Dataset Information

Optimization of small extracellular vesicle isolation from expressed prostatic secretions in urine for in-depth proteomic analysis

ABSTRACT: Label-free quantitative proteomics was employed to compare the protein content of extracellular vesicles isolated by various differential centrifugation-based approaches from expressed prostatic secretions in urine (EPS-urine) from men with prostate cancer. The developed optimized approach improved EV purity by depleting the high-abundance urine protein Tamm-Horsfall protein (THP) and other common contaminants and achieved relative enrichment of prostate cancer-associated EV-resident proteins.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Urine

DISEASE(S): Prostate Cancer

SUBMITTER: Vanessa Correll

LAB HEAD: O. John Semmes

PROVIDER: PXD026974 | Pride | 2022-02-09

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	MaxQuant_results_txt_zipped.zip	Other
	vlc_10182019_DDA_2ug_UEPSExo_DTTALK_1.raw	Raw
	vlc_10182019_DDA_2ug_UEPSExo_DTTALK_2.raw	Raw
	vlc_10182019_DDA_2ug_UEPSExo_DTTALK_3.raw	Raw
	vlc_10182019_DDA_2ug_UEPSExo_DTTPBS_1.raw	Raw

Items per page:

1 - 5 of 10

Publications

Optimization of small extracellular vesicle isolation from expressed prostatic secretions in urine for in-depth proteomic analysis.

Correll Vanessa L VL Otto Joseph J JJ Risi Cristina M CM Main Brian P BP Boutros Paul C PC Kislinger Thomas T Galkin Vitold E VE Nyalwidhe Julius O JO Semmes O John OJ Yang Lifang L

Journal of extracellular vesicles 20220201 2

The isolation and subsequent molecular analysis of extracellular vesicles (EVs) derived from patient samples is a widely used strategy to understand vesicle biology and to facilitate biomarker discovery. Expressed prostatic secretions in urine are a tumor proximal fluid that has received significant attention as a source of potential prostate cancer (PCa) biomarkers for use in liquid biopsy protocols. Standard EV isolation methods like differential ultracentrifugation (dUC) co-isolate protein co ...[more]

PMID: 35119778

Similar Datasets

Project description:Objectives: Secretion of extracellular vesicles (EV) and associated micro-RNAs (miR) is altered during cellular stress and may serve as biomarkers of organ injury. We hypothesized that measuring changes in urinary levels of EV and miR will predict the onset of acute kidney injury in cardiac surgery patients. Design: Predictive accuracy biomarker study performed in the cohort of the REVAKI-2 trial Setting: Single center ICU between September 2015 and September 2018 Interventions: Intravenous sildenafil citrate 12.5 mg kg-1 over 150 min or dextrose 5% at the commencement of surgery. Measurements and main results: Urine samples were collected before and 24 hours after the procedure from 93 cardiac surgery patients. Urine EV concentrations and size distribution were assessed using NanoSight. EV derivation and levels were measured using flow cytometry. Samples from 10 selected patients were sequenced to detect differentially expressed miR. Verification was performed with advanced TaqMan assays in samples from all patients. Urine EV concentrations significantly increased in patients with AKI after surgery, with the percentage of EV positive for aquaporin-2 and β1-integrin also increasing. Pre surgery podocalyxin-positive EV were significantly lower, and β1-integrin EV werehigher in patients with AKI. The levels of the former correlated with the severity of theinjury. miR-125a-5p was expressed at higher levels in urine from patients with AKI stage 2/3. Levels of miR-10a-5p decreased after surgery in AKI patients; its levels correlated with the severity of the injury. Preoperative levels of podocalyxin EVs and miR-125a-5p had moderate AKI predictive value and, in a logistic model together with ICU lactate levels, offered good (AUC = 80.9%) AKI prediction. Conclusions: Lower levels of podocalyxin-positive EV at baseline predict the severity of post-surgery AKI. Urine EV concentrations and miR expression offer excellent predictive accuracy when combined with commonly measured biomarkers.