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Cancer cell-derived EVs have been the main object of an extensive investigation in the field because they carry cancer-specific molecular cargo and can promote cancer progression. Cancer-derived EVs include populations of atypically large EVs (L-EVs), which have been referred to as tumor microvesicles, large oncosomes, or simply L-EVs. While small EVs (S-EVs), which include exosomes, have been investigated by a plethora of reports, little is known about L-EVs. The paucity of studies comparing protein cargo of L- and S-EVs and studies focusing on protein-coding RNA, and the absence of integrative analyses to compare the protein and gene expression in different EV fractions, prompted us to perform mass spectrometry to profile three different, size-based EV fractions generated by three cancer cell models (glioma, prostate and breast cancer). We identified protein signatures for L- and S-EVs either common to all cell types or specific to each of them individually. The proteins enriched in prostate cancer cell-derived L-EVs were also identified in L-EVs from patients with metastatic prostate cancer by a SWATH proteomic assay. We also performed RNA-Seq on the prostate cancer model and integrated proteomic and transcriptomic datasets. GSEA revealed that mitochondrial function was enriched in L-EVs versus S-EVs at both the RNA and protein level. The mitochondrial signature at the transcriptome level was confirmed by single cell RNA-Seq of L- EVs in vitro. The integrated L-EV proteomic and transcriptomic signature enabled distinction between benign and localized prostate cancer, as well as between localized cancer and metastatic castration-resistant cancer. Overall design: Extracellular vesicle (EV) isolation was performed using a PC3 cell line at three different centrifugations</long_description><repository>ENA</repository></additional><is_claimable>false</is_claimable><name>Whole proteome and transcriptome analysis of cancer-derived EVs overlap in specific pathways and distinct EV population</name><description>Whole proteome and transcriptome analysis of cancer-derived EVs overlap in specific pathways and distinct EV population</description><dates><last_updated>2025-09-24</last_updated><first_public>2025-04-25</first_public></dates><accession>PRJNA887099</accession><cross_references><GEO>GSE214804</GEO><taxon>9606</taxon></cross_references></HashMap>