Evolution of the genomic landscape of circulating tumor DNA (ctDNA) in metastatic prostate cancer over treatment and time. (2019)

• Record Type: Journal Article
• Authors: Hahn, Andrew W.; Stenehjem, David; Nussenzveig, Roberto; Carroll, Emma; Bailey, Erin; Batten, Julia; Maughan, Benjamin L.; Agarwal, Neeraj
• Is Part Of: Cancer treatment and research communications. Number 19(2019)
• Publication Date: 2019
• Subjects: Circulating tumor DNA -- Liquid biopsy -- Metastatic prostate cancer -- Genomic evolution -- Intratumoral heterogeneity
• DOI: 10.1016/j.ctarc.2019.100120
• Languages: English
• ISSNs: 2468-2942

Abstract

Abstract: Background: Targeted therapies have shown promise for men with metastatic castration-resistant prostate cancer (mCRPC). Due to the difficulty with obtaining tumor tissue in bony metastases, liquid biopsies are a promising alternative to guide treatment selection. While concurrent tissue next-generation sequencing (tNGS) and liquid biopsy has high concordance, it is unknown whether the genomic landscape of metastatic prostate cancer (mPC) changes over time or treatment. Herein, we hypothesize that the genomic landscape of mPC evolves with new treatments and/or time between tests. Patients and Methods: Men with mPC from the University of Utah with matched tNGS and liquid biopsy were included. Clinical data was collected retrospectively. Exonic regions from 69 genes covered by both platforms were included for analysis. Paired t tests were used to assess number of genomic alterations (GAs) between testing platforms. Number of alterations was assessed by time and number of treatments between testing by multivariate nonparametric trend tests. Results: 101 men with mPC were eligible and included. In men with no new treatments and ≤ 1 year between tests, a similar number of GAs were detected in both tests (2.0 vs. 2.2). In contrast, men with ≥ 1 new treatment between tests had significantly more GAs after treatment (5.0 vs. 2.4, p = 0.005). Total number of GAs was correlated with number of new treatments between testing ( p = 0.003) and not time between testing ( p = 0.76). Conclusion: The genomic landscape of mPC evolves with subsequent therapies. This finding suggests that contemporary tumor genomic profile upon disease progression may optimize guidance towards subsequent therapy selection.