Accurate Detection of Urothelial Bladder Cancer Using Targeted Deep Sequencing of Urine DNA

Dongin Lee, Wookjae Lee, Hwang Phill Kim, Myong Kim, Hyun Kyu Ahn, Duhee Bang, Kwang Hyun Kim

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Patients with hematuria are commonly given an invasive cystoscopy test to detect bladder cancer (BC). To avoid the risks associated with cystoscopy, several urine-based methods for BC detection have been developed, the most prominent of which is the deep sequencing of urine DNA. However, the current methods for urine-based BC detection have significant levels of false-positive signals. In this study, we report on uAL100, a method to precisely detect BC tumor DNA in the urine without tumor samples. Using urine samples from 43 patients with BC and 21 healthy donors, uAL100 detected BC with 83.7% sensitivity and 100% specificity. The mutations identified in the urine DNA by uAL100 for BC detection were highly associated with BC tumorigenesis and progression. We suggest that uAL100 has improved accuracy compared to other urine-based methods for early BC detection and can reduce unnecessary cystoscopy tests for patients with hematuria.

Original languageEnglish
Article number2868
JournalCancers
Volume15
Issue number10
DOIs
StatePublished - May 2023

Bibliographical note

Publisher Copyright:
© 2023 by the authors.

Keywords

  • bladder cancer
  • early cancer detection
  • non-invasive cancer detection
  • target deep sequencing
  • urine tumor DNA

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