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Liquid biopsy of peripheral blood using mass spectrometry detects primary extramedullary disease in multiple myeloma patients

M. Vlachová, L. Pečinka, J. Gregorová, L. Moráň, T. Růžičková, P. Kovačovicová, M. Almáši, L. Pour, M. Štork, R. Hájek, T. Jelínek, T. Popková, M. Večeřa, J. Havel, P. Vaňhara, S. Ševčíková

. 2024 ; 14 (1) : 18777. [pub] 20240813

Language English Country England, Great Britain

Document type Journal Article

Persistent link   https://www.medvik.cz/link/bmc24019344

Grant support
NU21-03-00076 Ministerstvo Zdravotnictví Ceské Republiky
MUNI/A/1587/2023 Masarykova Univerzita
LX22NPO5102 Next generation EU
CZ.02.01.01/00/22_008/0004644 Ministerstvo skolstvi, mladeze a telovychovy

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.

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$a 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.
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