The emergence of and transitions between distinct phenotypes in isogenic cells can be attributed to the intricate interplay of epigenetic marks, external signals, and gene regulatory elements. These elements include chromatin remodelers, histone modifiers, transcription factors, and regulatory RNAs. Mathematical models known as Gene Regulatory Networks (GRNs) are an increasingly important tool to unravel the workings of such complex networks. In such models, epigenetic factors are usually proposed to act on the chromatin regions directly involved in the expression of relevant genes. However, it has been well-established that these factors operate globally and compete with each other for targets genome-wide. Therefore, a perturbation of the activity of a regulator can redistribute epigenetic marks across the genome and modulate the levels of competing regulators. These interactions have been brought to the fore by recent experiments (Zhang, Donaher et al, 2022) reporting that the knockouts of different histone methyltransferases can induce two distinct trajectories of EMT, characterized by distinct and unexpected changes in gene expression profiles. In this work, we propose a new modeling framework that combines local transcriptional regulation with global epigenetic control, and show that complex interplay between transcriptional and epigenetic control can lead to rich gene expression dynamics. We use our modeling framework to understand the effects of various epigenetic perturbations on the epithelial-mesenchymal transition, a crucial cellular process involved in both health and disease. We note that the interplay between epigenetic competition, the EMT transcriptional network, and the baseline transcriptional context can result in counter-intuitive experimental observations, and generate unique paths for cells to transition between epithelial and mesenchymal states. We apply our modeling framework to explain the aforementioned recent experimental findings (Zhang, Donaher et al, 2022), and we use it to offer verifiable predictions. One crucial takeaway from our modeling is that experiments involving epigenetic perturbations must be analyzed with care due to the possibility of widespread cross-talk between the genomic targets of different epigenetic factors. This means that the biological consequence of perturbation to an epigenetic modifier could be an outcome of changes in the expression levels of its direct genomic targets or simply a side-effect from the dilution and distribution of an entirely different epigenetic modifier.
Citation Format: M. Ali Al-Radhawi, Shubham Tripath, Yun Zhang, Eduardo Sontag, Herbert Levine. Epigenetic factor competition reshapes the EMT landscape. [abstract]. In: Proceedings of the AACR Special Conference: Cancer Epigenomics; 2022 Oct 6-8; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2022;82(23 Suppl_2):Abstract nr A026.