Tools for rapid therapeutic selection for pancreatic ductal adenocarcinoma (PDAC) patients are vital to improved survival as PDAC is the third leading cause of cancer death, with an average life expectancy of 5-7 months post diagnosis. Treatment options are limited to surgery and chemotherapy, where Gemcitabine has been the cornerstone of therapy since 1997. However, Gemcitabine resistance prevents PDAC cure and mechanisms of resistance are not fully understood. Yet, with average survival times still <1 year, improved treatment selection and early assessment of response are urgently needed. Our group has recently developed a promising imaging based technology that will improve patient specific treatment selection and provide a platform for assessment of newly developed therapeutics with improved efficacy prediction compared to drug distribution alone. We have established a spatially-resolved, quantitative imaging methodology termed paired agent imaging (PAI), that enables quantification of drug target sites at the single cell level, allowing direct visualization of drug target availability (DTA) in situ, a parameter directly related to therapeutic efficacy. Using PAI, we examined the mechanisms of cancer therapy resistance on a cell-by-cell basis with the goal of utilizing explants for rapid, patient-specific therapy selection as they can predict treatment response in <5 days. As proof of concept we have studied Erlotinib, synthesizing paired targeted and untargeted fluorescently labeled derivatives. Overall, we anticipate that our spatially resolved maps of DTA will be predictive of therapeutic efficacy in patient PDAC explants, providing a platform technology for patient specific therapy selection <1 week after resection or biopsy.
Emily Schultz, Allison Solanki, Lei Wang, Kenneth M. Tichauer, and Summer L. Gibbs, "Paired agent imaging enables rapid assessment of therapeutic efficacy for personalized therapy
(Conference Presentation)," Proc. SPIE 10475, Visualizing and Quantifying Drug Distribution in Tissue II, 104750K (Presented at SPIE BiOS: January 28, 2018; Published: 14 March 2018); https://doi.org/10.1117/12.2290626.5751475980001.
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