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Translocator Protein PET Imaging in a Preclinical Prostate Cancer Model

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PurposeThe identification and targeting of biomarkers specific to prostate cancer (PCa) could improve its detection. Given the high expression of translocator protein (TSPO) in PCa, we investigated the use of… Click to show full abstract

PurposeThe identification and targeting of biomarkers specific to prostate cancer (PCa) could improve its detection. Given the high expression of translocator protein (TSPO) in PCa, we investigated the use of [18F]VUIIS1008 (a novel TSPO-targeting radioligand) coupled with positron emission tomography (PET) to identify PCa in mice and to characterize their TSPO uptake.ProceduresPtenpc−/−, Trp53pc−/− prostate cancer-bearing mice (n = 9, 4–6 months old) were imaged in a 7T MRI scanner for lesion localization. Within 24 h, the mice were imaged using a microPET scanner for 60 min in dynamic mode following a retro-orbital injection of ~ 18 MBq [18F]VUIIS1008. Following imaging, tumors were harvested and stained with a TSPO antibody. Regions of interest (ROIs) were drawn around the tumor and muscle (hind limb) in the PET images. Time-activity curves (TACs) were recorded over the duration of the scan for each ROI. The mean activity concentrations between 40 and 60 min post radiotracer administration between tumor and muscle were compared.ResultsTumor presence was confirmed by visual inspection of the MR images. The uptake of [18F]VUIIS1008 in the tumors was significantly higher (p < 0.05) than that in the muscle, where the percent injected dose per unit volume for tumor was 7.1 ± 1.6 % ID/ml and that of muscle was < 1 % ID/ml. In addition, positive TSPO expression was observed in tumor tissue analysis.ConclusionsThe foregoing preliminary data suggest that TSPO may be a useful biomarker of PCa. Therefore, using TSPO-targeting PET ligands, such as [18F]VUIIS1008, may improve PCa detectability and characterization.

Keywords: pet; prostate cancer; translocator protein; 18f vuiis1008; pca; cancer

Journal Title: Molecular Imaging and Biology
Year Published: 2017

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