Intrinsically disordered domain of transcription factor TCF-1 is required for T cell developmental fidelity.

In development, pioneer transcription factors access silent chromatin to reveal lineage-specific gene programs. The structured DNA-binding domains of pioneer factors have been well characterized, but whether and how intrinsically disordered regions affect chromatin and control cell fate is unclear. Here, we report that deletion of an intrinsically disordered region of the pioneer factor TCF-1 (termed L1) leads to an early developmental block in T cells. The few T cells that develop from progenitors expressing TCF-1 lacking L1 exhibit lineage infidelity distinct from the lineage diversion of TCF-1-deficient cells. Mechanistically, L1 is required for activation of T cell genes and repression of GATA2-driven genes, normally reserved to the mast cell and dendritic cell lineages. Underlying this lineage diversion, L1 mediates binding of TCF-1 to its earliest target genes, which are subject to repression as T cells develop. These data suggest that the intrinsically disordered N terminus of TCF-1 maintains T cell lineage fidelity.

EBF1 nuclear repositioning instructs chromatin refolding to promote therapy resistance in T leukemic cells.

Chromatin misfolding has been implicated in cancer pathogenesis; yet, its role in therapy resistance remains unclear. Here, we systematically integrated sequencing and imaging data to examine the spatial and linear chromatin structures in targeted therapy-sensitive and -resistant human T cell acute lymphoblastic leukemia (T-ALL). We found widespread alterations in successive layers of chromatin organization including spatial compartments, contact domain boundaries, and enhancer positioning upon the emergence of targeted therapy resistance. The reorganization of genome folding structures closely coincides with the restructuring of chromatin activity and redistribution of architectural proteins. Mechanistically, the derepression and repositioning of the B-lineage-determining transcription factor EBF1 from the heterochromatic nuclear envelope to the euchromatic interior instructs widespread genome refolding and promotes therapy resistance in leukemic T cells. Together, our findings suggest that lineage-determining transcription factors can instruct changes in genome topology as a driving force for epigenetic adaptations in targeted therapy resistance.

Genetic Variation in Type 1 Diabetes Reconfigures the 3D Chromatin Organization of T Cells and Alters Gene Expression.

Genetics is a major determinant of susceptibility to autoimmune disorders. Here, we examined whether genome organization provides resilience or susceptibility to sequence variations, and how this would contribute to the molecular etiology of an autoimmune disease. We generated high-resolution maps of linear and 3D genome organization in thymocytes of NOD mice, a model of type 1 diabetes (T1D), and the diabetes-resistant C57BL/6 mice. Multi-enhancer interactions formed at genomic regions harboring genes with prominent roles in T cell development in both strains. However, diabetes risk-conferring loci coalesced enhancers and promoters in NOD, but not C57BL/6 thymocytes. 3D genome mapping of NODxC57BL/6 F1 thymocytes revealed that genomic misfolding in NOD mice is mediated in cis. Moreover, immune cells infiltrating the pancreas of humans with T1D exhibited increased expression of genes located on misfolded loci in mice. Thus, genetic variation leads to altered 3D chromatin architecture and associated changes in gene expression that may underlie autoimmune pathology.

ZMYND8-regulated IRF8 transcription axis is an acute myeloid leukemia dependency.

The transformed state in acute leukemia requires gene regulatory programs involving transcription factors and chromatin modulators. Here, we uncover an IRF8-MEF2D transcriptional circuit as an acute myeloid leukemia (AML)-biased dependency. We discover and characterize the mechanism by which the chromatin "reader" ZMYND8 directly activates IRF8 in parallel with the MYC proto-oncogene through their lineage-specific enhancers. ZMYND8 is essential for AML proliferation in vitro and in vivo and associates with MYC and IRF8 enhancer elements that we define in cell lines and in patient samples. ZMYND8 occupancy at IRF8 and MYC enhancers requires BRD4, a transcription coactivator also necessary for AML proliferation. We show that ZMYND8 binds to the ET domain of BRD4 via its chromatin reader cassette, which in turn is required for proper chromatin occupancy and maintenance of leukemic growth in vivo. Our results rationalize ZMYND8 as a potential therapeutic target for modulating essential transcriptional programs in AML.

Identification of early replicating fragile sites that contribute to genome instability.

DNA double-strand breaks (DSBs) in B lymphocytes arise stochastically during replication or as a result of targeted DNA damage by activation-induced cytidine deaminase (AID). Here we identify recurrent, early replicating, and AID-independent DNA lesions, termed early replication fragile sites (ERFSs), by genome-wide localization of DNA repair proteins in B cells subjected to replication stress. ERFSs colocalize with highly expressed gene clusters and are enriched for repetitive elements and CpG dinucleotides. Although distinct from late-replicating common fragile sites (CFS), the stability of ERFSs and CFSs is similarly dependent on the replication-stress response kinase ATR. ERFSs break spontaneously during replication, but their fragility is increased by hydroxyurea, ATR inhibition, or deregulated c-Myc expression. Moreover, greater than 50% of recurrent amplifications/deletions in human diffuse large B cell lymphoma map to ERFSs. In summary, we have identified a source of spontaneous DNA lesions that drives instability at preferred genomic sites.

53BP1 mediates productive and mutagenic DNA repair through distinct phosphoprotein interactions.

The DNA damage response (DDR) protein 53BP1 protects DNA ends from excessive resection in G1, and thereby favors repair by nonhomologous end-joining (NHEJ) as opposed to homologous recombination (HR). During S phase, BRCA1 antagonizes 53BP1 to promote HR. The pro-NHEJ and antirecombinase functions of 53BP1 are mediated in part by RIF1, the only known factor that requires 53BP1 phosphorylation for its recruitment to double-strand breaks (DSBs). Here, we show that a 53BP1 phosphomutant, 53BP18A, comprising alanine substitutions of the eight most N-terminal S/TQ phosphorylation sites, mimics 53BP1 deficiency by restoring genome stability in BRCA1-deficient cells yet behaves like wild-type 53BP1 with respect to immunoglobulin class switch recombination (CSR). 53BP18A recruits RIF1 but fails to recruit the DDR protein PTIP to DSBs, and disruption of PTIP phenocopies 53BP18A. We conclude that 53BP1 promotes productive CSR and suppresses mutagenic DNA repair through distinct phosphodependent interactions with RIF1 and PTIP.

Tumor Cell-Intrinsic Factors Underlie Heterogeneity of Immune Cell Infiltration and Response to Immunotherapy.

The biological and functional heterogeneity between tumors-both across and within cancer types-poses a challenge for immunotherapy. To understand the factors underlying tumor immune heterogeneity and immunotherapy sensitivity, we established a library of congenic tumor cell clones from an autochthonous mouse model of pancreatic adenocarcinoma. These clones generated tumors that recapitulated T cell-inflamed and non-T-cell-inflamed tumor microenvironments upon implantation in immunocompetent mice, with distinct patterns of infiltration by immune cell subsets. Co-injecting tumor cell clones revealed the non-T-cell-inflamed phenotype is dominant and that both quantitative and qualitative features of intratumoral CD8+ T cells determine response to therapy. Transcriptomic and epigenetic analyses revealed tumor-cell-intrinsic production of the chemokine CXCL1 as a determinant of the non-T-cell-inflamed microenvironment, and ablation of CXCL1 promoted T cell infiltration and sensitivity to a combination immunotherapy regimen. Thus, tumor cell-intrinsic factors shape the tumor immune microenvironment and influence the outcome of immunotherapy.

Oncogenic Notch Promotes Long-Range Regulatory Interactions within Hyperconnected 3D Cliques.

Chromatin loops enable transcription-factor-bound distal enhancers to interact with their target promoters to regulate transcriptional programs. Although developmental transcription factors such as active forms of Notch can directly stimulate transcription by activating enhancers, the effect of their oncogenic subversion on the 3D organization of cancer genomes is largely undetermined. By mapping chromatin looping genome-wide in Notch-dependent triple-negative breast cancer and B cell lymphoma, we show that beyond the well-characterized role of Notch as an activator of distal enhancers, Notch regulates its direct target genes by instructing enhancer repositioning. Moreover, a large fraction of Notch-instructed regulatory loops form highly interacting enhancer and promoter spatial clusters termed "3D cliques." Loss- and gain-of-function experiments show that Notch preferentially targets hyperconnected 3D cliques that regulate the expression of crucial proto-oncogenes. Our observations suggest that oncogenic hijacking of developmental transcription factors can dysregulate transcription through widespread effects on the spatial organization of cancer genomes.

TooManyCells identifies and visualizes relationships of single-cell clades.

Identifying and visualizing transcriptionally similar cells is instrumental for accurate exploration of the cellular diversity revealed by single-cell transcriptomics. However, widely used clustering and visualization algorithms produce a fixed number of cell clusters. A fixed clustering 'resolution' hampers our ability to identify and visualize echelons of cell states. We developed TooManyCells, a suite of graph-based algorithms for efficient and unbiased identification and visualization of cell clades. TooManyCells introduces a visualization model built on a concept intentionally orthogonal to dimensionality-reduction methods. TooManyCells is also equipped with an efficient matrix-free divisive hierarchical spectral clustering different from prevalent single-resolution clustering methods. TooManyCells enables multiresolution and multifaceted exploration of single-cell clades. An advantage of this paradigm is the immediate detection of rare and common populations that outperforms popular clustering and visualization algorithms, as demonstrated using existing single-cell transcriptomic data sets and new data modeling drug-resistance acquisition in leukemic T cells.

The DNA damage- and transcription-associated protein paxip1 controls thymocyte development and emigration.

Histone 3 lysine 4 trimethylation (H3K4me3) is associated with promoters of active genes and found at hot spots for DNA recombination. Here we have shown that PAXIP1 (also known as PTIP), a protein associated with MLL3 and MLL4 methyltransferase and the DNA damage response, regulates RAG-mediated cleavage and repair during V(D)J recombination in CD4(+) CD8(+) DP thymocytes. Loss of PAXIP1 in developing thymocytes diminished Jα H3K4me3 and germline transcription, suppressed double strand break formation at 3' Jα segments, but resulted in accumulation of unresolved T cell receptor α-chain gene (Tcra) breaks. Moreover, PAXIP1 was essential for release of mature single positive (SP) αß T cells from the thymus through transcriptional activation of sphingosine-1-phosphate receptor S1pr1 as well as for natural killer T cell development. Thus, in addition to maintaining genome integrity during Tcra rearrangements, PAXIP1 controls distinct transcriptional programs during DP differentiation necessary for Tcra locus accessibility, licensing mature thymocytes for trafficking and natural killer T cell development.

DNA-damage-induced differentiation of leukaemic cells as an anti-cancer barrier.

Self-renewal is the hallmark feature both of normal stem cells and cancer stem cells. Since the regenerative capacity of normal haematopoietic stem cells is limited by the accumulation of reactive oxygen species and DNA double-strand breaks, we speculated that DNA damage might also constrain leukaemic self-renewal and malignant haematopoiesis. Here we show that the histone methyl-transferase MLL4, a suppressor of B-cell lymphoma, is required for stem-cell activity and an aggressive form of acute myeloid leukaemia harbouring the MLL-AF9 oncogene. Deletion of MLL4 enhances myelopoiesis and myeloid differentiation of leukaemic blasts, which protects mice from death related to acute myeloid leukaemia. MLL4 exerts its function by regulating transcriptional programs associated with the antioxidant response. Addition of reactive oxygen species scavengers or ectopic expression of FOXO3 protects MLL4(-/-) MLL-AF9 cells from DNA damage and inhibits myeloid maturation. Similar to MLL4 deficiency, loss of ATM or BRCA1 sensitizes transformed cells to differentiation, suggesting that myeloid differentiation is promoted by loss of genome integrity. Indeed, we show that restriction-enzyme-induced double-strand breaks are sufficient to induce differentiation of MLL-AF9 blasts, which requires cyclin-dependent kinase inhibitor p21(Cip1) (Cdkn1a) activity. In summary, we have uncovered an unexpected tumour-promoting role of genome guardians in enforcing the oncogene-induced differentiation blockade in acute myeloid leukaemia.

BRCA1 functions independently of homologous recombination in DNA interstrand crosslink repair.

Brca1 is required for DNA repair by homologous recombination (HR) and normal embryonic development. Here we report that deletion of the DNA damage response factor 53BP1 overcomes embryonic lethality in Brca1-nullizygous mice and rescues HR deficiency, as measured by hypersensitivity to polyADP-ribose polymerase (PARP) inhibition. However, Brca1,53BP1 double-deficient cells are hypersensitive to DNA interstrand crosslinks (ICLs), indicating that BRCA1 has an additional role in DNA crosslink repair that is distinct from HR. Disruption of the nonhomologous end-joining (NHEJ) factor, Ku, promotes DNA repair in Brca1-deficient cells; however deletion of either Ku or 53BP1 exacerbates genomic instability in cells lacking FANCD2, a mediator of the Fanconi anemia pathway for ICL repair. BRCA1 therefore has two separate roles in ICL repair that can be modulated by manipulating NHEJ, whereas FANCD2 provides a key activity that cannot be bypassed by ablation of 53BP1 or Ku.

Functional proteogenomics reveals biomarkers and therapeutic targets in lymphomas.

Identification of biomarkers and therapeutic targets is a critical goal of precision medicine. N-glycoproteins are a particularly attractive class of proteins that constitute potential cancer biomarkers and therapeutic targets for small molecules, antibodies, and cellular therapies. Using mass spectrometry (MS), we generated a compendium of 1,091 N-glycoproteins (from 40 human primary lymphomas and cell lines). Hierarchical clustering revealed distinct subtype signatures that included several subtype-specific biomarkers. Orthogonal immunological studies in 671 primary lymphoma tissue biopsies and 32 lymphoma-derived cell lines corroborated MS data. In anaplastic lymphoma kinase-positive (ALK+) anaplastic large cell lymphoma (ALCL), integration of N-glycoproteomics and transcriptome sequencing revealed an ALK-regulated cytokine/receptor signaling network, including vulnerabilities corroborated by a genome-wide clustered regularly interspaced short palindromic screen. Functional targeting of IL-31 receptor ß, an ALCL-enriched and ALK-regulated N-glycoprotein in this network, abrogated ALK+ALCL growth in vitro and in vivo. Our results highlight the utility of functional proteogenomic approaches for discovery of cancer biomarkers and therapeutic targets.

Enhancer-promoter hubs organize transcriptional networks promoting oncogenesis and drug resistance.

Recent advances in high-resolution mapping of spatial interactions among regulatory elements support the existence of complex topological assemblies of enhancers and promoters known as enhancer-promoter hubs or cliques. Yet, organization principles of these multi-interacting enhancer-promoter hubs and their potential role in regulating gene expression in cancer remains unclear. Here, we systematically identified enhancer-promoter hubs in breast cancer, lymphoma, and leukemia. We found that highly interacting enhancer-promoter hubs form at key oncogenes and lineage-associated transcription factors potentially promoting oncogenesis of these diverse cancer types. Genomic and optical mapping of interactions among enhancer and promoter elements further showed that topological alterations in hubs coincide with transcriptional changes underlying acquired resistance to targeted therapy in T cell leukemia and B cell lymphoma. Together, our findings suggest that enhancer-promoter hubs are dynamic and heterogeneous topological assemblies with the potential to control gene expression circuits promoting oncogenesis and drug resistance.

Oncogenic transcription factors instruct promoter-enhancer hubs in individual triple negative breast cancer cells.

Sequencing-based mapping of ensemble pairwise interactions among regulatory elements support the existence of topological assemblies known as promoter-enhancer hubs or cliques in cancer. Yet, prevalence, regulators, and functions of promoter-enhancer hubs in individual cancer cells remain unclear. Here, we systematically integrated functional genomics, transcription factor screening, and optical mapping of promoter-enhancer interactions to identify key promoter-enhancer hubs, examine heterogeneity of their assembly, determine their regulators, and elucidate their role in gene expression control in individual triple negative breast cancer (TNBC) cells. Optical mapping of individual SOX9 and MYC alleles revealed the existence of frequent multiway interactions among promoters and enhancers within spatial hubs. Our single-allele studies further demonstrated that lineage-determining SOX9 and signaling-dependent NOTCH1 transcription factors compact MYC and SOX9 hubs. Together, our findings suggest that promoter-enhancer hubs are dynamic and heterogeneous topological assemblies, which are controlled by oncogenic transcription factors and facilitate subtype-restricted gene expression in cancer.

Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets.

Type 1 diabetes (T1D) is a chronic condition in which beta cells are destroyed by immune cells. Despite progress in immunotherapies that could delay T1D onset, early detection of autoimmunity remains challenging. Here, we evaluate the utility of machine learning for early prediction of T1D using single-cell analysis of islets. Using gradient-boosting algorithms, we model changes in gene expression of single cells from pancreatic tissues in T1D and non-diabetic organ donors. We assess if mathematical modeling could predict the likelihood of T1D development in non-diabetic autoantibody-positive donors. While most autoantibody-positive donors are predicted to be non-diabetic, select donors with unique gene signatures are classified as T1D. Our strategy also reveals a shared gene signature in distinct T1D-associated models across cell types, suggesting a common effect of the disease on transcriptional outputs of these cells. Our study establishes a precedent for using machine learning in early detection of T1D.

AnnoSpat annotates cell types and quantifies cellular arrangements from spatial proteomics.

Cellular composition and anatomical organization influence normal and aberrant organ functions. Emerging spatial single-cell proteomic assays such as Image Mass Cytometry (IMC) and Co-Detection by Indexing (CODEX) have facilitated the study of cellular composition and organization by enabling high-throughput measurement of cells and their localization directly in intact tissues. However, annotation of cell types and quantification of their relative localization in tissues remain challenging. To address these unmet needs for atlas-scale datasets like Human Pancreas Analysis Program (HPAP), we develop AnnoSpat (Annotator and Spatial Pattern Finder) that uses neural network and point process algorithms to automatically identify cell types and quantify cell-cell proximity relationships. Our study of data from IMC and CODEX shows the higher performance of AnnoSpat in rapid and accurate annotation of cell types compared to alternative approaches. Moreover, the application of AnnoSpat to type 1 diabetic, non-diabetic autoantibody-positive, and non-diabetic organ donor cohorts recapitulates known islet pathobiology and shows differential dynamics of pancreatic polypeptide (PP) cell abundance and CD8+ T cells infiltration in islets during type 1 diabetes progression.

Spatial promoter-enhancer hubs in cancer: organization, regulation, and function.

Transcriptional dysregulation is a hallmark of cancer and can be driven by altered enhancer landscapes. Recent studies in genome organization have revealed that multiple enhancers and promoters can spatially coalesce to form dynamic topological assemblies, known as promoter-enhancer hubs, which strongly correlate with elevated gene expression. In this review, we discuss the structure and complexity of promoter-enhancer hubs recently identified in multiple cancer types. We further discuss underlying mechanisms driving dysregulation of promoter-enhancer hubs and speculate on their functional role in pathogenesis. Understanding the role of promoter-enhancer hubs in transcriptional dysregulation can provide insight into new therapeutic approaches to target these complex features of genome organization.

Computational workflow and interactive analysis of single-cell expression profiling of islets generated by the Human Pancreas Analysis Program.

Type 1 and Type 2 diabetes are distinct genetic diseases of the pancreas which are defined by the abnormal level of blood glucose. Understanding the initial molecular perturbations that occur during the pathogenesis of diabetes is of critical importance in understanding these disorders. The inability to biopsy the human pancreas of living donors hampers insights into early detection, as the majority of diabetes studies have been performed on peripheral leukocytes from the blood, which is not the site of pathogenesis. Therefore, efforts have been made by various teams including the Human Pancreas Analysis Program (HPAP) to collect pancreatic tissues from deceased organ donors with different clinical phenotypes. HPAP is designed to define the molecular pathogenesis of islet dysfunction by generating detailed datasets of functional, cellular, and molecular information in pancreatic tissues of clinically well-defined organ donors with Type 1 and Type 2 diabetes. Moreover, data generated by HPAP continously become available through a centralized database, PANC-DB, thus enabling the diabetes research community to access these multi-dimensional data prepublication. Here, we present the computational workflow for single-cell RNA-seq data analysis of 258,379 high-quality cells from the pancreatic islets of 67 human donors generated by HPAP, the largest existing scRNA-seq dataset of human pancreatic tissues. We report various computational steps including preprocessing, doublet removal, clustering and cell type annotation across single-cell RNA-seq data from islets of four distintct classes of organ donors, i.e. non-diabetic control, autoantibody positive but normoglycemic, Type 1 diabetic, and Type 2 diabetic individuals. Moreover, we present an interactive tool, called CellxGene developed by the Chan Zuckerberg initiative, to navigate these high-dimensional datasets. Our data and interactive tools provide a reliable reference for singlecell pancreatic islet biology studies, especially diabetes-related conditions.

AnnoSpat annotates cell types and quantifies cellular arrangements from spatial proteomics.

Cellular composition and anatomical organization influence normal and aberrant organ functions. Emerging spatial single-cell proteomic assays such as Image Mass Cytometry (IMC) and Co-Detection by Indexing (CODEX) have facilitated the study of cellular composition and organization by enabling high-throughput measurement of cells and their localization directly in intact tissues. However, annotation of cell types and quantification of their relative localization in tissues remain challenging. To address these unmet needs, we developed AnnoSpat (Annotator and Spatial Pattern Finder) that uses neural network and point process algorithms to automatically identify cell types and quantify cell-cell proximity relationships. Our study of data from IMC and CODEX show the superior performance of AnnoSpat in rapid and accurate annotation of cell types compared to alternative approaches. Moreover, the application of AnnoSpat to type 1 diabetic, non-diabetic autoantibody-positive, and non-diabetic organ donor cohorts recapitulated known islet pathobiology and showed differential dynamics of pancreatic polypeptide (PP) cell abundance and CD8+ T cells infiltration in islets during type 1 diabetes progression.