A cationic amino acid polymer nanocarrier synthesized in supercritical CO2 for co-delivery of drug and gene to cervical cancer cells.
By: K V Kavya, Stella Vargheese, Shruti Shukla, Imran Khan, Debasish Kumar Dey, Vivek K Bajpai, Kavitha Thangavelu, Raju Vivek, R T Rajendra Kumar, Young-Kyu Han, Yun Suk Huh, Yuvaraj Haldorai

Department of Nanoscience and Technology, Bharathiar University, Coimbatore, Tamilnadu 641046, India.
2022-02-22; doi: 10.1016/j.colsurfb.2022.112584
Abstract

The present study was undertaken to investigate the ability of a drug curcumin-loaded polymer to inhibit the growth of cervical cancer cells by enhancing the anti-cancer efficiency of curcumin. We synthesized poly(methacryloyl beta-alanine) (PMBA) as a nanocarrier by radical polymerization in supercritical CO2. The results showed that the curcumin encapsulated and folic acid (FA)-treated PMBA (Poly@Cur-FA) for 24 h activated the reactive oxygen species-mediated programmed cell death machinery in HeLa cells. This remarkable effect of Poly@Cur-FA treatment was visualized using different fluorescent probes, which demonstrated that the Poly@Cur-FA treatment disrupted the cell membrane, as also supported by scanning electron microscopy observations. The effect of Poly@Cur-FA dispersion on the cells was observed under a transmission electron microscope. Further, the HeLa cells were treated with the polymer encapsulated curcumin and Bcl2 siRNA (Pol-Cur-siRNA) for 24 h, which effectively suppressed the Bcl2 and simulated the autophagic pathway. This co-delivery system was designed to inhibit curcumin efflux and can enhance the treatment efficacy by targeting multiple signaling pathways, including cell cycle, apoptotic, and autophagic pathways. Collectively, the Pol-Cur-siRNA system appears to offer an efficient combinational therapeutic strategy that might overcome the problems associated with the chemosensitivity against the standard synthetic anti-cancer drugs. To support the experimental data, an artificial neural network model was developed to foresee the drug and gene release behaviors.



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PMID:35617878






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