Yanpu Wang1, Chenran Zhang1, Jianhao Lai1, Yang Zhao1, Dehua Lu1, Rui Bao1, Xun Feng1, Ting Zhang1, Zhaofei Liu2. 1. Medical Isotopes Research Center and Department of Radiation Medicine, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, 100191, China. 2. Medical Isotopes Research Center and Department of Radiation Medicine, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, 100191, China. liuzf@bjmu.edu.cn.
Abstract
PURPOSE: The role that gut microbiota plays in determining the efficacy of the anti-tumor effect of immune checkpoint inhibitors is gaining increasing attention, and fecal bacterial transplantation has been recognized as a promising strategy for improving or rescuing the effect of immune checkpoint inhibition. However, techniques for the precise monitoring of in vivo bacterial behaviors after transplantation are limited. In this study, we aimed to use metabolic labeling and subsequent positron emission tomography (PET) imaging to track the in vivo behaviors of gut bacteria that are responsible for the efficacy of anti-PD-1 therapy in living mice. METHODS: The antitumor effect of anti-PD-1 blockade was tested in a low-response 4T1 syngeneic mouse model with or without fecal transplantation and with or without broad-spectrum antibiotic imipenem treatment. High-throughput sequencing analyses of 16S rRNA gene amplicons in feces of 4T1 tumor-bearing mice pre- and post-anti-PD-1 treatment were performed. The identified bacteria, Bacteroides fragilis (B. fragilis), were labeled with 64Cu and fluorescence dye by the metabolic labeling of N3 followed by click chemistry. In vivo PET and optical imaging of B. fragilis were performed in mice after oral gavage. RESULTS: The disturbance of gut microbiota reduced the efficacy of anti-PD-1 treatment, and the combination of B. fragilis gavage and PD-1 blockade was beneficial in rescuing the antitumor effect of anti-PD-1 therapy. Metabolic oligosaccharide engineering and biorthogonal click chemistry resulted in successful B. fragilis labeling with 64Cu and fluorescence dye with high in vitro and in vivo stability and no effect on viability. PET imaging successfully detected the in vivo behaviors of B. fragilis after transplantation. CONCLUSION: PET tracking by metabolic labeling is a powerful, noninvasive tool for the real-time tracking and quantitative imaging of gut microbiota. This strategy is clinically translatable and may also be extended to the PET tracking of other functional cells to guide cell-based adoptive therapies.
PURPOSE: The role that gut microbiota plays in determining the efficacy of the anti-tumor effect of immune checkpoint inhibitors is gaining increasing attention, and fecal bacterial transplantation has been recognized as a promising strategy for improving or rescuing the effect of immune checkpoint inhibition. However, techniques for the precise monitoring of in vivo bacterial behaviors after transplantation are limited. In this study, we aimed to use metabolic labeling and subsequent positron emission tomography (PET) imaging to track the in vivo behaviors of gut bacteria that are responsible for the efficacy of anti-PD-1 therapy in living mice. METHODS: The antitumor effect of anti-PD-1 blockade was tested in a low-response 4T1 syngeneic mouse model with or without fecal transplantation and with or without broad-spectrum antibiotic imipenem treatment. High-throughput sequencing analyses of 16S rRNA gene amplicons in feces of 4T1 tumor-bearing mice pre- and post-anti-PD-1 treatment were performed. The identified bacteria, Bacteroides fragilis (B. fragilis), were labeled with 64Cu and fluorescence dye by the metabolic labeling of N3 followed by click chemistry. In vivo PET and optical imaging of B. fragilis were performed in mice after oral gavage. RESULTS: The disturbance of gut microbiota reduced the efficacy of anti-PD-1 treatment, and the combination of B. fragilis gavage and PD-1 blockade was beneficial in rescuing the antitumor effect of anti-PD-1 therapy. Metabolic oligosaccharide engineering and biorthogonal click chemistry resulted in successful B. fragilis labeling with 64Cu and fluorescence dye with high in vitro and in vivo stability and no effect on viability. PET imaging successfully detected the in vivo behaviors of B. fragilis after transplantation. CONCLUSION: PET tracking by metabolic labeling is a powerful, noninvasive tool for the real-time tracking and quantitative imaging of gut microbiota. This strategy is clinically translatable and may also be extended to the PET tracking of other functional cells to guide cell-based adoptive therapies.
Entities:
Keywords:
64Cu; Gut microbiota; Metabolic labeling; Molecular imaging; PET tracking
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