Nature Structural & Molecular BiologyMolecular BiologyPeer-reviewed journal article
Super-silencer perturbation by EZH2 and REST inhibition leads to large loss of chromatin interactions and reduction in cancer growth
Ying ZhangiD, Kaijing CheniD, Seng Chuan TangiD, Yichao CaiiD, Akiko Niibori-NambuiD, Yi Xiang SeeiD, Chaoyu FuiD, Anandhkumar RajuiD, Benjamin LebeauiD, Zixun Ling, Jia Jia ChaniD, Yvonne TayiD, Marek MutwiliD, Manikandan LakshmananiD, Greg Tucker‐KelloggiD, Wee Joo ChngiD, Daniel Geoffrey TeneniD, Motomi OsatoiD, Vinay Tergaonkar, Melissa J. FullwoodiD
Abstract
Human silencers have been shown to exist and regulate developmental gene expression. However, the functional importance of human silencers needs to be elucidated, such as whether they can form "super-silencers" and whether they are linked to cancer progression. Here, through interrogating two putative silencer components of FGF18 gene, we found that two nearby silencers can cooperate via compensatory chromatin interactions to form a "super-silencer". Furthermore, double knockout of two silencers exhibited synergistic upregulation of FGF18 expression and changes of cell identity. To perturb the "super-silencers", we applied combinational treatment of an EZH2 inhibitor GSK343, and a REST inhibitor, X5050 ("GR"). We found that GR led to severe loss of TADs and loops, while the use of one inhibitor by itself only showed mild changes. Such changes in TADs and loops were associated with reduced CTCF and TOP2A mRNA levels. Moreover, GSK343 and X5050 synergistically upregulated super-silencer-controlled genes related to cell cycle, apoptosis and DNA damage, leading to anticancer effects both in vitro and in vivo. Overall, our data demonstrated the first example of a "super-silencer" and showed that combinational usage of GSK343 and X5050 to disrupt "super-silencers" could potentially lead to cancer ablation.
- organism: human
- assay: ChIP-seq
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: drug response / drug discovery
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
- 12
- FWCI
- 1.63
- Field percentile
- top 16%
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