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American Association for Cancer Research, Clinical Cancer Research, 8(29), p. 1582-1591, 2023

DOI: 10.1158/1078-0432.ccr-22-3250

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Cell-Free Urine and Plasma DNA Mutational Analysis Predicts Neoadjuvant Chemotherapy Response and Outcome in Patients with Muscle-Invasive Bladder Cancer

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Abstract Purpose: To investigate the use of plasma and urine DNA mutation analysis for predicting neoadjuvant chemotherapy (NAC) response and oncological outcome in patients with muscle-invasive bladder cancer. Experimental Design: Whole-exome sequencing of tumor and germline DNA was performed for 92 patients treated with NAC followed by radical cystectomy (RC). A custom NGS-panel capturing approximately 50 mutations per patient was designed and used to track mutated tumor DNA in plasma and urine. A total of 447 plasma samples, 281 urine supernatants, and 123 urine pellets collected before, during, and after treatment were analyzed. Patients were enrolled from 2013 to 2019, with a median follow-up time of 41.3 months after RC. Results: We identified tumor DNA before NAC in 89% of urine supernatants, 85% of urine pellets, and 43% of plasma samples. Tumor DNA levels were higher in urine supernatants and urine pellets compared with plasma samples (P < 0.001). In plasma, detection of circulating tumor DNA (ctDNA) before NAC was associated with a lower NAC response rate (P < 0.001). Detection of tumor DNA after NAC was associated with lower response rates in plasma, urine supernatant, and urine pellet (P < 0.001, P = 0.03, P = 0.002). Tumor DNA dynamics during NAC was predictive of NAC response and outcome in urine supernatant and plasma (P = 0.006 and P = 0.002). A combined measure from plasma and urine supernatant tumor DNA dynamics stratified patients by outcome (P = 0.003). Conclusions: Analysis of tumor DNA in plasma and urine samples both separately and combined has a potential to predict treatment response and outcome.