(2016) Breast cancer cell targeted MR molecular imaging probe: Anti-MUC1 antibody-based magnetic nanoparticles. In: 10th International Seminar on Medical Physics, ISMP 2016 and 1st AMDI International Oncology Symposium, IOS 2016.
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Abstract
Effective and specific diagnostic imaging techniques are important in early-stage breast cancer treatment. The objective of this study was to develop a specific breast cancer contrast agent for magnetic resonance imaging (MRI). In so doing, superparamagnetic iron oxide nanoparticles (SPIONs) were conjugated to C595 monoclonal antibody using EDC chemistry to produce nanoprobe with high relaxivity and narrow size (87.4±0.7 nm). To test the developed nanoprobe in vitro, assessments including Cell toxicity, targeting efficacy, cellular binding, and MR imaging were carried out. The results indicated that after 6 hrs incubation with MCF-7 cells at 200 to 25 μg Fe/ml doses, 76 to 16 T2 reduction was obtained. The presence of iron localised in MCF-7 cells measured by atomic absorption spectroscopy (AAS) was about 9.95±0.09 ppm iron/cell at higher doses of nanoprobe. Moreover, a linear relationship between iron concentration of nontoxic SPION-C595 and T2 relaxation times was observed. This study also revealed that developed nanoprobe might be used as a specific negative contrast agent for detecting breast cancer. © Published under licence by IOP Publishing Ltd.
Item Type: | Conference or Workshop Item (Paper) |
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Keywords: | Absorption spectroscopy Antibodies Atomic absorption spectrometry Cells Cytology Diagnosis Diseases Imaging techniques Iron Magnetic resonance imaging Molecular imaging Monoclonal antibodies Nanomagnetics Nanoparticles Nanoprobes Oncology Atomic absorption spectroscopy Breast cancer cells Early-stage breast cancer Iron concentrations Linear relationships Magnetic nano-particles Superparamagnetic iron oxide nanoparticles Targeting efficacies Medical imaging |
Journal Index: | Scopus |
Volume: | 851 |
Publisher: | Institute of Physics Publishing |
Identification Number: | https://doi.org/10.1088/1742-6596/851/1/012014 |
ISBN: | 17426588 (ISSN) |
Depositing User: | مهندس مهدی شریفی |
URI: | http://eprints.mui.ac.ir/id/eprint/1947 |
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