An atlas of cells in the human tonsil.

Palatine tonsils are secondary lymphoid organs (SLOs) representing the first line of immunological defense against inhaled or ingested pathogens. We generated an atlas of the human tonsil composed of >556,000 cells profiled across five different data modalities, including single-cell transcriptome, epigenome, proteome, and immune repertoire sequencing, as well as spatial transcriptomics. This census identified 121 cell types and states, defined developmental trajectories, and enabled an understanding of the functional units of the tonsil. Exemplarily, we stratified myeloid slan-like subtypes, established a BCL6 enhancer as locally active in follicle-associated T and B cells, and identified SIX5 as putative transcriptional regulator of plasma cell maturation. Analyses of a validation cohort confirmed the presence, annotation, and markers of tonsillar cell types and provided evidence of age-related compositional shifts. We demonstrate the value of this resource by annotating cells from B cell-derived mantle cell lymphomas, linking transcriptional heterogeneity to normal B cell differentiation states of the human tonsil.

Germ line variants in patients with acute myeloid leukemia without a suspicion of hereditary hematologic malignancy syndrome.

Germ line predisposition in acute myeloid leukemia (AML) has gained attention in recent years because of a nonnegligible frequency and an impact on management of patients and their relatives. Risk alleles for AML development may be present in patients without a clinical suspicion of hereditary hematologic malignancy syndrome. In this study we investigated the presence of germ line variants (GVs) in 288 genes related to cancer predisposition in 47 patients with available paired, tumor-normal material, namely bone marrow stroma cells (n = 29), postremission bone marrow (n = 17), and saliva (n = 1). These patients correspond to 2 broad AML categories with heterogeneous genetic background (AML myelodysplasia related and AML defined by differentiation) and none of them had phenotypic abnormalities, previous history of cytopenia, or strong cancer aggregation. We found 11 pathogenic or likely pathogenic variants, 6 affecting genes related to autosomal dominant cancer predisposition syndromes (ATM, DDX41, and CHEK2) and 5 related to autosomal recessive bone marrow failure syndromes (FANCA, FANCM, SBDS, DNAJC21, and CSF3R). We did not find differences in clinical characteristics nor outcome between carriers of GVs vs noncarriers. Further studies in unselected AML cohorts are needed to determine GV incidence and penetrance and, in particular, to clarify the role of ATM nonsense mutations in AML predisposition.

Dissecting the Origin of Heterogeneity in Uterine and Ovarian Carcinosarcomas.

Gynecologic carcinosarcomas (CS) are biphasic neoplasms composed of carcinomatous (C) and sarcomatous (S) malignant components. Because of their rarity and histologic complexity, genetic and functional studies on CS are scarce and the mechanisms of initiation and development remain largely unknown. Whole-genome analysis of the C and S components reveals shared genomic alterations, thus emphasizing the clonal evolution of CS. Reconstructions of the evolutionary history of each tumor further reveal that C and S samples are composed of both ancestral cell populations and component-specific subclones, supporting a common origin followed by distinct evolutionary trajectories. However, while we do not find any recurrent genomic features associated with phenotypic divergence, transcriptomic and methylome analyses identify a common mechanism across the cohort, the epithelial-to-mesenchymal transition (EMT), suggesting a role for nongenetic factors in inflicting changes to cellular fate. Altogether, these data accredit the hypothesis that CS tumors are driven by both clonal evolution and transcriptomic reprogramming, essential for susceptibility to transdifferentiation upon encountering environmental cues, thus linking CS heterogeneity to genetic, transcriptomic, and epigenetic influences. Significance: We have provided a detailed characterization of the genomic landscape of CS and identified EMT as a common mechanism associated with phenotypic divergence, linking CS heterogeneity to genetic, transcriptomic, and epigenetic influences.

Machine learning and multi-omics data in chronic lymphocytic leukemia: the future of precision medicine?

Chronic lymphocytic leukemia is a complex and heterogeneous hematological malignancy. The advance of high-throughput multi-omics technologies has significantly influenced chronic lymphocytic leukemia research and paved the way for precision medicine approaches. In this review, we explore the role of machine learning in the analysis of multi-omics data in this hematological malignancy. We discuss recent literature on different machine learning models applied to single omic studies in chronic lymphocytic leukemia, with a special focus on the potential contributions to precision medicine. Finally, we highlight the recently published machine learning applications in multi-omics data in this area of research as well as their potential and limitations.

DNA methylation in human gastric epithelial cells defines regional identity without restricting lineage plasticity.

BACKGROUND: Epigenetic modifications in mammalian DNA are commonly manifested by DNA methylation. In the stomach, altered DNA methylation patterns have been observed following chronic Helicobacter pylori infections and in gastric cancer. In the context of epigenetic regulation, the regional nature of the stomach has been rarely considered in detail. RESULTS: Here, we establish gastric mucosa derived primary cell cultures as a reliable source of native human epithelium. We describe the DNA methylation landscape across the phenotypically different regions of the healthy human stomach, i.e., antrum, corpus, fundus together with the corresponding transcriptomes. We show that stable regional DNA methylation differences translate to a limited extent into regulation of the transcriptomic phenotype, indicating a largely permissive epigenetic regulation. We identify a small number of transcription factors with novel region-specific activity and likely epigenetic impact in the stomach, including GATA4, IRX5, IRX2, PDX1 and CDX2. Detailed analysis of the Wnt pathway reveals differential regulation along the craniocaudal axis, which involves non-canonical Wnt signaling in determining cell fate in the proximal stomach. By extending our analysis to pre-neoplastic lesions and gastric cancers, we conclude that epigenetic dysregulation characterizes intestinal metaplasia as a founding basis for functional changes in gastric cancer. We present insights into the dynamics of DNA methylation across anatomical regions of the healthy stomach and patterns of its change in disease. Finally, our study provides a well-defined resource of regional stomach transcription and epigenetics.

Detection of early seeding of Richter transformation in chronic lymphocytic leukemia.

Richter transformation (RT) is a paradigmatic evolution of chronic lymphocytic leukemia (CLL) into a very aggressive large B cell lymphoma conferring a dismal prognosis. The mechanisms driving RT remain largely unknown. We characterized the whole genome, epigenome and transcriptome, combined with single-cell DNA/RNA-sequencing analyses and functional experiments, of 19 cases of CLL developing RT. Studying 54 longitudinal samples covering up to 19 years of disease course, we uncovered minute subclones carrying genomic, immunogenetic and transcriptomic features of RT cells already at CLL diagnosis, which were dormant for up to 19 years before transformation. We also identified new driver alterations, discovered a new mutational signature (SBS-RT), recognized an oxidative phosphorylation (OXPHOS)high-B cell receptor (BCR)low-signaling transcriptional axis in RT and showed that OXPHOS inhibition reduces the proliferation of RT cells. These findings demonstrate the early seeding of subclones driving advanced stages of cancer evolution and uncover potential therapeutic targets for RT.

PLCγ1/PKCθ Downstream Signaling Controls Cutaneous T-Cell Lymphoma Development and Progression.

Developing mechanistic rationales can improve the clinical management of cutaneous T-cell lymphomas. There is considerable genetic and biological evidence of a malignant network of signaling mechanisms, highly influenced by deregulated TCR/PLCγ1 activity, controlling the biology of these lesions. In addition, activated signal transducer and activator of transcription 3 is associated with clinical progression, although the alterations responsible for this have not been fully elucidated. Here, we studied PLCγ1-dependent mechanisms that can mediate STAT3 activation and control tumor growth and progression. Downstream of PLCγ1, the pharmacological inhibition and genetic knockdown of protein kinase C theta (PKCθ) inhibited signal transducer and activator of transcription 3 activation, impaired proliferation, and promoted apoptosis in cutaneous T-cell lymphoma cells. A PKCθ-dependent transcriptome in mycosis fungoides/Sézary syndrome cells revealed potential effector genes controlling cytokine signaling, TP53, and actin cytoskeleton dynamics. Consistently, an in vivo chicken embryo model xenografted with mycosis fungoides cells showed that PKCθ blockage abrogates tumor growth and spread to distant organs. Finally, the expression of a number of PKCθ target genes found in mycosis fungoides cells significantly correlated with that of PRKCQ (PKCθ) in 81 human mycosis fungoides samples. In summary, PKCθ can play a central role in the activation of malignant cutaneous T-cell lymphoma mechanisms via multiple routes, including, but not restricted to, STAT3. These mechanisms may, in turn, serve as targets for specific therapies.

A single-cell tumor immune atlas for precision oncology.

The tumor immune microenvironment is a main contributor to cancer progression and a promising therapeutic target for oncology. However, immune microenvironments vary profoundly between patients, and biomarkers for prognosis and treatment response lack precision. A comprehensive compendium of tumor immune cells is required to pinpoint predictive cellular states and their spatial localization. We generated a single-cell tumor immune atlas, jointly analyzing published data sets of >500,000 cells from 217 patients and 13 cancer types, providing the basis for a patient stratification based on immune cell compositions. Projecting immune cells from external tumors onto the atlas facilitated an automated cell annotation system. To enable in situ mapping of immune populations for digital pathology, we applied SPOTlight, combining single-cell and spatial transcriptomics data and identifying colocalization patterns of immune, stromal, and cancer cells in tumor sections. We expect the tumor immune cell atlas, together with our versatile toolbox for precision oncology, to advance currently applied stratification approaches for prognosis and immunotherapy.

SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes.

Spatially resolved gene expression profiles are key to understand tissue organization and function. However, spatial transcriptomics (ST) profiling techniques lack single-cell resolution and require a combination with single-cell RNA sequencing (scRNA-seq) information to deconvolute the spatially indexed datasets. Leveraging the strengths of both data types, we developed SPOTlight, a computational tool that enables the integration of ST with scRNA-seq data to infer the location of cell types and states within a complex tissue. SPOTlight is centered around a seeded non-negative matrix factorization (NMF) regression, initialized using cell-type marker genes and non-negative least squares (NNLS) to subsequently deconvolute ST capture locations (spots). Simulating varying reference quantities and qualities, we confirmed high prediction accuracy also with shallowly sequenced or small-sized scRNA-seq reference datasets. SPOTlight deconvolution of the mouse brain correctly mapped subtle neuronal cell states of the cortical layers and the defined architecture of the hippocampus. In human pancreatic cancer, we successfully segmented patient sections and further fine-mapped normal and neoplastic cell states. Trained on an external single-cell pancreatic tumor references, we further charted the localization of clinical-relevant and tumor-specific immune cell states, an illustrative example of its flexible application spectrum and future potential in digital pathology.

Dynamics of genome architecture and chromatin function during human B cell differentiation and neoplastic transformation.

To investigate the three-dimensional (3D) genome architecture across normal B cell differentiation and in neoplastic cells from different subtypes of chronic lymphocytic leukemia and mantle cell lymphoma patients, here we integrate in situ Hi-C and nine additional omics layers. Beyond conventional active (A) and inactive (B) compartments, we uncover a highly-dynamic intermediate compartment enriched in poised and polycomb-repressed chromatin. During B cell development, 28% of the compartments change, mostly involving a widespread chromatin activation from naive to germinal center B cells and a reversal to the naive state upon further maturation into memory B cells. B cell neoplasms are characterized by both entity and subtype-specific alterations in 3D genome organization, including large chromatin blocks spanning key disease-specific genes. This study indicates that 3D genome interactions are extensively modulated during normal B cell differentiation and that the genome of B cell neoplasias acquires a tumor-specific 3D genome architecture.

Framework for quality assessment of whole genome cancer sequences.

Bringing together cancer genomes from different projects increases power and allows the investigation of pan-cancer, molecular mechanisms. However, working with whole genomes sequenced over several years in different sequencing centres requires a framework to compare the quality of these sequences. We used the Pan-Cancer Analysis of Whole Genomes cohort as a test case to construct such a framework. This cohort contains whole cancer genomes of 2832 donors from 18 sequencing centres. We developed a non-redundant set of five quality control (QC) measurements to establish a star rating system. These QC measures reflect known differences in sequencing protocol and provide a guide to downstream analyses and allow for exclusion of samples of poor quality. We have found that this is an effective framework of quality measures. The implementation of the framework is available at: https://dockstore.org/containers/quay.io/jwerner_dkfz/pancanqc:1.2.2 .

Chromatin activation as a unifying principle underlying pathogenic mechanisms in multiple myeloma.

Multiple myeloma (MM) is a plasma cell neoplasm associated with a broad variety of genetic lesions. In spite of this genetic heterogeneity, MMs share a characteristic malignant phenotype whose underlying molecular basis remains poorly characterized. In the present study, we examined plasma cells from MM using a multi-epigenomics approach and demonstrated that, when compared to normal B cells, malignant plasma cells showed an extensive activation of regulatory elements, in part affecting coregulated adjacent genes. Among target genes up-regulated by this process, we found members of the NOTCH, NF-kB, MTOR signaling, and TP53 signaling pathways. Other activated genes included sets involved in osteoblast differentiation and response to oxidative stress, all of which have been shown to be associated with the MM phenotype and clinical behavior. We functionally characterized MM-specific active distant enhancers controlling the expression of thioredoxin (TXN), a major regulator of cellular redox status and, in addition, identified PRDM5 as a novel essential gene for MM. Collectively, our data indicate that aberrant chromatin activation is a unifying feature underlying the malignant plasma cell phenotype.

Blueprint of human thymopoiesis reveals molecular mechanisms of stage-specific TCR enhancer activation.

Cell differentiation is accompanied by epigenetic changes leading to precise lineage definition and cell identity. Here we present a comprehensive resource of epigenomic data of human T cell precursors along with an integrative analysis of other hematopoietic populations. Although T cell commitment is accompanied by large scale epigenetic changes, we observed that the majority of distal regulatory elements are constitutively unmethylated throughout T cell differentiation, irrespective of their activation status. Among these, the TCRA gene enhancer (Eα) is in an open and unmethylated chromatin structure well before activation. Integrative analyses revealed that the HOXA5-9 transcription factors repress the Eα enhancer at early stages of T cell differentiation, while their decommission is required for TCRA locus activation and enforced αß T lineage differentiation. Remarkably, the HOXA-mediated repression of Eα is paralleled by the ectopic expression of homeodomain-related oncogenes in T cell acute lymphoblastic leukemia. These results highlight an analogous enhancer repression mechanism at play in normal and cancer conditions, but imposing distinct developmental constraints.

The ELIXIR Human Copy Number Variations Community: building bioinformatics infrastructure for research.

Copy number variations (CNVs) are major causative contributors both in the genesis of genetic diseases and human neoplasias. While "High-Throughput" sequencing technologies are increasingly becoming the primary choice for genomic screening analysis, their ability to efficiently detect CNVs is still heterogeneous and remains to be developed. The aim of this white paper is to provide a guiding framework for the future contributions of ELIXIR's recently established human CNV Community, with implications beyond human disease diagnostics and population genomics. This white paper is the direct result of a strategy meeting that took place in September 2018 in Hinxton (UK) and involved representatives of 11 ELIXIR Nodes. The meeting led to the definition of priority objectives and tasks, to address a wide range of CNV-related challenges ranging from detection and interpretation to sharing and training. Here, we provide suggestions on how to align these tasks within the ELIXIR Platforms strategy, and on how to frame the activities of this new ELIXIR Community in the international context.

High degree of polyclonality hinders somatic mutation calling in lung brush samples of COPD cases and controls.

Chronic obstructive pulmonary disease (COPD) is induced by cigarette smoking and characterized by inflammation of airway tissue. Since smokers with COPD have a higher risk of developing lung cancer than those without, we hypothesized that they carry more mutations in affected tissue. We called somatic mutations in airway brush samples from medium-coverage whole genome sequencing data from healthy never and ex-smokers (n = 8), as well as from ex-smokers with variable degrees of COPD (n = 4). Owing to the limited concordance of resulting calls between the applied tools we built a consensus, a strategy that was validated with high accuracy for cancer data. However, consensus calls showed little promise of representing true positives due to low mappability of corresponding sequence reads and high overlap with positions harbouring known genetic polymorphisms. A targeted re-sequencing approach suggested that only few mutations would survive stringent verification testing and that our data did not allow the inference of any difference in the mutational load of bronchial brush samples between former smoking COPD cases and controls. High polyclonality in airway brush samples renders medium-depth sequencing insufficient to provide the resolution to detect somatic mutations. Deep sequencing data of airway biopsies are needed to tackle the question.

Recurrent somatic mutations reveal new insights into consequences of mutagenic processes in cancer.

The sheer size of the human genome makes it improbable that identical somatic mutations at the exact same position are observed in multiple tumours solely by chance. The scarcity of cancer driver mutations also precludes positive selection as the sole explanation. Therefore, recurrent mutations may be highly informative of characteristics of mutational processes. To explore the potential, we use recurrence as a starting point to cluster >2,500 whole genomes of a pan-cancer cohort. We describe each genome with 13 recurrence-based and 29 general mutational features. Using principal component analysis we reduce the dimensionality and create independent features. We apply hierarchical clustering to the first 18 principal components followed by k-means clustering. We show that the resulting 16 clusters capture clinically relevant cancer phenotypes. High levels of recurrent substitutions separate the clusters that we link to UV-light exposure and deregulated activity of POLE from the one representing defective mismatch repair, which shows high levels of recurrent insertions/deletions. Recurrence of both mutation types characterizes cancer genomes with somatic hypermutation of immunoglobulin genes and the cluster of genomes exposed to gastric acid. Low levels of recurrence are observed for the cluster where tobacco-smoke exposure induces mutagenesis and the one linked to increased activity of cytidine deaminases. Notably, the majority of substitutions are recurrent in a single tumour type, while recurrent insertions/deletions point to shared processes between tumour types. Recurrence also reveals susceptible sequence motifs, including TT[C>A]TTT and AAC[T>G]T for the POLE and 'gastric-acid exposure' clusters, respectively. Moreover, we refine knowledge of mutagenesis, including increased C/G deletion levels in general for lung tumours and specifically in midsize homopolymer sequence contexts for microsatellite instable tumours. Our findings are an important step towards the development of a generic cancer diagnostic test for clinical practice based on whole-genome sequencing that could replace multiple diagnostics currently in use.

The Genome Sequence of the Eastern Woodchuck (Marmota monax) - A Preclinical Animal Model for Chronic Hepatitis B.

The Eastern woodchuck (Marmota monax) has been extensively used in research of chronic hepatitis B and liver cancer because its infection with the woodchuck hepatitis virus closely resembles a human hepatitis B virus infection. Development of novel immunotherapeutic approaches requires genetic information on immune pathway genes in this animal model. The woodchuck genome was assembled with a combination of high-coverage whole-genome shotgun sequencing of Illumina paired-end, mate-pair libraries and fosmid pool sequencing. The result is a 2.63 Gigabase (Gb) assembly with a contig N50 of 74.5 kilobases (kb), scaffold N50 of 892 kb, and genome completeness of 99.2%. RNA sequencing (RNA-seq) from seven different tissues aided in the annotation of 30,873 protein-coding genes, which in turn encode 41,826 unique protein products. More than 90% of the genes have been functionally annotated, with 82% of them containing open reading frames. This genome sequence and its annotation will enable further research in chronic hepatitis B and hepatocellular carcinoma and contribute to the understanding of immunological responses in the woodchuck.

Pheno-seq - linking visual features and gene expression in 3D cell culture systems.

Patient-derived 3D cell culture systems are currently advancing cancer research since they potentiate the molecular analysis of tissue-like properties and drug response under well-defined conditions. However, our understanding of the relationship between the heterogeneity of morphological phenotypes and the underlying transcriptome is still limited. To address this issue, we here introduce "pheno-seq" to directly link visual features of 3D cell culture systems with profiling their transcriptome. As prototypic applications breast and colorectal cancer (CRC) spheroids were analyzed by pheno-seq. We identified characteristic gene expression signatures of epithelial-to-mesenchymal transition that are associated with invasive growth behavior of clonal breast cancer spheroids. Furthermore, we linked long-term proliferative capacity in a patient-derived model of CRC to a lowly abundant PROX1-positive cancer stem cell subtype. We anticipate that the ability to integrate transcriptome analysis and morphological patho-phenotypes of cancer cells will provide novel insight on the molecular origins of intratumor heterogeneity.

Partially methylated domains are hypervariable in breast cancer and fuel widespread CpG island hypermethylation.

Global loss of DNA methylation and CpG island (CGI) hypermethylation are key epigenomic aberrations in cancer. Global loss manifests itself in partially methylated domains (PMDs) which extend up to megabases. However, the distribution of PMDs within and between tumor types, and their effects on key functional genomic elements including CGIs are poorly defined. We comprehensively show that loss of methylation in PMDs occurs in a large fraction of the genome and represents the prime source of DNA methylation variation. PMDs are hypervariable in methylation level, size and distribution, and display elevated mutation rates. They impose intermediate DNA methylation levels incognizant of functional genomic elements including CGIs, underpinning a CGI methylator phenotype (CIMP). Repression effects on tumor suppressor genes are negligible as they are generally excluded from PMDs. The genomic distribution of PMDs reports tissue-of-origin and may represent tissue-specific silent regions which tolerate instability at the epigenetic, transcriptomic and genetic level.

Clonal dynamics monitoring during clinical evolution in chronic lymphocytic leukaemia.

Chronic lymphocytic leukaemia is the most prevalent leukaemia in Western countries. It is an incurable disease characterized by a highly variable clinical course. Chronic lymphocytic leukaemia is an ideal model for studying clonal heterogeneity and dynamics during cancer progression, response to therapy and/or relapse because the disease usually develops over several years. Here we report an analysis by deep sequencing of sequential samples taken at different times from the affected organs of two patients with 12- and 7-year disease courses, respectively. One of the patients followed a linear pattern of clonal evolution, acquiring and selecting new mutations in response to salvage therapy and/or allogeneic transplantation, while the other suffered loss of cellular tumoral clones during progression and histological transformation.