Effects of bromodomain and extra-terminal inhibitor JQ1 and interleukin-6 on breast cancer cells
Background: Bromodomain and extra-terminal (BET) proteins are recognized acetylated lysine of histone 4 and act as scaffolds to recruit many other proteins to promoters and enhancers of active genes, especially at the super-enhancers of key genes, driving the transcription process and have been identified as potential therapeutic targets in breast cancer. However, the efficacy of BET inhibitors such as JQ1 in breast cancer therapy is impeded by interleukin-6 (IL-6) through an as-yet-defined mechanism. Methods and results: We investigated the interplay between IL-6 and JQ1 in MCF-7 and MDA-MB-231 human breast cancer cells. The results demonstrate that the efficacy of JQ1 on the inhibition of cell growth and apoptosis was stronger in MDA-MB-231 cells than in MCF-7 cells. Further, MCF-7 cells, but not MDA-MB-231 cells, exhibited increased expression of CXCR4 following IL-6 treatment. JQ1 significantly reduced CXCR4 surface expression in both cell lines and diminished the effects of IL-6 pre-treatment on MCF-7 cells. While IL-6 suppressed the extension of breast cancer stem cells in MCF-7 cells, JQ1 impeded its inhibitory effect. In MCF-7 cells JQ1 increased the number of senescent cells in a time-dependent manner. Conclusion: Analysis of gene expression indicated that JQ1 and IL-6 synergistically increase SNAIL expression and decrease c-MYC expression in MCF-7 cells. So, the BET proteins are promising, novel therapeutic targets in late-stage breast cancers. BET inhibitors similar to JQ1 show promise as therapeutic candidates for breast cancers, especially when triple-negative breast cancer cells are increased and/or tumor-promoting factors like IL-6 exist in the tumor microenvironment.Keywords: BET inhibitor; Breast cancer; Breast cancer stem cell; CXCR4; IL-6; JQ1.
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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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