High-risk prostate cancer (PC) is the second most common cause of cancer-related death in men. Improvements in overall survival and long-term morbidity will depend on the ability of the operating surgeon to completely resect regional metastatic lymph nodes (LNs) and obtain negative surgical margins; failure to do so increases the likelihood of local tumor recurrence and added tumor burden. Unfortunately, surgical resection techniques have principally relied upon visual cues and tactile information. While significant advances have been made in real-time intraoperative fluorescence imaging techniques, there are no targeted intraoperative imaging probes that can specifically detect local disease or identify one or more molecular signatures defining the cancer itself. This highlights the importance of developing new and clinically translatable high-resolution intraoperative visualization tools that can specifically localize nodal metastases and residual disease along margins, while permitting accurate molecular characterization or phenotyping of tumor. One such next-generation imaging technology is an ultrabright, sub-8-nm diameter fluorescent core-shell silica nanoparticle, Cornell prime dots (C? dots), that can be surface-modified with PC-targeting peptides for accurately identifying one or more metastatic markers, including PSMA. Since not all high-risk PCs express PSMA, it is important to assay other targets, such as GRPr, as part of a complementary multiplexing strategy. Therefore, a long-term goal of this proposal is to create PC-targeting fluorescence-based multiplexing tools (Cornell prime dots, C? dots) for improving the intraoperative detection of cancer targets in high-risk PC patients. Such a precision-based approach can be used to stratify high-risk PC patients potentially curable by surgical resection from those requiring systemic therapy. This strategy also builds upon our prior successful translational and clinical trial efforts. As an extension of our previous R01 application, we completed a Phase 1, first-in-human PET imaging trial in metastatic melanoma patients using a first-generation FDA IND-approved integrin-targeting particle tracer with favorable ?target-or-clear? capabilities. Our active intraoperative clinical trials have exploited this highly-fluorescent particle technology for image-guided treatment of nodal metastases in melanoma patients. In this application, we will target two well-characterized PC markers, PSMA and GRPr, using Cy5.5-containing PSMA- and cw800-containing GRPr-targeting C? dots, according to the following aims: (1) determine tunable surface chemistries for near-infrared dye (NIR)-encapsulated PSMA- and GRPr-targeted C' dots to optimize in vitro biological properties; (2) assess tumor-selective uptake and pharmacokinetic profiles of optimized hybrid C? dots in PSMA- and GRPr-expressing models; (3) develop spectrally-distinct NIR dye-containing C? dots from lead candidates to permit accurate and sensitive concurrent detection of multiple markers expressed on nodal and distant metastases; and (4) identify a lead PSMA-targeting C? dot candidate for IND-enabling studies and an early-phase clinical trial to assess feasibility, particle safety, dosimetry, and cancer-detection capabilities.
Although surgery remains the cornerstone of treatment for patients with localized high-risk prostate cancer, current intraoperative management is limited by a lack of specific, image-guided visualization tools to accurately define tumor margins, map lymph node metastases, and investigate cancer heterogeneity which, in turn, can adversely impact patient outcomes. We propose to develop clinically-translatable ultrasmall particle imaging technologies that not only visualize the extent of local disease, but molecularly characterize tumor in vivo by targeting multiple molecular signatures, each driving a different oncogenic process. Such a precision-based approach may better identify patients that are potentially curable by surgical resection, improve surgical curability, and better tailor targeted treatment management.