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Hyaluronan and Glucose Dual-targeting Probe: Synthesis and Application
Henan Zhang1, Changsheng Chen1, Jingjun Han1
1National Glycoengineering Research Center, Shandong Key Laboratory of Carbohydrate Chemistry and Glycobiology, Shandong University, Qingdao 266237, China.
Bioorganic Chemistry
|September 14, 2024
Summary
This study introduces a novel dual-targeting probe for enhanced tumor detection. The probe simultaneously targets CD44 and glucose transporter 1 (GLUT1) receptors, improving accuracy in vitro and in vivo.
Area of Science:
- Biomedical Engineering
- Molecular Imaging
- Cancer Research
Background:
- Cancer cells often overexpress specific cell surface receptors like CD44 and glucose transporters (GLUTs).
- Developing targeted probes is crucial for improving the specificity and efficacy of cancer detection and treatment.
Purpose of the Study:
- To design and evaluate a novel dual-targeting probe (HGR) for enhanced tumor detection.
- To investigate the impact of hyaluronan (HA) oligosaccharide structure on probe targeting efficacy.
- To assess the in vitro and in vivo performance of the HGR probe.
Main Methods:
- Synthesis of a dual-targeting probe (HGR) comprising hyaluronan (HA) oligosaccharide and glucose (Glc) labeled with Rhodamine B.
- In vitro evaluation of probe's cytocompatibility and targeting specificity using CD44 and GLUT1 expression levels.
- In vivo studies in murine models to assess tumor targeting efficacy and biocompatibility.
Main Results:
- The HGR probe demonstrated superior targeting ability and cytocompatibility compared to single-targeting probes in vitro.
- HGR showed a marked preference for cells with high CD44 and GLUT1 expression.
- In vivo studies confirmed significantly enhanced tumor targeting efficacy and excellent biocompatibility of the HGR probe.
Conclusions:
- The developed dual-targeting probe (HGR) effectively targets tumors by simultaneously engaging CD44 and GLUT1.
- The probe exhibits excellent biocompatibility and enhanced targeting efficacy, showing potential for clinical tumor detection applications.
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