Multifunctional Dendrimer-Entrapped Gold Nanoparticles for Labeling and Tracking T Cells Via Dual-Modal Computed Tomography and Fluorescence Imaging.
Meixiu ChenOshra BetzerYu FanYue GaoXiangyang ShiTamar SadanRachela PopovtzerXiangyang ShiPublished in: Biomacromolecules (2020)
Nanosystems for monitoring and tracking T cells provide an important basis for evaluating the functionality and efficacy of T cell-based immunotherapy. To this end, we designed herein an efficient nanoprobe for T cell monitoring and tracking using poly(amidoamine) (PAMAM) dendrimer-entrapped gold nanoparticles (Au DENPs) conjugated with Fluo-4 for dual-mode computed tomography (CT) and fluorescence imaging. In this study, PAMAM dendrimers of generation 5 (G5) were modified with hydroxyl-terminated polyethylene glycol (PEG) and then used to entrap 2.0 nm Au NPs followed by acetylation of the excess amine groups on the dendrimer surface. Subsequently, the calcium ion probe was covalently attached to the dendrimer nanohybrids through the PEG hydroxyl end groups to gain the functional {(Au0)25-G5.NHAc-(PEG)14-(Fluo-4)2} nanoprobe. This nanoprobe had excellent water solubility, high X-ray attenuation coefficient, and good cytocompatibility in the given concentration range, as well as a high T cell labeling efficiency. Confocal microscopy and flow cytometry results demonstrated that the nanoprobe was able to fluorescently sense activated T cells. Moreover, the nanoprobe was able to realize both CT and fluorescence imaging of subcutaneously injected T cells in vivo. Thus, the developed novel dendrimer-based nanosystem may hold great promise for advancing and improving the clinical application of T cell-based immunotherapy.
Keyphrases
- fluorescence imaging
- computed tomography
- photodynamic therapy
- gold nanoparticles
- dual energy
- reduced graphene oxide
- living cells
- drug delivery
- positron emission tomography
- image quality
- flow cytometry
- contrast enhanced
- fluorescent probe
- sensitive detection
- magnetic resonance imaging
- single molecule
- magnetic resonance
- high resolution
- mass spectrometry
- big data
- cancer therapy
- machine learning
- deep learning