Heterochromatin Protein 1: A Multiplayer in Cancer Progression

Physical modeling of nucleosome clustering in euchromatin resulting from interactions between epigenetic reader proteins

Euchromatin is an accessible phase of genetic material containing genes that encode proteins with increased expression levels. The structure of euchromatin in vitro has been described as a 30-nm fiber formed from ordered nucleosome arrays. However, recent advances in microscopy have revealed an in vivo euchromatin architecture that is much more disordered, characterized by variable-length linker DNA and sporadic nucleosome clusters. In this work, we develop a theoretical model to elucidate factors contributing to the disordered in vivo architecture of euchromatin. We begin by developing a 1D model of nucleosome positioning that captures the interactions between bound epigenetic reader proteins to predict the distribution of DNA linker lengths between adjacent nucleosomes. We then use the predicted linker lengths to construct 3D chromatin configurations consistent with the physical properties of DNA within the nucleosome array, and we evaluate the distribution of nucleosome cluster sizes in those configurations. Our model reproduces experimental cluster-size distributions, which are dramatically influenced by the local pattern of epigenetic marks and the concentration of reader proteins. Based on our model, we attribute the disordered arrangement of euchromatin to the heterogeneous binding of reader proteins and subsequent short-range interactions between bound reader proteins on adjacent nucleosomes. By replicating experimental results with our physics-based model, we propose a mechanism for euchromatin organization in the nucleus that impacts gene regulation and the maintenance of epigenetic marks.

The Effect of Intratumor Heterogeneity in Pancreatic Ductal Adenocarcinoma Progression and Treatment

BACKGROUND AND OBJECTIVES

Pancreatic cancer is one of the most lethal malignancies. Even though many substantial improvements in the survival rates for other major cancer forms were made, pancreatic cancer survival rates have remained relatively unchanged since the 1960s. Even more, no standard classification system for pancreatic cancer is based on cellular biomarkers. This review will discuss and provide updates about the role of stem cells in the progression of PC, the genetic changes associated with it, and the promising biomarkers for diagnosis.

MATERIALS AND METHODS

The search process used PubMed, Cochrane Library, and Scopus databases to identify the relevant and related articles. Articles had to be published in English to be considered.

RESULTS

The increasing number of studies in recent years has revealed that the diversity of cancer-associated fibroblasts is far greater than previously acknowledged, which highlights the need for further research to better understand the various cancer-associated fibroblast subpopulations. Despite the huge diversity in pancreatic cancer, some common features can be noted to be shared among patients. Mutations involving CDKN2, P53, and K-RAS can be seen in a big number of patients, for example. Similarly, some patterns of genes and biomarkers expression and the level of their expression can help in predicting cancer behavior such as metastasis and drug resistance. The current trend in cancer research, especially with the advancement in technology, is to sequence everything in hopes of finding disease-related mutations.

CONCLUSION

Optimizing pancreatic cancer treatment requires clear classification, understanding CAF roles, and exploring stroma reshaping approaches.

Interplay between charge distribution and DNA in shaping HP1 paralog phase separation and localization

The heterochromatin protein 1 (HP1) family is a crucial component of heterochromatin with diverse functions in gene regulation, cell cycle control, and cell differentiation. In humans, there are three paralogs, HP1α, HP1β, and HP1γ, which exhibit remarkable similarities in their domain architecture and sequence properties. Nevertheless, these paralogs display distinct behaviors in liquid-liquid phase separation (LLPS), a process linked to heterochromatin formation. Here, we employ a coarse-grained simulation framework to uncover the sequence features responsible for the observed differences in LLPS. We highlight the significance of the net charge and charge patterning along the sequence in governing paralog LLPS propensities. We also show that both highly conserved folded and less-conserved disordered domains contribute to the observed differences. Furthermore, we explore the potential co-localization of different HP1 paralogs in multicomponent assemblies and the impact of DNA on this process. Importantly, our study reveals that DNA can significantly reshape the stability of a minimal condensate formed by HP1 paralogs due to competitive interactions of HP1α with HP1β and HP1γ versus DNA. In conclusion, our work highlights the physicochemical nature of interactions that govern the distinct phase-separation behaviors of HP1 paralogs and provides a molecular framework for understanding their role in chromatin organization.

Simulation of STAT and HP1 interaction by molecular docking

Heterochromatin Protein 1 (HP1) is a major component of heterochromatin. Multiple proteins have been shown to interact with HP1 with the HP1-binding motif PxVxL/I, thereby affecting heterochromatin stability. The HP1-interacting proteins include the signal transducer and activator of transcription (STAT) protein, which can be regulated by phosphorylation on a tyrosine around amino acid 700 in the carboxyl terminus. Previous research has shown that unphosphorylated STAT (uSTAT) binds to HP1 via a PxVxI HP1-binding motif and maintains the stability of heterochromatin, while phosphorylated STAT (pSTAT) dissociates from HP1, resulting in heterochromatin disruption. To understand the theoretical basis of the biochemical observations, we employed computational modeling to investigate STAT-HP1 binding configurations and the effect of STAT phosphorylation on their interaction. Using STAT3 and HP1α protein structures for molecular docking and thermodynamic calculations, our computations predict that uSTAT homodimers have a higher affinity for HP1 and a lower affinity for DNA than pSTAT homodimers, and that phosphorylation induces a conformational change in STAT, shifting its binding preference from HP1 to DNA. The results of our modeling studies support the idea that phosphorylation drives STAT from HP1-binding to DNA-binding, suggesting a potential role for uSTAT in both maintaining and initiating heterochromatin formation.

Writers and readers of H3K9me2 form distinct protein networks during the cell cycle that include candidates for H3K9 mimicry

Histone H3 lysine 9 methylation (H3K9me), which is written by the Euchromatic Histone Lysine Methyltransferases EHMT1 and EHMT2 and read by the heterochromatin protein 1 (HP1) chromobox (CBX) protein family, is dysregulated in many types of cancers. Approaches to inhibit regulators of this pathway are currently being evaluated for therapeutic purposes. Thus, knowledge of the complexes supporting the function of these writers and readers during the process of cell proliferation is critical for our understanding of their role in carcinogenesis. Here, we immunopurified each of these proteins and used mass spectrometry to define their associated non-histone proteins, individually and at two different phases of the cell cycle, namely G1/S and G2/M. Our findings identify novel binding proteins for these writers and readers, as well as corroborate known interactors, to show the formation of distinct protein complex networks in a cell cycle phase-specific manner. Furthermore, there is an organizational switch between cell cycle phases for interactions among specific writer-reader pairs. Through a multi-tiered bioinformatics-based approach, we reveal that many interacting proteins exhibit histone mimicry, based on an H3K9-like linear motif. Gene ontology analyses, pathway enrichment, and network reconstruction inferred that these comprehensive EHMT and CBX-associated interacting protein networks participate in various functions, including transcription, DNA repair, splicing, and membrane disassembly. Combined, our data reveals novel complexes that provide insight into key functions of cell cycle-associated epigenomic processes that are highly relevant for better understanding these chromatin-modifying proteins during cell cycle and carcinogenesis.

Chromobox proteins in cancer: Multifaceted functions and strategies for modulation (Review)

Chromobox (CBX) proteins are important epigenetic regulatory proteins and are widely involved in biological processes, such as embryonic development, the maintenance of stem cell characteristics and the regulation of cell proliferation and apoptosis. Disorder and dysfunction of CBXs in cancer usually lead to the blockade or ectoptic activation of developmental pathways, promoting the occurrence, development and progression of cancer. In the present review, the characteristics and functions of CBXs were first introduced. Subsequently, the expression of CBXs in cancers and the relationship between CBXs and clinical characteristics (mainly cancer grade, stage, metastasis and relapse) and prognosis were discussed. Finally, it was described how CBXs regulate cell proliferation and self‑renewal, apoptosis and the acquisition of malignant phenotypes, such as invasion, migration and chemoresistance, through mechanisms involving epigenetic modification, nuclear translocation, noncoding RNA interactions, transcriptional regulation, posttranslational modifications, protein‑protein interactions, signal transduction and metabolic reprogramming. The study also focused on cancer therapies targeting CBXs. The present review provides new insight and a comprehensive basis for follow‑up research on CBXs and cancer.

Pan-cancer analysis of Chromobox (CBX) genes for prognostic significance and cancer classification

Polycomb group of proteins play a significant role in chromatin remodelling essential for epigenetic regulation of transcription. Chromobox (CBX) gene family is an important part of canonical polycomb repressive complex 1 (PRC1), belonging to the polycomb group involved in chromatin remodelling. Aberrations in CBX expression are linked to various cancers. To assess their biomarker significance, we performed a pan-cancer analysis of CBX mRNA levels in 18 cancer types. We also performed cancer classification using CBX genes as distinctive features for machine learning model development. Logistic regression (L.R.), support vector machine (SVM), random forest (R.F.), decision tree (D.T.), and XGBoost (XGB) algorithms for model training and classification. The expression of CBX genes was significantly changed in four cancer types, i.e., cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), lung adenocarcinoma (LUAD), and lung squamous cell carcinoma (LUSC). The fold change (FC) values suggest that CBX2 was significantly upregulated in CHOL (FC = 1.639), COAD (FC = 1.734), and LUSC (FC = 1.506). On the other hand, CBX7 was found downregulated in COAD (FC = -1.209), LUAD (FC = -1.190), and LUSC (FC = -1.214). The performance of machine learning models for classification was excellent. L.R., R.F., SVM, and XGB obtained a prediction accuracy of 100 % for most cancers. However, D.T. performed comparatively poorly in prediction accuracy. The results suggest that CBX expression is significantly altered in all the cancers studied; therefore, they might be treated as potential biomarkers for therapeutic intervention of these cancers.

N6 -Methyladenosine-Modified CBX1 Regulates Nasopharyngeal Carcinoma Progression Through Heterochromatin Formation and STAT1 Activation

Epitranscriptomic remodeling such as N⁶ -methyladenosine (m⁶ A) modification plays a critical role in tumor development. However, little is known about the underlying mechanisms connecting m⁶ A modification and nasopharyngeal carcinoma (NPC) progression. Here, CBX1 is identified, a histone methylation regulator, to be significantly upregulated with m⁶ A hypomethylation in metastatic NPC tissues. The m⁶ A-modified CBX1 mRNA transcript is recognized and destabilized by the m⁶ A reader YTHDF3. Furthermore, it is revealed that CBX1 promotes NPC cell migration, invasion, and proliferation through transcriptional repression of MAP7 via H3K9me3-mediated heterochromatin formation. In addition to its oncogenic effect, CBX1 can facilitate immune evasion through IFN-γ-STAT1 signaling-mediated PD-L1 upregulation. Clinically, CBX1 serves as an independent predictor for unfavorable prognosis in NPC patients. The results reveal a crosstalk between epitranscriptomic and epigenetic regulation in NPC progression, and shed light on the functions of CBX1 in tumorigenesis and immunomodulation, which may provide an appealing therapeutic target in NPC.

Beyond the marks: reader-effectors as drivers of epigenetics and chromatin engineering

Chromatin is a system of proteins and DNA that regulates chromosome organization and gene expression in eukaryotes. Essential features that support these processes include biochemical marks on histones and DNA, 'writer' enzymes that generate or remove these marks and proteins that translate the marks into transcriptional regulation: reader-effectors. Here, we review recent studies that reveal how reader-effectors drive chromatin-mediated processes. Advances in proteomics and epigenomics have accelerated the discovery of chromatin marks and their correlation with gene states, outpacing our understanding of the corresponding reader-effectors. Therefore, we summarize the current state of knowledge and open questions about how reader-effectors impact cellular function and human disease and discuss how synthetic biology can deepen our knowledge of reader-effector activity.

The Dysregulation of SOX Family Correlates with DNA Methylation and Immune Microenvironment Characteristics to Predict Prognosis in Hepatocellular Carcinoma

Background

Due to the molecular heterogeneity of hepatocellular carcinoma (HCC), majority of patients respond poorly among various of therapy. This study is aimed at conducting a comprehensive analysis about roles of SOX family in HCC for obtaining more therapeutic targets and biomarkers which may bring new ideas for the treatment of HCC.

Methods

UALCAN, Kaplan Meier plotter, cBioPortal, STRING, WebGestalt, Metascape, TIMER 2.0, DiseaseMeth, MethSurv, HPA, CCLE database, and Cytoscape software were used to comprehensively analyze the bioinformatic data.

Results

SOX2, SOX4, SOX8, SOX10, SOX11, SOX12, SOX17, and SOX18 were significantly differentially expressed in HCC and normal tissues and were valuable for the grade and survival of HCC patients. In addition, the gene alterations of SOX family happened frequently, and SOX4 and SOX17 had the highest mutation rate. The function of SOX family on HCC may be closely correlated with the regulation of angiogenesis-related signaling pathways. Moreover, SOX4, SOX8, SOX11, SOX12, SOX17, and SOX18 were correlation with 8 types of immune cells (including CD8+ T cell, CD4+ T cell, B cell, Tregs, neutrophil, macrophage, myeloid DC, and NK cell), and we found that most types of immune cells had a positive correlation with SOX family. Notably, CD4+ T cell and macrophage were positively related with all these SOX family. NK cells were negatively related with most SOX family genes. DNA methylation levels in promoter area of SOX2, SOX4, and SOX10 were lower in HCC than normal tissues, while SOX8, SOX11, SOX17, and SOX18 had higher DNA methylation levels than normal tissues. Moreover, higher DNA methylation level of SOX12 and SOX18 demonstrated worse survival rates in patients with HCC.

Conclusion

SOX family genes could predict the prognosis of HCC. In addition, the regulation of angiogenesis-related signaling pathways may participate in the development of HCC. DNA methylation level and immune microenvironment characteristics (especially CD4+ T cell and macrophage immune cell infiltration) could be a novel insight for predicting prognosis in HCC.