Abstract

BACKGROUND. Poly(ADP-ribose) polymerase (PARP) inhibitors are effective in a broad population of patients with ovarian cancer; however, resistance caused by low enzyme expression of the drug target PARP-1 remains to be clinically evaluated in this context. We hypothesize that PARP-1 expression is variable in ovarian cancer and can be quantified in primary and metastatic disease using a novel PET imaging agent. METHODS. We used a translational approach to describe the significance of PET imaging of PARP-1 in ovarian cancer. First, we produced PARP1-KO ovarian cancer cell lines using CRISPR/Cas9 gene editing to test the loss of PARP-1 as a resistance mechanism to all clinically used PARP inhibitors. Next, we performed preclinical microPET imaging studies using ovarian cancer patient–derived xenografts in mouse models. Finally, in a phase I PET imaging clinical trial we explored PET imaging as a regional marker of PARP-1 expression in primary and metastatic disease through correlative tissue histology. RESULTS. We found that deletion of PARP1 causes resistance to all PARP inhibitors in vitro, and microPET imaging provides proof of concept as an approach to quantify PARP-1 in vivo. Clinically, we observed a spectrum of standard uptake values (SUVs) ranging from 2–12 for PARP-1 in tumors. In addition, we found a positive correlation between PET SUVs and fluorescent immunohistochemistry for PARP-1 (r2 = 0.60). CONCLUSION. This work confirms the translational potential of a PARP-1 PET imaging agent and supports future clinical trials to test PARP-1 expression as a method to stratify patients for PARP inhibitor therapy. TRIAL REGISTRATION. Clinicaltrials.gov NCT02637934. FUNDING. Research reported in this publication was supported by the Department of Defense OC160269, a Basser Center team science grant, NIH National Cancer Institute R01CA174904, a Department of Energy training grant DE-SC0012476, Abramson Cancer Center Radiation Oncology pilot grants, the Marsha Rivkin Foundation, Kaleidoscope of Hope Foundation, and Paul Calabresi K12 Career Development Award 5K12CA076931.

Authors

Mehran Makvandi, Austin Pantel, Lauren Schwartz, Erin Schubert, Kuiying Xu, Chia-Ju Hsieh, Catherine Hou, Hyoung Kim, Chi-Chang Weng, Harrison Winters, Robert Doot, Michael D. Farwell, Daniel A. Pryma, Roger A. Greenberg, David A. Mankoff, Fiona Simpkins, Robert H. Mach, Lilie L. Lin

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