ABSTRACT
Monoclonal gammopathies are a group of blood diseases characterized by presence of abnormal immunoglobulins in peripheral blood and/or urine of patients. Multiple myeloma and plasma cell leukemia are monoclonal gammopathies with unclear etiology, caused by malignant transformation of bone marrow plasma cells. Mass spectrometry with matrix-assisted laser desorption/ionization and time-of-flight detection is commonly used for investigation of the peptidome and small proteome of blood plasma with high accuracy, robustness, and cost-effectivity. In addition, mass spectrometry coupled with advanced statistics can be used for molecular profiling, classification, and diagnosis of liquid biopsies and tissue specimens in various malignancies. Despite the fact there have been fully optimized protocols for mass spectrometry of normal blood plasma available for decades, in monoclonal gammopathy patients, the massive alterations of biophysical and biochemical parameters of peripheral blood plasma often limit the mass spectrometry measurements. In this paper, we present a new two-step extraction protocol and demonstrated the enhanced resolution and intensity (>50×) of mass spectra obtained from extracts of peripheral blood plasma from monoclonal gammopathy patients. When coupled with advanced statistics and machine learning, the mass spectra profiles enabled the direct identification, classification, and discrimination of multiple myeloma and plasma cell leukemia patients with high accuracy and precision. A model based on PLS-DA achieved the best performance with 71.5% accuracy (95% confidence interval, CI = 57.1-83.3%) when the 10× repeated 5-fold CV was performed. In summary, the two-step extraction protocol improved the analysis of monoclonal gammopathy peripheral blood plasma samples by mass spectrometry and provided a tool for addressing the complex molecular etiology of monoclonal gammopathies.
Subject(s)
Leukemia, Plasma Cell , Multiple Myeloma , Paraproteinemias , Humans , Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization/methods , Multiple Myeloma/diagnosis , Paraproteinemias/diagnosis , PlasmaABSTRACT
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.
