Collaborative study from the Bladder Cancer Advocacy Network for the genomic analysis of metastatic urothelial cancer

Jeffrey S. Damrauer, Wolfgang Beckabir, Jeff Klomp, Mi Zhou, Elizabeth R. Plimack, Matthew D. Galsky, Petros Grivas, Noah M. Hahn, Peter H. O’Donnell, Gopa Iyer, David I. Quinn, Benjamin G. Vincent, Diane Zipursky Quale, Sara E. Wobker, Katherine A. Hoadley, William Y. Kim () and Matthew I. Milowsky ()
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Jeffrey S. Damrauer: University of North Carolina
Wolfgang Beckabir: University of North Carolina
Jeff Klomp: University of North Carolina
Mi Zhou: University of North Carolina
Elizabeth R. Plimack: Fox Chase Cancer Center, Temple Health
Matthew D. Galsky: Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai
Petros Grivas: University of Washington
Noah M. Hahn: Johns Hopkins University School of Medicine
Peter H. O’Donnell: University of Chicago
Gopa Iyer: Memorial Sloan Kettering Cancer Center
David I. Quinn: University of Southern California Norris Comprehensive Cancer Center
Benjamin G. Vincent: University of North Carolina
Diane Zipursky Quale: Bladder Cancer Advocacy Network
Sara E. Wobker: University of North Carolina
Katherine A. Hoadley: University of North Carolina
William Y. Kim: University of North Carolina
Matthew I. Milowsky: University of North Carolina

Nature Communications, 2022, vol. 13, issue 1, 1-15

Abstract: Abstract Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (NCT02643043), UC-GENOME, is a genomic analysis and biospecimen repository study in 218 patients with metastatic urothelial carcinoma. Here we report on the primary outcome of the UC-GENOME—the proportion of subjects who received next generation sequencing (NGS) with treatment options—and present the initial genomic analyses and clinical correlates. 69.3% of subjects had potential treatment options, however only 5.0% received therapy based on NGS. We found an increased frequency of TP53E285K mutations as compared to non-metastatic cohorts and identified features associated with benefit to chemotherapy and immune checkpoint inhibition, including: Ba/Sq and Stroma-rich subtypes, APOBEC mutational signature (SBS13), and inflamed tumor immune phenotype. Finally, we derive a computational model incorporating both genomic and clinical features predictive of immune checkpoint inhibitor response. Future work will utilize the biospecimens alongside these foundational analyses toward a better understanding of urothelial carcinoma biology.

Date: 2022
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DOI: 10.1038/s41467-022-33980-9

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