Author Correction: Epigenetic stress responses induce muscle stem-cell ageing by Hoxa9 developmental signals.

An Amendment to this paper has been published and can be accessed via a link at the top of the paper.

DNMT1 Deficiency Impacts on Plasmacytoid Dendritic Cells in Homeostasis and Autoimmune Disease.

Dendritic cells (DCs) are heterogeneous immune regulators involved in autoimmune diseases. Epigenomic mechanisms orchestrating DC development and DC subset diversification remain insufficiently understood but could be important to modulate DC fate for clinical purposes. By combining whole-genome methylation assessment with the analysis of mice expressing reduced DNA methyltransferase 1 levels, we show that distinct DNA methylation levels and patterns are required for the development of plasmacytoid DC and conventional DC subsets. We provide clonal in vivo evidence for DC lineage establishment at the stem cell level, and we show that a high DNA methylation threshold level is essential for Flt3-dependent survival of DC precursors. Importantly, reducing methylation predominantly depletes plasmacytoid DC and alleviates systemic lupus erythematosus in an autoimmunity mouse model. This study shows how DNA methylation regulates the production of DC subsets and provides a potential rationale for targeting autoimmune disease using hypomethylating agents.

Epigenomic technologies for precision oncology.

Epigenetic patterns in a cell control the expression of genes and consequently determine the phenotype of a cell. Cancer cells possess altered epigenomes which include aberrant patterns of DNA methylation, histone tail modifications, nucleosome positioning and of the three-dimensional chromatin organization within a nucleus. These altered epigenetic patterns are potential useful biomarkers to detect cancer cells and to classify tumor types. In addition, the cancer epigenome dictates the response of a cancer cell to therapeutic intervention and, therefore its knowledge, will allow to predict response to different therapeutic approaches. Here we review the current state-of-the-art technologies that have been developed to decipher epigenetic patterns on the genomic level and discuss how these methods are potentially useful for precision oncology.

DNA methylation landscape of tumor-associated macrophages reveals pathways, transcription factors and prognostic value relevant to triple-negative breast cancer patients.

The accumulation of myeloid cells, particularly tumor-associated macrophages (TAMs), characterizes the tumor microenvironment (TME) of many solid cancers, including breast cancer. Compared to healthy tissue-resident macrophages, TAMs acquire distinct transcriptomes and tumor-promoting functions by largely unknown mechanisms. Here, we hypothesize the involvement of TME signaling and subsequent epigenetic reprogramming of TAMs. Using the 4T1 mouse model of triple-negative breast cancer, we demonstrate that the presence of cancer cells significantly alters the DNA methylation landscape of macrophages and, to a lesser extent, bone marrow-derived monocytes (BMDMs). TAM methylomes, dissected into BMDM-originating and TAM-specific epigenetic programs, implicated transcription factors (TFs) and signaling pathways involved in TAM reprogramming, correlated with cancer-specific gene expression patterns. Utilizing published single-cell gene expression data, we linked microenvironmentally-derived signals to the cancer-specific DNA methylation landscape of TAMs. These integrative analyses highlighted the role of altered cytokine production in the TME (eg, TGF-ß, IFN-γ and CSF1) on the induction of specific TFs (eg, FOSL2, STAT1 and RUNX3) responsible for the epigenetic reprogramming of TAMs. DNA methylation deconvolution identified a TAM-specific signature associated with the identified signaling pathways and TFs, corresponding with severe tumor grade and poor prognosis of breast cancer patients. Similarly, immunosuppressive TAM functions were identified, such as induction of the immune inhibitory receptor-ligand PD-L1 by DNA hypomethylation of Cd274. Collectively, these results provide strong evidence that the epigenetic landscapes of macrophages and monocytes are perturbed by the presence of breast cancer, pointing to molecular mechanisms of TAM reprogramming, impacting patient outcomes.

DNA methylation biomarkers for noninvasive detection of triple-negative breast cancer using liquid biopsy.

Noninvasive detection of aberrant DNA methylation could provide invaluable biomarkers for earlier detection of triple-negative breast cancer (TNBC) which could help clinicians with easier and more efficient treatment options. We evaluated genome-wide DNA methylation data derived from TNBC and normal breast tissues, peripheral blood of TNBC cases and controls and reference samples of sorted blood and mammary cells. Differentially methylated regions (DMRs) between TNBC and normal breast tissues were stringently selected, verified and externally validated. A machine-learning algorithm was applied to select the top DMRs, which then were evaluated on plasma-derived circulating cell-free DNA (cfDNA) samples of TNBC patients and healthy controls. We identified 23 DMRs accounting for the methylation profile of blood cells and reference mammary cells and then selected six top DMRs for cfDNA analysis. We quantified un-/methylated copies of these DMRs by droplet digital PCR analysis in a plasma test set from TNBC patients and healthy controls and confirmed our findings obtained on tissues. Differential cfDNA methylation was confirmed in an independent validation set of plasma samples. A methylation score combining signatures of the top three DMRs overlapping with the SPAG6, LINC10606 and TBCD/ZNF750 genes had the best capability to discriminate TNBC patients from controls (AUC = 0.78 in the test set and AUC = 0.74 in validation set). Our findings demonstrate the usefulness of cfDNA-based methylation signatures as noninvasive liquid biopsy markers for the diagnosis of TNBC.

The age of the bone marrow microenvironment influences B-cell acute lymphoblastic leukemia progression via CXCR5-CXCL13.

B-cell acute lymphoblastic leukemia (B-ALL) occurs most commonly in children, whereas chronic myeloid leukemia is more frequent in adults. The myeloid bias of hematopoiesis in elderly individuals has been considered causative, but the age of the bone marrow microenvironment (BMM) may be contributory. Using various murine models of B-ALL in young vs old mice, we recapitulated B-ALL preponderance in children vs adults. We showed differential effects of young vs old BM macrophages on B-ALL cell function. Molecular profiling using RNA- and ATAC-sequencing revealed pronounced differences in young vs old BMM-derived macrophages and enrichment for gene sets associated with inflammation. In concordance with the role of C-X-C motif chemokine (CXCL) 13 for disease-associated B-cell chemoattraction, we found CXCL13 to be highly expressed in young macrophages on a translational compared with a transcriptional level. Inhibition of CXCL13 in BM macrophages impaired leukemia cell migration and decreased the proliferation of cocultured B-ALL cells, whereas recombinant CXCL13 increased pAKT and B-ALL cell expansion. Pretreatment of B-ALL-initiating cells with CXCL13 accelerated B-ALL progression. Deficiency of Cxcr5, the receptor for CXCL13, on B-ALL-initiating cells prolonged murine survival, whereas high expression of CXCR5 in pediatric B-ALL may predict central nervous system relapse. CXCL13 staining was increased in bone sections from pediatric compared with adult patients with B-ALL. Taken together, our study shows that the age of the BMM and, in particular, BM macrophages influence the leukemia phenotype. The CXCR5-CXCL13 axis may act as prognostic marker and an attractive novel target for the treatment of B-ALL.

Molecular tumor classification using DNA methylome analysis.

Tumor classifiers based on molecular patterns promise to define and reliably classify tumor entities. The high tissue- and cell type-specificity of DNA methylation, as well as its high stability, makes DNA methylation an ideal choice for the development of tumor classifiers. Herein, we review existing tumor classifiers using DNA methylome analysis and will provide an overview on their emerging impact on cancer classification, the detection of novel cancer subentities and patient stratification with a focus on brain tumors, sarcomas and hematopoietic malignancies. Furthermore, we provide an outlook on the enormous potential of DNA methylome analysis to complement classical histopathological and genetic diagnostics, including the emerging field of epigenomic analysis in liquid biopsies.

Methrix: an R/Bioconductor package for systematic aggregation and analysis of bisulfite sequencing data.

MOTIVATION: Whole-genome bisulfite sequencing (WGBS) measures DNA methylation at base pair resolution resulting in large bedGraph like coverage files. Current options for processing such files are hindered by discrepancies in file format specification, speed, and memory requirements. RESULTS: We developed methrix, an R package, which provides a toolset for systematic analysis of large datasets. Core functionality of the package includes a comprehensive bedGraph or similar tab-separated text file reader-which summarizes methylation calls based on annotated reference indices, infers and collapses strands and handles uncovered reference CpG sites while facilitating a flexible input file format specification. Additional optimized functions for quality control filtering, subsetting and visualization allow user-friendly and effective processing of WGBS results. Easy integration with tools for differentially methylated region (DMR) calling and annotation further eases the analysis of genome-wide methylation data. Overall, methrix enriches established WGBS workflows by bringing together computational efficiency and versatile functionality. AVAILABILITY AND IMPLEMENTATION: Methrix is implemented as an R package, made available under MIT license at https://github.com/CompEpigen/methrix and can be installed from the Bioconductor repository. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Epigenetic stress responses induce muscle stem-cell ageing by Hoxa9 developmental signals.

The functionality of stem cells declines during ageing, and this decline contributes to ageing-associated impairments in tissue regeneration and function. Alterations in developmental pathways have been associated with declines in stem-cell function during ageing, but the nature of this process remains poorly understood. Hox genes are key regulators of stem cells and tissue patterning during embryogenesis with an unknown role in ageing. Here we show that the epigenetic stress response in muscle stem cells (also known as satellite cells) differs between aged and young mice. The alteration includes aberrant global and site-specific induction of active chromatin marks in activated satellite cells from aged mice, resulting in the specific induction of Hoxa9 but not other Hox genes. Hoxa9 in turn activates several developmental pathways and represents a decisive factor that separates satellite cell gene expression in aged mice from that in young mice. The activated pathways include most of the currently known inhibitors of satellite cell function in ageing muscle, including Wnt, TGFß, JAK/STAT and senescence signalling. Inhibition of aberrant chromatin activation or deletion of Hoxa9 improves satellite cell function and muscle regeneration in aged mice, whereas overexpression of Hoxa9 mimics ageing-associated defects in satellite cells from young mice, which can be rescued by the inhibition of Hoxa9-targeted developmental pathways. Together, these data delineate an altered epigenetic stress response in activated satellite cells from aged mice, which limits satellite cell function and muscle regeneration by Hoxa9-dependent activation of developmental pathways.

Hepatic leukemia factor is a novel leukemic stem cell regulator in DNMT3A, NPM1, and FLT3-ITD triple-mutated AML.

FLT3, DNMT3A, and NPM1 are the most frequently mutated genes in cytogenetically normal acute myeloid leukemia (AML), but little is known about how these mutations synergize upon cooccurrence. Here we show that triple-mutated AML is characterized by high leukemia stem cell (LSC) frequency, an aberrant leukemia-specific GPR56 highCD34low immunophenotype, and synergistic upregulation of Hepatic Leukemia Factor (HLF). Cell sorting based on the LSC marker GPR56 allowed isolation of triple-mutated from DNMT3A/NPM1 double-mutated subclones. Moreover, in DNMT3A R882-mutated patients, CpG hypomethylation at the HLF transcription start site correlated with high HLF mRNA expression, which was itself associated with poor survival. Loss of HLF via CRISPR/Cas9 significantly reduced the CD34+GPR56+ LSC compartment of primary human triple-mutated AML cells in serial xenotransplantation assays. HLF knockout cells were more actively cycling when freshly harvested from mice, but rapidly exhausted when reintroduced in culture. RNA sequencing of primary human triple-mutated AML cells after shRNA-mediated HLF knockdown revealed the NOTCH target Hairy and Enhancer of Split 1 (HES1) and the cyclin-dependent kinase inhibitor CDKN1C/p57 as novel targets of HLF, potentially mediating these effects. Overall, our data establish HLF as a novel LSC regulator in this genetically defined high-risk AML subgroup.

Integrating Patient Data Into Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review.

BACKGROUND: Recent years have been witnessing a substantial improvement in the accuracy of skin cancer classification using convolutional neural networks (CNNs). CNNs perform on par with or better than dermatologists with respect to the classification tasks of single images. However, in clinical practice, dermatologists also use other patient data beyond the visual aspects present in a digitized image, further increasing their diagnostic accuracy. Several pilot studies have recently investigated the effects of integrating different subtypes of patient data into CNN-based skin cancer classifiers. OBJECTIVE: This systematic review focuses on the current research investigating the impact of merging information from image features and patient data on the performance of CNN-based skin cancer image classification. This study aims to explore the potential in this field of research by evaluating the types of patient data used, the ways in which the nonimage data are encoded and merged with the image features, and the impact of the integration on the classifier performance. METHODS: Google Scholar, PubMed, MEDLINE, and ScienceDirect were screened for peer-reviewed studies published in English that dealt with the integration of patient data within a CNN-based skin cancer classification. The search terms skin cancer classification, convolutional neural network(s), deep learning, lesions, melanoma, metadata, clinical information, and patient data were combined. RESULTS: A total of 11 publications fulfilled the inclusion criteria. All of them reported an overall improvement in different skin lesion classification tasks with patient data integration. The most commonly used patient data were age, sex, and lesion location. The patient data were mostly one-hot encoded. There were differences in the complexity that the encoded patient data were processed with regarding deep learning methods before and after fusing them with the image features for a combined classifier. CONCLUSIONS: This study indicates the potential benefits of integrating patient data into CNN-based diagnostic algorithms. However, how exactly the individual patient data enhance classification performance, especially in the case of multiclass classification problems, is still unclear. Moreover, a substantial fraction of patient data used by dermatologists remains to be analyzed in the context of CNN-based skin cancer classification. Further exploratory analyses in this promising field may optimize patient data integration into CNN-based skin cancer diagnostics for patients' benefits.

Germline SDHB-inactivating mutation in gastric spindle cell sarcoma.

Gastrointestinal stromal tumors (GISTs) are the most frequent mesenchymal tumors of the gastrointestinal tract. Inactivating mutations or epigenetic deregulation of succinate dehydrogenase complex (SDH) genes are considered defining features of a subset of GIST occurring in the stomach. Based on comprehensive molecular profiling and biochemical analysis within a precision oncology program, we identified hallmarks of SDH deficiency (germline SDHB-inactivating mutation accompanied by somatic loss of heterozygosity, lack of SDHB expression, global DNA hypermethylation, and elevated succinate/fumarate ratio) in a 40-year-old woman with undifferentiated gastric spindle cell sarcoma that did not meet the diagnostic criteria for other mesenchymal tumors of the stomach, including GIST. These data reveal that the loss of SDH function can be involved in the pathogenesis of non-GIST sarcoma of the gastrointestinal tract.

Integrative Analysis Defines Distinct Prognostic Subgroups of Intrahepatic Cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (iCCA) is the second most common primary liver cancer. It is defined by cholangiocytic differentiation and has poor prognosis. Recently, epigenetic processes have been shown to play an important role in cholangiocarcinogenesis. We performed an integrative analysis on 52 iCCAs using both genetic and epigenetic data with a specific focus on DNA methylation components. We found recurrent isocitrate dehydrogenase 1 (IDH1) and IDH2 (28%) gene mutations, recurrent arm-length copy number alterations (CNAs), and focal alterations such as deletion of 3p21 or amplification of 12q15, which affect BRCA1 Associated Protein 1, polybromo 1, and mouse double minute 2 homolog. DNA methylome analysis revealed excessive hypermethylation of iCCA, affecting primarily the bivalent genomic regions marked with both active and repressive histone modifications. Integrative clustering of genetic and epigenetic data identified four iCCA subgroups with prognostic relevance further designated as IDH, high (H), medium (M), and low (L) alteration groups. The IDH group consisted of all samples with IDH1 or IDH2 mutations and showed, together with the H group, a highly disrupted genome, characterized by frequent deletions of chromosome arms 3p and 6q. Both groups showed excessive hypermethylation with distinct patterns. The M group showed intermediate characteristics regarding both genetic and epigenetic marks, whereas the L group exhibited few methylation changes and mutations and a lack of CNAs. Methylation-based latent component analysis of cell-type composition identified differences among these four groups. Prognosis of the H and M groups was significantly worse than that of the L group. Conclusion: Using an integrative genomic and epigenomic analysis approach, we identified four major iCCA subgroups with widespread genomic and epigenomic differences and prognostic implications. Furthermore, our data suggest differences in the cell-of-origin of the iCCA subtypes.

Impact of DNA methylation programming on normal and pre-leukemic hematopoiesis.

Epigenome regulation is a critical mechanism that governs cell identity, lineage specification and developmental cell fates. With the advent of low-input and single-cell technologies as well as sophisticated cell labeling techniques, our understanding of transcriptional and epigenetic regulation of hematopoiesis is currently undergoing dramatic changes. Increasingly, evidence suggests that the epigenome conformation acts as a critical decision-making mechanism that instructs self-renewal, differentiation and developmental fates of hematopoietic progenitor cells. When dysregulated, this leads to the evolution of disease states such as leukemia. Indeed, aberrations in DNA methylation, histone modifications and genome architecture are characteristic features of many hematopoietic neoplasms in which epigenetic enzymes are frequently mutated. Sequencing studies and characterization of the epigenetic landscape in lymphomas, leukemias and in aged healthy individuals with clonal hematopoiesis have been indispensible to identify epigenetic regulators that play a role in transformation or pre-disposition to hematopoietic malignancies. In this review, we outline the current view of the hematopoietic system and the epigenetic mechanisms regulating hematopoiesis under homeostatic conditions, with a particular focus on the role of DNA methylation in this process. We will also summarize the current knowledge on the mechanisms underlying dysregulated DNA methylation in hematologic malignancies and how this contributes to our understanding of the physiological functions of epigenetic regulators in hematopoiesis.

Histone methyltransferase SETDB1 contributes to melanoma tumorigenesis and serves as a new potential therapeutic target.

Alterations in histone modifications play a crucial role in the progression of various types of cancer. The histone methyltransferase SETDB1 catalyzes the addition of methyl groups to histone H3 at lysine 9. Here, we describe how overexpression of SETDB1 contributes to melanoma tumorigenesis. SETDB1 is highly amplified in melanoma cells and in the patient tumors. Increased expression of SETDB1, which correlates with SETDB1 amplification, is associated with a more aggressive phenotype in in vitro and in vivo studies. Mechanistically, SETDB1 implements its effects via regulation of thrombospondin 1, and the SET-domain of SETDB1 is essential for the maintenance of its tumorigenic activity. Inhibition of SETDB1 reduces cell growth in melanomas resistant to targeted treatments. Our results indicate that SETDB1 is a major driver of melanoma development and may serve as a potential future target for the treatment of this disease.

Identification of Cell Type-Specific Differences in Erythropoietin Receptor Signaling in Primary Erythroid and Lung Cancer Cells.

Lung cancer, with its most prevalent form non-small-cell lung carcinoma (NSCLC), is one of the leading causes of cancer-related deaths worldwide, and is commonly treated with chemotherapeutic drugs such as cisplatin. Lung cancer patients frequently suffer from chemotherapy-induced anemia, which can be treated with erythropoietin (EPO). However, studies have indicated that EPO not only promotes erythropoiesis in hematopoietic cells, but may also enhance survival of NSCLC cells. Here, we verified that the NSCLC cell line H838 expresses functional erythropoietin receptors (EPOR) and that treatment with EPO reduces cisplatin-induced apoptosis. To pinpoint differences in EPO-induced survival signaling in erythroid progenitor cells (CFU-E, colony forming unit-erythroid) and H838 cells, we combined mathematical modeling with a method for feature selection, the L1 regularization. Utilizing an example model and simulated data, we demonstrated that this approach enables the accurate identification and quantification of cell type-specific parameters. We applied our strategy to quantitative time-resolved data of EPO-induced JAK/STAT signaling generated by quantitative immunoblotting, mass spectrometry and quantitative real-time PCR (qRT-PCR) in CFU-E and H838 cells as well as H838 cells overexpressing human EPOR (H838-HA-hEPOR). The established parsimonious mathematical model was able to simultaneously describe the data sets of CFU-E, H838 and H838-HA-hEPOR cells. Seven cell type-specific parameters were identified that included for example parameters for nuclear translocation of STAT5 and target gene induction. Cell type-specific differences in target gene induction were experimentally validated by qRT-PCR experiments. The systematic identification of pathway differences and sensitivities of EPOR signaling in CFU-E and H838 cells revealed potential targets for intervention to selectively inhibit EPO-induced signaling in the tumor cells but leave the responses in erythroid progenitor cells unaffected. Thus, the proposed modeling strategy can be employed as a general procedure to identify cell type-specific parameters and to recommend treatment strategies for the selective targeting of specific cell types.

Dysregulated serum response factor triggers formation of hepatocellular carcinoma.

UNLABELLED: The ubiquitously expressed transcriptional regulator serum response factor (SRF) is controlled by both Ras/MAPK (mitogen-activated protein kinase) and Rho/actin signaling pathways, which are frequently activated in hepatocellular carcinoma (HCC). We generated SRF-VP16iHep mice, which conditionally express constitutively active SRF-VP16 in hepatocytes, thereby controlling subsets of both Ras/MAPK- and Rho/actin-stimulated target genes. All SRF-VP16iHep mice develop hyperproliferative liver nodules that progresses to lethal HCC. Some murine (m)HCCs acquire Ctnnb1 mutations equivalent to those in human (h)HCC. The resulting transcript signatures mirror those of a distinct subgroup of hHCCs, with shared activation of oncofetal genes including Igf2, correlating with CpG hypomethylation at the imprinted Igf2/H19 locus. CONCLUSION: SRF-VP16iHep mHCC reveal convergent Ras/MAPK and Rho/actin signaling as a highly oncogenic driver mechanism for hepatocarcinogenesis. This suggests simultaneous inhibition of Ras/MAPK and Rho/actin signaling as a treatment strategy in hHCC therapy.

Neutrophil-specific expression of JAK2-V617F or CALRmut induces distinct inflammatory profiles in myeloproliferative neoplasia.

BACKGROUND: Neutrophils play a crucial role in inflammation and in the increased thrombotic risk in myeloproliferative neoplasms (MPNs). We have investigated how neutrophil-specific expression of JAK2-V617F or CALRdel re-programs the functions of neutrophils. METHODS: Ly6G-Cre JAK2-V617F and Ly6G-Cre CALRdel mice were generated. MPN parameters as blood counts, splenomegaly and bone marrow histology were compared to wild-type mice. Megakaryocyte differentiation was investigated using lineage-negative bone marrow cells upon in vitro incubation with TPO/IL-1ß. Cytokine concentrations in serum of mice were determined by Mouse Cytokine Array. IL-1α expression in various hematopoietic cell populations was determined by intracellular FACS analysis. RNA-seq to analyse gene expression of inflammatory cytokines was performed in isolated neutrophils from JAK2-V617F and CALR-mutated mice and patients. Bioenergetics of neutrophils were recorded on a Seahorse extracellular flux analyzer. Cell motility of neutrophils was monitored in vitro (time lapse microscopy), and in vivo (two-photon microscopy) upon creating an inflammatory environment. Cell adhesion to integrins, E-selectin and P-selection was investigated in-vitro. Statistical analysis was carried out using GraphPad Prism. Data are shown as mean ± SEM. Unpaired, two-tailed t-tests were applied. RESULTS: Strikingly, neutrophil-specific expression of JAK2-V617F, but not CALRdel, was sufficient to induce pro-inflammatory cytokines including IL-1 in serum of mice. RNA-seq analysis in neutrophils from JAK2-V617F mice and patients revealed a distinct inflammatory chemokine signature which was not expressed in CALR-mutant neutrophils. In addition, IL-1 response genes were significantly enriched in neutrophils of JAK2-V617F patients as compared to CALR-mutant patients. Thus, JAK2-V617F positive neutrophils, but not CALR-mutant neutrophils, are pathogenic drivers of inflammation in MPN. In line with this, expression of JAK2-V617F or CALRdel elicited a significant difference in the metabolic phenotype of neutrophils, suggesting a stronger inflammatory activity of JAK2-V617F cells. Furthermore, JAK2-V617F, but not CALRdel, induced a VLA4 integrin-mediated adhesive phenotype in neutrophils. This resulted in reduced neutrophil migration in vitro and in an inflamed vessel. This mechanism may contribute to the increased thrombotic risk of JAK2-V617F patients compared to CALR-mutant individuals. CONCLUSIONS: Taken together, our findings highlight genotype-specific differences in MPN-neutrophils that have implications for the differential pathophysiology of JAK2-V617F versus CALR-mutant disease.

Multi-omic and functional analysis for classification and treatment of sarcomas with FUS-TFCP2 or EWSR1-TFCP2 fusions.

Linking clinical multi-omics with mechanistic studies may improve the understanding of rare cancers. We leverage two precision oncology programs to investigate rhabdomyosarcoma with FUS/EWSR1-TFCP2 fusions, an orphan malignancy without effective therapies. All tumors exhibit outlier ALK expression, partly accompanied by intragenic deletions and aberrant splicing resulting in ALK variants that are oncogenic and sensitive to ALK inhibitors. Additionally, recurrent CKDN2A/MTAP co-deletions provide a rationale for PRMT5-targeted therapies. Functional studies show that FUS-TFCP2 blocks myogenic differentiation, induces transcription of ALK and truncated TERT, and inhibits DNA repair. Unlike other fusion-driven sarcomas, TFCP2-rearranged tumors exhibit genomic instability and signs of defective homologous recombination. DNA methylation profiling demonstrates a close relationship with undifferentiated sarcomas. In two patients, sarcoma was preceded by benign lesions carrying FUS-TFCP2, indicating stepwise sarcomagenesis. This study illustrates the potential of linking precision oncology with preclinical research to gain insight into the classification, pathogenesis, and therapeutic vulnerabilities of rare cancers.

Dynamic DNA methylation reveals novel cis-regulatory elements in mouse hematopoiesis.

Differentiation of hematopoietic stem and progenitor cells to terminally differentiated immune cells is accompanied by large-scale remodeling of the DNA methylation landscape. Although significant insights into the molecular mechanisms of hematopoietic tissue regeneration were derived from mouse models, profiling of DNA methylation has been hampered by high cost or low resolution using available methods. The recent development of the Infinium Mouse Methylation BeadChip (MMBC) array facilitates methylation profiling of the mouse genome at a single CpG resolution at affordable cost. We extended the RnBeads package to provide a computational framework for the analysis of MMBC data. This framework was applied to a newly generated reference map of mouse hematopoiesis encompassing nine different cell types. Analysis of dynamically regulated CpG sites showed progressive and unidirectional DNA methylation changes from hematopoietic stem and progenitor cells to differentiated hematopoietic cells and allowed the identification of lineage- and cell type-specific DNA methylation programs. Comparison with previously published catalogs of cis-regulatory elements (CREs) revealed 12,856 novel putative CREs that were dynamically regulated by DNA methylation (mdCREs). These mdCREs were predominantly associated with patterns of cell type-specific DNA hypomethylation and could be identified as epigenetic control regions regulating the expression of key hematopoietic genes during differentiation. In summary, we established an analysis pipeline for MMBC data sets and provide a DNA methylation atlas of mouse hematopoiesis. This resource allowed us to identify novel putative CREs involved in hematopoiesis and will serve as a platform to study epigenetic regulation of normal and malignant hematopoiesis.