| Autor: |
Rashid, Raizulnasuha Ab, Sisin, Noor Nabilah Talik, Razak, Khairunisak Abdul, Geso, Moshi, Akasaka, Hiroaki, Sasaki, Ryohei, Tominaga, Takahiro, Miura, Hayato, Nishi, Masashi, Almutery, Aml Aied, Rahman, Wan Nordiana |
| Zdroj: |
Journal of Radiation Research and Applied Sciences; 20240101, Issue: Preprints |
| Abstrakt: |
Combining therapy and radiosensitizer depicted a promising future for cancer patients. This study evaluating on the radiosensitization effects of gold nanoparticles (AuNPs) for proton beam therapy using different radiobiological cell survival models. Human colon carcinoma cell lines (HCT 116) were used with 1.9 nm AuNPs and irradiated by different doses of a 150 MeV proton beam within the Spread-out Bragg Peak (SOBP) region. Clonogenic assay were used to obtain cell survival data which then be fitted to Linear Quadratic (LQ), Multi-target (MT), Repairable Conditionally Repairable (RCR), Pade’ Linear Quadratic (PLQ), Kavanagh-Newman (KN), and Two Components (2C). The cellular uptake, localization, cytotoxicity and ROS measurement study were also conducted. The results show internalization of AuNPs manifested with the increase granulation of cells presented by side scattering (SSC) result of 7.3% compared to control. AuNPs were seen localized in the cytoplasm, yet no traces in nucleus area. Evaluation on the radiosensitization effects depicted sensitization enhancement ratio (SER) of 3.78 with LQ model, while other models also indicate similar increment of SER but less goodness of fit with the experimental data. The percentage of reactive oxygen species (ROS) induced by AuNPs are found to be around 234% which is double compared to control. In conclusion, the cell survival analysis with different radiobiological models shows radiosensitization effects by AuNPs when irradiated with proton beam. The evidence is also supported by the ROS data and the analysis of the model’s parameter that could also be used to predict and quantify radiosensitization effects. |
| Databáze: |
Supplemental Index |
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