Bivalent chromatin as a therapeutic target in cancer: An in silico predictive approach for combining epigenetic drugs

Understanding How Chromatin Folding and Enzyme Competition Affect Rugged Epigenetic Landscapes

Epigenetics plays a key role in cellular differentiation and maintaining cell identity, enabling cells to regulate their genetic activity without altering the DNA sequence. Epigenetic regulation occurs within the context of hierarchically folded chromatin, yet the interplay between the dynamics of epigenetic modifications and chromatin architecture remains poorly understood. In addition, it remains unclear what mechanisms drive the formation of rugged epigenetic patterns, characterised by alternating genomic regions enriched in activating and repressive marks. In this study, we focus on post-translational modifications of histone H3 tails, particularly H3K27me3, H3K4me3, and H3K27ac. We introduce a mesoscopic stochastic model that incorporates chromatin architecture and competition of histone-modifying enzymes into the dynamics of epigenetic modifications in small genomic loci comprising several nucleosomes. Our approach enables us to investigate the mechanisms by which epigenetic patterns form on larger scales of chromatin organisation, such as loops and domains. Through bifurcation analysis and stochastic simulations, we demonstrate that the model can reproduce uniform chromatin states (open, closed, and bivalent) and generate previously unexplored rugged profiles. Our results suggest that enzyme competition and chromatin conformations with high-frequency interactions between distant genomic loci can drive the emergence of rugged epigenetic landscapes. Additionally, we hypothesise that bivalent chromatin can act as an intermediate state, facilitating transitions between uniform and rugged landscapes. This work offers a powerful mathematical framework for understanding the dynamic interactions between chromatin architecture and epigenetic regulation, providing new insights into the formation of complex epigenetic patterns.

The art of modeling gene regulatory circuits

The amazing complexity of gene regulatory circuits, and biological systems in general, makes mathematical modeling an essential tool to frame and develop our understanding of their properties. Here, we present some fundamental considerations to develop and analyze a model of a gene regulatory circuit of interest, either representing a natural, synthetic, or theoretical system. A mathematical model allows us to effectively evaluate the logical implications of our hypotheses. Using our models to systematically perform in silico experiments, we can then propose specific follow-up assessments of the biological system as well as to reformulate the original assumptions, enriching both our knowledge and our understanding of the system. We want to invite the community working on different aspects of gene regulatory circuits to explore the power and benefits of mathematical modeling in their system.

Modeling of covalent modifications of histones to estimate the binding affinity

Covalent histone modifications such as methylation, acetylation, phosphorylation, and other epigenetic modifications of the chromatin play an essential role in regulating eukaryotic cells of which most of these reactions are catalyzed by the enzymes. The binding energy of enzymes is often determined by experimental data via mathematical and statistical models due to specific modifications. Many theoretical models have been introduced to study histone modifications and reprogramming experiments in mammalian cells, in which all efforts in determining the affinity binding are essential part of the work. Here, we introduce a one-dimensional statistical Potts model to accurately determine the enzyme's binding free energy using the experimental data for various types of cells. We study the methylation of lysine 4 and 27 on histone H3 and suppose that each histone has one modification site with one of the seven states: H3K27me3, H3K27me2, H3K27me1, unmodified, H3K4me1, H3K4me2, and H3K4me3. Based on this model, the histone covalent modification is described. Moreover, by using simulation data, the histone's binding free energy and the energy of chromatin states are determined, when they are subject to changes from unmodified to active or repressive states, by finding the probability of the transition.

H3 histone methylation landscape in male urogenital cancers: from molecular mechanisms to epigenetic biomarkers and therapeutic targets

During the last decades, male urogenital cancers (including prostate, renal, bladder and testicular cancers) have become one of the most frequently encountered malignancies affecting all ages. While their great variety has promoted the development of various diagnosis, treatment and monitoring strategies, some aspects such as the common involvement of epigenetic mechanisms are still not elucidated. Epigenetic processes have come into the spotlight in the past years as important players in the initiation and progression of tumors, leading to a plethora of studies highlighting their potential as biomarkers for diagnosis, staging, prognosis, and even as therapeutic targets. Thus, fostering research on the various epigenetic mechanisms and their roles in cancer remains a priority for the scientific community. This review focuses on one of the main epigenetic mechanisms, namely, the methylation of the histone H3 at various sites and its involvement in male urogenital cancers. This histone modification presents a great interest due to its modulatory effect on gene expression, leading either to activation (e.g., H3K4me3, H3K36me3) or repression (e.g., H3K27me3, H3K9me3). In the last few years, growing evidence has demonstrated the aberrant expression of enzymes that methylate/demethylate histone H3 in cancer and inflammatory diseases, that might contribute to the initiation and progression of such disorders. We highlight how these particular epigenetic modifications are emerging as potential diagnostic and prognostic biomarkers or targets for the treatment of urogenital cancers.

Epigenetic factor competition reshapes the EMT landscape

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. In this paper, we propose a conceptual and mathematical modeling framework that incorporates both local and global competition effects between antagonistic epigenetic regulators, in addition to local transcription factors, and show the counterintuitive consequences of such interactions. We apply our approach to recent experimental findings on the epithelial-mesenchymal transition (EMT). We show that it can explain the puzzling experimental data, as well as provide verifiable predictions.

Targeting Epigenetic Modifiers of Tumor Plasticity and Cancer Stem Cell Behavior

Tumor heterogeneity poses one of the greatest challenges to a successful treatment of cancer. Tumor cell populations consist of different subpopulations that have distinct phenotypic and genotypic profiles. Such variability poses a challenge in successfully targeting all tumor subpopulations at the same time. Relapse after treatment has been previously explained using the cancer stem cell model and the clonal evolution model. Cancer stem cells are an important subpopulation of tumor cells that regulate tumor plasticity and determine therapeutic resistance. Tumor plasticity is controlled by genetic and epigenetic changes of crucial genes involved in cancer cell survival, growth and metastasis. Targeting epigenetic modulators associated with cancer stem cell survival can unlock a promising therapeutic approach in completely eradicating cancer. Here, we review various factors governing epigenetic dysregulation of cancer stem cells ranging from the role of epigenetic mediators such as histone and DNA methyltransferases, histone deacetylases, histone methyltransferases to various signaling pathways associated with cancer stem cell regulation. We also discuss current treatment regimens targeting these factors and other promising inhibitors in clinical trials.

Epigenetics and Testicular Cancer: Bridging the Gap Between Fundamental Biology and Patient Care

Testicular cancer is the most common solid tumor affecting young males. Most testicular cancers are testicular germ cell tumors (TGCTs), which are divided into seminomas (SGCTs) and non-seminomatous testicular germ cell tumors (NSGCTs). During their development, primordial germ cells (PGCs) undergo epigenetic modifications and any disturbances in their pattern might lead to cancer development. The present study provides a comprehensive review of the epigenetic mechanisms–DNA methylation, histone post-translational modifications, bivalent marks, non-coding RNA–associated with TGCT susceptibility, initiation, progression and response to chemotherapy. Another important purpose of this review is to highlight the recent investigations regarding the identification and development of epigenetic biomarkers as powerful tools for the diagnostic, prognostic and especially for epigenetic-based therapy.

Transition Therapy: Tackling the Ecology of Tumor Phenotypic Plasticity

Phenotypic switching in cancer cells has been found to be present across tumor types. Recent studies on Glioblastoma report a remarkably common architecture of four well-defined phenotypes coexisting within high levels of intra-tumor genetic heterogeneity. Similar dynamics have been shown to occur in breast cancer and melanoma and are likely to be found across cancer types. Given the adaptive potential of phenotypic switching (PHS) strategies, understanding how it drives tumor evolution and therapy resistance is a major priority. Here we present a mathematical framework uncovering the ecological dynamics behind PHS. The model is able to reproduce experimental results, and mathematical conditions for cancer progression reveal PHS-specific features of tumors with direct consequences on therapy resistance. In particular, our model reveals a threshold for the resistant-to-sensitive phenotype transition rate, below which any cytotoxic or switch-inhibition therapy is likely to fail. The model is able to capture therapeutic success thresholds for cancers where nonlinear growth dynamics or larger PHS architectures are in place, such as glioblastoma or melanoma. By doing so, the model presents a novel set of conditions for the success of combination therapies able to target replication and phenotypic transitions at once. Following our results, we discuss transition therapy as a novel scheme to target not only combined cytotoxicity but also the rates of phenotypic switching.