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EOMES and T-BET are related T-box transcription factors that control natural killer (NK) cell development. Here we demonstrate that EOMES and T-BET regulate largely distinct gene sets during this process. EOMES is dominantly expressed in immature NK cells and drives early lineage specification by inducing hallmark receptors and functions. By contrast, T-BET is dominant in mature NK cells, where it induces responsiveness to IL-12 and represses the cell cycle, likely through transcriptional repressors. Regardless, many genes with distinct functions are co-regulated by the two transcription factors. By generating two gene-modified mice facilitating chromatin immunoprecipitation of endogenous EOMES and T-BET, we show a strong overlap in their DNA binding targets, as well as extensive epigenetic changes during NK cell differentiation. Our data thus suggest that EOMES and T-BET may distinctly govern, via differential expression and co-factors recruitment, NK cell maturation by inserting partially overlapping epigenetic regulations.

Primary liver cancer represents a major health problem. It comprises hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC), which differ markedly with regards to their morphology, metastatic potential and responses to therapy. However, the regulatory molecules and tissue context that commit transformed hepatic cells towards HCC or ICC are largely unknown. Here we show that the hepatic microenvironment epigenetically shapes lineage commitment in mosaic mouse models of liver tumorigenesis. Whereas a necroptosis-associated hepatic cytokine microenvironment determines ICC outgrowth from oncogenically transformed hepatocytes, hepatocytes containing identical oncogenic drivers give rise to HCC if they are surrounded by apoptotic hepatocytes. Epigenome and transcriptome profiling of mouse HCC and ICC singled out Tbx3 and Prdm5 as major microenvironment-dependent and epigenetically regulated lineage-commitment factors, a function that is conserved in humans. Together, our results provide insight into lineage commitment in liver tumorigenesis, and explain molecularly why common liver-damaging risk factors can lead to either HCC or ICC. The tumour microenvironment determines which type of liver cancer develops, with transformed hepatocytes giving rise to intrahepatic cholangiocarcinoma or hepatocellular carcinoma depending or whether they are surrounded by cells undergoing necroptosis or apoptosis.

ZBTB7A is frequently mutated in acute myeloid leukemia (AML) with t(8;21) translocation. However, the oncogenic collaboration between mutated ZBTB7A and the RUNX1–RUNX1T1 fusion gene in AML t(8;21) remains unclear. Here, we investigate the role of ZBTB7A and its mutations in the context of normal and malignant hematopoiesis. We demonstrate that clinically relevant ZBTB7A mutations in AML t(8;21) lead to loss of function and result in perturbed myeloid differentiation with block of the granulocytic lineage in favor of monocytic commitment. In addition, loss of ZBTB7A increases glycolysis and hence sensitizes leukemic blasts to metabolic inhibition with 2-deoxy-d-glucose. We observed that ectopic expression of wild-type ZBTB7A prevents RUNX1-RUNX1T1-mediated clonal expansion of human CD34+ cells, whereas the outgrowth of progenitors is enabled by ZBTB7A mutation. Finally, ZBTB7A expression in t(8;21) cells lead to a cell cycle arrest that could be mimicked by inhibition of glycolysis. Our findings suggest that loss of ZBTB7A may facilitate the onset of AML t(8;21), and that RUNX1-RUNX1T1-rearranged leukemia might be treated with glycolytic inhibitors.

Spatial transcriptomics (ST) technology through in situ capturing has enabled topographical gene expression profiling of tumor tissues. However, each capturing spot may contain diverse immune and malignant cells, with different cell densities across tissue regions. Cell type deconvolution in tumor ST data remains challenging for existing methods designed to decompose general ST or bulk tumor data. We develop the Spatial Cellular Estimator for Tumors (SpaCET) to infer cell identities from tumor ST data. SpaCET first estimates cancer cell abundance by integrating a gene pattern dictionary of copy number alterations and expression changes in common malignancies. A constrained regression model then calibrates local cell densities and determines immune and stromal cell lineage fractions. SpaCET provides higher accuracy than existing methods based on simulation and real ST data with matched double-blind histopathology annotations as ground truth. Further, coupling cell fractions with ligand-receptor coexpression analysis, SpaCET reveals how intercellular interactions at the tumor-immune interface promote cancer progression. Cell type deconvolution in tumor spatial transcriptomics (ST) data remains challenging. Here, the authors develop Spatial Cellular Estimator for Tumors (SpaCET) to infer cell types and intercellular interactions from ST data in cancer across different platforms, with improved performance over similar methods.

During development, blood generation begins in the yolk sac with the differentiation of haemato-endothelial mesoderm forming haematopoietic progenitors. This study aims to identify the crucial molecular regulators of haemato-endothelial mesoderm formation and to extend our knowledge of the process in an unbiased way. We employ a murine embryonic stem cell model that recapitulates embryonic blood development, and perform targeted CRISPR-Cas9 knock out screens focusing on transcription factors and chromatin regulators. We identify the transcription factors ETV2, LDB1, SMAD1, SIX4 and ZBTB7b as regulators of haemato-endothelial mesoderm commitment. Embryonic stem cells lacking these regulators give rise to mesodermal subsets with a defined lineage differentiation bias, while transcriptome analysis of these cells uncovers the precise impact of each factor on gene expression in the developing mesoderm. Our study reveals molecular pathways governing mesodermal development crucial to allow endothelial and haematopoietic lineage specification and paves the way for future advances in haematopoietic stem cell applications. During development, blood is generated in the yolk sac by differentiation of haemato-endothelial mesoderm into haematopoietic progenitors. Using CRISPR-Cas9 screens, the authors identify Etv2, Smad1, Ldb1, Six4 and Zbtb7b as regulators of haemato-endothelial mesoderm commitment. Lack of these regulators gave rise to mesodermal subsets with a defined lineage differentiation bias.

B cell chronic lymphocytic leukemia (CLL) is a disease of expanding monoclonal B cells whose B cell receptor (BCR) mutational status defines 2 subgroups; patients with mutated BCRs have a more favorable prognosis than those with unmutated BCRs. CLL B cells express a restricted BCR repertoire including antibodies with quasi-identical complementarity-determining region 3 (CDR3), which suggests specific antigen recognition. The antigens recognized by CLL antibodies may include autoantigens since about half of CLL B cells produce autoreactive antibodies. However, the distribution of autoreactive antibodies between Ig heavy-chain variable-unmutated (IgV-unmutated) CLL (UM-CLL) and IgV-mutated CLL (M-CLL) is unknown. To determine the role of antibody reactivity and the impact of somatic hypermutation (SHM) on CLL antibody specificity, we cloned and expressed in vitro recombinant antibodies from M- and UM-CLL B cells and tested their reactivity by ELISA. We found that UM-CLL B cells expressed highly polyreactive antibodies whereas most M-CLL B cells did not. When mutated nonautoreactive CLL antibody sequences were reverted in vitro to their germline counterparts, they encoded polyreactive and autoreactive antibodies. We concluded that both UM-CLLs and M-CLLs originate from self-reactive B cell precursors and that SHM plays an important role in the development of the disease by altering original BCR autoreactivity.

Background Mitochondrial genome copy number (MT-CN) varies among humans and across tissues and is highly heritable, but its causes and consequences are not well understood. When measured by bulk DNA sequencing in blood, MT-CN may reflect a combination of the number of mitochondria per cell and cell-type composition. Here, we studied MT-CN variation in blood-derived DNA from 19184 Finnish individuals using a combination of genome (N = 4163) and exome sequencing (N = 19034) data as well as imputed genotypes (N = 17718). Results We identified two loci significantly associated with MT-CN variation: a common variant at the MYB-HBS1L locus (P = 1.6 × 10 −8 ), which has previously been associated with numerous hematological parameters; and a burden of rare variants in the TMBIM1 gene (P = 3.0 × 10 −8 ), which has been reported to protect against non-alcoholic fatty liver disease. We also found that MT-CN is strongly associated with insulin levels (P = 2.0 × 10 −21 ) and other metabolic syndrome (metS)-related traits. Using a Mendelian randomization framework, we show evidence that MT-CN measured in blood is causally related to insulin levels. We then applied an MT-CN polygenic risk score (PRS) derived from Finnish data to the UK Biobank, where the association between the PRS and metS traits was replicated. Adjusting for cell counts largely eliminated these signals, suggesting that MT-CN affects metS via cell-type composition. Conclusion These results suggest that measurements of MT-CN in blood-derived DNA partially reflect differences in cell-type composition and that these differences are causally linked to insulin and related traits.

The derivation of induced pluripotent stem cells (iPSCs) over a decade ago sparked widespread enthusiasm for the development of new models of human disease, enhanced platforms for drug discovery and more widespread use of autologous cell-based therapy. Early studies using directed differentiation of iPSCs frequently uncovered cell-level phenotypes in monogenic diseases, but translation to tissue-level and organ-level diseases has required development of more complex, 3D, multicellular systems. Organoids and human–rodent chimaeras more accurately mirror the diverse cellular ecosystems of complex tissues and are being applied to iPSC disease models to recapitulate the pathobiology of a broad spectrum of human maladies, including infectious diseases, genetic disorders and cancer.Enthusiasm for patient-specific therapies based on induced pluripotent stem cells (iPSCs) has risen in parallel with rapid advances in genome editing. This Review summarizes the progress in iPSC-based disease modelling over the past decade, with a focus on 3D organoid systems and chimeric models being exploited for new therapeutic approaches.

The deposition of chemical modifications into RNA is a crucial regulator of temporal and spatial gene expression programs during development. Accordingly, altered RNA modification patterns are widely linked to developmental diseases. Recently, the dysregulation of RNA modification pathways also emerged as a contributor to cancer. By modulating cell survival, differentiation, migration and drug resistance, RNA modifications add another regulatory layer of complexity to most aspects of tumourigenesis. Sylvain et al. review cellular functions of various RNA modifications and their roles in regulating cell fate in normal and cancer tissues.

Recent evidence has elucidated how multipotent blood progenitors transform their identities in the thymus and undergo commitment to become T cells. Together with environmental signals, a core group of transcription factors have essential roles in this process by directly activating and repressing specific genes. Many of these transcription factors also function in later T cell development, but control different genes. Here, we review how these transcription factors work to change the activities of specific genomic loci during early intrathymic development to establish T cell lineage identity. We introduce the key regulators and highlight newly emergent insights into the rules that govern their actions. Whole-genome deep sequencing-based analysis has revealed unexpectedly rich relationships between inherited epigenetic states, transcription factor–DNA binding affinity thresholds and influences of given transcription factors on the activities of other factors in the same cells. Together, these mechanisms determine T cell identity and make the lineage choice irreversible.A transcription factor network triggered by Notch signalling in the thymus guides proliferating, multipotent progenitor cells into the T cell pathway. This Review describes how these factors work to establish regulatory target specificity, epigenomic impact and irreversibility for T cell identity.