Multiple myeloma (MM) is a highly heterogeneous disease of malignant plasma cells. Diagnosis and monitoring of MM patients is based on bone marrow biopsies and detection of abnormal immunoglobulin in serum and/or urine. However, biopsies have a single-site bias; thus, new diagnostic tests and early detection strategies are needed. Matrix-Assisted Laser Desorption/Ionization Time-of Flight Mass Spectrometry (MALDI-TOF MS) is a powerful method that found its applications in clinical diagnostics. Artificial intelligence approaches, such as Artificial Neural Networks (ANNs), can handle non-linear data and provide prediction and classification of variables in multidimensional datasets. In this study, we used MALDI-TOF MS to acquire low mass profiles of peripheral blood plasma obtained from MM patients and healthy donors. Informative patterns in mass spectra served as inputs for ANN that specifically predicted MM samples with high sensitivity (100%), specificity (95%) and accuracy (98%). Thus, mass spectrometry coupled with ANN can provide a minimally invasive approach for MM diagnostics.

Babak Myeloma Group Department of Pathological Physiology Faculty of Medicine Masaryk University Brno Czech Republic

Department of Chemistry Analytical Chemistry Division Faculty of Science University of La Laguna La Laguna Spain

Department of Chemistry Faculty of Science Masaryk University Brno Czech Republic

Department of Chemistry Faculty of Science University of Girona Girona Spain

Department of Clinical Hematology University Hospital Brno Brno Czech Republic

Department of Histology and Embryology Faculty of Medicine Masaryk University Brno Czech Republic

Department of Internal Medicine Hematology and Oncology University Hospital Brno Brno Czech Republic

Experimental Neurophysiology and Clinical Anatomy Department of Medical Sciences University of Girona Girona Spain

International Clinical Research Center St Anne's University Hospital Brno Czech Republic

Research Group of Clinical Anatomy Embryology and Neuroscience Department of Medical Sciences University of Girona Girona Spain

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