Time-Course Expression Profiling Reveals Early and Late Responders to a Synthetic Chromatin Regulator

Epigenetic therapy, to activate non-mutated tumor suppressors in cancer cells, is gaining traction as an alternative to traditional chemotherapies that inhibit DNA replication and repair. Currently, epigenetic treatments for cancer are limited to small molecules that bind specific chromatin-modifying enzymes: histone methyltransferases, deacetylases, and DNA methyltransferases. Inhibition of these enzymes passively affects gene regulation, can affect cellular processes outside of chromatin, and is therefore not ideal for direct epigenetic modulations. To achieve targeted epigenetic control of a broad range of repressed therapeutic genes, we constructed the first synthetic transcriptional activator, the Polycomb-based transcription factor (PcTF). Our previous work has shown that the PcTF fusion protein reads H3K27me3 DNA modification and activates a subset of H3K27me3-enriched genes. However, there remains a subset of those genes that are not upregulated by PcTF. Here, we present a new study to fully understand the mechanism of gene regulation through targeted interactions between chromatin reader-effectors and histones.

To fully elucidate the activation mechanism of PcTF we have developed stable MCF-7 cell lines that inducibly express full length PcTF or truncations of the full-length protein, to be utilized as controls. After induction, we harvested total mRNA at 10, 24, and 48 hours for RNA-seq. Bioinformatic analysis of the RNA-seq data stratified early and late-activated groups of target genes that specifically respond to full-length PcTF. This result shows that we can distinguish genes by their response to PcTF and establishes a foundation to investigate differences in the physical interaction of PcTF with specific promoters and enhancers, as well as differences in local chromatin structure. To this end, we are using CUT&RUN and a novel transposase mapping system (Calling Cards, R. Mitra lab) to track PcTF interactions and map chromatin features. Ultimately, our work will guide clinical use of synthetic reader-effectors to reprogram gene expression in cancer cells.