Journal Article Preprint Epublish
PubMed: 42818596 DOI: 10.64898/2026.09.03.747025
The RNA cargo of plasma-derived extracellular vesicles in mCRPC patients captures cancer cells and tumor microenvironment signals.
bioRxiv
Authors: Federico Vannuccini, Yari Ciani, Vera Mugoni, Orsetta Quaini, Francesco Orlando, Veronica Weber, Ariadna Camacho Martinez, Angela Martinelli, Elisa Biada, Alessia Marinelli, Irene Casanova-Salas, Fabio Pessina, Dolores Di Vizio, Alessandro Vannini, Paolo Cremaschi, Stefano Lise, Caterina Nardella, Ugo De Giorgi, Consuelo Buttigliero, Orazio Caffo, Umberto Basso, Joaquin Mateo, Gerhardt Attard, Francesca Demichelis
Abstract
UNLABELLED
Circulating analytes in cancer patients capture tumor-related signals. We profiled matched extracellular vesicle (EV) total RNA and cell-free DNA (cfDNA) from the same plasma aliquots of chemo-naive metastatic castration-resistant prostate cancer (mCRPC) patients treated with Enzalutamide (n=54 patients, n=119 longitudinal samples; NCT06981377 ) at four Italian clinical centers and interrogated data from >10,000 cancer patients' and healthy individuals' samples. Transcript integrity analysis identified coding and non-coding species with fragmentation patterns varying across RNA biotypes. EV-RNA data deconvolution revealed signal from immune populations, including fractions classified as CD4+ T cells, whose abundance increased with disease progression in plasma EVs and mCRPC tissues. By leveraging tissue data-informed mining, we established a novel prostate cancer-related EV-RNA signature that resulted in an independent predictor of poor prognosis and captured tumor microenvironment-derived signals. Integrating EV-RNA and ctDNA information improved patient stratification for progression-free survival. These findings suggest a multifaceted role for plasma EVs as a source of cancer biomarkers.
STATEMENT OF SIGNIFICANCE
EV-RNA provides biologically relevant tumor and immune-derived signals in mCRPC. Integration with cfDNA improves patient stratification, highlighting EVs as a complementary source of translational information for monitoring disease progression and therapeutic response in prostate cancer.
MeSH
Cells, Extracellular Vesicles, Neoplasms, Disease Progression, Prostate, Prostatic Neoplasms, Tissues, Tumor Microenvironment, Plasma