Network-Based Integration of Multi-Omics Data Identifies the Determinants of miR-491-5p Effects

基于网络的多组学数据整合可识别 miR-491-5p 效应的决定因素

阅读:7
作者:Matthieu Meryet-Figuiere, Mégane Vernon, Mamy Andrianteranagna, Bernard Lambert, Célia Brochen, Jean-Paul Issartel, Audrey Guttin, Pascal Gauduchon, Emilie Brotin, Florent Dingli, Damarys Loew, Nicolas Vigneron, Anaïs Wambecke, Edwige Abeilard, Emmanuel Barillot, Laurent Poulain, Loredana Martignett

Abstract

The identification of miRNAs' targets and associated regulatory networks might allow the definition of new strategies using drugs whose association mimics a given miRNA's effects. Based on this assumption we devised a multi-omics approach to precisely characterize miRNAs' effects. We combined miR-491-5p target affinity purification, RNA microarray, and mass spectrometry to perform an integrated analysis in ovarian cancer cell lines. We thus constructed an interaction network that highlighted highly connected hubs being either direct or indirect targets of miR-491-5p effects: the already known EGFR and BCL2L1 but also EP300, CTNNB1 and several small-GTPases. By using different combinations of specific inhibitors of these hubs, we could greatly enhance their respective cytotoxicity and mimic the miR-491-5p-induced phenotype. Our methodology thus constitutes an interesting strategy to comprehensively study the effects of a given miRNA. Moreover, we identified targets for which pharmacological inhibitors are already available for a clinical use or in clinical trials. This study might thus enable innovative therapeutic options for ovarian cancer, which remains the leading cause of death from gynecological malignancies in developed countries.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。