# Exploiting Urine Derived DNA for the Assessment of Bladder Cancer using High Accuracy Sequencing

> **NIH NIH R21** · UNIVERSITY OF WASHINGTON · 2021 · $181,741

## Abstract

PROJECT SUMMARY
 Many attempts have been made to develop urine-based biomarkers for bladder cancer surveillance and
monitoring. However, the most widely used approach, urine cytology, is most effective for high-grade lesions. To
date, none of the current FDA-approved tests have been widely adopted due to low sensitivities (55%–70%) and
specificities (71%–83%). Performance is poor for low-grade tumors due to the low abundance of aneuploid cells
and high levels of interobserver variability. Previous studies identified several recurrently mutated genes
occurring in 70-80% of both muscle invasive and non-muscle invasive bladder cancers (MIBC and NMIBC,
respectively). Detection of these mutations could help in early cancer detection, initial stratification for treatment
options, detection of minimal residual disease, or identification of emerging chemotherapy resistance. As with
most other solid cancers, accessing tumor tissue either by biopsy or surgical resection is often limited or
unobtainable. Furthermore, these characteristically small samples are not necessarily representative of the entire
tumor. For this reason, tumor cells and/or DNA shed into the urine holds the promise of yielding detailed genetic
information about a tumor using a simple, non-invasive, urine test. The advent of next-generation sequencing
(NGS) has opened up the possibility of clinically exploiting DNA as a cancer monitoring analyte. However, high
error rates of NGS has proven to be a major impediment for using this technology for low frequency variant
detection. To overcome this limitation, we have previously developed Duplex Sequencing (Duplex-Seq). Using
this technique we can detect a single variants present in ~5x107 wild-type bases. We hypothesize that
assessment of urine derived DNA (uDNA) by Duplex-Seq will perform better than urine cytology or conventional
NGS-based approaches for detecting post-treatment residual cancer. Such information would eventually be used
in determining treatment response and clinical decision making. We propose to develop and validate the use of
Duplex-Seq for use in frequently encountered clinical scenarios, as well as in normal, cancer free, individuals. In
Specific Aim 1, we will determine the biological occurrence of bladder cancer-associated mutations in normal
individuals and establish age-defined thresholds across several different frequently mutated genes. In Specific
Aim 2, we will determine if the presence or absence of NMIBC tumor mutations in uDNA is predictive of
recurrence at the conclusion of intravesical BCG therapy, potentially reducing the need for repeated and
unpleasant cystoscopies.

## Key facts

- **NIH application ID:** 10197377
- **Project number:** 1R21CA259780-01
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Scott Robert Kennedy
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $181,741
- **Award type:** 1
- **Project period:** 2021-04-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10197377

## Citation

> US National Institutes of Health, RePORTER application 10197377, Exploiting Urine Derived DNA for the Assessment of Bladder Cancer using High Accuracy Sequencing (1R21CA259780-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10197377. Licensed CC0.

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