Depletion of tet2 results in age-dependent changes in DNA methylation and gene expression in a zebrafish model of myelodysplastic syndrome.

Introduction: Myelodysplastic syndrome (MDS) is a heterogeneous group of clonal hematopoietic disorders characterized by ineffective hematopoiesis, cytopenias, and dysplasia. The gene encoding ten-eleven translocation 2 (tet2), a dioxygenase enzyme that catalyzes the conversion of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine, is a recurrently mutated tumor suppressor gene in MDS and other myeloid malignancies. Previously, we reported a stable zebrafish line with a loss-of-function mutation in the tet2 gene. The tet2m/m-mutant zebrafish developed a pre-MDS state with kidney marrow dysplasia, but normal circulating blood counts by 11 months of age and accompanying anemia, signifying the onset of MDS, by 24 months of age. Methods: In the current study, we collected progenitor cells from the kidney marrows of the adult tet2m/m and tet2wt/wt fish at 4 and 15 months of age and conducted enhanced reduced representation of bisulfite sequencing (ERRBS) and bulk RNA-seq to measure changes in DNA methylation and gene expression of hematopoietic stem and progenitor cells (HSPCs). Results and discussion: A global increase in DNA methylation of gene promoter regions and CpG islands was observed in tet2m/m HSPCs at 4 months of age when compared with the wild type. Furthermore, hypermethylated genes were significantly enriched for targets of SUZ12 and the metal-response-element-binding transcription factor 2 (MTF2)-involved in the polycomb repressive complex 2 (PRC2). However, between 4 and 15 months of age, we observed a paradoxical global decrease in DNA methylation in tet2m/m HSPCs. Gene expression analyses identified upregulation of genes associated with mTORC1 signaling and interferon gamma and alpha responses in tet2m/m HSPCs at 4 months of age when compared with the wild type. Downregulated genes in HSPCs of tet2-mutant fish at 4 months of age were enriched for cell cycle regulation, heme metabolism, and interleukin 2 (IL2)/signal transducer and activator of transcription 5 (STAT5) signaling, possibly related to increased self-renewal and clonal advantage in HSPCs with tet2 loss of function. Finally, there was an overall inverse correlation between overall increased promoter methylation and gene expression.

Immunotherapy targeting different immune compartments in combination with radiation therapy induces regression of resistant tumors.

Radiation therapy (RT) increases tumor response to CTLA-4 inhibition (CTLA4i) in mice and in some patients, yet deep responses are rare. To identify rational combinations of immunotherapy to improve responses we use models of triple negative breast cancer highly resistant to immunotherapy in female mice. We find that CTLA4i promotes the expansion of CD4+ T helper cells, whereas RT enhances T cell clonality and enriches for CD8+ T cells with an exhausted phenotype. Combination therapy decreases regulatory CD4+ T cells and increases effector memory, early activation and precursor exhausted CD8+ T cells. A combined gene signature comprising these three CD8+ T cell clusters is associated with survival in patients. Here we show that targeting additional immune checkpoints expressed by intratumoral T cells, including PD1, is not effective, whereas CD40 agonist therapy recruits resistant tumors into responding to the combination of RT and CTLA4i, indicating the need to target different immune compartments.

The SEQC2 epigenomics quality control (EpiQC) study.

BACKGROUND: Cytosine modifications in DNA such as 5-methylcytosine (5mC) underlie a broad range of developmental processes, maintain cellular lineage specification, and can define or stratify types of cancer and other diseases. However, the wide variety of approaches available to interrogate these modifications has created a need for harmonized materials, methods, and rigorous benchmarking to improve genome-wide methylome sequencing applications in clinical and basic research. Here, we present a multi-platform assessment and cross-validated resource for epigenetics research from the FDA's Epigenomics Quality Control Group. RESULTS: Each sample is processed in multiple replicates by three whole-genome bisulfite sequencing (WGBS) protocols (TruSeq DNA methylation, Accel-NGS MethylSeq, and SPLAT), oxidative bisulfite sequencing (TrueMethyl), enzymatic deamination method (EMSeq), targeted methylation sequencing (Illumina Methyl Capture EPIC), single-molecule long-read nanopore sequencing from Oxford Nanopore Technologies, and 850k Illumina methylation arrays. After rigorous quality assessment and comparison to Illumina EPIC methylation microarrays and testing on a range of algorithms (Bismark, BitmapperBS, bwa-meth, and BitMapperBS), we find overall high concordance between assays, but also differences in efficiency of read mapping, CpG capture, coverage, and platform performance, and variable performance across 26 microarray normalization algorithms. CONCLUSIONS: The data provided herein can guide the use of these DNA reference materials in epigenomics research, as well as provide best practices for experimental design in future studies. By leveraging seven human cell lines that are designated as publicly available reference materials, these data can be used as a baseline to advance epigenomics research.

Epigenetic encoding, heritability and plasticity of glioma transcriptional cell states.

Single-cell RNA sequencing has revealed extensive transcriptional cell state diversity in cancer, often observed independently of genetic heterogeneity, raising the central question of how malignant cell states are encoded epigenetically. To address this, here we performed multiomics single-cell profiling-integrating DNA methylation, transcriptome and genotype within the same cells-of diffuse gliomas, tumors characterized by defined transcriptional cell state diversity. Direct comparison of the epigenetic profiles of distinct cell states revealed key switches for state transitions recapitulating neurodevelopmental trajectories and highlighted dysregulated epigenetic mechanisms underlying gliomagenesis. We further developed a quantitative framework to directly measure cell state heritability and transition dynamics based on high-resolution lineage trees in human samples. We demonstrated heritability of malignant cell states, with key differences in hierarchal and plastic cell state architectures in IDH-mutant glioma versus IDH-wild-type glioblastoma, respectively. This work provides a framework anchoring transcriptional cancer cell states in their epigenetic encoding, inheritance and transition dynamics.

Targeted detection and quantitation of histone modifications from 1,000 cells.

Histone post-translational modifications (PTMs) create a powerful regulatory mechanism for maintaining chromosomal integrity in cells. Histone acetylation and methylation, the most widely studied histone PTMs, act in concert with chromatin-associated proteins to control access to genetic information during transcription. Alterations in cellular histone PTMs have been linked to disease states and have crucial biomarker and therapeutic potential. Traditional bottom-up mass spectrometry of histones requires large numbers of cells, typically one million or more. However, for some cell subtype-specific studies, it is difficult or impossible to obtain such large numbers of cells and quantification of rare histone PTMs is often unachievable. An established targeted LC-MS/MS method was used to quantify the abundance of histone PTMs from cell lines and primary human specimens. Sample preparation was modified by omitting nuclear isolation and reducing the rounds of histone derivatization to improve detection of histone peptides down to 1,000 cells. In the current study, we developed and validated a quantitative LC-MS/MS approach tailored for a targeted histone assay of 75 histone peptides with as few as 10,000 cells. Furthermore, we were able to detect and quantify 61 histone peptides from just 1,000 primary human stem cells. Detection of 37 histone peptides was possible from 1,000 acute myeloid leukemia patient cells. We anticipate that this revised method can be used in many applications where achieving large cell numbers is challenging, including rare human cell populations.

Somatic mutations and cell identity linked by Genotyping of Transcriptomes.

Defining the transcriptomic identity of malignant cells is challenging in the absence of surface markers that distinguish cancer clones from one another, or from admixed non-neoplastic cells. To address this challenge, here we developed Genotyping of Transcriptomes (GoT), a method to integrate genotyping with high-throughput droplet-based single-cell RNA sequencing. We apply GoT to profile 38,290 CD34+ cells from patients with CALR-mutated myeloproliferative neoplasms to study how somatic mutations corrupt the complex process of human haematopoiesis. High-resolution mapping of malignant versus normal haematopoietic progenitors revealed an increasing fitness advantage with myeloid differentiation of cells with mutated CALR. We identified the unfolded protein response as a predominant outcome of CALR mutations, with a considerable dependency on cell identity, as well as upregulation of the NF-κB pathway specifically in uncommitted stem cells. We further extended the GoT toolkit to genotype multiple targets and loci that are distant from transcript ends. Together, these findings reveal that the transcriptional output of somatic mutations in myeloproliferative neoplasms is dependent on the native cell identity.

Epigenetic evolution and lineage histories of chronic lymphocytic leukaemia.

Genetic and epigenetic intra-tumoral heterogeneity cooperate to shape the evolutionary course of cancer1. Chronic lymphocytic leukaemia (CLL) is a highly informative model for cancer evolution as it undergoes substantial genetic diversification and evolution after therapy2,3. The CLL epigenome is also an important disease-defining feature4,5, and growing populations of cells in CLL diversify by stochastic changes in DNA methylation known as epimutations6. However, previous studies using bulk sequencing methods to analyse the patterns of DNA methylation were unable to determine whether epimutations affect CLL populations homogeneously. Here, to measure the epimutation rate at single-cell resolution, we applied multiplexed single-cell reduced-representation bisulfite sequencing to B cells from healthy donors and patients with CLL. We observed that the common clonal origin of CLL results in a consistently increased epimutation rate, with low variability in the cell-to-cell epimutation rate. By contrast, variable epimutation rates across healthy B cells reflect diverse evolutionary ages across the trajectory of B cell differentiation, consistent with epimutations serving as a molecular clock. Heritable epimutation information allowed us to reconstruct lineages at high-resolution with single-cell data, and to apply this directly to patient samples. The CLL lineage tree shape revealed earlier branching and longer branch lengths than in normal B cells, reflecting rapid drift after the initial malignant transformation and a greater proliferative history. Integration of single-cell bisulfite sequencing analysis with single-cell transcriptomes and genotyping confirmed that genetic subclones mapped to distinct clades, as inferred solely on the basis of epimutation information. Finally, to examine potential lineage biases during therapy, we profiled serial samples during ibrutinib-associated lymphocytosis, and identified clades of cells that were preferentially expelled from the lymph node after treatment, marked by distinct transcriptional profiles. The single-cell integration of genetic, epigenetic and transcriptional information thus charts the lineage history of CLL and its evolution with therapy.