Nucleosome repositioning in chronic lymphocytic leukemia.

The location of nucleosomes in the human genome determines the primary chromatin structure and regulates access to regulatory regions. However, genome-wide information on deregulated nucleosome occupancy and its implications in primary cancer cells is scarce. Here, we conducted a genome-wide comparison of high-resolution nucleosome maps in peripheral blood B cells from patients with chronic lymphocytic leukemia (CLL) and healthy individuals at single-base-pair resolution. Our investigation uncovered significant changes of nucleosome positioning in CLL. Globally, the spacing between nucleosomes-the nucleosome repeat length (NRL)-is shortened in CLL. This effect is stronger in the more aggressive IGHV-unmutated CLL subtype than in the IGHV-mutated CLL subtype. Changes in nucleosome occupancy at specific sites are linked to active chromatin remodeling and reduced DNA methylation. Nucleosomes lost or gained in CLL marks differential binding of 3D chromatin organizers such as CTCF as well as immune response-related transcription factors and delineated mechanisms of epigenetic deregulation. The principal component analysis of nucleosome occupancy in cancer-specific regions allowed the classification of samples between cancer subtypes and normal controls. Furthermore, patients could be better assigned to CLL subtypes according to differential nucleosome occupancy than based on DNA methylation or gene expression. Thus, nucleosome positioning constitutes a novel readout to dissect molecular mechanisms of disease progression and to stratify patients. Furthermore, we anticipate that the global nucleosome repositioning detected in our study, such as changes in the NRL, can be exploited for liquid biopsy applications based on cell-free DNA to stratify patients and monitor disease progression.

Epigenetic signals that direct cell type-specific interferon beta response in mouse cells.

The antiviral response induced by type I interferon (IFN) via the JAK-STAT signaling cascade activates hundreds of IFN-stimulated genes (ISGs) across human and mouse tissues but varies between cell types. However, the links between the underlying epigenetic features and the ISG profile are not well understood. We mapped ISGs, binding sites of the STAT1 and STAT2 transcription factors, chromatin accessibility, and histone H3 lysine modification by acetylation (ac) and mono-/tri-methylation (me1, me3) in mouse embryonic stem cells and fibroblasts before and after IFNß treatment. A large fraction of ISGs and STAT-binding sites was cell type specific with promoter binding of a STAT1/2 complex being a key driver of ISGs. Furthermore, STAT1/2 binding to putative enhancers induced ISGs as inferred from a chromatin co-accessibility analysis. STAT1/2 binding was dependent on the chromatin context and positively correlated with preexisting H3K4me1 and H3K27ac marks in an open chromatin state, whereas the presence of H3K27me3 had an inhibitory effect. Thus, chromatin features present before stimulation represent an additional regulatory layer for the cell type-specific antiviral response.

Interleukin-10 receptor signaling promotes the maintenance of a PD-1int TCF-1+ CD8+ T cell population that sustains anti-tumor immunity.

T cell exhaustion limits anti-tumor immunity and responses to immunotherapy. Here, we explored the microenvironmental signals regulating T cell exhaustion using a model of chronic lymphocytic leukemia (CLL). Single-cell analyses identified a subset of PD-1hi, functionally impaired CD8+ T cells that accumulated in secondary lymphoid organs during disease progression and a functionally competent PD-1int subset. Frequencies of PD-1int TCF-1+ CD8+ T cells decreased upon Il10rb or Stat3 deletion, leading to accumulation of PD-1hi cells and accelerated tumor progression. Mechanistically, inhibition of IL-10R signaling altered chromatin accessibility and disrupted cooperativity between the transcription factors NFAT and AP-1, promoting a distinct NFAT-associated program. Low IL10 expression or loss of IL-10R-STAT3 signaling correlated with increased frequencies of exhausted CD8+ T cells and poor survival in CLL and in breast cancer patients. Thus, balance between PD-1hi, exhausted CD8+ T cells and functional PD-1int TCF-1+ CD8+ T cells is regulated by cell-intrinsic IL-10R signaling, with implications for immunotherapy.

Methylome-based cell-of-origin modeling (Methyl-COOM) identifies aberrant expression of immune regulatory molecules in CLL.

BACKGROUND: In cancer, normal epigenetic patterns are disturbed and contribute to gene expression changes, disease onset, and progression. The cancer epigenome is composed of the epigenetic patterns present in the tumor-initiating cell at the time of transformation, and the tumor-specific epigenetic alterations that are acquired during tumor initiation and progression. The precise dissection of these two components of the tumor epigenome will facilitate a better understanding of the biological mechanisms underlying malignant transformation. Chronic lymphocytic leukemia (CLL) originates from differentiating B cells, which undergo extensive epigenetic programming. This poses the challenge to precisely determine the epigenomic ground state of the cell-of-origin in order to identify CLL-specific epigenetic aberrations. METHODS: We developed a linear regression model, methylome-based cell-of-origin modeling (Methyl-COOM), to map the cell-of-origin for individual CLL patients based on the continuum of epigenomic changes during normal B cell differentiation. RESULTS: Methyl-COOM accurately maps the cell-of-origin of CLL and identifies CLL-specific aberrant DNA methylation events that are not confounded by physiologic epigenetic B cell programming. Furthermore, Methyl-COOM unmasks abnormal action of transcription factors, altered super-enhancer activities, and aberrant transcript expression in CLL. Among the aberrantly regulated transcripts were many genes that have previously been implicated in T cell biology. Flow cytometry analysis of these markers confirmed their aberrant expression on malignant B cells at the protein level. CONCLUSIONS: Methyl-COOM analysis of CLL identified disease-specific aberrant gene regulation. The aberrantly expressed genes identified in this study might play a role in immune-evasion in CLL and might serve as novel targets for immunotherapy approaches. In summary, we propose a novel framework for in silico modeling of reference DNA methylomes and for the identification of cancer-specific epigenetic changes, a concept that can be broadly applied to other human malignancies.

Linking aberrant chromatin features in chronic lymphocytic leukemia to transcription factor networks.

In chronic lymphocytic leukemia (CLL), a diverse set of genetic mutations is embedded in a deregulated epigenetic landscape that drives cancerogenesis. To elucidate the role of aberrant chromatin features, we mapped DNA methylation, seven histone modifications, nucleosome positions, chromatin accessibility, binding of EBF1 and CTCF, as well as the transcriptome of B cells from CLL patients and healthy donors. A globally increased histone deacetylase activity was detected and half of the genome comprised transcriptionally downregulated partially DNA methylated domains demarcated by CTCF CLL samples displayed a H3K4me3 redistribution and nucleosome gain at promoters as well as changes of enhancer activity and enhancer linkage to target genes. A DNA binding motif analysis identified transcription factors that gained or lost binding in CLL at sites with aberrant chromatin features. These findings were integrated into a gene regulatory enhancer containing network enriched for B-cell receptor signaling pathway components. Our study predicts novel molecular links to targets of CLL therapies and provides a valuable resource for further studies on the epigenetic contribution to the disease.

Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets.

Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49. Initially, we based the reconstruction on genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis. This initial draft was manually curated with the final reconstruction accounting for 480 genes associated with 576 reactions and 558 metabolites. In order to constrain the model further, we performed growth experiments of wild type and arcA deletion strains of S. pyogenes M49 in a chemically defined medium and calculated nutrient uptake and production fluxes. We additionally performed amino acid auxotrophy experiments to test the consistency of the model. The established genome-scale model can be used to understand the growth requirements of the human pathogen S. pyogenes and define optimal and suboptimal conditions, but also to describe differences and similarities between S. pyogenes and related lactic acid bacteria such as L. lactis in order to find strategies to reduce the growth of the pathogen and propose drug targets.