Preliminary Clinical Application of RGD-Containing Peptides as PET Radiotracers for Imaging Tumors - Li, Li; Chen, Xiaoyuan; Yu, Jinming; Yuan, Shuanghu (Frontiers in Oncology, 2022)
Angiogenesis is a common feature of many physiological processes and pathological conditions. RGD-containing peptides can strongly bind to integrin αvβ3 expressed on endothelial cells in neovessels and several tumor cells with high specificity, making them promising molecular agents for imaging angiogenesis. Although studies of RGD-containing peptides combined with radionuclides including 18F, 64Cu and 68Ga for positron emission tomography (PET) imaging have shown high spatial resolution and accurate quantification of tracer uptake, only a few of these radiotracers have been successfully translated into clinical use. This review summarizes the RGD-based tracers in terms of accumulation in tumors and adjacent tissues, and comparison with traditional 18F-fluorodeoxyglucose (FDG) imaging. The value of RGD-based tracers for diagnosis, differential diagnosis, tumor subvolume delineation, and therapeutic response prediction is mainly discussed. Very low RGD accumulation, in contrast to high FDG metabolism, was found in normal brain tissue, indicating that RGD-based imaging provides an excellent tumor-to-background ratio for improved brain tumor imaging. However, the RGD-based tracers’ intensity is much higher than FDG in normal liver tissue, which could lead to underestimation of primary or metastatic lesions in liver. In multiple studies, RGD-based imaging successfully realized the diagnosis and differential diagnosis of solid tumors as well as the prediction of chemoradiotherapy response, providing complementary rather than similar information relative to FDG imaging. Of most interest, baseline RGD uptake values can not only be used to predict the tumor efficacy of antiangiogenic therapy, but also to monitor the occurrence of adverse events in normal organs. This unique dual predictive value in antiangiogenic therapy may be better than that of FDG-based imaging.