Suppr超能文献

上皮-间充质转化中表型稳定所需反馈环的动态。

Dynamics of the feedback loops required for the phenotypic stabilization in the epithelial-mesenchymal transition.

机构信息

Universidade Federal de Santa Maria, Santa Maria, RS, Brazil.

出版信息

FEBS J. 2020 Feb;287(3):578-588. doi: 10.1111/febs.15062. Epub 2019 Oct 1.

Abstract

The epithelial-mesenchymal transition (EMT) is a complex mechanism in which cells undergo a transition from epithelial to mesenchymal phenotypes (there is also an intermediary hybrid state) in response to microenvironmental alterations and aberrant stimuli triggered by molecules such as TGF-β. Recent studies in breast cancer progression reported new feedback loops and new participant molecules such as microRNAs 340 and 1199. In this work, we propose a logical model of EMT contemplating the influence of these new published molecules on the regulatory core of EMT. The model results were compared with theoretical and experimental data for the human breast epithelial cell line MCF10A presenting excellent agreement. We propose that the miRNAs 340 and 1199 should be considered phenotypic stability factors of the hybrid state based on the positive feedback loops they form with ZEB1. In addition, the model allows the prediction of phenotype probabilities at the coexistence region. For the tristable dynamics when epithelial, hybrid, and mesenchymal phenotypes coexist, we found that the hybrid state is the most probable, agreeing with experiments. Our results highlight new mechanisms related to the EMT dynamics in response to TGF-β stimulus in epithelial breast cells and might help the design of therapeutic strategies for breast cancer.

摘要

上皮-间质转化(EMT)是一种复杂的机制,当细胞对微环境改变和 TGF-β等分子触发的异常刺激做出反应时,会从上皮表型向间质表型(也存在中间杂交状态)转变。最近在乳腺癌进展的研究中报道了新的反馈回路和新的参与分子,如 microRNA340 和 1199。在这项工作中,我们提出了一个 EMT 的逻辑模型,考虑了这些新发表的分子对 EMT 调控核心的影响。模型结果与 MCF10A 人乳腺上皮细胞系的理论和实验数据进行了比较,结果非常吻合。我们提出,基于 miRNA340 和 1199 与 ZEB1 形成的正反馈回路,它们应该被认为是杂交状态的表型稳定性因素。此外,该模型还可以预测共存区域的表型概率。对于上皮、杂交和间质表型共存的三稳定动力学,我们发现杂交状态是最有可能的,这与实验结果一致。我们的结果强调了与 TGF-β刺激反应相关的 EMT 动力学的新机制,并可能有助于设计乳腺癌的治疗策略。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验