Wnt-β-catenin activation epigenetically reprograms Treg cells in inflammatory bowel disease and dysplastic progression.
TL;DR: In this paper, Wnt-β-catenin activation induced newly accessible chromatin sites in these genes and upregulated their expression, leading to a disease-associated increase in the frequency of RORγt+ Treg cells coexpressing multiple pro-inflammatory cytokines.
Abstract: The diversity of regulatory T (Treg) cells in health and in disease remains unclear. Individuals with colorectal cancer harbor a subpopulation of RORγt+ Treg cells with elevated expression of β-catenin and pro-inflammatory properties. Here we show progressive expansion of RORγt+ Treg cells in individuals with inflammatory bowel disease during inflammation and early dysplasia. Activating Wnt-β-catenin signaling in human and murine Treg cells was sufficient to recapitulate the disease-associated increase in the frequency of RORγt+ Treg cells coexpressing multiple pro-inflammatory cytokines. Binding of the β-catenin interacting partner, TCF-1, to DNA overlapped with Foxp3 binding at enhancer sites of pro-inflammatory pathway genes. Sustained Wnt-β-catenin activation induced newly accessible chromatin sites in these genes and upregulated their expression. These findings indicate that TCF-1 and Foxp3 together limit the expression of pro-inflammatory genes in Treg cells. Activation of β-catenin signaling interferes with this function and promotes the disease-associated RORγt+ Treg phenotype.
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TL;DR: Wang et al. as discussed by the authors studied the Wnt pathway and analyzed the relevant targets when drugs or inhibitors act on the pathway, to clarify the medication ideas of drugs/ inhibitors for the treatment of diseases, especially colorectal cancer.
Abstract: Abstract Background The Wnt signaling pathway is a complex network of protein interactions that functions most commonly in embryonic development and cancer, but is also involved in normal physiological processes in adults. The canonical Wnt signaling pathway regulates cell pluripotency and determines the differentiation fate of cells during development. The canonical Wnt signaling pathway (also known as the Wnt/β-catenin signaling pathway) is a recognized driver of colon cancer and one of the most representative signaling pathways. As a functional effector molecule of Wnt signaling, the modification and degradation of β-catenin are key events in the Wnt signaling pathway and the development and progression of colon cancer. Therefore, the Wnt signaling pathway plays an important role in the pathogenesis of diseases, especially the pathogenesis of colorectal cancer (CRC). Objective Inhibit the Wnt signaling pathway to explore the therapeutic targets of colorectal cancer. Methods Based on studying the Wnt pathway, master the biochemical processes related to the Wnt pathway, and analyze the relevant targets when drugs or inhibitors act on the Wnt pathway, to clarify the medication ideas of drugs or inhibitors for the treatment of diseases, especially colorectal cancer. Results Wnt signaling pathways include: Wnt/β-catenin or canonical Wnt signaling pathway, planar cell polarity (Wnt-PCP) pathway and Wnt-Ca 2+ signaling pathway. The Wnt signaling pathway is closely related to cancer cell proliferation, stemness, apoptosis, autophagy, metabolism, inflammation and immunization, microenvironment, resistance, ion channel, heterogeneity, EMT/migration/invasion/metastasis. Drugs/phytochemicals and molecular preparations for the Wnt pathway of CRC treatment have now been developed. Wnt inhibitors are also commonly used clinically for the treatment of CRC. Conclusion The development of drugs/phytochemicals and molecular inhibitors targeting the Wnt pathway can effectively treat colorectal cancer clinically.
88 citations
TL;DR: In this paper, a single-cell RNA-sequencing analysis identified effector memory T cells and central memory Treg cells with differential expression of Klf2 and memory and activation markers.
Abstract: The transcription factor TCF-1 is essential for the development and function of regulatory T (Treg) cells; however, its function is poorly understood. Here, we show that TCF-1 primarily suppresses transcription of genes that are co-bound by Foxp3. Single-cell RNA-sequencing analysis identified effector memory T cells and central memory Treg cells with differential expression of Klf2 and memory and activation markers. TCF-1 deficiency did not change the core Treg cell transcriptional signature, but promoted alternative signaling pathways whereby Treg cells became activated and gained gut-homing properties and characteristics of the TH17 subset of helper T cells. TCF-1-deficient Treg cells strongly suppressed T cell proliferation and cytotoxicity, but were compromised in controlling CD4+ T cell polarization and inflammation. In mice with polyposis, Treg cell-specific TCF-1 deficiency promoted tumor growth. Consistently, tumor-infiltrating Treg cells of patients with colorectal cancer showed lower TCF-1 expression and increased TH17 expression signatures compared to adjacent normal tissue and circulating T cells. Thus, Treg cell-specific TCF-1 expression differentially regulates TH17-mediated inflammation and T cell cytotoxicity, and can determine colorectal cancer outcome.
30 citations
TL;DR: In this article, the effect of Foxp3-specific ablation of Blimp1 in Treg cells resulted in impaired suppressive activity and a reprogramming into effector T-cells, which were largely restricted to the tumor-infiltrating Treg population.
Abstract: Accumulation of Foxp3+ regulatory T (Treg) cells in the tumor often represents an important mechanism for cancer immune evasion and a critical barrier to anti-tumor immunity and immunotherapy. Many tumor-infiltrating Treg cells display an activated phenotype and express the transcription factor Blimp1. However, the specific impact of these Blimp1+ Treg cells and their follicular regulatory T (TFR) cell subset on tumor and the underlying mechanisms of action are not yet well-explored. Various transplantable tumor models were established in immunocompetent wild-type mice and mice with a Foxp3-specific ablation of Blimp1. Tumor specimens from patients with metastatic melanoma and TCGA datasets were analyzed to support the potential role of Treg and TFR cells in tumor immunity. In vitro culture assays and in vivo adoptive transfer assays were used to understand how Treg, TFR cells and antibody responses influence tumor control. RNA sequencing and NanoString analysis were performed to reveal the transcriptome of tumor-infiltrating Treg cells and tumor cells, respectively. Finally, the therapeutic effects of anti-PD-1 treatment combined with the disruption of Blimp1+ Treg activity were evaluated. Blimp1+ Treg and TFR cells were enriched in the tumors, and higher tumoral TFR signatures indicated increased risk of melanoma metastasis. Deletion of Blimp1 in Treg cells resulted in impaired suppressive activity and a reprogramming into effector T-cells, which were largely restricted to the tumor-infiltrating Treg population. This destabilization combined with increased anti-tumor effector cellular responses, follicular helper T-cell expansion, enhanced tumoral IgE deposition and activation of macrophages secondary to dysregulated TFR cells, remodeled the tumor microenvironment and delayed tumor growth. The increased tumor immunogenicity with MHC upregulation improved response to anti-PD-1 blockade. Mechanistically, Blimp1 enforced intratumoral Treg cells with a unique transcriptional program dependent on Eomesodermin (Eomes) expression; deletion of Eomes in Blimp1-deficient Treg cells restored tumor growth and attenuated anti-tumor immunity. These findings revealed Blimp1 as a new critical regulator of tumor-infiltrating Treg cells and a potential target for modulating Treg activity to treat cancer. Our study has also revealed two FCERIA-containing immune signatures as promising diagnostic or prognostic markers for melanoma patients.
20 citations
TL;DR: Gounari et al. as mentioned in this paper discuss the current understanding of the multiple roles of TCF-1 in T cell development and function and their mechanistic underpinnings.
Abstract: The T cell-specific DNA-binding protein TCF-1 is a central regulator of T cell development and function along multiple stages and lineages. Because it interacts with β-catenin, TCF-1 has been classically viewed as a downstream effector of canonical Wnt signaling, although there is strong evidence for β-catenin-independent TCF-1 functions. TCF-1 co-binds accessible regulatory regions containing or lacking its conserved motif and cooperates with other nuclear factors to establish context-dependent epigenetic and transcription programs that are essential for T cell development and for regulating immune responses to infection, autoimmunity and cancer. Although it has mostly been associated with positive regulation of chromatin accessibility and gene expression, TCF-1 has the potential to reduce chromatin accessibility and thereby suppress gene expression. In addition, the binding of TCF-1 bends the DNA and affects the chromatin conformation genome wide. This Review discusses the current understanding of the multiple roles of TCF-1 in T cell development and function and their mechanistic underpinnings. The transcription factor TCF-1 has multiple roles during T cell development and in mature T cells. Gounari and Khazaie review the potential mechanisms by which TCF-1 regulates gene expression.
14 citations
TL;DR: The role of Treg cells as principal guardians of the immune system can be attributed to their ability to restrain all currently recognized major types of inflammatory responses through modulating the activity of a wide range of cells of the innate and adaptive immune system as discussed by the authors .
14 citations
References
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TL;DR: The Gene Set Enrichment Analysis (GSEA) method as discussed by the authors focuses on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation.
Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
34,830 citations
TL;DR: EdgeR as mentioned in this paper is a Bioconductor software package for examining differential expression of replicated count data, which uses an overdispersed Poisson model to account for both biological and technical variability and empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference.
Abstract: Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org).
29,413 citations
TL;DR: The Kyoto Encyclopedia of Genes and Genomes (KEGG) as discussed by the authors is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules.
Abstract: Kyoto Encyclopedia of Genes and Genomes (KEGG) is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules. The major component of KEGG is the PATHWAY database that consists of graphical diagrams of biochemical pathways including most of the known metabolic pathways and some of the known regulatory pathways. The pathway information is also represented by the ortholog group tables summarizing orthologous and paralogous gene groups among different organisms. KEGG maintains the GENES database for the gene catalogs of all organisms with complete genomes and selected organisms with partial genomes, which are continuously re-annotated, as well as the LIGAND database for chemical compounds and enzymes. Each gene catalog is associated with the graphical genome map for chromosomal locations that is represented by Java applet. In addition to the data collection efforts, KEGG develops and provides various computational tools, such as for reconstructing biochemical pathways from the complete genome sequence and for predicting gene regulatory networks from the gene expression profiles. The KEGG databases are daily updated and made freely available (http://www.genome.ad.jp/kegg/).
24,024 citations
TL;DR: In comparative timings, the new algorithms are considerably faster than competing methods and can handle large problems and can also deal efficiently with sparse features.
Abstract: We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multinomial regression problems while the penalties include l(1) (the lasso), l(2) (ridge regression) and mixtures of the two (the elastic net). The algorithms use cyclical coordinate descent, computed along a regularization path. The methods can handle large problems and can also deal efficiently with sparse features. In comparative timings we find that the new algorithms are considerably faster than competing methods.
13,656 citations
TL;DR: This work presents Model-based Analysis of ChIP-Seq data, MACS, which analyzes data generated by short read sequencers such as Solexa's Genome Analyzer, and uses a dynamic Poisson distribution to effectively capture local biases in the genome, allowing for more robust predictions.
Abstract: We present Model-based Analysis of ChIP-Seq data, MACS, which analyzes data generated by short read sequencers such as Solexa's Genome Analyzer. MACS empirically models the shift size of ChIP-Seq tags, and uses it to improve the spatial resolution of predicted binding sites. MACS also uses a dynamic Poisson distribution to effectively capture local biases in the genome, allowing for more robust predictions. MACS compares favorably to existing ChIP-Seq peak-finding algorithms, and is freely available.
13,008 citations