SEanalysis: a web tool for super-enhancer associated regulatory analysis

Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits

Methylation quantitative trait loci (mQTLs) are essential for understanding the role of DNA methylation changes in genetic predisposition, yet they have not been fully characterized in East Asians (EAs). Here we identified mQTLs in whole blood from 3,523 Chinese individuals and replicated them in additional 1,858 Chinese individuals from two cohorts. Over 9% of mQTLs displayed specificity to EAs, facilitating the fine-mapping of EA-specific genetic associations, as shown for variants associated with height. Trans-mQTL hotspots revealed biological pathways contributing to EA-specific genetic associations, including an ERG-mediated 233 trans-mCpG network, implicated in hematopoietic cell differentiation, which likely reflects binding efficiency modulation of the ERG protein complex. More than 90% of mQTLs were shared between different blood cell lineages, with a smaller fraction of lineage-specific mQTLs displaying preferential hypomethylation in the respective lineages. Our study provides new insights into the mQTL landscape across genetic ancestries and their downstream effects on cellular processes and diseases/traits.

Pathogenic role of super-enhancers as potential therapeutic targets in lung cancer

Lung cancer is still one of the deadliest malignancies today, and most patients with advanced lung cancer pass away from disease progression that is uncontrollable by medications. Super-enhancers (SEs) are large clusters of enhancers in the genome's non-coding sequences that actively trigger transcription. Although SEs have just been identified over the past 10 years, their intricate structure and crucial role in determining cell identity and promoting tumorigenesis and progression are increasingly coming to light. Here, we review the structural composition of SEs, the auto-regulatory circuits, the control mechanisms of downstream genes and pathways, and the characterization of subgroups classified according to SEs in lung cancer. Additionally, we discuss the therapeutic targets, several small-molecule inhibitors, and available treatment options for SEs in lung cancer. Combination therapies have demonstrated considerable advantages in preclinical models, and we anticipate that these drugs will soon enter clinical studies and benefit patients.

Mechanistic insights into super-enhancer-driven genes as prognostic signatures in patients with glioblastoma

BACKGROUND

Glioblastoma (GBM) is one of the most common malignant brain tumors in adults and is characterized by high aggressiveness and rapid progression, poor treatment, high recurrence rate, and poor prognosis. Although super-enhancer (SE)-driven genes haven been recognized as prognostic markers for several cancers, whether it can be served as effective prognostic markers for patients with GBM has not been evaluated.

METHODS

We first combined histone modification data with transcriptome data to identify SE-driven genes associated with prognosis in patients with GBM. Second, we developed a SE-driven differentially expressed genes (SEDEGs) risk score prognostic model by univariate Cox analysis, KM survival analysis, multivariate Cox analysis and least absolute shrinkage and selection operator (LASSO) regression. Its reliability in predicting was verified by two external data sets. Third, through mutation analysis, immune infiltration, we explored the molecular mechanisms of prognostic genes. Next, Genomics of Drug Sensitivity in Cancer (GDSC) and the Connectivity Map (cMap) database were employed to assess different sensitivities to chemotherapeutic agents and small-molecule drug candidates between high- and low-risk patients. Finally, SEanalysis database was chosen to identify SE-driven transcription factors (TFs) regulating prognostic markers which will reveal a potential SE-driven transcriptional regulatory network.

RESULTS

First, we developed a 11-gene risk score prognostic model (NCF2, MTHFS, DUSP6, G6PC3, HOXB2, EN2, DLEU1, LBH, ZEB1-AS1, LINC01265, and AGAP2-AS1) selected from 1,154 SEDEGs, which is not only an independent prognostic factor for patients, but also can effectively predict the survival rate of patients. The model can effectively predict 1-, 2- and 3-year survival of patients and was validated in external Chinese Glioma Genome Atlas (CGGA) and Gene Expression Omnibus (GEO) datasets. Second, the risk score was positively correlated with the infiltration of regulatory T cell, CD4 memory activated T cell, activated NK cell, neutrophil, resting mast cell, M0 macrophage, and memory B cell. Third, we found that high-risk patients showed higher sensitivity than low-risk patients to both 27 chemotherapeutic agents and 4 small-molecule drug candidates which might benefit further precision therapy for GBM patients. Finally, 13 potential SE-driven TFs imply how SE regulates GBM patient's prognosis.

CONCLUSION

The SEDEG risk model not only helps to elucidate the impact of SEs on the course of GBM, but also provides a bright future for prognosis determination and choice of treatment for GBM patients.

Super-enhancers complexes zoom in transcription in cancer

Super-enhancers (SEs) consist of multiple typical enhancers enriched at high density with transcription factors, histone-modifying enzymes and cofactors. Oncogenic SEs promote tumorigenesis and malignancy by altering protein-coding gene expression and noncoding regulatory element function. Therefore, they play central roles in the treatment of cancer. Here, we review the structural characteristics, organization, identification, and functions of SEs and the underlying molecular mechanism by which SEs drive oncogenic transcription in tumor cells. We then summarize abnormal SE complexes, SE-driven coding genes, and noncoding RNAs involved in tumor development. In summary, we believe that SEs show great potential as biomarkers and therapeutic targets.

CenhANCER: a comprehensive cancer enhancer database for primary tissues and cell lines

Enhancers, which are key tumorigenic factors with wide applications for subtyping, diagnosis and treatment of cancer, are attracting increasing attention in the cancer research. However, systematic analysis of cancer enhancers poses a challenge due to the lack of integrative data resources, especially those from tumor primary tissues. To provide a comprehensive enhancer profile across cancer types, we developed a cancer enhancer database CenhANCER by curating public resources including all the public H3K27ac ChIP-Seq data from 805 primary tissue samples and 671 cell line samples across 41 cancer types. In total, 57 029 408 typical enhancers, 978 411 super-enhancers and 226 726 enriched transcription factors were identified. We annotated the super-enhancers with chromatin accessibility regions, cancer expression quantitative trait loci (eQTLs), genotype-tissue expression eQTLs and genome-wide association study risk single nucleotide polymorphisms (SNPs) for further functional analysis. The identified enhancers were highly consistent with accessible chromatin regions in the corresponding cancer types, and all the 10 super-enhancer regions identified from one colorectal cancer study were recapitulated in our CenhANCER, both of which testified the high quality of our data. CenhANCER with high-quality cancer enhancer candidates and transcription factors that are potential therapeutic targets across multiple cancer types provides a credible resource for single cancer analysis and for comparative studies of various cancer types. Database URL http://cenhancer.chenzxlab.cn/.

Superenhancers as master gene regulators and novel therapeutic targets in brain tumors

Transcriptional deregulation, a cancer cell hallmark, is driven by epigenetic abnormalities in the majority of brain tumors, including adult glioblastoma and pediatric brain tumors. Epigenetic abnormalities can activate epigenetic regulatory elements to regulate the expression of oncogenes. Superenhancers (SEs), identified as novel epigenetic regulatory elements, are clusters of enhancers with cell-type specificity that can drive the aberrant transcription of oncogenes and promote tumor initiation and progression. As gene regulators, SEs are involved in tumorigenesis in a variety of tumors, including brain tumors. SEs are susceptible to inhibition by their key components, such as bromodomain protein 4 and cyclin-dependent kinase 7, providing new opportunities for antitumor therapy. In this review, we summarized the characteristics and identification, unique organizational structures, and activation mechanisms of SEs in tumors, as well as the clinical applications related to SEs in tumor therapy and prognostication. Based on a review of the literature, we discussed the relationship between SEs and different brain tumors and potential therapeutic targets, focusing on glioblastoma.

CanMethdb: a database for genome-wide DNA methylation annotation in cancers

MOTIVATION

DNA methylation within gene body and promoters in cancer cells is well documented. An increasing number of studies showed that cytosine-phosphate-guanine (CpG) sites falling within other regulatory elements could also regulate target gene activation, mainly by affecting transcription factors (TFs) binding in human cancers. This led to the urgent need for comprehensively and effectively collecting distinct cis-regulatory elements and TF-binding sites (TFBS) to annotate DNA methylation regulation.

RESULTS

We developed a database (CanMethdb, http://meth.liclab.net/CanMethdb/) that focused on the upstream and downstream annotations for CpG-genes in cancers. This included upstream cis-regulatory elements, especially those involving distal regions to genes, and TFBS annotations for the CpGs and downstream functional annotations for the target genes, computed through integrating abundant DNA methylation and gene expression profiles in diverse cancers. Users could inquire CpG-target gene pairs for a cancer type through inputting a genomic region, a CpG, a gene name, or select hypo/hypermethylated CpG sets. The current version of CanMethdb documented a total of 38 986 060 CpG-target gene pairs (with 6 769 130 unique pairs), involving 385 217 CpGs and 18 044 target genes, abundant cis-regulatory elements and TFs for 33 TCGA cancer types. CanMethdb might help biologists perform in-depth studies of target gene regulations based on DNA methylations in cancer.

AVAILABILITY AND IMPLEMENTATION

The main program is available at https://github.com/chunquanlipathway/CanMethdb.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

GREAP: a comprehensive enrichment analysis software for human genomic regions

The rapid development of genomic high-throughput sequencing has identified a large number of DNA regulatory elements with abundant epigenetics markers, which promotes the rapid accumulation of functional genomic region data. The comprehensively understanding and research of human functional genomic regions is still a relatively urgent work at present. However, the existing analysis tools lack extensive annotation and enrichment analytical abilities for these regions. Here, we designed a novel software, Genomic Region sets Enrichment Analysis Platform (GREAP), which provides comprehensive region annotation and enrichment analysis capabilities. Currently, GREAP supports 85 370 genomic region reference sets, which cover 634 681 107 regions across 11 different data types, including super enhancers, transcription factors, accessible chromatins, etc. GREAP provides widespread annotation and enrichment analysis of genomic regions. To reflect the significance of enrichment analysis, we used the hypergeometric test and also provided a Locus Overlap Analysis. In summary, GREAP is a powerful platform that provides many types of genomic region sets for users and supports genomic region annotations and enrichment analyses. In addition, we developed a customizable genome browser containing >400 000 000 customizable tracks for visualization. The platform is freely available at http://www.liclab.net/Greap/view/index.

Analysis of the landscape of human enhancer sequences in biological databases

The process of gene regulation extends as a network in which both genetic sequences and proteins are involved. The levels of regulation and the mechanisms involved are multiple. Transcription is the main control mechanism for most genes, being the downstream steps responsible for refining the transcription patterns. In turn, gene transcription is mainly controlled by regulatory events that occur at promoters and enhancers. Several studies are focused on analyzing the contribution of enhancers in the development of diseases and their possible use as therapeutic targets. The study of regulatory elements has advanced rapidly in recent years with the development and use of next generation sequencing techniques. All this information has generated a large volume of information that has been transferred to a growing number of public repositories that store this information. In this article, we analyze the content of those public repositories that contain information about human enhancers with the aim of detecting whether the knowledge generated by scientific research is contained in those databases in a way that could be computationally exploited. The analysis will be based on three main aspects identified in the literature: types of enhancers, type of evidence about the enhancers, and methods for detecting enhancer-promoter interactions. Our results show that no single database facilitates the optimal exploitation of enhancer data, most types of enhancers are not represented in the databases and there is need for a standardized model for enhancers. We have identified major gaps and challenges for the computational exploitation of enhancer data.

The molecular understanding of super-enhancer dysregulation in cancer

Abnormalities in the regulation of gene expression are associated with various pathological conditions. Among the distal regulatory elements in the genome, the activation of target genes by enhancers plays a central role in the formation of cell type-specific gene expression patterns. Super-enhancers are a subclass of enhancers that frequently contain multiple enhancer-like elements and are characterized by dense binding of master transcription factors and Mediator complexes and high signals of active histone marks. Super-enhancers have been studied in detail as important regulatory regions that control cell identity and contribute to the pathogenesis of diverse diseases. In cancer, super-enhancers have multifaceted roles by activating various oncogenes and other cancer-related genes and shaping characteristic gene expression patterns in cancer cells. Alterations in super-enhancer activities in cancer involve multiple mechanisms, including the dysregulation of transcription factors and the super-enhancer-associated genomic abnormalities. The study of super-enhancers could contribute to the identification of effective biomarkers and the development of cancer therapeutics targeting transcriptional addiction. In this review, we summarize the roles of super-enhancers in cancer biology, with a particular focus on hematopoietic malignancies, in which multiple super-enhancer alteration mechanisms have been reported.

ESR1 mutant breast cancers show elevated basal cytokeratins and immune activation

Estrogen receptor alpha (ER/ESR1) is frequently mutated in endocrine resistant ER-positive (ER+) breast cancer and linked to ligand-independent growth and metastasis. Despite the distinct clinical features of ESR1 mutations, their role in intrinsic subtype switching remains largely unknown. Here we find that ESR1 mutant cells and clinical samples show a significant enrichment of basal subtype markers, and six basal cytokeratins (BCKs) are the most enriched genes. Induction of BCKs is independent of ER binding and instead associated with chromatin reprogramming centered around a progesterone receptor-orchestrated insulated neighborhood. BCK-high ER+ primary breast tumors exhibit a number of enriched immune pathways, shared with ESR1 mutant tumors. S100A8 and S100A9 are among the most induced immune mediators and involve in tumor-stroma paracrine crosstalk inferred by single-cell RNA-seq from metastatic tumors. Collectively, these observations demonstrate that ESR1 mutant tumors gain basal features associated with increased immune activation, encouraging additional studies of immune therapeutic vulnerabilities.

TF-Marker: a comprehensive manually curated database for transcription factors and related markers in specific cell and tissue types in human

Transcription factors (TFs) play key roles in biological processes and are usually used as cell markers. The emerging importance of TFs and related markers in identifying specific cell types in human diseases increases the need for a comprehensive collection of human TFs and related markers sets. Here, we developed the TF-Marker database (TF-Marker, http://bio.liclab.net/TF-Marker/), aiming to provide cell/tissue-specific TFs and related markers for human. By manually curating thousands of published literature, 5905 entries including information about TFs and related markers were classified into five types according to their functions: (i) TF: TFs which regulate expression of the markers; (ii) T Marker: markers which are regulated by the TF; (iii) I Marker: markers which influence the activity of TFs; (iv) TFMarker: TFs which play roles as markers and (v) TF Pmarker: TFs which play roles as potential markers. The 5905 entries of TF-Marker include 1316 TFs, 1092 T Markers, 473 I Markers, 1600 TFMarkers and 1424 TF Pmarkers, involving 383 cell types and 95 tissue types in human. TF-Marker further provides a user-friendly interface to browse, query and visualize the detailed information about TFs and related markers. We believe TF-Marker will become a valuable resource to understand the regulation patterns of different tissues and cells.

Cancer CRC: A Comprehensive Cancer Core Transcriptional Regulatory Circuit Resource and Analysis Platform

A core transcriptional regulatory circuit (CRC) is a group of interconnected auto-regulating transcription factors (TFs) that form loops and can be identified by super-enhancers (SEs). Studies have indicated that CRCs play an important role in defining cellular identity and determining cellular fate. Additionally, core TFs in CRCs are regulators of cell-type-specific transcriptional regulation. However, a global view of CRC properties across various cancer types has not been generated. Thus, we integrated paired cancer ATAC-seq and H3K27ac ChIP-seq data for specific cell lines to develop the Cancer CRC (http://bio.liclab.net/Cancer_crc/index.html). This platform documented 94,108 cancer CRCs, including 325 core TFs. The cancer CRC also provided the “SE active core TFs analysis” and “TF enrichment analysis” tools to identify potentially key TFs in cancer. In addition, we performed a comprehensive analysis of core TFs in various cancer types to reveal conserved and cancer-specific TFs.

Employing core regulatory circuits to define cell identity

The interplay between extrinsic signaling and downstream gene networks controls the establishment of cell identity during development and its maintenance in adult life. Advances in next-generation sequencing and single-cell technologies have revealed additional layers of complexity in cell identity. Here, we review our current understanding of transcription factor (TF) networks as key determinants of cell identity. We discuss the concept of the core regulatory circuit as a set of TFs and interacting factors that together define the gene expression profile of the cell. We propose the core regulatory circuit as a comprehensive conceptual framework for defining cellular identity and discuss its connections to cell function in different contexts.

Super-enhancer-mediated core regulatory circuitry in human cancer

Super-enhancers (SEs) are congregated enhancer clusters with high level of loading of transcription factors (TFs), cofactors and epigenetic modifications. Through direct co-occupancy at their own SEs as well as each other's, a small set of so called "master" TFs form interconnected core regulatory circuitry (CRCs) to orchestrate transcriptional programs in both normal and malignant cells. These master TFs can be predicted mathematically using epigenomic methods. In this Review, we summarize the identification of SEs and CRCs in cancer cells, the mechanisms by which master TFs and SEs cooperatively regulate cancer-type-specific expression programs, and the cancer-type- and subtype-specificity of CRC and the significance in cancer biology.

Chromatin occupancy and target genes of the haematopoietic master transcription factor MYB

The transcription factor MYB is a master regulator in haematopoietic progenitor cells and a pioneer factor affecting differentiation and proliferation of these cells. Leukaemic transformation may be promoted by high MYB levels. Despite much accumulated molecular knowledge of MYB, we still lack a comprehensive understanding of its target genes and its chromatin action. In the present work, we performed a ChIP-seq analysis of MYB in K562 cells accompanied by detailed bioinformatics analyses. We found that MYB occupies both promoters and enhancers. Five clusters (C1-C5) were found when we classified MYB peaks according to epigenetic profiles. C1 was enriched for promoters and C2 dominated by enhancers. C2-linked genes were connected to hematopoietic specific functions and had GATA factor motifs as second in frequency. C1 had in addition to MYB-motifs a significant frequency of ETS-related motifs. Combining ChIP-seq data with RNA-seq data allowed us to identify direct MYB target genes. We also compared ChIP-seq data with digital genomic footprinting. MYB is occupying nearly a third of the super-enhancers in K562. Finally, we concluded that MYB cooperates with a subset of the other highly expressed TFs in this cell line, as expected for a master regulator.

EphA2 super-enhancer promotes tumor progression by recruiting FOSL2 and TCF7L2 to activate the target gene EphA2

Super-enhancers or stretch enhancers (SEs) consist of large clusters of active transcription enhancers which promote the expression of critical genes that define cell identity during development and disease. However, the role of many super-enhancers in tumor cells remains unclear. This study aims to explore the function and mechanism of a new super-enhancer in various tumor cells. A new super-enhancer that exists in a variety of tumors named EphA2-Super-enhancer (EphA2-SE) was found using multiple databases and further identified. CRISPR/Cas9-mediated deletion of EphA2-SE results in the significant downregulation of its target gene EphA2. Mechanistically, we revealed that the core active region of EphA2-SE comprises E1 component enhancer, which recruits TCF7L2 and FOSL2 transcription factors to drive the expression of EphA2, induce cell proliferation and metastasis. Bioinformatics analysis of RNA-seq data and functional experiments in vitro illustrated that EphA2-SE deletion inhibited cell growth and metastasis by blocking PI3K/AKT and Wnt/β-catenin pathway in HeLa, HCT-116 and MCF-7 cells. Overexpression of EphA2 in EphA2-SE-/- clones rescued the effect of EphA2-SE deletion on proliferation and metastasis. Subsequent xenograft animal model revealed that EphA2-SE deletion suppressed tumor proliferation and survival in vivo. Taken together, these findings demonstrate that EphA2-SE plays an oncogenic role and promotes tumor progression in various tumors by recruiting FOSL2 and TCF7L2 to drive the expression of oncogene EphA2.

Myeloma-specific superenhancers affect genes of biological and clinical relevance in myeloma

Multiple myeloma (MM) is an aggressive plasma cell neoplasm characterized by genomic heterogeneity. Superenhancers (SEs) are defined as large clusters of enhancers in close genomic proximity, which regulate genes for maintaining cellular identity and promote oncogenic transcription to which cancer cells highly addicted. Here, we analyzed cis-regulatory elements in MM samples with H3K27ac ChIP-seq, to identify novel SE-associated genes involved in the myeloma pathogenesis. SEs and their associated genes in cancerous tissue were compared with the control samples, and we found SE analysis alone uncovered cell-lineage-specific transcription factors and well-known oncogenes ST3GAL6 and ADM. Using a transcriptional CDK7 inhibitor, THZ1, coupled with H3K27ac ChlP-seq, we identified MAGI2 as a novel SE-associated gene of myeloma cells. Elevated MAGI2 was related to myelomagenesis with gradual increased expression from MGUS, SMM to newly diagnosed and relapsed MM. High prevalence of MAGI2 was also associated with poor survival of MM patients. Importantly, inhibition of the SE activity associated with MAGI2 decreased MAGI2 expression, inhibited cell growth and induced cell apoptosis. Mechanistically, we revealed that the oncogenic transcription factor, MAF, directly bound to the SE region and activated gene transcription. In summary, the discoveries of these acquired SEs-associated genes and the novel mechanism by which they are regulated provide new insights into MM biology and MAGI2-MAF-SE regulatory circuit offer potential novel targets for disease treatment.

LncSEA: a platform for long non-coding RNA related sets and enrichment analysis

Long non-coding RNAs (lncRNAs) have been proven to play important roles in transcriptional processes and various biological functions. Establishing a comprehensive collection of human lncRNA sets is urgent work at present. Using reference lncRNA sets, enrichment analyses will be useful for analyzing lncRNA lists of interest submitted by users. Therefore, we developed a human lncRNA sets database, called LncSEA, which aimed to document a large number of available resources for human lncRNA sets and provide annotation and enrichment analyses for lncRNAs. LncSEA supports >40 000 lncRNA reference sets across 18 categories and 66 sub-categories, and covers over 50 000 lncRNAs. We not only collected lncRNA sets based on downstream regulatory data sources, but also identified a large number of lncRNA sets regulated by upstream transcription factors (TFs) and DNA regulatory elements by integrating TF ChIP-seq, DNase-seq, ATAC-seq and H3K27ac ChIP-seq data. Importantly, LncSEA provides annotation and enrichment analyses of lncRNA sets associated with upstream regulators and downstream targets. In summary, LncSEA is a powerful platform that provides a variety of types of lncRNA sets for users, and supports lncRNA annotations and enrichment analyses. The LncSEA database is freely accessible at http://bio.liclab.net/LncSEA/index.php.

VARAdb: a comprehensive variation annotation database for human

With the study of human diseases and biological processes increasing, a large number of non-coding variants have been identified and facilitated. The rapid accumulation of genetic and epigenomic information has resulted in an urgent need to collect and process data to explore the regulation of non-coding variants. Here, we developed a comprehensive variation annotation database for human (VARAdb, http://www.licpathway.net/VARAdb/), which specifically considers non-coding variants. VARAdb provides annotation information for 577,283,813 variations and novel variants, prioritizes variations based on scores using nine annotation categories, and supports pathway downstream analysis. Importantly, VARAdb integrates a large amount of genetic and epigenomic data into five annotation sections, which include ‘Variation information’, ‘Regulatory information’, ‘Related genes’, ‘Chromatin accessibility’ and ‘Chromatin interaction’. The detailed annotation information consists of motif changes, risk SNPs, LD SNPs, eQTLs, clinical variant-drug-gene pairs, sequence conservation, somatic mutations, enhancers, super enhancers, promoters, transcription factors, chromatin states, histone modifications, chromatin accessibility regions and chromatin interactions. This database is a user-friendly interface to query, browse and visualize variations and related annotation information. VARAdb is a useful resource for selecting potential functional variations and interpreting their effects on human diseases and biological processes.

Integrative Epigenomic Analysis of Transcriptional Regulation of Human CircRNAs

Circular RNAs (circRNAs) are evolutionarily conserved and abundant non-coding RNAs whose functions and regulatory mechanisms remain largely unknown. Here, we identify and characterize an epigenomically distinct group of circRNAs (TAH-circRNAs), which are transcribed to a higher level than their host genes. By integrative analysis of cistromic and transcriptomic data, we find that compared with other circRNAs, TAH-circRNAs are expressed more abundantly and have more transcription factors (TFs) binding sites and lower DNA methylation levels. Concordantly, TAH-circRNAs are enriched in open and active chromatin regions. Importantly, ChIA-PET results showed that 23–52% of transcription start sites (TSSs) of TAH-circRNAs have direct interactions with cis-regulatory regions, strongly suggesting their independent transcriptional regulation from host genes. In addition, we characterize molecular features of super-enhancer-driven circRNAs in cancer biology. Together, this study comprehensively analyzes epigenomic characteristics of circRNAs and identifies a distinct group of TAH-circRNAs that are independently transcribed via enhancers and super-enhancers by TFs. These findings substantially advance our understanding of the regulatory mechanism of circRNAs and may have important implications for future investigations of this class of non-coding RNAs.

ATACdb: a comprehensive human chromatin accessibility database

Accessible chromatin is a highly informative structural feature for identifying regulatory elements, which provides a large amount of information about transcriptional activity and gene regulatory mechanisms. Human ATAC-seq datasets are accumulating rapidly, prompting an urgent need to comprehensively collect and effectively process these data. We developed a comprehensive human chromatin accessibility database (ATACdb, http://www.licpathway.net/ATACdb), with the aim of providing a large amount of publicly available resources on human chromatin accessibility data, and to annotate and illustrate potential roles in a tissue/cell type-specific manner. The current version of ATACdb documented a total of 52 078 883 regions from over 1400 ATAC-seq samples. These samples have been manually curated from over 2200 chromatin accessibility samples from NCBI GEO/SRA. To make these datasets more accessible to the research community, ATACdb provides a quality assurance process including four quality control (QC) metrics. ATACdb provides detailed (epi)genetic annotations in chromatin accessibility regions, including super-enhancers, typical enhancers, transcription factors (TFs), common single-nucleotide polymorphisms (SNPs), risk SNPs, eQTLs, LD SNPs, methylations, chromatin interactions and TADs. Especially, ATACdb provides accurate inference of TF footprints within chromatin accessibility regions. ATACdb is a powerful platform that provides the most comprehensive accessible chromatin data, QC, TF footprint and various other annotations.

MiRNA-Mediated Subpathway Identification and Network Module Analysis to Reveal Prognostic Markers in Human Pancreatic Cancer

Background

Pancreatic cancer (PC) remains one of the most lethal cancers. In contrast to the steady increase in survival for most cancers, the 5-year survival remains low for PC patients.

Methods

We describe a new pipeline that can be used to identify prognostic molecular biomarkers by identifying miRNA-mediated subpathways associated with PC. These modules were then further extracted from a comprehensive miRNA-gene network (CMGN). An exhaustive survival analysis was performed to estimate the prognostic value of these modules.

Results

We identified 105 miRNA-mediated subpathways associated with PC. Two subpathways within the MAPK signaling and cell cycle pathways were found to be highly related to PC. Of the miRNA-mRNA modules extracted from CMGN, six modules showed good prognostic performance in both independent validated datasets.

Conclusions

Our study provides novel insight into the mechanisms of PC. We inferred that six miRNA-mRNA modules could serve as potential prognostic molecular biomarkers in PC based on the pipeline we proposed.

Chromatin remodeling in peripheral blood cells reflects COVID-19 symptom severity

SARS-CoV-2 infection triggers highly variable host responses and causes varying degrees of illness in humans. We sought to harness the peripheral blood mononuclear cell (PBMC) response over the course of illness to provide insight into COVID-19 physiology. We analyzed PBMCs from subjects with variable symptom severity at different stages of clinical illness before and after IgG seroconversion to SARS-CoV-2. Prior to seroconversion, PBMC transcriptomes did not distinguish symptom severity. In contrast, changes in chromatin accessibility were associated with symptom severity. Furthermore, single-cell analyses revealed evolution of the chromatin accessibility landscape and transcription factor motif occupancy for individual PBMC cell types. The most extensive remodeling occurred in CD14+ monocytes where sub-populations with distinct chromatin accessibility profiles were associated with disease severity. Our findings indicate that pre-seroconversion chromatin remodeling in certain innate immune populations is associated with divergence in symptom severity, and the identified transcription factors, regulatory elements, and downstream pathways provide potential prognostic markers for COVID-19 subjects.

The emerging role of super enhancer-derived noncoding RNAs in human cancer

Super enhancers (SEs) are large clusters of adjacent enhancers that drive the expression of genes which regulate cellular identity; SE regions can be enriched with a high density of transcription factors, co-factors, and enhancer-associated epigenetic modifications. Through enhanced activation of their target genes, SEs play an important role in various diseases and conditions, including cancer. Recent studies have shown that SEs not only activate the transcriptional expression of coding genes to directly regulate biological functions, but also drive the transcriptional expression of non-coding RNAs (ncRNAs) to indirectly regulate biological functions. SE-derived ncRNAs play critical roles in tumorigenesis, including malignant proliferation, metastasis, drug resistance, and inflammatory response. Moreover, the abnormal expression of SE-derived ncRNAs is closely related to the clinical and pathological characterization of tumors. In this review, we summarize the functions and roles of SE-derived ncRNAs in tumorigenesis and discuss their prospective applications in tumor therapy. A deeper understanding of the potential mechanism underlying the action of SE-derived ncRNAs in tumorigenesis may provide new strategies for the early diagnosis of tumors and targeted therapy.

Bromodomain-containing protein 4 regulates interleukin-34 expression in mouse ovarian cancer cells

Background

Interleukin (IL)-34 acts as an alternative ligand for the colony-stimulating factor-1 receptor and controls the biology of myeloid cells, including survival, proliferation, and differentiation. IL-34 has been reported to be expressed in cancer cells and to promote tumor progression and metastasis of certain cancers via the promotion of angiogenesis and immunosuppressive macrophage differentiation. We have shown in our previous reports that targeting IL-34 in chemo-resistant tumors in vitro resulted in a remarkable inhibition of tumor growth. Also, we reported poor prognosis in patients with IL-34-expressing tumor. Therefore, blocking of IL-34 is considered as a promising therapeutic strategy to suppress tumor progression. However, the molecular mechanisms that control IL-34 production are still largely unknown.

Methods

IL-34 producing ovarian cancer cell line HM-1 was treated by bromodomain and extra terminal inhibitor JQ1. The mRNA and protein expression of IL-34 was evaluated after JQ1 treatment. Chromatin immunoprecipitation was performed to confirm the involvement of bromodomain-containing protein 4 (Brd4) in the regulation of the Il34 gene. Anti-tumor effect of JQ1 was evaluated in mouse tumor model.

Results

We identified Brd4 as one of the critical molecules that regulate Il34 expression in cancer cells. Consistent with this, we found that JQ1 is capable of efficiently suppressing the recruitment of Brd4 to the promotor region of Il34 gene. Additionally, JQ1 treatment of mice bearing IL-34-producing tumor inhibited the tumor growth along with decreasing Il34 expression in the tumor.

Conclusion

The results unveiled for the first time the responsible molecule Brd4 that regulates Il34 expression in cancer cells and suggested its possibility as a treatment target.

TP63, SOX2, and KLF5 Establish a Core Regulatory Circuitry That Controls Epigenetic and Transcription Patterns in Esophageal Squamous Cell Carcinoma Cell Lines

BACKGROUND & AIMS

We investigated the transcriptome of esophageal squamous cell carcinoma (ESCC) cells, activity of gene regulatory (enhancer and promoter regions), and the effects of blocking epigenetic regulatory proteins.

METHODS

We performed chromatin immunoprecipitation sequencing with antibodies against H3K4me1, H3K4me3, and H3K27ac and an assay for transposase-accessible chromatin to map the enhancer regions and accessible chromatin in 8 ESCC cell lines. We used the CRC_Mapper algorithm to identify core regulatory circuitry transcription factors in ESCC cell lines, and determined genome occupancy profiles for 3 of these factors. In ESCC cell lines, expression of transcription factors was knocked down with small hairpin RNAs, promoter and enhancer regions were disrupted by CRISPR/Cas9 genome editing, or bromodomains and extraterminal (BET) family proteins and histone deacetylases (HDACs) were inhibited with ARV-771 and romidepsin, respectively. ESCC cell lines were then analyzed by whole-transcriptome sequencing, immunoprecipitation, immunoblots, immunohistochemistry, and viability assays. Interactions between distal enhancers and promoters were identified and verified with circular chromosome conformation capture sequencing. NOD-SCID mice were given injections of modified ESCC cells, some mice where given injections of HDAC or BET inhibitors, and growth of xenograft tumors was measured.

RESULTS

We identified super-enhancer-regulated circuits and transcription factors TP63, SOX2, and KLF5 as core regulatory factors in ESCC cells. Super-enhancer regulation of ALDH3A1 mediated by core regulatory factors was required for ESCC viability. We observed direct interactions between the promoter region of TP63 and functional enhancers, mediated by the core regulatory circuitry transcription factors. Deletion of enhancer regions from ESCC cells decreased expression of the core regulatory circuitry transcription factors and reduced cell viability; these same results were observed with knockdown of each core regulatory circuitry transcription factor. Incubation of ESCC cells with BET and HDAC disrupted the core regulatory circuitry program and the epigenetic modifications observed in these cells; mice given injections of HDAC or BET inhibitors developed smaller xenograft tumors from the ESCC cell lines. Xenograft tumors grew more slowly in mice given the combination of ARV-771 and romidepsin than mice given either agent alone.

CONCLUSIONS

In epigenetic and transcriptional analyses of ESCC cell lines, we found the transcription factors TP63, SOX2, and KLF5 to be part of a core regulatory network that determines chromatin accessibility, epigenetic modifications, and gene expression patterns in these cells. A combination of epigenetic inhibitors slowed growth of xenograft tumors derived from ESCC cells in mice.

Characterization of super-enhancer-associated functional lncRNAs acting as ceRNAs in ESCC

Long noncoding RNAs (lncRNAs) have important regulatory roles in cancer biology. Although some lncRNAs have well-characterized functions, the vast majority of this class of molecules remains functionally uncharacterized. To systematically pinpoint functional lncRNAs, a computational approach was proposed for identification of lncRNA-mediated competing endogenous RNAs (ceRNAs) through combining global and local regulatory direction consistency of expression. Using esophageal squamous cell carcinoma (ESCC) as model, we further identified many known and novel functional lncRNAs acting as ceRNAs (ce-lncRNAs). We found that most of them significantly regulated the expression of cancer-related hallmark genes. These ce-lncRNAs were significantly regulated by enhancers, especially super-enhancers (SEs). Landscape analyses for lncRNAs further identified SE-associated functional ce-lncRNAs in ESCC, such as HOTAIR, XIST, SNHG5, and LINC00094. THZ1, a specific CDK7 inhibitor, can result in global transcriptional downregulation of SE-associated ce-lncRNAs. We further demonstrate that a SE-associated ce-lncRNA, LINC00094 can be activated by transcription factors TCF3 and KLF5 through binding to SE regions and promoted ESCC cancer cell growth. THZ1 downregulated expression of LINC00094 through inhibiting TCF3 and KLF5. Our data demonstrated the important roles of SE-associated ce-lncRNAs in ESCC oncogenesis and might serve as targets for ESCC diagnosis and therapy.

Perspectives on the use of super-enhancers as a defining feature of cell/tissue-identity genes

Super-enhancers (SE) have become a popular concept and are widely used as a feature defining key identity genes. Here, we provide perspectives on the use of SE to define and identify cell/tissue-identity genes. By mining SE and their associated genes using murine functional genomics data, we highlight and discuss current limitations and open questions regarding both the sensitivity and specificity of identity genes/transcription factors predicted by SE. In this context, we point to cell/tissue-specific promoters as an important additional level of information, which we propose to combine with SE when aiming to define potential identity genes.

A STAT3 of Addiction: Adipose Tissue, Adipocytokine Signalling and STAT3 as Mediators of Metabolic Remodelling in the Tumour Microenvironment

Metabolic remodelling of the tumour microenvironment is a major mechanism by which cancer cells survive and resist treatment. The pro-oncogenic inflammatory cascade released by adipose tissue promotes oncogenic transformation, proliferation, angiogenesis, metastasis and evasion of apoptosis. STAT3 has emerged as an important mediator of metabolic remodelling. As a downstream effector of adipocytokines and cytokines, its canonical and non-canonical activities affect mitochondrial functioning and cancer metabolism. In this review, we examine the central role played by the crosstalk between the transcriptional and mitochondrial roles of STAT3 to promote survival and further oncogenesis within the tumour microenvironment with a particular focus on adipose-breast cancer interactions.

TRlnc: a comprehensive database for human transcriptional regulatory information of lncRNAs

Long noncoding RNAs (lncRNAs) have been proven to play important roles in transcriptional processes and biological functions. With the increasing study of human diseases and biological processes, information in human H3K27ac ChIP-seq, ATAC-seq and DNase-seq datasets is accumulating rapidly, resulting in an urgent need to collect and process data to identify transcriptional regulatory regions of lncRNAs. We therefore developed a comprehensive database for human regulatory information of lncRNAs (TRlnc, http://bio.licpathway.net/TRlnc), which aimed to collect available resources of transcriptional regulatory regions of lncRNAs and to annotate and illustrate their potential roles in the regulation of lncRNAs in a cell type-specific manner. The current version of TRlnc contains 8 683 028 typical enhancers/super-enhancers and 32 348 244 chromatin accessibility regions associated with 91 906 human lncRNAs. These regions are identified from over 900 human H3K27ac ChIP-seq, ATAC-seq and DNase-seq samples. Furthermore, TRlnc provides the detailed genetic and epigenetic annotation information within transcriptional regulatory regions (promoter, enhancer/super-enhancer and chromatin accessibility regions) of lncRNAs, including common SNPs, risk SNPs, eQTLs, linkage disequilibrium SNPs, transcription factors, methylation sites, histone modifications and 3D chromatin interactions. It is anticipated that the use of TRlnc will help users to gain in-depth and useful insights into the transcriptional regulatory mechanisms of lncRNAs.