Identifies urinary peptides as biomarkers for detecting multiple myeloma, suggesting non-invasive diagnosis methods.
Multiple myeloma (MM) evolves from monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM) with annual progression rates of 1% and 10%, respectively. Current risk models don't fully capture the underlying dynamic molecular processes. We hypothesized that urinary peptides reflect disease-specific microenvironmental alterations in plasma cell dyscrasias. To test this hypothesis, capillary electrophoresis coupled to mass spectrometry (CE-MS) was applied to profile the urinary peptidome of 314 individuals, including a discovery group (42 MGUS, 27 SMM, 14 MM), an independent validation group (45 MGUS, 9 SMM, 7 MM, 9 with plasmacytoma), 86 without underlying malignancy, and 75 patients with impaired kidney function. One hundred twenty-one peptides were significantly altered between MM and MGUS and displayed a monotonic abundance trend across the MGUS-SMM-MM continuum. These peptides predominantly derived from collagens, beta-2 microglobulin, alpha-1 antitrypsin, and antithrombin-III. Integration of these 121 peptides into a support vector machine classifier achieved an area under the curve of 0.94 (0.85-0.99; 95% CI) in the independent validation cohort, with 100% sensitivity and 82% specificity for MM detection. The finding that urinary peptides enable non-invasive molecular discrimination of MM from precursor states represents a solid basis for a prospective evaluation in prognosis and detection of progression.
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Frantzi et al. (2026) studied this question.
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