The BLUEPRINT Data Analysis Portal

Single-stranded pre-methylated 5mC adapters uncover the methylation profile of plasma ultrashort Single-stranded cell-free DNA

Whole-genome bisulfite sequencing (BS-Seq) measures cytosine methylation changes at single-base resolution and can be used to profile cell-free DNA (cfDNA). In plasma, ultrashort single-stranded cfDNA (uscfDNA, ∼50 nt) has been identified together with 167 bp double-stranded mononucleosomal cell-free DNA (mncfDNA). However, the methylation profile of uscfDNA has not been described. Conventional BS-Seq workflows may not be helpful because bisulfite conversion degrades larger DNA into smaller fragments, leading to erroneous categorization as uscfDNA. We describe the '5mCAdpBS-Seq' workflow in which pre-methylated 5mC (5-methylcytosine) single-stranded adapters are ligated to heat-denatured cfDNA before bisulfite conversion. This method retains only DNA fragments that are unaltered by bisulfite treatment, resulting in less biased uscfDNA methylation analysis. Using 5mCAdpBS-Seq, uscfDNA had lower levels of DNA methylation (∼15%) compared to mncfDNA and was enriched in promoters and CpG islands. Hypomethylated uscfDNA fragments were enriched in upstream transcription start sites (TSSs), and the intensity of enrichment was correlated with expressed genes of hemopoietic cells. Using tissue-of-origin deconvolution, we inferred that uscfDNA is derived primarily from eosinophils, neutrophils, and monocytes. As proof-of-principle, we show that characteristics of the methylation profile of uscfDNA can distinguish non-small cell lung carcinoma from non-cancer samples. The 5mCAdpBS-Seq workflow is recommended for any cfDNA methylation-based investigations.

The tidyomics ecosystem: enhancing omic data analyses

The growth of omic data presents evolving challenges in data manipulation, analysis and integration. Addressing these challenges, Bioconductor provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming offers a revolutionary data organization and manipulation standard. Here we present the tidyomics software ecosystem, bridging Bioconductor to the tidy R paradigm. This ecosystem aims to streamline omic analysis, ease learning and encourage cross-disciplinary collaborations. We demonstrate the effectiveness of tidyomics by analyzing 7.5 million peripheral blood mononuclear cells from the Human Cell Atlas, spanning six data frameworks and ten analysis tools.

The tidyomics ecosystem: Enhancing omic data analyses

The growth of omic data presents evolving challenges in data manipulation, analysis, and integration. Addressing these challenges, Bioconductor1 provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming2 offers a revolutionary standard for data organisation and manipulation. Here, we present the tidyomics software ecosystem, bridging Bioconductor to the tidy R paradigm. This ecosystem aims to streamline omic analysis, ease learning, and encourage cross-disciplinary collaborations. We demonstrate the effectiveness of tidyomics by analysing 7.5 million peripheral blood mononuclear cells from the Human Cell Atlas3, spanning six data frameworks and ten analysis tools.

A multi-organ map of the human immune system across age, sex and ethnicity

Understanding tissue biology's heterogeneity is crucial for advancing precision medicine. Despite the centrality of the immune system in tissue homeostasis, a detailed and comprehensive map of immune cell distribution and interactions across human tissues and demographics remains elusive. To fill this gap, we harmonised data from 12,981 single-cell RNA sequencing samples and curated 29 million cells from 45 anatomical sites to create a comprehensive compositional and transcriptional healthy map of the healthy immune system. We used this resource and a novel multilevel modelling approach to track immune ageing and test differences across sex and ethnicity. We uncovered conserved and tissue-specific immune-ageing programs, resolved sex-dependent differential ageing and identified ethnic diversity in clinically critical immune checkpoints. This study provides a quantitative baseline of the immune system, facilitating advances in precision medicine. By sharing our immune map, we hope to catalyse further breakthroughs in cancer, infectious disease, immunology and precision medicine.

Tissue informative cell-free DNA methylation sites in amyotrophic lateral sclerosis

Cell-free DNA (cfDNA) is increasingly recognized as a promising biomarker candidate for disease monitoring. However, its utility in neurodegenerative diseases, like amyotrophic lateral sclerosis (ALS), remains underexplored. Existing biomarker discovery approaches are tailored to a specific disease context or are too expensive to be clinically practical. Here, we address these challenges through a new approach combining advances in molecular and computational technologies. First, we develop statistical tools to select tissue-informative DNA methylation sites relevant to a disease process of interest. We then employ a capture protocol to select these sites and perform targeted methylation sequencing. Multi-modal information about the DNA methylation patterns are then utilized in machine learning algorithms trained to predict disease status and disease progression. We applied our method to two independent cohorts of ALS patients and controls (n=192). Overall, we found that the targeted sites accurately predicted ALS status and replicated between cohorts. Additionally, we identified epigenetic features associated with ALS phenotypes, including disease severity. These findings highlight the potential of cfDNA as a non-invasive biomarker for ALS.

Epigenetic variation impacts individual differences in the transcriptional response to influenza infection

Humans display remarkable interindividual variation in their immune response to identical challenges. Yet, our understanding of the genetic and epigenetic factors contributing to such variation remains limited. Here we performed in-depth genetic, epigenetic and transcriptional profiling on primary macrophages derived from individuals of European and African ancestry before and after infection with influenza A virus. We show that baseline epigenetic profiles are strongly predictive of the transcriptional response to influenza A virus across individuals. Quantitative trait locus (QTL) mapping revealed highly coordinated genetic effects on gene regulation, with many cis-acting genetic variants impacting concomitantly gene expression and multiple epigenetic marks. These data reveal that ancestry-associated differences in the epigenetic landscape can be genetically controlled, even more than gene expression. Lastly, among QTL variants that colocalized with immune-disease loci, only 7% were gene expression QTL, while the remaining genetic variants impact epigenetic marks, stressing the importance of considering molecular phenotypes beyond gene expression in disease-focused studies.

A personalized network framework reveals predictive axis of anti-TNF response across diseases

Personalized treatment of complex diseases has been mostly predicated on biomarker identification of one drug-disease combination at a time. Here, we use a computational approach termed Disruption Networks to generate a data type, contextualized by cell-centered individual-level networks, that captures biology otherwise overlooked when performing standard statistics. This data type extends beyond the "feature level space", to the "relations space", by quantifying individual-level breaking or rewiring of cross-feature relations. Applying Disruption Networks to dissect high-dimensional blood data, we discover and validate that the RAC1-PAK1 axis is predictive of anti-TNF response in inflammatory bowel disease. Intermediate monocytes, which correlate with the inflammatory state, play a key role in the RAC1-PAK1 responses, supporting their modulation as a therapeutic target. This axis also predicts response in rheumatoid arthritis, validated in three public cohorts. Our findings support blood-based drug response diagnostics across immune-mediated diseases, implicating common mechanisms of non-response.

cellsig plug-in enhances CIBERSORTx signature selection for multidataset transcriptomes with sparse multilevel modelling

MOTIVATION

The precise characterization of cell-type transcriptomes is pivotal to understanding cellular lineages, deconvolution of bulk transcriptomes, and clinical applications. Single-cell RNA sequencing resources like the Human Cell Atlas have revolutionised cell-type profiling. However, challenges persist due to data heterogeneity and discrepancies across different studies. One limitation of prevailing tools such as CIBERSORTx is their inability to address hierarchical data structures and handle nonoverlapping gene sets across samples, relying on filtering or imputation.

RESULTS

Here, we present cellsig, a Bayesian sparse multilevel model designed to improve signature estimation by adjusting data for multilevel effects and modelling for gene-set sparsity. Our model is tailored to large-scale, heterogeneous pseudobulk and bulk RNA sequencing data collections with nonoverlapping gene sets. We tested the performances of cellsig on a novel curated Human Bulk Cell-type Catalogue, which harmonizes 1435 samples across 58 datasets. We show that cellsig significantly enhances cell-type marker gene ranking performance. This approach is valuable for cell-type signature selection, with implications for marker gene validation, single-cell annotation, and deconvolution benchmarks.

AVAILABILITY AND IMPLEMENTATION

Codes and the interactive app are available at https://github.com/stemangiola/cellsig; and the database is available at https://doi.org/10.5281/zenodo.7582421.

An intronic LINE-1 regulates IFNAR1 expression in human immune cells

BACKGROUND

Despite their origins as selfish parasitic sequences, some transposons in the human genome have been co-opted to serve as regulatory elements, contributing to the evolution of transcriptional networks. Most well-characterized examples of transposon-derived regulatory elements derive from endogenous retroviruses (ERVs), due to the intrinsic regulatory activity of proviral long terminal repeat regions. However, one subclass of transposable elements, the Long Interspersed Nuclear Elements (LINEs), have been largely overlooked in the search for functional regulatory transposons, and considered to be broadly epigenetically repressed.

RESULTS

We examined the chromatin state of LINEs by analyzing epigenomic data from human immune cells. Many LINEs are marked by the repressive H3K9me3 modification, but a subset exhibits evidence of enhancer activity in human immune cells despite also showing evidence of epigenetic repression. We hypothesized that these competing forces of repressive and activating epigenetic marks might lead to inducible enhancer activity. We investigated a specific L1M2a element located within the first intron of Interferon Alpha/Beta Receptor 1 (IFNAR1). This element shows epigenetic signatures of B cell-specific enhancer activity, despite being repressed by the Human Silencing Hub (HUSH) complex. CRISPR deletion of the element in B lymphoblastoid cells revealed that the element acts as an enhancer that regulates both steady state and interferon-inducible expression of IFNAR1.

CONCLUSIONS

Our study experimentally demonstrates that an L1M2a element was co-opted to function as an interferon-inducible enhancer of IFNAR1, creating a feedback loop wherein IFNAR1 is transcriptionally upregulated by interferon signaling. This finding suggests that other LINEs may exhibit cryptic cell type-specific or context-dependent enhancer activity. LINEs have received less attention than ERVs in the effort to understand the contribution of transposons to the regulatory landscape of cellular genomes, but these are likely important, lineage-specific players in the rapid evolution of immune system regulatory networks and deserve further study.

Inferring chromatin accessibility during murine hematopoiesis through phylogenetic analysis

OBJECTIVE

Diversification of cell types and changes in epigenetic states during cell differentiation processes are important for understanding development. Recently, phylogenetic analysis using DNA methylation and histone modification information has been shown useful for inferring these processes. The purpose of this study was to examine whether chromatin accessibility data can help infer these processes in murine hematopoiesis.

RESULTS

Chromatin accessibility data could partially infer the hematopoietic differentiation hierarchy. Furthermore, based on the ancestral state estimation of internal nodes, the open/closed chromatin states of differentiating progenitor cells could be predicted with a specificity of 0.86-0.99 and sensitivity of 0.29-0.72. These results suggest that the phylogenetic analysis of chromatin accessibility could offer important information on cell differentiation, particularly for organisms from which progenitor cells are difficult to obtain.

Circulating cell-free methylated DNA reveals tissue-specific, cellular damage from radiation treatment

Radiation therapy is an effective cancer treatment, although damage to healthy tissues is common. Here we analyzed cell-free, methylated DNA released from dying cells into the circulation to evaluate radiation-induced cellular damage in different tissues. To map the circulating DNA fragments to human and mouse tissues, we established sequencing-based, cell-type-specific reference DNA methylation atlases. We found that cell-type-specific DNA blocks were mostly hypomethylated and located within signature genes of cellular identity. Cell-free DNA fragments were captured from serum samples by hybridization to CpG-rich DNA panels and mapped to the DNA methylation atlases. In a mouse model, thoracic radiation-induced tissue damage was reflected by dose-dependent increases in lung endothelial and cardiomyocyte methylated DNA in serum. The analysis of serum samples from patients with breast cancer undergoing radiation treatment revealed distinct dose-dependent and tissue-specific epithelial and endothelial responses to radiation across multiple organs. Strikingly, patients treated for right-sided breast cancers also showed increased hepatocyte and liver endothelial DNA in the circulation, indicating the impact on liver tissues. Thus, changes in cell-free methylated DNA can uncover cell-type-specific effects of radiation and provide a readout of the biologically effective radiation dose received by healthy tissues.

sciMET-cap: High-throughput single-cell methylation analysis with a reduced sequencing burden

DNA methylation is a key component of the mammalian epigenome, playing a regulatory role in development, disease, and other processes. Robust, high-throughput single-cell DNA methylation assays are now possible (sciMET); however, the genome-wide nature of DNA methylation results in a high sequencing burden per cell. Here, we leverage target enrichment with sciMET to capture sufficient information per cell for cell type assignment using substantially fewer sequence reads (sciMET-cap). Sufficient off-target coverage further enables the production of near-complete methylomes for individual cell types. We characterize sciMET-cap on human PBMCs and brain (middle frontal gyrus).

Exploring the Role of Enhancer-Mediated Transcriptional Regulation in Precision Biology

The emergence of precision biology has been driven by the development of advanced technologies and techniques in high-resolution biological research systems. Enhancer-mediated transcriptional regulation, a complex network of gene expression and regulation in eukaryotes, has attracted significant attention as a promising avenue for investigating the underlying mechanisms of biological processes and diseases. To address biological problems with precision, large amounts of data, functional information, and research on the mechanisms of action of biological molecules is required to address biological problems with precision. Enhancers, including typical enhancers and super enhancers, play a crucial role in gene expression and regulation within this network. The identification and targeting of disease-associated enhancers hold the potential to advance precision medicine. In this review, we present the concepts, progress, importance, and challenges in precision biology, transcription regulation, and enhancers. Furthermore, we propose a model of transcriptional regulation for multi-enhancers and provide examples of their mechanisms in mammalian cells, thereby enhancing our understanding of how enhancers achieve precise regulation of gene expression in life processes. Precision biology holds promise in providing new tools and platforms for discovering insights into gene expression and disease occurrence, ultimately benefiting individuals and society as a whole.

Cell type deconvolution of methylated cell-free DNA at the resolution of individual reads

Cell-free DNA (cfDNA) are DNA fragments originating from dying cells that are detectable in bodily fluids, such as the plasma. Accelerated cell death, for example caused by disease, induces an elevated concentration of cfDNA. As a result, determining the cell type origins of cfDNA molecules can provide information about an individual's health. In this work, we aim to increase the sensitivity of methylation-based cell type deconvolution by adapting an existing method, CelFiE, which uses the methylation beta values of individual CpG sites to estimate cell type proportions. Our new method, CelFEER, instead differentiates cell types by the average methylation values within individual reads. We additionally improved the originally reported performance of CelFiE by using a new approach for finding marker regions that are differentially methylated between cell types. We show that CelFEER estimates cell type proportions with a higher correlation (r = 0.94 ± 0.04) than CelFiE (r = 0.86 ± 0.09) on simulated mixtures of cell types. Moreover, we show that the cell type proportion estimated by CelFEER can differentiate between ALS patients and healthy controls, between pregnant women in their first and third trimester, and between pregnant women with and without gestational diabetes.

Elevated cfDNA after exercise is derived primarily from mature polymorphonuclear neutrophils, with a minor contribution of cardiomyocytes

Strenuous physical exercise causes a massive elevation in the concentration of circulating cell-free DNA (cfDNA), which correlates with effort intensity and duration. The cellular sources and physiological drivers of this phenomenon are unknown. Using methylation patterns of cfDNA and associated histones, we show that cfDNA in exercise originates mostly in extramedullary polymorphonuclear neutrophils. Strikingly, cardiomyocyte cfDNA concentration increases after a marathon, consistent with elevated troponin levels and indicating low-level, delayed cardiac cell death. Physical impact, low oxygen levels, and elevated core body temperature contribute to neutrophil cfDNA release, while muscle contraction, increased heart rate, β-adrenergic signaling, or steroid treatment fail to cause elevation of cfDNA. Physical training reduces neutrophil cfDNA release after a standard exercise, revealing an inverse relationship between exercise-induced cfDNA release and training level. We speculate that the release of cfDNA from neutrophils in exercise relates to the activation of neutrophils in the context of exercise-induced muscle damage.

Multi-population genome-wide association study implicates immune and non-immune factors in pediatric steroid-sensitive nephrotic syndrome

Pediatric steroid-sensitive nephrotic syndrome (pSSNS) is the most common childhood glomerular disease. Previous genome-wide association studies (GWAS) identified a risk locus in the HLA Class II region and three additional independent risk loci. But the genetic architecture of pSSNS, and its genetically driven pathobiology, is largely unknown. Here, we conduct a multi-population GWAS meta-analysis in 38,463 participants (2440 cases). We then conduct conditional analyses and population specific GWAS. We discover twelve significant associations-eight from the multi-population meta-analysis (four novel), two from the multi-population conditional analysis (one novel), and two additional novel loci from the European meta-analysis. Fine-mapping implicates specific amino acid haplotypes in HLA-DQA1 and HLA-DQB1 driving the HLA Class II risk locus. Non-HLA loci colocalize with eQTLs of monocytes and numerous T-cell subsets in independent datasets. Colocalization with kidney eQTLs is lacking but overlap with kidney cell open chromatin suggests an uncharacterized disease mechanism in kidney cells. A polygenic risk score (PRS) associates with earlier disease onset. Altogether, these discoveries expand our knowledge of pSSNS genetic architecture across populations and provide cell-specific insights into its molecular drivers. Evaluating these associations in additional cohorts will refine our understanding of population specificity, heterogeneity, and clinical and molecular associations.

Single-cell RNA sequencing reveals changes in glioma-associated macrophage polarization and cellular states of malignant gliomas with high AQP4 expression

Glioma is the most common primary central nervous system tumor in adults. Aquaporin-4, as a water channel protein encoded by AQP4 in the brain, is reported to alter its aggregation status to affect plasma membrane dynamics and provide the potential for metastasis of tumor cells and components of the tumor microenvironment. We performed single-cell RNA transcriptome sequencing of 53059 cells from 13 malignant glioma samples and spotted that the expression of AQP4 differed between samples. The same result was observed in the TCGA glioma database, showing poor overall survival and poor response to chemotherapy in AQP4 overexpressed populations. Concomitant with the overexpression of AQP4, genes related to the immune system were also over-expressed, such as CD74, HES1, CALD1, and HEBP2, indicating AQP4 may relate to immune factors of tumor progression. We also found that tumor-associated macrophages tended to polarize toward M2 macrophages in the high AQP4 group. In glioblastoma samples, we examined cell status differences and identified that cell status differs according to AQP4 expression levels. Briefly, our study revealed substantial heterogeneity within malignant gliomas with different AQP4 expression levels, indicating the intricate connection between tumor cells and the tumor immune environment.

Genome-wide association study of the age of onset of type 1 diabetes reveals HTATIP2 as a novel T cell regulator

Introduction

Type 1 diabetes, a disorder caused by autoimmune destruction of pancreatic insulin-producing cells, is more difficult to manage when it presents at a younger age. We sought to identify genetic correlates of the age of onset by conducting the first genome-wide association study (GWAS) treating the age of first diagnosis as a quantitative trait.

Methods

We performed GWAS with a discovery cohort of 4,014 cases and a replication cohort of 493 independent cases. Genome-wide significant SNPs were mapped to a causal variant by Bayesian conditional analysis and gel shift assay. The causal protein-coding gene was identified and characterized by RNA interference treatment of primary human pan-CD4+ T cells with RNA-seq of the transcriptome. The candidate gene was evaluated functionally in primary cells by CD69 staining and proliferation assays.

Results

Our GWAS replicated the known association of the age of diagnosis with the human leukocyte antigen complex (HLA-DQB1). The second signal identified was in an intron of the NELL1 gene on chromosome 11 and fine-mapped to variant rs10833518 (P < 1.54 × 10^-9). Homozygosity for the risk allele leads to average age of onset one year earlier. Knock-down of HIV TAT-interacting protein 2 (HTATIP2), but not other genes in the locus, resulted in alterations to gene expression in signal transduction pathways including MAP kinases and PI3-kinase. Higher levels of HTATIP2 expression are associated with increased viability, proliferation, and activation of T cells in the presence of signals from antigen and cytokine receptors.

Discussion

This study implicates HTATIP2 as a new type 1 diabetes gene acting via T cell regulation. Larger population sample sizes are expected to reveal additional loci.

Longitudinal monitoring of cell-free DNA methylation in ALK-positive non-small cell lung cancer patients

BACKGROUND

DNA methylation (5-mC) signals in cell-free DNA (cfDNA) of cancer patients represent promising biomarkers for minimally invasive tumor detection. The high abundance of cancer-associated 5-mC alterations permits parallel and highly sensitive assessment of multiple 5-mC biomarkers. Here, we performed genome-wide 5-mC profiling in the plasma of metastatic ALK-rearranged non-small cell lung cancer (NSCLC) patients receiving tyrosine kinase inhibitor therapy. We established a strategy to identify ALK-specific 5-mC changes from cfDNA and demonstrated the suitability of the identified markers for cancer detection, prognosis, and therapy monitoring.

METHODS

Longitudinal plasma samples (n = 79) of 21 ALK-positive NSCLC patients and 13 healthy donors were collected alongside 15 ALK-positive tumor tissue and 10 healthy lung tissue specimens. All plasma and tissue samples were analyzed by cell-free DNA methylation immunoprecipitation sequencing to generate genome-wide 5-mC profiles. Information on genomic alterations (i.e., somatic mutations/fusions and copy number alterations) determined in matched plasma samples was available from previous studies.

RESULTS

We devised a strategy that identified tumor-specific 5-mC biomarkers by reducing 5-mC background signals derived from hematopoietic cells. This was followed by differential methylation analysis (cases vs. controls) and biomarker validation using 5-mC profiles of ALK-positive tumor tissues. The resulting 245 differentially methylated regions were enriched for lung adenocarcinoma-specific 5-mC patterns in TCGA data and indicated transcriptional repression of several genes described to be silenced in NSCLC (e.g., PCDH10, TBX2, CDO1, and HOXA9). Additionally, 5-mC-based tumor DNA (5-mC score) was highly correlated with other genomic alterations in cell-free DNA (Spearman, ρ > 0.6), while samples with high 5-mC scores showed significantly shorter overall survival (log-rank p = 0.025). Longitudinal 5-mC scores reflected radiologic disease assessments and were significantly elevated at disease progression compared to the therapy start (p = 0.0023). In 7 out of 8 instances, rising 5-mC scores preceded imaging-based evaluation of disease progression.

CONCLUSION

We demonstrated a strategy to identify 5-mC biomarkers from the plasma of cancer patients and integrated them into a quantitative measure of cancer-associated 5-mC alterations. Using longitudinal plasma samples of ALK-positive NSCLC patients, we highlighted the suitability of cfDNA methylation for prognosis and therapy monitoring.

Vitamin C enhances NF-κB-driven epigenomic reprogramming and boosts the immunogenic properties of dendritic cells

Dendritic cells (DCs), the most potent antigen-presenting cells, are necessary for effective activation of naïve T cells. DCs’ immunological properties are modulated in response to various stimuli. Active DNA demethylation is crucial for DC differentiation and function. Vitamin C, a known cofactor of ten-eleven translocation (TET) enzymes, drives active demethylation. Vitamin C has recently emerged as a promising adjuvant for several types of cancer; however, its effects on human immune cells are poorly understood. In this study, we investigate the epigenomic and transcriptomic reprogramming orchestrated by vitamin C in monocyte-derived DC differentiation and maturation. Vitamin C triggers extensive demethylation at NF-κB/p65 binding sites, together with concordant upregulation of antigen-presentation and immune response-related genes during DC maturation. p65 interacts with TET2 and mediates the aforementioned vitamin C-mediated changes, as demonstrated by pharmacological inhibition. Moreover, vitamin C increases TNFβ production in DCs through NF-κB, in concordance with the upregulation of its coding gene and the demethylation of adjacent CpGs. Finally, vitamin C enhances DC’s ability to stimulate the proliferation of autologous antigen-specific T cells. We propose that vitamin C could potentially improve monocyte-derived DC-based cell therapies.

Computational methods to explore chromatin state dynamics

The human genome is marked by several singular and combinatorial histone modifications that shape the different states of chromatin and its three-dimensional organization. Genome-wide mapping of these marks as well as histone variants and open chromatin regions is commonly carried out via profiling DNA-protein binding or via chromatin accessibility methods. After the generation of epigenomic datasets in a cell type, statistical models can be used to annotate the noncoding regions of DNA and infer the combinatorial histone marks or chromatin states (CS). These methods involve partitioning the genome and labeling individual segments based on their CS patterns. Chromatin labels enable the systematic discovery of genomic function and activity and can label the gene body, promoters or enhancers without using other genomic maps. CSs are dynamic and change under different cell conditions, such as in normal, preneoplastic or tumor cells. This review aims to explore the available computational tools that have been developed to capture CS alterations under two or more cellular conditions.

High-throughput mutagenesis identifies mutations and RNA-binding proteins controlling CD19 splicing and CART-19 therapy resistance

Following CART-19 immunotherapy for B-cell acute lymphoblastic leukaemia (B-ALL), many patients relapse due to loss of the cognate CD19 epitope. Since epitope loss can be caused by aberrant CD19 exon 2 processing, we herein investigate the regulatory code that controls CD19 splicing. We combine high-throughput mutagenesis with mathematical modelling to quantitatively disentangle the effects of all mutations in the region comprising CD19 exons 1-3. Thereupon, we identify ~200 single point mutations that alter CD19 splicing and thus could predispose B-ALL patients to developing CART-19 resistance. Furthermore, we report almost 100 previously unknown splice isoforms that emerge from cryptic splice sites and likely encode non-functional CD19 proteins. We further identify cis-regulatory elements and trans-acting RNA-binding proteins that control CD19 splicing (e.g., PTBP1 and SF3B4) and validate that loss of these factors leads to pervasive CD19 mis-splicing. Our dataset represents a comprehensive resource for identifying predictive biomarkers for CART-19 therapy.

Multiple alternative splicing events in CD19 mRNA have been associated with resistance/relapse to CD19 CAR-T therapy in patients with B cell malignancies. Here, by combining patient data and a high-throughput mutagenesis screen, the authors identify single point mutations and RNA-binding proteins that can control CD19 splicing and be associated with CD19 CAR-T therapy resistance.

Regulatory Programs of B-cell Activation and Germinal Center Reaction Allow B-ALL Escape from CD19 CAR T-cell Therapy

Chimeric antigen receptor (CAR) T-cell therapy has led to tremendous successes in the treatment of B-cell malignancies. However, a large fraction of treated patients relapse, often with disease expressing reduced levels of the target antigen. Here, we report that exposing CD19+ B-cell acute lymphoblastic leukemia (B-ALL) cells to CD19 CAR T cells reduced CD19 expression within hours. Initially, CD19 CAR T cells caused clustering of CD19 at the T cell-leukemia cell interface followed by CD19 internalization and decreased CD19 surface expression on the B-ALL cells. CD19 expression was then repressed by transcriptional rewiring. Using single-cell RNA sequencing and single-cell assay for transposase-accessible chromatin using sequencing, we demonstrated that a subset of refractory CD19low cells sustained decreased CD19 expression through transcriptional programs of physiologic B-cell activation and germinal center reaction. Inhibiting B-cell activation programs with the Bruton's tyrosine kinase inhibitor ibrutinib increased the cytotoxicity of CD19 CAR T cells without affecting CAR T-cell viability. These results demonstrate transcriptional plasticity as an underlying mechanism of escape from CAR T cells and highlight the importance of combining CAR T-cell therapy with targeted therapies that aim to overcome this plasticity. See related Spotlight by Zhao and Melenhorst, p. 1040.

Early macrophage response to obesity encompasses Interferon Regulatory Factor 5 regulated mitochondrial architecture remodelling

Adipose tissue macrophages (ATM) adapt to changes in their energetic microenvironment. Caloric excess, in a range from transient to diet-induced obesity, could result in the transition of ATMs from highly oxidative and protective to highly inflammatory and metabolically deleterious. Here, we demonstrate that Interferon Regulatory Factor 5 (IRF5) is a key regulator of macrophage oxidative capacity in response to caloric excess. ATMs from mice with genetic-deficiency of Irf5 are characterised by increased oxidative respiration and mitochondrial membrane potential. Transient inhibition of IRF5 activity leads to a similar respiratory phenotype as genomic deletion, and is reversible by reconstitution of IRF5 expression. We find that the highly oxidative nature of Irf5-deficient macrophages results from transcriptional de-repression of the mitochondrial matrix component Growth Hormone Inducible Transmembrane Protein (GHITM) gene. The Irf5-deficiency-associated high oxygen consumption could be alleviated by experimental suppression of Ghitm expression. ATMs and monocytes from patients with obesity or with type-2 diabetes retain the reciprocal regulatory relationship between Irf5 and Ghitm. Thus, our study provides insights into the mechanism of how the inflammatory transcription factor IRF5 controls physiological adaptation to diet-induced obesity via regulating mitochondrial architecture in macrophages.

Interferon Regulatory Factor 5 levels have been shown to increase in adipose tissue macrophages in diet-induced obesity. Here authors show that IRF5 transcriptionally represses the Growth Hormone Inducible Transmembrane Protein gene encoding a mitochondrial protein important for oxidative respiration in macrophages, thus driving the detrimental metabolic changes observed in obesity.

Identifying common transcriptome signatures of cancer by interpreting deep learning models

Background

Cancer is a set of diseases characterized by unchecked cell proliferation and invasion of surrounding tissues. The many genes that have been genetically associated with cancer or shown to directly contribute to oncogenesis vary widely between tumor types, but common gene signatures that relate to core cancer pathways have also been identified. It is not clear, however, whether there exist additional sets of genes or transcriptomic features that are less well known in cancer biology but that are also commonly deregulated across several cancer types.

Results

Here, we agnostically identify transcriptomic features that are commonly shared between cancer types using 13,461 RNA-seq samples from 19 normal tissue types and 18 solid tumor types to train three feed-forward neural networks, based either on protein-coding gene expression, lncRNA expression, or splice junction use, to distinguish between normal and tumor samples. All three models recognize transcriptome signatures that are consistent across tumors. Analysis of attribution values extracted from our models reveals that genes that are commonly altered in cancer by expression or splicing variations are under strong evolutionary and selective constraints. Importantly, we find that genes composing our cancer transcriptome signatures are not frequently affected by mutations or genomic alterations and that their functions differ widely from the genes genetically associated with cancer.

Conclusions

Our results highlighted that deregulation of RNA-processing genes and aberrant splicing are pervasive features on which core cancer pathways might converge across a large array of solid tumor types.

Supplementary Information

The online version contains supplementary material available at (10.1186/s13059-022-02681-3).

Comparative analysis of genome-wide DNA methylation identifies patterns that associate with conserved transcriptional programs in osteosarcoma

Osteosarcoma is an aggressive tumor of the bone that primarily affects young adults and adolescents. Osteosarcoma is characterized by genomic chaos and heterogeneity. While inactivation of tumor protein p53 (TP53) is nearly universal other high frequency mutations or structural variations have not been identified. Despite this genomic heterogeneity, key conserved transcriptional programs associated with survival have been identified across human, canine and induced murine osteosarcoma. The epigenomic landscape, including DNA methylation, plays a key role in establishing transcriptional programs in all cell types. The role of epigenetic dysregulation has been studied in a variety of cancers but has yet to be explored at scale in osteosarcoma. Here we examined genome-wide DNA methylation patterns in 24 human and 44 canine osteosarcoma samples identifying groups of highly correlated DNA methylation marks in human and canine osteosarcoma samples. We also link specific DNA methylation patterns to key transcriptional programs in both human and canine osteosarcoma. Building on previous work, we built a DNA methylation-based measure for the presence and abundance of various immune cell types in osteosarcoma. Finally, we determined that the underlying state of the tumor, and not changes in cell composition, were the main driver of differences in DNA methylation across the human and canine samples. SIGNIFICANCE: Genome wide comparison of DNA methylation patterns in osteosarcoma across two species lays the ground work for the exploration of DNA methylation programs that help establish conserved transcriptional programs in the context of varied mutational landscapes.

Severe COVID-19-associated variants linked to chemokine receptor gene control in monocytes and macrophages

Genome-wide association studies have identified 3p21.31 as the main risk locus for severe COVID-19, although underlying mechanisms remain elusive. We perform an epigenomic dissection of 3p21.31, identifying a CTCF-dependent tissue-specific 3D regulatory chromatin hub that controls the activity of several chemokine receptor genes. Risk SNPs colocalize with regulatory elements and are linked to increased expression of CCR1, CCR2 and CCR5 in monocytes and macrophages. As excessive organ infiltration of inflammatory monocytes and macrophages is a hallmark of severe COVID-19, our findings provide a rationale for the genetic association of 3p21.31 variants with elevated risk of hospitalization upon SARS-CoV-2 infection.

Differentially expressed genes prediction by multiple self-attention on epigenetics data

Predicting differentially expressed genes (DEGs) from epigenetics signal data is the key to understand how epigenetics controls cell functional heterogeneity by gene regulation. This knowledge can help developing 'epigenetics drugs' for complex diseases like cancers. Most of existing machine learning-based methods suffer defects in prediction accuracy, interpretability or training speed. To address these problems, in this paper, we propose a Multiple Self-Attention model for predicting DEGs on Epigenetic data (Epi-MSA). Epi-MSA first uses convolutional neural networks for neighborhood bins information embedding, and then employs multiple self-attention encoders on different input epigenetics factors data to learn which locations of genes are important for predicting DEGs. Next it trains a soft attention module to pick out which epigenetics factors are significant. The attention mechanism makes the model interpretable, and the pure matrix operation of self-attention enables the model to be parallel calculated and speeds up the training. Experiments on datasets from the Roadmap Epigenome Project and BluePrint Data Analysis Portal (BDAP) show that the performance of Epi-MSA is better than existing competitive methods, and Epi-MSA also has a smaller standard deviation, which shows that Epi-MSA is effective and stable. In addition, Epi-MSA has a good interpretability, this is confirmed by referring its attention weight matrix with existing biological knowledge.

Modulation of CD22 Protein Expression in Childhood Leukemia by Pervasive Splicing Aberrations: Implications for CD22-Directed Immunotherapies

Downregulation of surface epitopes causes postimmunotherapy relapses in B-lymphoblastic leukemia (B-ALL). Here we demonstrate that mRNA encoding CD22 undergoes aberrant splicing in B-ALL. We describe the plasma membrane-bound CD22 Δex5-6 splice isoform, which is resistant to chimeric antigen receptor (CAR) T cells targeting the third immunoglobulin-like domain of CD22. We also describe splice variants skipping the AUG-containing exon 2 and failing to produce any identifiable protein, thereby defining an event that is rate limiting for epitope presentation. Indeed, forcing exon 2 skipping with morpholino oligonucleotides reduced CD22 protein expression and conferred resistance to the CD22-directed antibody-drug conjugate inotuzumab ozogamicin in vitro. Furthermore, among inotuzumab-treated pediatric patients with B-ALL, we identified one nonresponder in whose leukemic blasts Δex2 isoforms comprised the majority of CD22 transcripts. In a second patient, a sharp reduction in CD22 protein levels during relapse was driven entirely by increased CD22 exon 2 skipping. Thus, dysregulated CD22 splicing is a major mechanism of epitope downregulation and ensuing resistance to immunotherapy.

SIGNIFICANCE

The mechanism(s) underlying downregulation of surface CD22 following CD22-directed immunotherapy remains underexplored. Our biochemical and correlative studies demonstrate that in B-ALL, CD22 expression levels are controlled by inclusion/skipping of CD22 exon 2. Thus, aberrant splicing of CD22 is an important driver/biomarker of de novo and acquired resistance to CD22-directed immunotherapies. See related commentary by Bourcier and Abdel-Wahab, p. 87. This article is highlighted in the In This Issue feature, p. 85.

Potential role of regulatory DNA variants in modifying the risk of severe cutaneous reactions induced by aromatic anti-seizure medications

Objective

Stevens–Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are severe cutaneous adverse drug reactions. Antiseizure medications (ASMs) with aromatic ring structure, including carbamazepine, are among the most common culprits. Screening for human leukocyte antigen (HLA) allele HLA‐B*15:02 is recommended prior to initiating treatment with carbamazepine in Asians, but this allele has low positive predictive value.

Methods

We performed whole genome sequencing and analyzed 6 199 696 common variants among 113 aromatic ASM‐induced SJS/TEN cases and 84 tolerant controls of Han Chinese ethnicity.

Results

In the primary analysis, nine variants reached genome‐wide significance (p < 5e‐08), one in the carbamazepine subanalysis (85 cases vs. 77 controls) and a further eight identified in HLA‐B*15:02‐negative subanalysis (35 cases and 53 controls). Interaction analysis between each novel variant from the primary analysis found that five increased risk irrespective of HLA‐B*15:02 status or zygosity. HLA‐B*15:02‐positive individuals were found to have reduced risk if they also carried a chromosome 12 variant, chr12.9426934 (heterozygotes: relative risk = .71, p = .001; homozygotes: relative risk = .23, p < .001). All significant variants lie within intronic or intergenic regions with poorly understood functional consequence. In silico functional analysis of suggestive variants (p < 5e‐6) identified through the primary and subanalyses (stratified by HLA‐B*15:02 status and drug exposure) suggests that genetic variation within regulatory DNA may contribute to risk indirectly by disrupting the regulation of pathology‐related genes. The genes implicated were specific either to the primary analysis (CD9), HLA‐B*15:02 carriers (DOCK10), noncarriers (ABCA1), carbamazepine exposure (HLA‐E), or phenytoin exposure (CD24).

Significance

We identified variants that could explain why some carriers of HLA‐B*15:02 tolerate treatment, and why some noncarriers develop ASM‐induced SJS/TEN. Additionally, this analysis suggests that the mixing of HLA‐B*15:02 carrier status in previous studies might have masked variants contributing to susceptibility, and that inheritance of risk for ASM‐induced SJS/TEN is complex, likely involving multiple risk variants.

Epigenetic Regulation of F2RL3 Associates With Myocardial Infarction and Platelet Function

BACKGROUND

DNA hypomethylation at the F2RL3 (F2R like thrombin or trypsin receptor 3) locus has been associated with both smoking and atherosclerotic cardiovascular disease; whether these smoking-related associations form a pathway to disease is unknown. F2RL3 encodes protease-activated receptor 4, a potent thrombin receptor expressed on platelets. Given the role of thrombin in platelet activation and the role of thrombus formation in myocardial infarction, alterations to this biological pathway could be important for ischemic cardiovascular disease.

METHODS

We conducted multiple independent experiments to assess whether DNA hypomethylation at F2RL3 in response to smoking is associated with risk of myocardial infarction via changes to platelet reactivity. Using cohort data (N=3205), we explored the relationship between smoking, DNA hypomethylation at F2RL3, and myocardial infarction. We compared platelet reactivity in individuals with low versus high DNA methylation at F2RL3 (N=41). We used an in vitro model to explore the biological response of F2RL3 to cigarette smoke extract. Finally, a series of reporter constructs were used to investigate how differential methylation could impact F2RL3 gene expression.

RESULTS

Observationally, DNA methylation at F2RL3 mediated an estimated 34% of the smoking effect on increased risk of myocardial infarction. An association between methylation group (low/high) and platelet reactivity was observed in response to PAR4 (protease-activated receptor 4) stimulation. In cells, cigarette smoke extract exposure was associated with a 4.9% to 9.3% reduction in DNA methylation at F2RL3 and a corresponding 1.7-(95% CI, 1.2-2.4, P=0.04) fold increase in F2RL3 mRNA. Results from reporter assays suggest the exon 2 region of F2RL3 may help control gene expression.

CONCLUSIONS

Smoking-induced epigenetic DNA hypomethylation at F2RL3 appears to increase PAR4 expression with potential downstream consequences for platelet reactivity. Combined evidence here not only identifies F2RL3 DNA methylation as a possible contributory pathway from smoking to cardiovascular disease risk but from any feature potentially influencing F2RL3 regulation in a similar manner.

Identification and targeting of the developmental blockade in extranodal natural killer/T cell lymphoma

Extranodal natural killer/T-cell lymphoma (ENKTL) is an aggressive, rare lymphoma of natural killer (NK) cell origin with poor clinical outcomes. Here we used phenotypic and molecular profiling, including epigenetic analyses, to investigate how ENKTL ontogeny relates to normal NK-cell development. We demonstrate that neoplastic NK cells are stably, but reversibly, arrested at earlier stages of NK-cell maturation. Genes downregulated in the most epigenetic immature tumors were associated with polycomb silencing along with genomic gain and overexpression of EZH2. ENKTL cells exhibited genome-wide DNA hypermethylation. Tumor-specific DNA methylation gains were associated with polycomb-marked regions, involving extensive gene silencing and loss of transcription factor binding. To investigate therapeutic targeting, we treated novel patient-derived xenograft (PDX) models of ENKTL with the DNA hypomethylating agent, 5-azacytidine. Treatment led to reexpression of NK-cell developmental genes, phenotypic NK-cell differentiation, and prolongation of survival. These studies lay the foundation for epigenetic-directed therapy in ENKTL.

SIGNIFICANCE

Through epigenetic and transcriptomic analyses of ENKTL, a rare, aggressive malignancy, along with normal NK-cell developmental intermediates, we identified that extreme DNA hypermethylation targets genes required for NK-cell development. Disrupting this epigenetic blockade in novel PDX models led to ENKTL differentiation and improved survival. This article is highlighted in the In This Issue feature, p. 85.

Cell-free DNA profiling informs all major complications of hematopoietic cell transplantation

Allogeneic hematopoietic cell transplantation (HCT) provides effective treatment for hematologic malignancies and immune disorders. Monitoring of posttransplant complications is critical, yet current diagnostic options are limited. Here, we show that cell-free DNA (cfDNA) in blood is a versatile analyte for monitoring of the most important complications that occur after HCT: graft-versus-host disease (GVHD), a frequent immune complication of HCT, infection, relapse of underlying disease, and graft failure. We demonstrate that these therapeutic complications are informed from a single assay, low-coverage bisulfite sequencing of cfDNA, followed by disease-specific bioinformatic analyses. To inform GVHD, we profile cfDNA methylation marks to trace the cfDNA tissues-of-origin and to quantify tissue-specific injury. To inform infection, we implement metagenomic cfDNA profiling. To inform cancer relapse, we implement analyses of tumor-specific genomic aberrations. Finally, to detect graft failure, we quantify the proportion of donor- and recipient-specific cfDNA. We applied this assay to 170 plasma samples collected from 27 HCT recipients at predetermined timepoints before and after allogeneic HCT. We found that the abundance of solid-organ-derived cfDNA in the blood at 1 mo after HCT is predictive of acute GVHD (area under the curve, 0.88). Metagenomic profiling of cfDNA revealed the frequent occurrence of viral reactivation in this patient population. The fraction of donor-specific cfDNA was indicative of relapse and remission, and the fraction of tumor-specific cfDNA was informative of cancer relapse. This proof-of-principle study shows that cfDNA has the potential to improve the care of allogeneic HCT recipients by enabling earlier detection and better prediction of the complex array of complications that occur after HCT.

Epigenomic translocation of H3K4me3 broad domains over oncogenes following hijacking of super-enhancers

Chromosomal translocations are important drivers of haematological malignancies whereby proto-oncogenes are activated by juxtaposition with enhancers, often called enhancer hijacking. We analyzed the epigenomic consequences of rearrangements between the super-enhancers of the immunoglobulin heavy locus (IGH) and proto-oncogene CCND1 that are common in B cell malignancies. By integrating BLUEPRINT epigenomic data with DNA breakpoint detection, we characterized the normal chromatin landscape of the human IGH locus and its dynamics after pathological genomic rearrangement. We detected an H3K4me3 broad domain (BD) within the IGH locus of healthy B cells that was absent in samples with IGH-CCND1 translocations. The appearance of H3K4me3-BD over CCND1 in the latter was associated with overexpression and extensive chromatin accessibility of its gene body. We observed similar cancer-specific H3K4me3-BDs associated with hijacking of super-enhancers of other common oncogenes in B cell (MAF, MYC, and FGFR3/NSD2) and T cell malignancies (LMO2, TLX3, and TAL1). Our analysis suggests that H3K4me3-BDs can be created by super-enhancers and supports the new concept of epigenomic translocation, in which the relocation of H3K4me3-BDs from cell identity genes to oncogenes accompanies the translocation of super-enhancers.

Coordinated glucocorticoid receptor and MAFB action induces tolerogenesis and epigenome remodeling in dendritic cells

Glucocorticoids (GCs) exert potent anti-inflammatory effects in immune cells through the glucocorticoid receptor (GR). Dendritic cells (DCs), central actors for coordinating immune responses, acquire tolerogenic properties in response to GCs. Tolerogenic DCs (tolDCs) have emerged as a potential treatment for various inflammatory diseases. To date, the underlying cell type-specific regulatory mechanisms orchestrating GC-mediated acquisition of immunosuppressive properties remain poorly understood. In this study, we investigated the transcriptomic and epigenomic remodeling associated with differentiation to DCs in the presence of GCs. Our analysis demonstrates a major role of MAFB in this process, in synergy with GR. GR and MAFB both interact with methylcytosine dioxygenase TET2 and bind to genomic loci that undergo specific demethylation in tolDCs. We also show that the role of MAFB is more extensive, binding to thousands of genomic loci in tolDCs. Finally, MAFB knockdown erases the tolerogenic properties of tolDCs and reverts the specific DNA demethylation and gene upregulation. The preeminent role of MAFB is also demonstrated in vivo for myeloid cells from synovium in rheumatoid arthritis following GC treatment. Our results imply that, once directly activated by GR, MAFB plays a critical role in orchestrating the epigenomic and transcriptomic remodeling that define the tolerogenic phenotype.

A Transcriptional Signature of IL-2 Expanded Natural Killer Cells Predicts More Favorable Prognosis in Bladder Cancer

Activation of natural killer (NK) cell function is regulated by cytokines, such as IL-2, and secreted factors upregulated in the tumor microenvironment, such as platelet-derived growth factor D (PDGF-DD). In order to elucidate a clinical role for these important regulators of NK cell function in antitumor immunity, we generated transcriptional signatures representing resting, IL-2-expanded, and PDGF-DD-activated, NK cell phenotypes and established their abundance in The Cancer Genome Atlas bladder cancer (BLCA) dataset using CIBERSORT. The IL-2-expanded NK cell phenotype was the most abundant in low and high grades of BLCA tumors and was associated with improved prognosis. In contrast, PDGFD expression was associated with numerous cancer hallmark pathways in BLCA tumors compared with normal bladder tissue, and a high tumor abundance of PDGFD transcripts and the PDGF-DD-activated NK cell phenotype were associated with a poor BLCA prognosis. Finally, high tumor expression of transcripts encoding the activating NK cell receptors, KLRK1 and the CD160-TNFRSF14 receptor-ligand pair, was strongly correlated with the IL-2-expanded NK cell phenotype and improved BLCA prognosis. The transcriptional parameters we describe may be optimized to improve BLCA patient prognosis and risk stratification in the clinic and potentially provide gene targets of therapeutic significance for enhancing NK cell antitumor immunity in BLCA.

Rare t(X;14)(q28;q32) translocation reveals link between MTCP1 and chronic lymphocytic leukemia

Rare, recurrent balanced translocations occur in a variety of cancers but are often not functionally interrogated. Balanced translocations with the immunoglobulin heavy chain locus (IGH; 14q32) in chronic lymphocytic leukemia (CLL) are infrequent but have led to the discovery of pathogenic genes including CCND1, BCL2, and BCL3. Following identification of a t(X;14)(q28;q32) translocation that placed the mature T cell proliferation 1 gene (MTCP1) adjacent to the immunoglobulin locus in a CLL patient, we hypothesized that this gene may have previously unrecognized importance. Indeed, here we report overexpression of human MTCP1 restricted to the B cell compartment in mice produces a clonal CD5⁺/CD19⁺ leukemia recapitulating the major characteristics of human CLL and demonstrates favorable response to therapeutic intervention with ibrutinib. We reinforce the importance of genetic interrogation of rare, recurrent balanced translocations to identify cancer driving genes via the story of MTCP1 as a contributor to CLL pathogenesis.

Dynamic transcriptional reprogramming leads to immunotherapeutic vulnerabilities in myeloma

While there is extensive evidence for genetic variation as a basis for treatment resistance, other sources of variation result from cellular plasticity. Using multiple myeloma as an example of an incurable lymphoid malignancy, we show how cancer cells modulate lineage restriction, adapt their enhancer usage and employ cell-intrinsic diversity for survival and treatment escape. By using single-cell transcriptome and chromatin accessibility profiling, we show that distinct transcriptional states co-exist in individual cancer cells and that differential transcriptional regulon usage and enhancer rewiring underlie these alternative transcriptional states. We demonstrate that exposure to standard treatment further promotes transcriptional reprogramming and differential enhancer recruitment while simultaneously reducing developmental potential. Importantly, treatment generates a distinct complement of actionable immunotherapy targets, such as CXCR4, which can be exploited to overcome treatment resistance. Our studies therefore delineate how to transform the cellular plasticity that underlies drug resistance into immuno-oncologic therapeutic opportunities.

Wouters B, Bindels E, Smeenk L, Delwel R. The leukemic oncogene EVI1 hijacks a MYC super-enhancer by CTCF-facilitated loops

Chromosomal rearrangements are a frequent cause of oncogene deregulation in human malignancies. Overexpression of EVI1 is found in a subgroup of acute myeloid leukemia (AML) with 3q26 chromosomal rearrangements, which is often therapy resistant. In AMLs harboring a t(3;8)(q26;q24), we observed the translocation of a MYC super-enhancer (MYC SE) to the EVI1 locus. We generated an in vitro model mimicking a patient-based t(3;8)(q26;q24) using CRISPR-Cas9 technology and demonstrated hyperactivation of EVI1 by the hijacked MYC SE. This MYC SE contains multiple enhancer modules, of which only one recruits transcription factors active in early hematopoiesis. This enhancer module is critical for EVI1 overexpression as well as enhancer-promoter interaction. Multiple CTCF binding regions in the MYC SE facilitate this enhancer-promoter interaction, which also involves a CTCF binding site upstream of the EVI1 promoter. We hypothesize that this CTCF site acts as an enhancer-docking site in t(3;8) AML. Genomic analyses of other 3q26-rearranged AML patient cells point to a common mechanism by which EVI1 uses this docking site to hijack enhancers active in early hematopoiesis.

Epigenome-wide association study detects a novel loci associated with central obesity in healthy subjects

Background and aims

Central obesity is a condition that poses a significant risk to global health and requires the employment of novel scientific methods for exploration. The objective of this study is to use DNA methylation analysis to detect DNA methylation loci linked to obesity phenotypes, i.e. waist circumference and waist-to-hip ratio adjusted for BMI.

Methods and results

Two-hundred and ten healthy European participants from the STANISLAS Family Study (SFS), comprising 73 nuclear families, were comprehensively assessed for methylation status using Illumina Infinium HumanMethylation450 BeadChip. An epigenome-wide association study was performed, which identified a CpG site cg16170243 located on chromosome 18q21.2 significantly associated with waist circumference, after adjusting for BMI (β = 2.32, SE = 0.41, P_adj = 0.048). Cg16170243 corresponds to a 50 bp-length human methylation oligoprobe located within the AC090241.2 gene that overlaps ST8SIA5 gene. No significant association was observed with waist-to-hip ratio adjusted for BMI (P_adj > 0.05).

Conclusions

A novel association between DNA methylation and WC was identified, which is demonstrating that epigenetic mechanisms may have a significant impact on waist circumference ratio in healthy individuals. Further studies are warranted to address the causal effects of this association.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-01077-9.

A Transcriptional Signature of PDGF-DD Activated Natural Killer Cells Predicts More Favorable Prognosis in Low-Grade Glioma

The binding of platelet-derived growth factor D (PDGF-DD) to the NKp44 receptor activates a distinct transcriptional program in primary IL-2 expanded human natural killer (NK) cells. We were interested in knowing if the PDGF-DD-NKp44 pathway of NK cell activation might play a clinically relevant role in anti-tumor immunity. In order to address this question, we determined transcriptional signatures unique to resting, IL-2 expanded, and PDGF-DD activated, NK cells, in addition to different T cell subsets, and established the abundance of these immune cell phenotypes in The Cancer Genome Atlas (TCGA) low-grade glioma (LGG) dataset using CIBERSORT. Our results show that LGG patient tumors enriched for either the PDGF-DD activated NK cell or memory CD8⁺ T cell phenotypes are associated with a more favorable prognosis. Combined cell phenotype analyses revealed that patients with LGG tumors enriched for the PDGF-DD activated NK cell phenotype and the CD4⁺ T helper cell phenotype had a more favorable prognosis. High expression of transcripts encoding members of the killer cell lectin-like receptor (KLR) family, such as KLRK1 and KLRC2, KLRC3 and KLRC4 in LGG tumors were associated with more favorable prognosis, suggesting that these NK cell family receptors may play a prominent role in LGG anti-tumor immunity. Finally, many of the TCGA findings were reciprocated in LGG patients from the Chinese Glioma Genome Atlas (CGGA) dataset. Our results provide transcriptomic evidence that PDGF-DD activated NK cells and KLR family receptors may play an important clinical role in immune surveillance of LGG.

Restriction enzyme selection dictates detection range sensitivity in chromatin conformation capture-based variant-to-gene mapping approaches

Promoter-focused chromatin conformation techniques directly detect interactions between gene promoters and distal genomic sequences, providing structural information relevant to gene regulation without the excessive non-genic architectural data generated by full-scale Hi-C. 3D promoter 'interactome' maps are crucial for understanding how epigenomic features such as histone modifications and open chromatin, or genetic variants identified in genome-wide association studies (GWAS), contribute to biological function. However, variation in sensitivity between such promoter-focused methods, principally due to restriction enzyme selection, has not been systematically assessed. Here, we performed a head-to-head comparison of promoter capture datasets using 4 cutters (DpnII or MboI) versus the 6 cutter HindIII from the same five cell types. While HindIII generally produces a higher signal-to-noise ratio for significant interactions in comparison to 4-cutters, we show that DpnII/MboI detects more proximal interactions and shows little overlap with the HindIII detection range. Promoter-interacting genomic regions mapped by 4-cutters are more enriched for regulatory features and disease-associated genetic variation than 6-cutters maps, suggesting that high-resolution maps better capture gene regulatory architectures than do lower resolution approaches.

The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability

Background

Cancer evolution depends on epigenetic and genetic diversity. Historically, in multiple myeloma (MM), subclonal diversity and tumor evolution have been investigated mostly from a genetic perspective.

Methods

Here, we performed an analysis of 42 MM samples from 21 patients by using enhanced reduced representation bisulfite sequencing (eRRBS). We combined several metrics of epigenetic heterogeneity to analyze DNA methylation heterogeneity in MM patients.

Results

We show that MM is characterized by the continuous accumulation of stochastic methylation at the promoters of development-related genes. High combinatorial entropy change is associated with poor outcomes in our pilot study and depends predominantly on partially methylated domains (PMDs). These PMDs, which represent the major source of inter- and intrapatient DNA methylation heterogeneity in MM, are linked to other key epigenetic aberrations, such as CpG island (CGI)/transcription start site (TSS) hypermethylation and H3K27me3 redistribution as well as 3D organization alterations. In addition, transcriptome analysis revealed that intratumor methylation heterogeneity was associated with low-level expression and high variability.

Conclusions

We propose that disrupted DNA methylation in MM is responsible for high epigenetic and transcriptomic instability allowing tumor cells to adapt to environmental changes by tapping into a pool of evolutionary trajectories.

Supplementary Information

The online version contains supplementary material available at (10.1186/s13073-021-00938-3).

DNA Methylome Alterations are Associated with Airway Macrophage Differentiation and Phenotype During Lung Fibrosis

RATIONALE

Airway macrophages (AMs) are key regulators of the lung environment and are implicated in the pathogenesis of idiopathic pulmonary fibrosis (IPF), a fatal respiratory disease with no cure. However, knowledge of epigenetics of AMs in IPF are limited.

METHODS

We undertook DNA methylation profiling using Illumina EPIC (850k) arrays in sorted AMs from Healthy (n=14) and IPF (n=30) donors. Cell-type deconvolution was performed using reference myeloid-cell DNA methylomes.

MEASUREMENTS AND MAIN RESULTS

Our analysis revealed epigenetic heterogeneity was a key characteristic of IPF-AMs. DNAm 'clock' analysis indicated epigenetic alterations in IPF-AMs was not associated with accelerated ageing. In differential DNAm analysis, we identified numerous differentially methylated positions (DMPs, n=11) and regions (DMRs, n=49) between healthy and IPF AMs respectively. DMPs and DMRs encompassed genes involved in lipid (LPCAT1) and glucose (PFKFB3) metabolism and importantly, DNAm status was associated with disease severity in IPF.

CONCLUSIONS

Collectively, our data identify that changes in the epigenome are associated with development and function of AMs in the IPF lung.

Severe COVID-19 associated variants linked to chemokine receptor gene control in monocytes and macrophages

Genome-wide association studies have identified 3p21.31 as the main risk locus for severe disease in COVID-19 patients, although underlying biological mechanisms remain elusive. We performed a comprehensive epigenomic dissection of the 3p21.31 locus, identifying a CTCF-dependent tissue-specific 3D regulatory chromatin hub that controls the activity of several tissue-homing chemokine receptor (CCR) genes in monocytes and macrophages. Risk SNPs colocalized with regulatory elements and were linked to increased expression of CCR1, CCR2 and CCR5 in monocytes and macrophages. As excessive organ infiltration of inflammatory monocytes and macrophages is a hallmark of severe COVID-19, our findings provide a rationale for the genetic association of 3p21.31 variants with elevated risk of hospitalization upon SARS-CoV-2 infection.

Comprehensive cell type decomposition of circulating cell-free DNA with CelFiE

Circulating cell-free DNA (cfDNA) in the bloodstream originates from dying cells and is a promising noninvasive biomarker for cell death. Here, we propose an algorithm, CelFiE, to accurately estimate the relative abundances of cell types and tissues contributing to cfDNA from epigenetic cfDNA sequencing. In contrast to previous work, CelFiE accommodates low coverage data, does not require CpG site curation, and estimates contributions from multiple unknown cell types that are not available in external reference data. In simulations, CelFiE accurately estimates known and unknown cell type proportions from low coverage and noisy cfDNA mixtures, including from cell types composing less than 1% of the total mixture. When used in two clinically-relevant situations, CelFiE correctly estimates a large placenta component in pregnant women, and an elevated skeletal muscle component in amyotrophic lateral sclerosis (ALS) patients, consistent with the occurrence of muscle wasting typical in these patients. Together, these results show how CelFiE could be a useful tool for biomarker discovery and monitoring the progression of degenerative disease.

Tissue damage and turnover lead to the release of DNA in the blood and can be used to monitor changes in tissue state. Here, the authors developed a tool to accurately estimate the proportion of cell types contributing to cell-free DNA in the blood, with an application to pregnant women and ALS patients.

Single-cell RNA-seq reveals developmental plasticity with coexisting oncogenic states and immune evasion programs in ETP-ALL

Lineage plasticity and stemness have been invoked as causes of therapy resistance in cancer, because these flexible states allow cancer cells to dedifferentiate and alter their dependencies. We investigated such resistance mechanisms in relapsed/refractory early T-cell progenitor acute lymphoblastic leukemia (ETP-ALL) carrying activating NOTCH1 mutations via full-length single-cell RNA sequencing (scRNA-seq) of malignant and microenvironmental cells. We identified 2 highly distinct stem-like states that critically differed with regard to cell cycle and oncogenic signaling. Fast-cycling stem-like leukemia cells demonstrated Notch activation and were effectively eliminated in patients by Notch inhibition, whereas slow-cycling stem-like cells were Notch independent and rather relied on PI3K signaling, likely explaining the poor efficacy of Notch inhibition in this disease. Remarkably, we found that both stem-like states could differentiate into a more mature leukemia state with prominent immunomodulatory functions, including high expression of the LGALS9 checkpoint molecule. These cells promoted an immunosuppressive leukemia ecosystem with clonal accumulation of dysfunctional CD8+ T cells that expressed HAVCR2, the cognate receptor for LGALS9. Our study identified complex interactions between signaling programs, cellular plasticity, and immune programs that characterize ETP-ALL, illustrating the multidimensionality of tumor heterogeneity. In this scenario, combination therapies targeting diverse oncogenic states and the immune ecosystem seem most promising to successfully eliminate tumor cells that escape treatment through coexisting transcriptional programs.

Recommendations for the FAIRification of genomic track metadata

Background: Many types of data from genomic analyses can be represented as genomic tracks, i.e. features linked to the genomic coordinates of a reference genome. Examples of such data are epigenetic DNA methylation data, ChIP-seq peaks, germline or somatic DNA variants, as well as RNA-seq expression levels. Researchers often face difficulties in locating, accessing and combining relevant tracks from external sources, as well as locating the raw data, reducing the value of the generated information.

Description of work: We propose to advance the application of FAIR data principles (Findable, Accessible, Interoperable, and Reusable) to produce searchable metadata for genomic tracks. Findability and Accessibility of metadata can then be ensured by a track search service that integrates globally identifiable metadata from various track hubs in the Track Hub Registry and other relevant repositories. Interoperability and Reusability need to be ensured by the specification and implementation of a basic set of recommendations for metadata. We have tested this concept by developing such a specification in a JSON Schema, called FAIRtracks, and have integrated it into a novel track search service, called TrackFind. We demonstrate practical usage by importing datasets through TrackFind into existing examples of relevant analytical tools for genomic tracks: EPICO and the GSuite HyperBrowser.

Conclusion: We here provide a first iteration of a draft standard for genomic track metadata, as well as the accompanying software ecosystem. It can easily be adapted or extended to future needs of the research community regarding data, methods and tools, balancing the requirements of both data submitters and analytical end-users.

A plug and play microfluidic platform for standardized sensitive low-input chromatin immunoprecipitation

Epigenetic profiling by chromatin immunoprecipitation followed by sequencing (ChIP-seq) has become a powerful tool for genome-wide identification of regulatory elements, for defining transcriptional regulatory networks, and for screening for biomarkers. However, the ChIP-seq protocol for low-input samples is laborious and time-consuming and suffers from experimental variation, resulting in poor reproducibility and low throughput. Although prototypic microfluidic ChIP-seq platforms have been developed, these are poorly transferable as they require sophisticated custom-made equipment and in-depth microfluidic and ChIP expertise, while lacking parallelization. To enable standardized, automated ChIP-seq profiling of low-input samples, we constructed microfluidic PDMS-based plates capable of performing 24 sensitive ChIP reactions within 30 min of hands-on time and 4.5 h of machine-running time. These disposable plates can be conveniently loaded into a widely available controller for pneumatics and thermocycling. In light of the plug and play (PnP) ChIP plates and workflow, we named our procedure PnP-ChIP-seq. We show high-quality ChIP-seq on hundreds to a few thousand of cells for all six post-translational histone modifications that are included in the International Human Epigenome Consortium set of reference epigenomes. PnP-ChIP-seq robustly detects epigenetic differences on promoters and enhancers between naive and more primed mouse embryonic stem cells (mESCs). Furthermore, we used our platform to generate epigenetic profiles of rare subpopulations of mESCs that resemble the two-cell stage of embryonic development. PnP-ChIP-seq allows nonexpert laboratories worldwide to conveniently run robust, standardized ChIP-seq, whereas its high throughput, consistency, and sensitivity pave the way toward large-scale profiling of precious sample types such as rare subpopulations of cells or biopsies.

Approaching Shared Pathophysiology in Immune-Mediated Diseases through Functional Genomics

Immune-mediated diseases (IMDs) are complex pathologies that are strongly influenced by environmental and genetic factors. Associations between genetic loci and susceptibility to these diseases have been widely studied, and hundreds of risk variants have emerged during the last two decades, with researchers observing a shared genetic pattern among them. Nevertheless, the pathological mechanism behind these associations remains a challenge that has just started to be understood thanks to functional genomic approaches. Transcriptomics, regulatory elements, chromatin interactome, as well as the experimental characterization of genomic findings, constitute key elements in the emerging understandings of how genetics affects the etiopathogenesis of IMDs. In this review, we will focus on the latest advances in the field of functional genomics, centering our attention on systemic rheumatic IMDs.