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Sarvenaz Kashefi, Speaker at Drug Delivery Conferences
Tehran University of Medical Sciences, Iran (Islamic Republic of)
Title : The anti-cancer properties of miR-340 Plasmid-Chitosan Complexes (miR-340 CC) on murine model of breast cancer

Abstract:

MiRNA-340 (miR-340) has been found to have tumor-suppressing effects in breast cancer (BC). However, for clinical use, miRNAs need to be delivered safely and effectively to protect them from degradation. In our previous study, we used chitosan complexes as a safe carrier with anti-cancer properties to deliver miR-340 plasmid into 4T1 cells. This study explored further information concerning the anti-cancer impacts of both chitosan and miR-340 plasmid in a murine model of BC. Mice bearing 4T1 cells were intra-tumorally administered miR-340 plasmid-chitosan complexes (miR-340 CC). Afterwards, the potential of miR-340 CC in promoting anti-tumor immune responses was evaluated. MiR-340 CC significantly reduced tumor size, inhibited metastasis, and prolonged the survival of mice. MiR-340 CC up-regulates P-27 gene expression related to cancer cell apoptosis, and down-regulates gene expressions involved in angiogenesis and metastasis (breast regression protein-39 (BRP-39)) and CD163 as an anti-inflammatory macrophages (MQs) marker. Furthermore, CD47 expression as a MQs immune check-point was remarkably decreased after miR-340 CC treatment. The level of IL-12 in splenocytes of miR-340 CC treated mice increased, while the level of IL-10 decreased, indicating anti-cancer immune responses. Our findings display that miR-340 CC can be considered as a promising therapy in BC.

Biography:

Dr. Sarvenaz Kashefi studied a PhD in medical immunology at Shahid Beheshti Medical University, Tehran, Iran. She graduated in November 2023 and recently joined the Colorectal Cancer Research Center at Tehran University of Medical Sciences, Tehran, Iran. She is interested in drug delivery, especially in the tumor microenvironment, and her articles have been published in the areas of drugs and delivery systems. This abstract is the result of her work during her PhD thesis.

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