Authors
Natalia Platonova, Gilda Aiello, Domenica Ronchetti, Valentina Citro, Rosanna Asselta, Lavinia Casati, Domenica Giannandrea, Elisa Taiana, Antonino Neri, Gloria Sini, Elisabetta Calzavara, Mauro Turrini, Alfonsina D'Amato, Raffaella Chiaramonte
Published in
Cancer science. Jul 16, 2026. Epub Jul 16, 2026.
Abstract
Despite therapeutic advances, multiple myeloma (MM) remains characterized by progression and relapse, underscoring the need for reliable biomarkers for early detection and monitoring. Extracellular vesicles (EV) are cell-derived, lipid bilayer-enclosed particles that mediate intercellular communication and circulate in body fluids, making them promising biomarkers. This study compares the proteome of MM-derived EV with parental cells and evaluates whether EV represent a superior source of MM-specific biomarkers. We used high-resolution mass spectrometry to analyze MM cell lines and their EV. Cell line-derived EV offer a cleaner, tumor-specific protein profile, minimizing background from nonmalignant cells and improving biomarker accuracy. MS datasets were subjected to bioinformatic analysis, followed by functional enrichment using gene set libraries such as Gene Ontology, Jensen Compartments, TRRUST and DisGeNET, to extend interpretation beyond limited protein databases. Compared to cellular proteins, the EV proteome was enriched in functions related to oncogenic signaling, transcriptional regulation and MM pathophysiology, strengthening its potential as a cancer-related biomarker source. DisGeNET identified cancer-related proteins that were further evaluated to identify MM-specific candidates analyzing MM patients' gene expression databases containing clinical data. This led to the identification of macrophage migration inhibitory factor (MIF) and prohibitin. ELISA on plasma from MM patients detected significantly increased MIF levels in smoldering and active MM compared with healthy donors. Approximately half of circulating MIF was EV-associated in MM patients, indicating that MIF is distributed between vesicular and soluble plasma fractions and underscoring its potential as a noninvasive biomarker for MM early detection and patient monitoring.
PMID:
42460505
Bibliographic data and abstract were imported from PubMed on 16 Jul 2026.
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