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Technical Improvement of Urinary Extracellular Vesicles Isolation and Extraction of RNA for an Early Prediction of Cisplatin-induced Acute Kidney Injury

Presenters Name: 
Brandon Cho
Co Presenters Name: 
Primary Research Mentor: 
Uta Erdbruegger
Secondary Research Mentor: 
Luca Musante
2:00 - 3:15
Time of Presentation: 
2019 - 2:00pm to 3:15pm
Newcomb Hall Ballroom
Presentation Type: 
Presentations Academic Category: 
Grant Program Recipient: 
USOAR Program

Acute kidney injury (AKI) is a condition in which the kidney experiences a sudden loss of function, and is associated with increased mortality. Many cancer patients develop AKI as a common complication of Cisplatin, an effective chemotherapeutic drug in the treatment of about 20% of cancer patients. Unfortunately, Cisplatin causes AKI in up to 30% of patients, and predictive early biomarkers are necessary. Extracellular vesicles (EVs) are secreted from cells and have been proposed as candidate biomarkers for early and non-invasive diagnosis of AKI. EVs can be found in different body fluids, including urine. EV content consists of proteins, lipids, and genetic information, such as DNA and non-coding RNAs, such as miRNAs. Non-protein coding miRNAs play an active role in almost all cellular processes, making them of particular interest. One major goal of this project is to simplify collection methods for EV biomarker research and to optimize RNA extraction from urinary EVs of patients receiving Cisplatin. Our preliminary results show that 500ul of concentrated urinary EV volume used for miRNA isolation is optimal, and also, that the use of a reducing agent, such as B-mercaptoethanol, further improves miRNA yield. Additionally, comparative analysis of differential centrifugation protocol and hydrostatic filtration dialysis (HFD) EV isolation methods shows that HFD yields the most miRNAs in a relatively fast and comprehensive way. The exploration and investigation of urinary EV miRNAs as biomarkers in Cisplatin-induced AKI will further improve the understanding of drug-induced AKI, and innovate the field by providing effective, non-invasive biomarker identification methods.