Cell Death and Disease (Jun 2021)

Diagnostic and prognostic potential of the proteomic profiling of serum-derived extracellular vesicles in prostate cancer

  • Michele Signore,
  • Romina Alfonsi,
  • Giulia Federici,
  • Simona Nanni,
  • Antonio Addario,
  • Lucia Bertuccini,
  • Aurora Aiello,
  • Anna Laura Di Pace,
  • Isabella Sperduti,
  • Giovanni Muto,
  • Alessandro Giacobbe,
  • Devis Collura,
  • Lidia Brunetto,
  • Giuseppe Simone,
  • Manuela Costantini,
  • Lucio Crinò,
  • Stefania Rossi,
  • Claudio Tabolacci,
  • Marco Diociaiuti,
  • Tania Merlino,
  • Michele Gallucci,
  • Steno Sentinelli,
  • Rocco Papalia,
  • Ruggero De Maria,
  • Désirée Bonci

DOI
https://doi.org/10.1038/s41419-021-03909-z
Journal volume & issue
Vol. 12, no. 7
pp. 1 – 14

Abstract

Read online

Abstract Extracellular vesicles (EVs) and their cargo represent an intriguing source of cancer biomarkers for developing robust and sensitive molecular tests by liquid biopsy. Prostate cancer (PCa) is still one of the most frequent and deadly tumor in men and analysis of EVs from biological fluids of PCa patients has proven the feasibility and the unprecedented potential of such an approach. Here, we exploited an antibody-based proteomic technology, i.e. the Reverse-Phase Protein microArrays (RPPA), to measure key antigens and activated signaling in EVs isolated from sera of PCa patients. Notably, we found tumor-specific protein profiles associated with clinical settings as well as candidate markers for EV-based tumor diagnosis. Among others, PD-L1, ERG, Integrin-β5, Survivin, TGF-β, phosphorylated-TSC2 as well as partners of the MAP-kinase and mTOR pathways emerged as differentially expressed endpoints in tumor-derived EVs. In addition, the retrospective analysis of EVs from a 15-year follow-up cohort generated a protein signature with prognostic significance. Our results confirm that serum-derived EV cargo may be exploited to improve the current diagnostic procedures while providing potential prognostic and predictive information. The approach proposed here has been already applied to tumor entities other than PCa, thus proving its value in translational medicine and paving the way to innovative, clinically meaningful tools.