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Urine cell-free DNA multi-omics to detect MRD and predict survival in bladder cancer patients

Chauhan, Pradeep S. and Shiang, Alexander and Alahi, Irfan and Sundby, R. Taylor and Feng, Wenjia and Gungoren, Bilge and Nawaf, Cayce and Chen, Kevin and Babbra, Ramandeep K. and Harris, Peter K. and Qaium, Faridi and Hatscher, Casey and Antiporda, Anna and Brunt, Lindsey and Mayer, Lindsey R. and Shern, Jack F. and Baumann, Brian C. and Kim, Eric H. and Reimers, Melissa A. and Smith, Zachary L. and Chaudhuri, Aadel A. (2023) Urine cell-free DNA multi-omics to detect MRD and predict survival in bladder cancer patients. npj Precision Oncology, 7 . Art. No. 6. ISSN 2397-768X. PMCID PMC9852243. doi:10.1038/s41698-022-00345-w.

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Circulating tumor DNA (ctDNA) sensitivity remains subpar for molecular residual disease (MRD) detection in bladder cancer patients. To remedy this problem, we focused on the biofluid most proximal to the disease, urine, and analyzed urine tumor DNA in 74 localized bladder cancer patients. We integrated ultra-low-pass whole genome sequencing (ULP-WGS) with urine cancer personalized profiling by deep sequencing (uCAPP-Seq) to achieve sensitive MRD detection and predict overall survival. Variant allele frequency, inferred tumor mutational burden, and copy number-derived tumor fraction levels in urine cell-free DNA (cfDNA) significantly predicted pathologic complete response status, far better than plasma ctDNA was able to. A random forest model incorporating these urine cfDNA-derived factors with leave-one-out cross-validation was 87% sensitive for predicting residual disease in reference to gold-standard surgical pathology. Both progression-free survival (HR = 3.00, p = 0.01) and overall survival (HR = 4.81, p = 0.009) were dramatically worse by Kaplan–Meier analysis for patients predicted by the model to have MRD, which was corroborated by Cox regression analysis. Additional survival analyses performed on muscle-invasive, neoadjuvant chemotherapy, and held-out validation subgroups corroborated these findings. In summary, we profiled urine samples from 74 patients with localized bladder cancer and used urine cfDNA multi-omics to detect MRD sensitively and predict survival accurately.

Item Type:Article
Related URLs:
URLURL TypeDescription CentralArticle
Chauhan, Pradeep S.0000-0003-4304-011X
Shiang, Alexander0000-0002-7957-5418
Sundby, R. Taylor0000-0001-8485-0026
Feng, Wenjia0000-0002-6320-3927
Gungoren, Bilge0000-0001-8988-5594
Chen, Kevin0000-0003-3868-8456
Babbra, Ramandeep K.0000-0002-6244-5107
Harris, Peter K.0000-0003-1557-1722
Baumann, Brian C.0000-0002-7482-1413
Kim, Eric H.0000-0002-0284-8342
Reimers, Melissa A.0000-0002-5167-3630
Smith, Zachary L.0000-0002-0306-8364
Chaudhuri, Aadel A.0000-0003-3115-3061
Additional Information:This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit We are grateful to the patients, their families, and healthy volunteers involved in this study. We also thank A. Newman for providing critical feedback on the manuscript. Images from were used to create Fig. 1a. This work was supported by the National Cancer Institute (NCI) under award number K08CA238711 (A.A.C.), and the National Center for Advancing Translational Sciences (NCATS) under award number UL1TR002345 (Principal Investigator, Bradley Evanoff; A.A.C.). This work was additionally supported by the Washington University School of Medicine Dean’s Medical Student Research Fellowship (A.S), the Midwest Stone Institute (Z.L.S.), the Rabushka Bladder Cancer Research Fund (Z.L.S. and A.A.C.), the Alvin J. Siteman Cancer Research Fund (A.A.C.), the Cancer Research Foundation Young Investigator Award (A.A.C.), and the V Foundation V Scholar Award (A.A.C.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. These authors contributed equally: Pradeep S. Chauhan, Alexander Shiang, Irfan Alahi. Data availability. All FASTQ files corresponding to sequenced patient samples are available from the sequencing read archive (SRA) under accession number PRJNA907063 and ID number 907063. Competing interests. P.S.C., I.A., R.T.S., K.C., Z.L.S., and A.A.C. have patent filings related to cancer biomarkers. F.Q. has stock options in Centene, Gilead, and Horizon Therapeutics. B.C.B. discloses honoraria from Mevion Medical Systems and consulting work for Regeneron/Sanofi, outside of the submitted work. Z.L.S. serves as a consultant/advisor for Photocure, outside the submitted work. A.A.C. has licensed technology to Droplet Biosciences, Tempus Labs, and Biocognitive Labs. A.A.C. has served as a consultant/advisor to Roche, Tempus, Illumina, Geneoscopy, NuProbe, Daiichi Sankyo, AstraZeneca, AlphaSights, DeciBio, and Guidepoint. A.A.C. has received honoraria from Roche, Foundation Medicine, and Dava Oncology. A.A.C. has stock options in Geneoscopy, research support from Roche, Illumina and Tempus Labs, and ownership interests in Droplet Biosciences and LiquidCell Dx. The remaining authors declare no competing interests.
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Washington UniversityUNSPECIFIED
Cancer Research Foundation of AmericaUNSPECIFIED
V Foundation for Cancer ResearchUNSPECIFIED
PubMed Central ID:PMC9852243
Record Number:CaltechAUTHORS:20230209-988069100.17
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ID Code:119181
Deposited By: Research Services Depository
Deposited On:16 Mar 2023 15:28
Last Modified:16 Mar 2023 15:28

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