Cindy Yamamoto

Development of Glomerulus-, Tubule-, and Collecting Duct-Specific mRNA Assay in Human Urinary Exosomes and Microvesicles

Urinary exosomes and microvesicles (EMV) are promising biomarkers for renal diseases. Although the density of EMV is very low in urine, large quantity of urine can be easily obtained. In order to analyze urinary EMV mRNA, a unique filter device to adsorb urinary EMV from 10 mL urine was developed, which is far more convenient than the standard ultracentrifugation protocol. The filter part of the device is detachable and aligned to a 96-well microplate format, therefore multiple samples can be processed simultaneously in a high throughput manner following the isolation step. For EMV mRNA quantification, the EMV on the filter is lysed directly by adding lysis buffer and transferred to an oligo(dT)-immobilized microplate for mRNA isolation followed by cDNA synthesis and real-time PCR. Under the optimized assay condition, our method provided comparable or even superior results to the standard ultracentrifugation method in terms of mRNA assay sensitivity, linearity, intra-assay reproducibility, and ease of use. The assay system was applied to quantification of kidney-specific mRNAs such as NPHN and PDCN (glomerular filtration), SLC12A1 (tubular absorption), UMOD and ALB (tubular secretion), and AQP2 (collecting duct water absorption). 12-hour urine samples were collected from four healthy subjects for two weeks, and day-to-day and individual-to-individual variations were investigated. Kidney-specific genes as well as control genes (GAPDH, ACTB, etc.) were successfully detected and confirmed their stable expressions through the two-week study period. In conclusion, this method is readily available to clinical studies of kidney diseases.

Bladder cancer detection by urinary extracellular vesicle mRNA analysis.

Objective Urinary extracellular vesicles (EV) could be promising biomarkers for urological diseases. In this retrospective feasibility study, we conducted biomarker screening for early stage bladder cancer using EV mRNA analysis. Methods Biomarker candidates were identified through RNA-seq analysis of urinary EV from patients with non-muscle invasive bladder cancer (N=3), advanced urothelial cancer (N=3), no residual tumor after TURBT (N=2), and healthy and disease controls (N=4). Diagnostic performance was evaluated by RT-qPCR in a larger patient group including bladder cancer (N=173), renal pelvis and ureter cancer (N=33), no residual tumor and non-cancer disease control (N=36). Results Urinary EV SLC2A1, GPRC5A and KRT17 were overexpressed in pT1 and higher stage bladder cancer by 20.6-fold, 18.2-fold and 29.5-fold, respectively. These genes allowed detection of non-muscle invasive bladder cancer (AUC: 0.56 to 0.64 for pTa, 0.62 to 0.80 for pTis, and 0.82 to 0.86 for pT1) as well as pT2 and higher muscle invasive bladder cancer (AUC: 0.72 to 0.90). Subgroup analysis indicated that these markers could be useful for the detection of cytology-negative/-suspicious and recurrent bladder cancers. Conclusion Three urinary EV mRNA were discovered to be elevated in bladder cancer. Urinary EV mRNA are promising biomarkers of urothelial cancer and worth further investigation.

Uromodulin mRNA from Urinary Extracellular Vesicles Correlate to Kidney Function Decline in Type 2 Diabetes Mellitus

Background: Extracellular vesicles (EVs) enclose mRNA derived from their cell of origin and are considered a source of potential biomarkers. We examined urinary EV mRNA from individuals with diabetic kidney disease (DKD), chronic kidney disease, type 2 diabetes (T2DM), and obese and healthy controls to determine if such biomarkers had the potential to classify kidney disease and predict patients at higher risk of renal function decline. Methods: A total of 242 participants enrolled in this study. Urinary EV mRNA from all subjects were isolated by a filter-based platform, and the expression of 8 target genes were determined by quantitative polymerase chain reaction (qPCR). Changes in estimated glomerular filtration rate (eGFR) in 161 T2DM patients were evaluated for 2 consecutive years and compared with EV RNA profiles at baseline. Results: We observe that mild and severe DKD groups show a significant 3.2- and 4.4-fold increase in UMOD compared to healthy controls and expression increases linearly from healthy, diabetic, and DKD subjects. UMOD expression is significantly correlated to albumin creatinine ratio (ACR), eGFR, and HbA1c. Using linear discriminant analyses with mRNA from severe DKD and T2DM as training data, a multi-gene signature classified DKD and non-DKD with a sensitivity of 93% and specificity of 73% with area under the receiver operating characteristic (ROC) curve (AUC) = 0.90. Although 6% of T2DM were determined to have a > 80% posterior probability of developing DKD based on this mRNA profile, eGFR changes observed within the 2-year follow-up did not reveal a decline in kidney function. Conclusion: Urinary EV UMOD mRNA levels are progressively elevated from T2DM to DKD groups and correlate with widely used eGFR and ACR diagnostic criteria. An EV mRNA signature could identify DKD with greater than 90% sensitivity and 70% specificity.

Filter-Based Extracellular Vesicle mRNA Isolation and High-Throughput Gene Expression Analysis

Extracellular vesicles (EVs) are a heterogeneous group of membrane-encapsulated particles with different ranges of size, density, and cargo. Various types of RNA including mRNA are enclosed within EVs and can serve as novel biomarkers for disease detection and patient management. Ultracentrifugation, precipitation , antibody-based capture and filter-based methods are available as in-house laboratory procedures or commercially available kits to isolate EVs. Here, we describe a filter-based method for EV mRNA isolation that is designed for parallel processing of large sample numbers.