Alkaline Phosphatase-Targeted, Gadolinium-Labeled Nanoparticles for Enhanced Multimodal Imaging of Liver Cancer
Source abstract
Abstract
Liver cancer remains one of the most lethal malignancies worldwide, primarily due to limited diagnostic and therapeutic strategies. Biological imaging agents capable of selective accumulation in cancerous liver tissue offer a promising route for earlier detection and improved patient outcomes. In this work, we synthesized and characterized alkaline phosphatase (ALP)-targeted, gadolinium-labeled gold nanoparticles (AuNPs) designed for simultaneous detection using magnetic resonance imaging (MRI), computed tomography (CT), and fluorescence (Fl) microscopy. The synthesized AuNPs feature 13 nm gold cores functionalized with ALP-binding ligands and Gd(III)-macrocycles. Characterization by ultraviolet–visible (UV–vis) spectroscopy, dynamic light scattering (DLS), transmission electron microscopy (TEM), and energy dispersive X-ray spectroscopy (EDX) confirmed successful functionalization. During the functionalization process, variations in Gd(III) loading, surface packing density, and r 1 relaxivity were observed; however, high reproducibility was achieved when including methanol during the AuNP labeling protocol. In vitro studies with HepG2 liver cancer and HEK293 kidney cells demonstrated selective cellular uptake in relation to cellular ALP expression levels. Optimized uptake conditions demonstrated 10-fold increase in Gd(III) internalization into HepG2 versus HEK293 cells. Further imaging by scanning electron microscopy (SEM) and TEM on thinly sliced cell samples verified the intracellular localization of these nanoparticles. Collectively, these findings underscore the potential of ALP-targeted, gadolinium-labeled AuNPs as a versatile multimodal imaging platform for the early detection of liver cancer.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Nanoplatforms for cancer theranostics · Advanced Nanomaterials in Catalysis · Nanocluster Synthesis and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Departments of Chemistry, Molecular Biosciences, Neurobiology, and Radiology
Northwestern University
Funding
National Institutes of Health · National Institute of General Medical Sciences
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