Integrated Urinary and Tissue Proteomic Signatures Reveal Core and Progression Biomarkers in MRI-Visible and...

Background: Prostate cancer (PCa) shows a marked biological heterogeneity that is closely associated with tumor aggressiveness. A substantial proportion of clinically significant tumors remain undetected by multiparametric magnetic resonance imaging (mpMRI). Elucidating the molecular basis of MRI visibility and identifying non-invasive biomarkers could improve the risk stratification and clinical management of patients. Accordingly, this study aimed to assess tissue and urine proteomic signatures associated with PCa aggressiveness and mpMRI visibility. Methods: In this exploratory study, we performed an integrated proteomic analysis of prostate tissue and preoperative urine samples from 24 patients stratified into four groups: benign prostatic hyperplasia (BPH), indolent PCa (Gleason 6), clinically significant PCa with MRI-visible lesions, and clinically significant PCa with MRI-non-visible lesions. Data-independent acquisition mass spectrometry (DIA workflows) was used to identify differentially expressed proteins associated with malignancy, tumor aggressiveness, and MRI visibility. Results: Pairwise proteomic analyses revealed significant molecular differences between BPH and all PCa groups, identifying 694 non-redundant proteins differentially expressed in tissue and 482 in preoperative urine, showing molecular features associated with both disease presence and progression. Comparative tissue and urine analyses identified 82 proteins, reflecting shared biological pathways in metabolism, cytoskeletal organization, immune processes, and extracellular matrix remodeling. Finally, a direct comparison of MRI-visible and MRI-non-visible clinically significant PCa identified a panel of differentially expressed proteins, including LCN2/NGAL, S100A9, and AOC1/DAO, that showed differential urinary abundance and prognostic relevance in the TCGA-PRAD cohort. Conclusions: Our results suggest that proteomic alterations in PCa are associated with disease progression and aggressiveness and capture biologically relevant differences between tissue and urinary proteomes. These differences are also observed between MRI-visible and MRI-non-visible clinically significant prostate cancers, supporting the potential of urinary proteomics as a non-invasive complement to imaging-based diagnostics.