Project description:Intra-individual stability of the urine miRNA transcriptome was examined by investigating longitudinal changes over time in a cohort of patients with localized prostate cancer. Using training and validation cohorts, urinary miRNA biomarkers are characterized and validated their utility to identify aggressive prostate cancer.
Project description:Intra-individual stability of the urine miRNA transcriptome was examined by investigating longitudinal changes over time in a cohort of patients with localized prostate cancer. Using training and validation cohorts, urinary miRNA biomarkers are characterized and validated their utility to identify aggressive prostate cancer.
Project description:Intra-individual stability of the urine miRNA transcriptome was examined by investigating longitudinal changes over time in a cohort of patients with localized prostate cancer. Using training and validation cohorts, urinary miRNA biomarkers are characterized and validated their utility to identify aggressive prostate cancer.
Project description:RNA sequencing study on prostate cancer (PRC) cohort for small RNA characterization across biofluids, tissue types and isolation techniques.
Project description:Background: New molecular biomarkers for prostate cancer (PC) prognosis are urgently needed. Ratio-based models are attractive, as they require no additional normalization. Here, we train and independently validate a novel 4-miRNA prognostic ratio model for PC. Patients and methods: By genome-wide miRNA expression profiling of PC tissue samples from 123 men who underwent radical prostatectomy (RP) (PCA123, training cohort), we identified six top candidate prognostic miRNAs and systematically tested their ability to predict post-operative biochemical recurrence (BCR). The best miRNA-based prognostic ratio model (MiCaP) was validated in two independent cohorts (PCA352 and PCA476) including >800 RP patients in total. Clinical endpoints were BCR and prostate cancer-specific survival (CSS). The prognostic potential of MiCaP was assessed by univariate and multivariate Cox-regression analyses and Kaplan-Meier analyses. Results: We identified a 4-miRNA ratio model, MiCaP (miR-23a-3p×miR-10b-5p)/(miR-133a×miR-374b-5p), that predicted time to BCR independently of routine clinicopathological variables in the training cohort (PCA123) and was successfully validated in two independent RP cohorts. In addition, MiCaP was a significant predictor of CSS in univariate analysis (HR 3·35 [95% CI 1·34 – 8·35], P=0·0096) and in multivariate analysis (HR 2·43 [95% CI 1·45 – 4·07], P=0·0210). Limitations include low mortality rates (CSS: 5.4%). Conclusions: We identified a novel 4-miRNA ratio model (MiCaP) with significant independent prognostic value in three RP cohorts, indicating promising potential to improve PC risk stratification.
Project description:Here, we introduce a magnetic bead-based EV enrichment approach (EVrich) for automated and high-throughput processing of urine samples. Parallel enrichments can be performed in 96-well plates for downstream cargo analysis, including EV characterization, miRNA, proteomics and phosphoproteomics analysis. We applied the instrument to a cohort of clinical urine samples to achieve reproducible identification of over 47,562 unique EV peptides and 4,327 EV proteins in each one-ml urine sample. Quantitative phosphoproteomicsrevealed 186 unique phosphopeptides corresponding to 77 proteins that were significantly elevated in prostate cancer patients.