Rapid discrimination of multiple myeloma patients by artificial neural networks coupled with mass spectrometry of peripheral blood plasma.

Journal: Scientific reports
PMID: 31138828

Abstract

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.

Authors

  • Meritxell Deulofeu
    Department of Histology and Embryology, Faculty of Medicine, Masaryk University, Brno, Czech Republic.
  • Lenka Kolářová
    Department of Chemistry, Faculty of Science, Masaryk University, Brno, Czech Republic.
  • Victoria Salvadó
    Department of Chemistry, Faculty of Science, University of Girona, Girona, Spain.
  • Eladia María Peña-Méndez
    Department of Chemistry, Analytical Chemistry Division, Faculty of Science, University of La Laguna, La Laguna, Spain.
  • Martina Almáši
    Department of Clinical Hematology, University Hospital Brno, Brno, Czech Republic.
  • Martin Štork
    Department of Internal Medicine, Hematology and Oncology, University Hospital Brno, Brno, Czech Republic.
  • Luděk Pour
    Department of Internal Medicine, Hematology and Oncology, University Hospital Brno, Brno, Czech Republic.
  • Pere Boadas-Vaello
    Research Group of Clinical Anatomy, Embryology and Neuroscience (NEOMA), Department of Medical Sciences, University of Girona, Girona, Spain.
  • Sabina Ševčíková
    Babak Myeloma Group, Department of Pathological Physiology, Faculty of Medicine, Masaryk University, Brno, Czech Republic.
  • Josef Havel
    Department of Chemistry, Faculty of Science, Masaryk University, Brno, Czech Republic.
  • Petr Vaňhara
    Department of Histology and Embryology, Faculty of Medicine, Masaryk University, Brno, Czech Republic.

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