IGSF8 is an innate immune checkpoint and cancer immunotherapy target.

Antigen presentation defects in tumors are prevalent mechanisms of adaptive immune evasion and resistance to cancer immunotherapy, whereas how tumors evade innate immunity is less clear. Using CRISPR screens, we discovered that IGSF8 expressed on tumors suppresses NK cell function by interacting with human KIR3DL2 and mouse Klra9 receptors on NK cells. IGSF8 is normally expressed in neuronal tissues and is not required for cell survival in vitro or in vivo. It is overexpressed and associated with low antigen presentation, low immune infiltration, and worse clinical outcomes in many tumors. An antibody that blocks IGSF8-NK receptor interaction enhances NK cell killing of malignant cells in vitro and upregulates antigen presentation, NK cell-mediated cytotoxicity, and T cell signaling in vivo. In syngeneic tumor models, anti-IGSF8 alone, or in combination with anti-PD1, inhibits tumor growth. Our results indicate that IGSF8 is an innate immune checkpoint that could be exploited as a therapeutic target.

Comprehensive analysis of intercellular communication in the thermogenic adipose niche.

Brown adipose tissue (BAT) is responsible for regulating body temperature through adaptive thermogenesis. The ability of thermogenic adipocytes to dissipate chemical energy as heat counteracts weight gain and has gained considerable attention as a strategy against obesity. BAT undergoes major remodeling in a cold environment. This remodeling results from changes in the number and function of brown adipocytes, expanding the network of blood vessels and sympathetic nerves, and changes in the composition and function of immune cells. Such synergistic adaptation requires extensive crosstalk between individual cells in the tissue to coordinate their responses. To understand the mechanisms of intercellular communication in BAT, we apply the CellChat algorithm to single-cell transcriptomic data of mouse BAT. We construct an integrative network of the ligand-receptor interactome in BAT and identify the major signaling inputs and outputs of each cell type. By comparing the ligand-receptor interactions in BAT of mice housed at different environmental temperatures, we show that cold exposure enhances the intercellular interactions among the major cell types in BAT, including adipocytes, adipocyte progenitors, lymphatic and vascular endothelial cells, myelinated and non-myelinated Schwann cells, and immune cells. These interactions are predicted to regulate the remodeling of the extracellular matrix, the inflammatory response, angiogenesis, and neurite growth. Together, our integrative analysis of intercellular communications in BAT and their dynamic regulation in response to housing temperatures provides a new understanding of the mechanisms underlying BAT thermogenesis. The resources presented in this study offer a valuable platform for future investigations of BAT development and thermogenesis.

Epigenetic landscape reveals MECOM as an endothelial lineage regulator.

A comprehensive understanding of endothelial cell lineage specification will advance cardiovascular regenerative medicine. Recent studies found that unique epigenetic signatures preferentially regulate cell identity genes. We thus systematically investigate the epigenetic landscape of endothelial cell lineage and identify MECOM to be the leading candidate as an endothelial cell lineage regulator. Single-cell RNA-Seq analysis verifies that MECOM-positive cells are exclusively enriched in the cell cluster of bona fide endothelial cells derived from induced pluripotent stem cells. Our experiments demonstrate that MECOM depletion impairs human endothelial cell differentiation, functions, and Zebrafish angiogenesis. Through integrative analysis of Hi-C, DNase-Seq, ChIP-Seq, and RNA-Seq data, we find MECOM binds enhancers that form chromatin loops to regulate endothelial cell identity genes. Further, we identify and verify the VEGF signaling pathway to be a key target of MECOM. Our work provides important insights into epigenetic regulation of cell identity and uncovered MECOM as an endothelial cell lineage regulator.

A knowledge empowered explainable gene ontology fingerprint approach to improve gene functional explication and prediction.

Functional explication of genes is of great scientific value. However, conventional methods have challenges for those genes that may affect biological processes but are not annotated in public databases. Here, we developed a novel explainable gene ontology fingerprint (XGOF) method to automatically produce knowledge networks on biomedical literature in a given field which quantitatively characterizes the association between genes and ontologies. XGOF provides systematic knowledge for the potential function of genes and ontologically compares similarities and discrepancies in different disease-XGOFs integrating omics data. More importantly, XGOF can not only help to infer major cellular components in a disease microenvironment but also reveal novel gene panels or functions for in-depth experimental research where few explicit connections to diseases have previously been described in the literature. The reliability of XGOF is validated in four application scenarios, indicating a unique perspective of integrating text and data mining, with the potential to accelerate scientific discovery.

Cancer Cell Resistance to IFNγ Can Occur via Enhanced Double-Strand Break Repair Pathway Activity.

The pleiotropic cytokine interferon-gamma (IFNγ) is associated with cytostatic, antiproliferation, and proapoptotic functions in cancer cells. However, resistance to IFNγ occurs in many cancer cells, and the underlying mechanism is not fully understood. To investigate potential IFNγ-resistance mechanisms, we performed IFNγ-sensitivity screens in more than 40 cancer cell lines and characterized the sensitive and resistant cell lines. By applying CRISPR screening and transcriptomic profiling in both IFNγ-sensitive and IFNγ-resistant cells, we discovered that activation of double-strand break (DSB) repair genes could result in IFNγ resistance in cancer cells. Suppression of single-strand break (SSB) repair genes increased the dependency on DSB repair genes after IFNγ treatment. Furthermore, inhibition of the DSB repair pathway exhibited a synergistic effect with IFNγ treatment both in vitro and in vivo. The relationship between the activation of DSB repair genes and IFNγ resistance was further confirmed in clinical tumor profiles from The Cancer Genome Atlas (TCGA) and immune checkpoint blockade (ICB) cohorts. Our study provides comprehensive resources and evidence to elucidate a mechanism of IFNγ resistance in cancer and has the potential to inform combination therapies to overcome immunotherapy resistance.

Epsin Nanotherapy Regulates Cholesterol Transport to Fortify Atheroma Regression.

BACKGROUND: Excess cholesterol accumulation in lesional macrophages elicits complex responses in atherosclerosis. Epsins, a family of endocytic adaptors, fuel the progression of atherosclerosis; however, the underlying mechanism and therapeutic potential of targeting Epsins remains unknown. In this study, we determined the role of Epsins in macrophage-mediated metabolic regulation. We then developed an innovative method to therapeutically target macrophage Epsins with specially designed S2P-conjugated lipid nanoparticles, which encapsulate small-interfering RNAs to suppress Epsins. METHODS: We used single-cell RNA sequencing with our newly developed algorithm MEBOCOST (Metabolite-mediated Cell Communication Modeling by Single Cell Transcriptome) to study cell-cell communications mediated by metabolites from sender cells and sensor proteins on receiver cells. Biomedical, cellular, and molecular approaches were utilized to investigate the role of macrophage Epsins in regulating lipid metabolism and transport. We performed this study using myeloid-specific Epsin double knockout (LysM-DKO) mice and mice with a genetic reduction of ABCG1 (ATP-binding cassette subfamily G member 1; LysM-DKO-ABCG1fl/+). The nanoparticles targeting lesional macrophages were developed to encapsulate interfering RNAs to treat atherosclerosis. RESULTS: We revealed that Epsins regulate lipid metabolism and transport in atherosclerotic macrophages. Inhibiting Epsins by nanotherapy halts inflammation and accelerates atheroma resolution. Harnessing lesional macrophage-specific nanoparticle delivery of Epsin small-interfering RNAs, we showed that silencing of macrophage Epsins diminished atherosclerotic plaque size and promoted plaque regression. Mechanistically, we demonstrated that Epsins bound to CD36 to facilitate lipid uptake by enhancing CD36 endocytosis and recycling. Conversely, Epsins promoted ABCG1 degradation via lysosomes and hampered ABCG1-mediated cholesterol efflux and reverse cholesterol transport. In a LysM-DKO-ABCG1fl/+ mouse model, enhanced cholesterol efflux and reverse transport due to Epsin deficiency was suppressed by the reduction of ABCG1. CONCLUSIONS: Our findings suggest that targeting Epsins in lesional macrophages may offer therapeutic benefits for advanced atherosclerosis by reducing CD36-mediated lipid uptake and increasing ABCG1-mediated cholesterol efflux.

StripeDiff: Model-based algorithm for differential analysis of chromatin stripe.

Multiple recent studies revealed stripes as an architectural feature of three-dimensional chromatin and found stripes connected to epigenetic regulation of transcription. Whereas a couple of tools are available to define stripes in a single sample, there is yet no reported method to quantitatively measure the dynamic change of each stripe between samples. Here, we developed StripeDiff, a bioinformatics tool that delivers a set of statistical methods to detect differential stripes between samples. StripeDiff showed optimal performance in both simulation data analysis and real Hi-C data analysis. Applying StripeDiff to 12 sets of Hi-C data revealed new insights into the connection between change of chromatin stripe and change of chromatin modification, transcriptional regulation, and cell differentiation. StripeDiff will be a robust tool for the community to facilitate understanding of stripes and their function in numerous biological models.

Retinoblastoma protein as an intrinsic BRD4 inhibitor modulates small molecule BET inhibitor sensitivity in cancer.

Bromodomain and extraterminal (BET) proteins including BRD4 play important roles in oncogenesis and immune inflammation. Here we demonstrate that cancer cells with loss of the retinoblastoma (RB) tumor suppressor became resistant to small molecule bromodomain inhibitors of BET proteins. We find that RB binds to bromodomain-1 (BD1) of BRD4, but binding is impeded by CDK4/6-mediated RB phosphorylation at serine-249/threonine-252 (S249/T252). ChIP-seq analysis shows RB knockdown increases BRD4 occupancy at genomic loci of genes enriched in cancer-related pathways including the GPCR-GNBIL-CREB axis. S249/T252-phosphorylated RB positively correlates with GNBIL protein level in prostate cancer patient samples. BET inhibitor resistance in RB-deficient cells is abolished by co-administration of CREB inhibitor. Our study identifies RB protein as a bona fide intrinsic inhibitor of BRD4 and demonstrates that RB inactivation confers resistance to small molecule BET inhibitors, thereby revealing a regulatory hub that converges RB upstream signaling onto BRD4 functions in diseases such as cancer.

ViMIC: a database of human disease-related virus mutations, integration sites and cis-effects.

Molecular mechanisms of virus-related diseases involve multiple factors, including viral mutation accumulation and integration of a viral genome into the host DNA. With increasing attention being paid to virus-mediated pathogenesis and the development of many useful technologies to identify virus mutations (VMs) and viral integration sites (VISs), much research on these topics is available in PubMed. However, knowledge of VMs and VISs is widely scattered in numerous published papers which lack standardization, integration and curation. To address these challenges, we built a pilot database of human disease-related Virus Mutations, Integration sites and Cis-effects (ViMIC), which specializes in three features: virus mutation sites, viral integration sites and target genes. In total, the ViMIC provides information on 31 712 VMs entries, 105 624 VISs, 16 310 viral target genes and 1 110 015 virus sequences of eight viruses in 77 human diseases obtained from the public domain. Furthermore, in ViMIC users are allowed to explore the cis-effects of virus-host interactions by surveying 78 histone modifications, binding of 1358 transcription regulators and chromatin accessibility on these VISs. We believe ViMIC will become a valuable resource for the virus research community. The database is available at http://bmtongji.cn/ViMIC/index.php.

TISCH: a comprehensive web resource enabling interactive single-cell transcriptome visualization of tumor microenvironment.

Cancer immunotherapy targeting co-inhibitory pathways by checkpoint blockade shows remarkable efficacy in a variety of cancer types. However, only a minority of patients respond to treatment due to the stochastic heterogeneity of tumor microenvironment (TME). Recent advances in single-cell RNA-seq technologies enabled comprehensive characterization of the immune system heterogeneity in tumors but posed computational challenges on integrating and utilizing the massive published datasets to inform immunotherapy. Here, we present Tumor Immune Single Cell Hub (TISCH, http://tisch.comp-genomics.org), a large-scale curated database that integrates single-cell transcriptomic profiles of nearly 2 million cells from 76 high-quality tumor datasets across 27 cancer types. All the data were uniformly processed with a standardized workflow, including quality control, batch effect removal, clustering, cell-type annotation, malignant cell classification, differential expression analysis and functional enrichment analysis. TISCH provides interactive gene expression visualization across multiple datasets at the single-cell level or cluster level, allowing systematic comparison between different cell-types, patients, tissue origins, treatment and response groups, and even different cancer-types. In summary, TISCH provides a user-friendly interface for systematically visualizing, searching and downloading gene expression atlas in the TME from multiple cancer types, enabling fast, flexible and comprehensive exploration of the TME.

Determinants of transcription factor regulatory range.

Characterization of the genomic distances over which transcription factor (TF) binding influences gene expression is important for inferring target genes from TF chromatin immunoprecipitation followed by sequencing (ChIP-seq) data. Here we systematically examine the relationship between thousands of TF and histone modification ChIP-seq data sets with thousands of gene expression profiles. We develop a model for integrating these data, which reveals two classes of TFs with distinct ranges of regulatory influence, chromatin-binding preferences, and auto-regulatory properties. We find that the regulatory range of the same TF bound within different topologically associating domains (TADs) depend on intrinsic TAD properties such as local gene density and G/C content, but also on the TAD chromatin states. Our results suggest that considering TF type, binding distance to gene locus, as well as chromatin context is important in identifying implicated TFs from GWAS SNPs.

MUC1-C drives stemness in progression of colitis to colorectal cancer.

Colitis is associated with the development of colorectal cancer (CRC) by largely undefined mechanisms that are critical for understanding the link between inflammation and cancer. Intestinal stem cells (ISCs) marked by leucine-rich repeat-containing G protein-coupled receptor 5 (LGR5) expression are of importance in both the inflammatory response to colitis and progression to colitis-associated colon cancer (CACC). Here, we report in human mucin 1-transgenic (MUC1-transgenic) mouse models of CACC, targeting the MUC1-C oncogenic protein suppresses the (a) Lgr5+ ISC population, (b) induction of Myc and core pluripotency stem cell factors, and (c) severity and progression of colitis to dysplasia and cancer. By extension to human colon cancer cells, we demonstrate that MUC1-C drives MYC, forms a complex with MYC on the LGR5 promoter, and activates LGR5 expression. We also show in CRC cells that MUC1-C induces cancer stem cell (CSC) markers (BMI1, ALDH1, FOXA1, LIN28B) and the OCT4, SOX2, and NANOG pluripotency factors. Consistent with conferring the CSC state, targeting MUC1-C suppresses the capacity of CRC cells to promote wound healing, invasion, self-renewal, and tumorigenicity. In analysis of human tissues, MUC1 expression associates with activation of inflammatory pathways, development of colitis, and aggressiveness of CRCs. These results collectively indicate that MUC1-C is of importance for integrating stemness and pluripotency in colitis and CRC. Of clinical relevance, the findings further indicate that MUC1-C represents a potentially previously unrecognized target that is druggable for treating progression of colitis and CRC.

Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data.

We developed Lisa (http://lisa.cistrome.org/) to predict the transcriptional regulators (TRs) of differentially expressed or co-expressed gene sets. Based on the input gene sets, Lisa first uses histone mark ChIP-seq and chromatin accessibility profiles to construct a chromatin model related to the regulation of these genes. Using TR ChIP-seq peaks or imputed TR binding sites, Lisa probes the chromatin models using in silico deletion to find the most relevant TRs. Applied to gene sets derived from targeted TF perturbation experiments, Lisa boosted the performance of imputed TR cistromes and outperformed alternative methods in identifying the perturbed TRs.

GIDB: a knowledge database for the automated curation and multidimensional analysis of molecular signatures in gastrointestinal cancer.

Gastrointestinal (GI) cancer is common, characterized by high mortality, and includes oesophagus, gastric, liver, bile duct, pancreas, rectal and colon cancers. The insufficient specificity and sensitivity of biomarkers is still a key clinical hindrance for GI cancer diagnosis and successful treatment. The emergence of `precision medicine', `basket trial' and `field cancerization' concepts calls for an urgent need and importance for the understanding of how organ system cancers occur at the molecular levels. Knowledge from both the literature and data available in public databases is informative in elucidating the molecular alterations underlying GI cancer. Currently, most available cancer databases have not offered a comprehensive discovery of gene-disease associations, molecular alterations and clinical information by integrated text mining and data mining in GI cancer. We develop GIDB, a panoptic knowledge database that attempts to automate the curation of molecular signatures using natural language processing approaches and multidimensional analyses. GIDB covers information on 8730 genes with both literature and data supporting evidence, 248 miRNAs, 58 lncRNAs, 320 copy number variations, 49 fusion genes and 2381 semantic networks. It presents a comprehensive database, not only in parallelizing supporting evidence and data integration for signatures associated with GI cancer but also in providing the timeline feature of major molecular discoveries. It highlights the most comprehensive overview, research hotspots and the development of historical knowledge of genes in GI cancer. Furthermore, GIDB characterizes genomic abnormalities in multilevel analysis, including simple somatic mutations, gene expression, DNA methylation and prognosis. GIDB offers a user-friendly interface and two customizable online tools (Heatmap and Network) for experimental researchers and clinicians to explore data and help them shorten the learning curve and broaden the scope of knowledge. More importantly, GIDB is an ongoing research project that will continue to be updated and improve the automated method for reducing manual work.

Cistrome-GO: a web server for functional enrichment analysis of transcription factor ChIP-seq peaks.

Characterizing the ontologies of genes directly regulated by a transcription factor (TF), can help to elucidate the TF's biological role. Previously, we developed a widely used method, BETA, to integrate TF ChIP-seq peaks with differential gene expression (DGE) data to infer direct target genes. Here, we provide Cistrome-GO, a website implementation of this method with enhanced features to conduct ontology analyses of gene regulation by TFs in human and mouse. Cistrome-GO has two working modes: solo mode for ChIP-seq peak analysis; and ensemble mode, which integrates ChIP-seq peaks with DGE data. Cistrome-GO is freely available at http://go.cistrome.org/.

Cistrome Data Browser: expanded datasets and new tools for gene regulatory analysis.

The Cistrome Data Browser (DB) is a resource of human and mouse cis-regulatory information derived from ChIP-seq, DNase-seq and ATAC-seq chromatin profiling assays, which map the genome-wide locations of transcription factor binding sites, histone post-translational modifications and regions of chromatin accessible to endonuclease activity. Currently, the Cistrome DB contains approximately 47,000 human and mouse samples with about 24,000 newly collected datasets compared to the previous release two years ago. Furthermore, the Cistrome DB has a new Toolkit module with several features that allow users to better utilize the large-scale ChIP-seq, DNase-seq, and ATAC-seq data. First, users can query the factors which are likely to regulate a specific gene of interest. Second, the Cistrome DB Toolkit facilitates searches for factor binding, histone modifications, and chromatin accessibility in any given genomic interval shorter than 2Mb. Third, the Toolkit can determine the most similar ChIP-seq, DNase-seq, and ATAC-seq samples in terms of genomic interval overlaps with user-provided genomic interval sets. The Cistrome DB is a user-friendly, up-to-date, and well maintained resource, and the new tools will greatly benefit the biomedical research community. The database is freely available at http://cistrome.org/db, and the Toolkit is at http://dbtoolkit.cistrome.org.

Cistrome Cancer: A Web Resource for Integrative Gene Regulation Modeling in Cancer.

Cancer results from a breakdown of normal gene expression control, so the study of gene regulation is critical to cancer research. To gain insight into the transcriptional and epigenetic factors regulating abnormal gene expression patterns in cancers, we developed the Cistrome Cancer web resource (http://cistrome.org/CistromeCancer/). We conducted the systematic integration and modeling of over 10,000 tumor molecular profiles from The Cancer Genome Atlas (TCGA) with over 23,000 ChIP-seq and chromatin accessibility profiles from our Cistrome collection. The results include reconstruction of functional enhancer profiles, "super-enhancer" target genes, as well as predictions of active transcription factors and their target genes for each TCGA cancer type. Cistrome Cancer reveals novel insights from integrative analyses combining chromatin profiles with tumor molecular profiles and will be a useful resource to the cancer gene regulation community. Cancer Res; 77(21); e19-22. ©2017 AACR.

Cistrome Data Browser: a data portal for ChIP-Seq and chromatin accessibility data in human and mouse.

Chromatin immunoprecipitation, DNase I hypersensitivity and transposase-accessibility assays combined with high-throughput sequencing enable the genome-wide study of chromatin dynamics, transcription factor binding and gene regulation. Although rapidly accumulating publicly available ChIP-seq, DNase-seq and ATAC-seq data are a valuable resource for the systematic investigation of gene regulation processes, a lack of standardized curation, quality control and analysis procedures have hindered extensive reuse of these data. To overcome this challenge, we built the Cistrome database, a collection of ChIP-seq and chromatin accessibility data (DNase-seq and ATAC-seq) published before January 1, 2016, including 13 366 human and 9953 mouse samples. All the data have been carefully curated and processed with a streamlined analysis pipeline and evaluated with comprehensive quality control metrics. We have also created a user-friendly web server for data query, exploration and visualization. The resulting Cistrome DB (Cistrome Data Browser), available online at http://cistrome.org/db, is expected to become a valuable resource for transcriptional and epigenetic regulation studies.

Effect of Acrylamide on Oocyte Nuclear Maturation and Cumulus Cells Apoptosis in Mouse In Vitro.

Acrylamide (ACR) is a chemical compound with severe neurotoxicity, genotoxicity, carcinogenicity and reproductive toxicity. Recent studies showed that ACR impairs the function of reproductive organs, e.g., epididymis and testes. In vitro maturation of mouse oocyte is a sensitive assay to identify potential chemical hazard to female fertility. The aim of this study was to evaluate the adverse effects of ACR on the nuclear maturation and cumulus cells apoptosis of mouse oocytes in vitro. Cumulus-oocyte complexes were incubated in a maturation medium containing 0, 5, 10 and 20 µM of ACR. Chromosome alignment and spindle morphology of oocytes was determined by immunofluorescence and confocal microscopy. Our results showed that oocytes exposed to different doses of ACR in vitro were associated with a significant decrease of oocyte maturation, significant increase of chromosome misalignment rate, occurrence of abnormal spindle configurations, and the inhibition of oocyte parthenogenetic activation. Furthermore, apoptosis of cumulus cells was determined by TUNEL and CASPASE-3 assay. Results showed that apoptosis in cumulus cells was enhanced and the expression of CASPASE-3 was increased after cumulus-oocyte complexes were exposed to ACR. Therefore, ACR may affect the nuclear maturation of oocytes via the apoptosis of cumulus cells in vitro.