72.4%). Given the simplicity of this approach and its minimally invasive character, this method provides rapid identification of primary EMD and could prove helpful in clinical practice.

• Keywords
• Extramedullary disease, Liquid biopsy, MALDI-TOF mass spectrometry, Machine learning, Multiple myeloma, Partial least squares-discriminant analysis, Principal component analysis,
• MeSH
• Middle Aged MeSH
• Humans MeSH
• Multiple Myeloma * blood   diagnosis   MeSH
• Biomarkers, Tumor blood   MeSH
• Aged MeSH
• Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization methods   MeSH
• Liquid Biopsy methods   MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Biomarkers, Tumor MeSH

Extramedullary multiple myeloma (EMM) is an aggressive form of multiple myeloma (MM). This study represents the most comprehensive next-generation sequencing analysis of EMM tumors (N = 14) to date, uncovering key molecular features and describing the tumor microenvironment. We observed the co-occurrence of 1q21 gain/amplification and MAPK pathway mutations in 79% of EMM samples, suggesting that these are crucial mutational events in EMM development. We also demonstrated that patients with mutated KRAS and 1q21 gain/amplification at the time of diagnosis have a significantly higher risk of EMM development (HR = 2.4, p = 0.011) using data from a large CoMMpass dataset. We identified downregulation of CXCR4 and enhanced cell proliferation, along with reduced expression of therapeutic targets (CD38, SLAMF7, GPRC5D, FCRH5), potentially explaining diminished efficacy of immunotherapy. Conversely, we identified significantly upregulated EZH2 and CD70 as potential future therapeutic options. For the first time, we report on the tumor microenvironment of EMM, revealing CD8+ T cells and NK cells as predominant immune effector cells using single-cell sequencing. Finally, this is the first longitudinal study in EMM revealing the molecular changes from the time of diagnosis to EMM relapse.

• MeSH
• Bone Marrow pathology   MeSH
• Middle Aged MeSH
• Humans MeSH
• Multiple Myeloma * genetics   pathology   MeSH
• Mutation MeSH
• Biomarkers, Tumor genetics   MeSH
• Tumor Microenvironment * genetics   MeSH
• Prognosis MeSH
• Aged MeSH
• High-Throughput Nucleotide Sequencing * MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Biomarkers, Tumor MeSH

Extramedullary multiple myeloma (EMD) is an aggressive disease; malignant plasma cells lose their dependence in the bone marrow microenvironment and migrate into tissues. EMD is a negative prognostic factor of survival. Using flow cytometry and next-generation sequencing, we aimed to identify antigens and microRNAs (miRNAs) involved in EMD pathogenesis. Flow cytometry analysis revealed significant differences in the level of clonal plasma cells between MM and EMD patients, while the expression of CD markers was comparable between these two groups. Further, miR-26a-5p and miR-30e-5p were found to be significantly down-regulated in EMD compared to MM. Based on the expression of miR-26a-5p, we were able to distinguish these two groups of patients with high sensitivity and specificity. In addition, the involvement of deregulated miRNAs in cell cycle regulation, ubiquitin-mediated proteolysis and signaling pathways associated with infections or neurological disorders was observed using GO and KEGG pathways enrichment analysis. Subsequently, a correlation between the expression of analyzed miRNAs and the levels of CD molecules was observed. Finally, clinicopathological characteristics as well as CD antigens associated with the prognosis of MM and EMD patients were identified. Altogether, we identified several molecules possibly involved in the transformation of MM into EMD.

• Keywords
• NGS, bioinformatics, immunophenotyping, microRNA, multiple myeloma,
• MeSH
• Humans MeSH
• MicroRNAs * genetics   MeSH
• Multiple Myeloma * genetics   MeSH
• Tumor Microenvironment MeSH
• High-Throughput Nucleotide Sequencing MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• MicroRNAs * MeSH

In multiple myeloma (MM), malignant plasma cells infiltrate the bone marrow. In some cases, plasma cells migrate out of the bone marrow creating either para-skeletal plasmacytomas (PS) or infiltrating soft tissues as extramedullary plasmacytomas (EMD). The aim of this study was to define risk groups in newly diagnosed MM (NDMM) patients with PS and EMD plasmacytomas. In total, 523 NDMM patients with PS plasmacytomas and 196 NDMM patients with EMD plasmacytomas were diagnosed in the Czech Republic between 2004 and 2021 using modern imaging methods. Patients’ data were analyzed from the Registry of Monoclonal Gammopathies of the Czech Myeloma Group. In NDMM patients with PS plasmacytomas, we found a subgroup with <5% of bone-marrow plasma cells to have the best prognosis (mPFS: 58.3 months (95% CI: 33.0−NA); mOS: not reached). The subgroup with >5% of bone-marrow plasma cells and ≥3 plasmacytomas had the worst prognosis (mPFS: 19.3 months (95% CI: 13.4−28.8), p < 0.001; mOS: 27.9 months (95% CI: 19.3−67.8), p < 0.001). Our results show association between tumor burden and prognosis of NDMM patients with plasmacytomas. In the case of PS plasmacytomas, NDMM patients with low BM PC infiltration have an excellent prognosis.

• Keywords
• multiple myeloma, plasmacytomas, risk factors, survival,
• Publication type
• Journal Article MeSH