Andrew W Hahn1, David Stenehjem2, Roberto Nussenzveig1, Emma Carroll3, Erin Bailey1, Julia Batten1, Benjamin L Maughan1, Neeraj Agarwal4. 1. Division of Oncology, Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, 2000 Circle of Hope Drive Suite 5726, Salt Lake City, UT 84112, USA. 2. College of Pharmacy, University of Minnesota, Duluth, MN, USA. 3. Division of Oncology, Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, 2000 Circle of Hope Drive Suite 5726, Salt Lake City, UT 84112, USA; College of Pharmacy, University of Minnesota, Duluth, MN, USA. 4. Division of Oncology, Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, 2000 Circle of Hope Drive Suite 5726, Salt Lake City, UT 84112, USA. Electronic address: neeraj.agarwal@hci.utah.edu.
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.
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.