posted on 2023-11-24, 00:55authored byLukáš Pečinka, Monika Vlachová, Lukáš Moráň, Jana Gregorová, Volodymyr Porokh, Petra Kovačovicová, Martina Almáši, Luděk Pour, Martin Štork, Josef Havel, Sabina Ševčíková, Petr Vaňhara
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.