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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/31343
Title: MiR-520e can regulate Transforming growth Factor signaling and inhibit NSCLC invasion
Authors: Aka, H.
Kksayan, H.
Keywords: материалы конференций;miR-520e;factor-β;NSCLC
Issue Date: 2018
Publisher: БГУИР
Citation: Akзa, H. MiR-520e can regulate Transforming growth Factor signaling and inhibit NSCLC invasion / H. Akзa, H. Kьзьksayan // BIG DATA Advanced Analytics: collection of materials of the fourth international scientific and practical conference, Minsk, Belarus, May 3 – 4, 2018 / editorial board: М. Batura [etc.]. – Minsk, BSUIR, 2018. – Р. 98 – 97.
Abstract: Transforming growth factor-β (TGF-β) pathway plays crucial roles during the carcinogenesis and metastasis. Transforming growth factor-β receptor 2 (TGFBR2) is a key molecule for the regulation of TGF-β pathway and frequently downregulated or lost in several cancer types including non-small cell lung cancer (NSCLC). However, little is known about the mechanism of miRNA-mediated TGFBR2 downregulation in NSCLC. Also, TGF-β pathway is often regulated by negative feedback mechanisms, which allow cancer cells to escape growth inhibition from TGF-β. Here, we found that the significance of mir-520e for TGFBR2 downregulation and the negative regulation of TGF-β signaling in NSCLC. We demonstrate that mir-520e is upregulated in metastatic tumor tissues compared to non-metastatic ones and its expression is inversely correlated with that of TGFBR2 in clinical samples. We further discovered that TGF-β decreased TGFBR2 expression and, treatments of the chemical inhibitors of histone deacetylase and DNA methyltransferase did not influence TGF-β-induced TGFBR2 downregulation. TGF-β dramatically increased the expression of mir-520e targeting TGFBR2. ChIP-PCR experiments showed that mir-520e is transcriptionally induced by SMAD2/3 in response to TGF-β. Our findings reveal a novel negative feedback mechanism in TGF-β signaling via mir-520e and that mir-520e overexpression could be a predictive factor for NSCLC metastasis. This Work was financialy supported by TUBITAK ( Project code 215Z283).
URI: https://libeldoc.bsuir.by/handle/123456789/31343
Appears in Collections:BIG DATA and Advanced Analytics. Использование BIG DATA для оптимизации бизнеса и информационных технологий (2018)

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