CircRNA_OTUD7A upregulates FOXP1 expression to facilitate the progression of diffuse large B-cell lymphoma via acting as a sponge of miR-431-5p
Background: A growing number of studies have shown that circular RNA (circRNA) is an important regulator molecule in cancer progression, but it has been poorly studied in diffuse large b-cell lymphoma (DLBCL). Objective: This study aimed to explore the role of circ_OTUD7A in DLBCL. Methods: Relative expression levels of circ_OTUD7A, microRNA (miR)-431-5p and forkhead box P1 (FOXP1) were determined by quantitative real-time PCR (qRT-PCR). The proliferation of cells was elevated by colony formation assay and MTT assay. Western blot (WB) analysis was employed to measure the protein levels of proliferation marker, epithelial-mesenchymal transition (EMT) markers, cyclin marker, apoptosis markers and FOXP1. Moreover, the apoptosis, cell cycle process, migration and invasion of cells were detected using flow cytometry and transwell assay, respectively. In addition, the interaction between miR-431-5p and circ_OTUD7A or FOXP1 was confirmed by dual-luciferase reporter assay. Results: Circ_OTUD7A was highly expressed in DLBCL, and its knockdown could inhibit DLBCL cell proliferation and metastasis, while promote cell cycle arrest and apoptosis. Similarly, FOXP1 also was upregulated in DLBCL, and its silencing could restrain the progression of DLBCL cells. Further experiments revealed that circ_OTUD7A could sponge miR-431-5p and miR-431-5p could target FOXP1. MiR-431-5p inhibitor could reverse the suppressive effect of circ_OTUD7A silencing on DLBCL progression, and FOXP1 overexpression also could reverse the inhibitory effect of miR-431-5p mimic on DLBCL progression. Conclusion: Circ_OTUD7A promoted the progression of DLBCL by regulating the miR-431-5p/FOXP1 axis, which suggested that circ_OTUD7A might function as an oncogene in DLBCL.Keywords: Circ_OTUD7A; Diffuse large B-cell lymphoma; FOXP1; miR-431-5p.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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