Anti-epithelial cell adhesion molecule RNA aptamer-conjugated liposomal doxorubicin as an efficient targeted therapy in mice bearing colon carcinoma tumor model.
Mohammad Mahdi Barati JozanParvin ZamaniMaryam KarimiAmin MehrabianMahdieh ArabsalmaniJavad ZarqiSeyedeh Alia MoosavianMahmoud Reza JaafariPublished in: Biotechnology progress (2021)
To overcome the lack of selectivity and nonspecific biodistribution of drugs in the body, targeted delivery of chemotherapeutic agents with aptamers is a very effective method. In this strategy, aptamers could be specifically identified and attach to targeted molecules on the cancerous cells and deliver the chemotherapeutic agents to desired tissue with minimal or no damage to the normal cells. In this study, we designed anti-epithelial cell adhesion molecule (EpCAM) RNA aptamer conjugated PEGylated liposomal doxorubicin (ER-lip) to investigate its in vitro and in vivo anticancer abilities. Data showed that EpCAM aptamer was able to enhance cell uptake and cytotoxic effects of Dox in C26 cell line. The biodistribution study indicated that ER-lip enhanced the tumor accumulation of Dox compared to Caelyx. Also, double staining of isolated tumor cells with anti-CD44-PE-cy5 and anti-EpCAM Cy-7 antibodies indicated that tumor cells expressed a high level of EpCAM+ CD44+ cells (p ≤ .001) compared to cultured C26 cell line. in vivo results showed that ER-lip promoted survival and reduced tumor growth rate in animal model compared to Caelyx. In conclusion, these results suggested that the ER-lip could be served as promising formulation for the treatment of cancers with the high expression of EpCAM.
Keyphrases
- cell adhesion
- induced apoptosis
- circulating tumor cells
- cell cycle arrest
- gold nanoparticles
- drug delivery
- estrogen receptor
- sensitive detection
- endoplasmic reticulum
- signaling pathway
- type diabetes
- breast cancer cells
- stem cells
- endoplasmic reticulum stress
- cancer therapy
- nucleic acid
- electronic health record
- cell death
- mesenchymal stem cells
- computed tomography
- pet imaging
- staphylococcus aureus
- endothelial cells
- machine learning
- deep learning
- escherichia coli
- insulin resistance
- biofilm formation
- smoking cessation
- big data