A Novel Biocompatible Nanoprobe Based on Lipoproteins for Breast Cancer Cell Imaging

Authors

  • Mehdi Mirzaei Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran|Iran Ministry of Health and Medical Education, Deputy Ministry for Education, Tehran, Iran
  • Mohammad Esmaeil Akbari Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  • Mojdeh Mohseni Radiation Biology Research Center, Iran University of Medical Sciences, Tehran, Iran
  • Seyed Amir Mohsen Ziaee Labbafinejad Medical Center, Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Abstract:

Objective(s): Contrast-enhanced magnetic resonance imaging (MRI) of breast cancer provides valuable data on the disease state of patients. Biocompatible nanoprobes are expected to play a pivotal role in medical diagnosis in the future owing to their prominent advantages. The present study aimed to introduce a novel biocompatible nanoprobe based on lipoproteins for breast cancer cell imaging.Materials and Methods: In this study, a biocompatible nanoprobe based on high-density lipoprotein was synthesized successfully. Scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and dynamic light scattering (DLS) were used for material characterization, and cellular uptake and in-vitro and in-vivo imaging were investigated using the nanoprobe. Results: The nanoprobe could significantly reduce the relaxation time in the phantom and cancer cells with no toxicity in the studied cells. In addition, the nanoprobe demonstrated proper cellular uptake in the cancer cells. The in-vivo tumor images were obtained 30, 60, and 120 minutes after the injection of the nanoprobe (5.0 µmol/kg) via the tail vein, and the results indicated that the synthesized nanoprobe could be introduced as a potential MRI contrast agent. Conclusion: Future developments may allow the application of this nanoparticle to be used in pathological and physiological processes in preclinical models.

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Journal title

volume 7  issue 1

pages  73- 79

publication date 2020-01-01

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