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Cited by 253

The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.

Detection and Surveillance of Bladder Cancer Using Urine Tumor DNA

Open access
Dudley, Jonathan C., Schroers-Martin, Joseph, Lazzareschi, Daniel V., Shi, William Y., Chen, Simon B., Esfahani, Mohammad S., Trivedi, Dharati, Chabon, Jacob J., Chaudhuri, Aadel A., Stehr, Henning, Liu, Chih Long, Lim, Harumi, Costa, Helio A., Nabet, Barzin Y., Sin, Mandy L.Y., Liao, Joseph C., Alizadeh, Ash A., Diehn, Maximilian·2019·Cancer Discovery

Abstract

Current regimens for the detection and surveillance of bladder cancer are invasive and have suboptimal sensitivity. Here, we present a novel high-throughput sequencing (HTS) method for detection of urine tumor DNA (utDNA) called utDNA CAPP-Seq (uCAPP-Seq) and apply it to 67 healthy adults and 118 patients with early-stage bladder cancer who had urine collected either prior to treatment or during surveillance. Using this targeted sequencing approach, we detected a median of 6 mutations per patient with bladder cancer and observed surprisingly frequent mutations of the PLEKHS1 promoter (46%), suggesting these mutations represent a useful biomarker for detection of bladder cancer. We detected utDNA pretreatment in 93% of cases using a tumor mutation–informed approach and in 84% when blinded to tumor mutation status, with 96% to 100% specificity. In the surveillance setting, we detected utDNA in 91% of patients who ultimately recurred, with utDNA detection preceding clinical progression in 92% of cases. uCAPP-Seq outperformed a commonly used ancillary test (UroVysion, P = 0.02) and cytology and cystoscopy combined (P ≤ 0.006), detecting 100% of bladder cancer cases detected by cytology and 82% that cytology missed. Our results indicate that uCAPP-Seq is a promising approach for early detection and surveillance of bladder cancer. Significance: This study shows that utDNA can be detected using HTS with high sensitivity and specificity in patients with early-stage bladder cancer and during post-treatment surveillance, significantly outperforming standard diagnostic modalities and facilitating noninvasive detection, genotyping, and monitoring. This article is highlighted in the In This Issue feature, p. 453

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Metadata

Authors
Dudley, J. C., Schroers-Martin, J., Lazzareschi, D. V., Shi, W. Y., Chen, S. B., Esfahani, M. S., Trivedi, D., Chabon, J. J., Chaudhuri, A. A., Stehr, H., Liu, C. L., Lim, H., Costa, H. A., Nabet, B. Y., Sin, M. L. Y., Liao, J. C., Alizadeh, A. A., & Diehn, M.
Venue
Cancer Discovery
Published
2019-04-01
Volume
9
Issue
4
Pages
500-509
ISSN
  • 2159-8274 (ISSN-L)
  • 2159-8290
OpenAlex
W2906216049
Cited by
253
References
21
FWCI
5.69
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Detection and Surveillance of Bladder Cancer Using Urine Tumor DNA. https://app.cochat.ai/papers/10.1158/2159-8290.cd-18-0825
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Dudley, J. C., Schroers-Martin, J., Lazzareschi, D. V., Shi, W. Y., Chen, S. B., Esfahani, M. S., Trivedi, D., Chabon, J. J., Chaudhuri, A. A., Stehr, H., Liu, C. L., Lim, H., Costa, H. A., Nabet, B. Y., Sin, M. L. Y., Liao, J. C., Alizadeh, A. A., & Diehn, M. (2019). Detection and Surveillance of Bladder Cancer Using Urine Tumor DNA. Cancer Discovery. https://doi.org/10.1158/2159-8290.cd-18-0825

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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