The synovial and blood monocyte DNA methylomes mirror prognosis, evolution and treatment in early arthritis

Identifying predictive biomarkers at early stages of early inflammatory arthritis is crucial for starting appropriate therapies to avoid poor outcomes. Monocytes and macrophages, largely associated with arthritis, are contributors and sensors of inflammation through epigenetic modifications. In this study, we investigated associations between clinical features and DNA methylation in blood and synovial fluid (SF) monocytes in a prospective cohort of early inflammatory arthritis patients. Undifferentiated arthritis (UA) blood monocyte DNA methylation profiles exhibited significant alterations in comparison with those from healthy donors. We identified additional differences both in blood and SF monocytes after comparing UA patients grouped by their future outcomes, good versus poor. Patient profiles in subsequent visits revealed a reversion towards a healthy level in both groups, those requiring disease-modifying antirheumatic drugs (DMARDs) and those that remitted spontaneously. Changes in disease activity between visits also impacted DNA methylation, partially concomitant in the SF of UA and in blood monocytes of rheumatoid arthritis patients. Epigenetic similarities between arthritis types allow a common prediction of disease activity. Our results constitute a resource of DNA methylation-based biomarkers of poor prognosis, disease activity and treatment efficacy in early untreated UA patients for the personalized clinical management of early inflammatory arthritis patients

Prediction of the progression of undifferentiated arthritis to rheumatoid arthritis using DNA methylation profiling

Objective The term "undifferentiated arthritis (UA)" is used to refer to all cases of arthritis that do not fit a specific diagnosis. A significant percentage of UA patients progress to rheumatoid arthritis (RA), others to a different definite rheumatic disease, and the rest undergo spontaneous remission. Therapeutic intervention in patients with UA can delay or halt disease progression and its long-term consequences. It is therefore of inherent interest to identify those UA patients with a high probability of progressing to RA who would benefit from early appropriate therapy. This study was undertaken to investigate whether alterations in the DNA methylation profiles of immune cells may provide information on the genetically or environmentally determined status of patients and potentially discriminate between disease subtypes. Methods We performed DNA methylation profiling of a UA patient cohort, in which progression to RA occurred for a significant proportion of the patients. Results We found differential DNA methylation in UA patients compared to healthy controls. Most importantly, our analysis identified a DNA methylation signature characteristic of those UA cases that differentiated to RA. We demonstrated that the methylome of peripheral mononuclear cells can be used to anticipate the evolution of UA to RA, and that this methylome is associated with a number of inflammatory pathways and transcription factors. Finally, we designed a machine learning strategy for DNA methylation-based classification that predicts the differentiation of UA toward RA. Conclusion Our findings indicate that DNA methylation profiling provides a good predictor of UA-to-RA progression to anticipate targeted treatments and improve clinical management.Pathophysiology and treatment of rheumatic disease

HDAC7 Is a Repressor of Myeloid Genes Whose Downregulation Is Required for Transdifferentiation of Pre-B Cells into Macrophages

B lymphopoiesis is the result of several cell-commitment, lineage-choice, and differentiation processes. Every differentiation step is characterized by the activation of a new, lineage-specific, genetic program and the extinction of the previous one. To date, the central role of specific transcription factors in positively regulating these distinct differentiation processes to acquire a B cell-specific genetic program is well established. However, the existence of specific transcriptional repressors responsible for the silencing of lineage inappropriate genes remains elusive. Here we addressed the molecular mechanism behind repression of non-lymphoid genes in B cells. We report that the histone deacetylase HDAC7 was highly expressed in pre-B cells but dramatically down-regulated during cellular lineage conversion to macrophages. Microarray analysis demonstrated that HDAC7 re-expression interfered with the acquisition of the gene transcriptional program characteristic of macrophages during cell transdifferentiation; the presence of HDAC7 blocked the induction of key genes for macrophage function, such as immune, inflammatory, and defense response, cellular response to infections, positive regulation of cytokines production, and phagocytosis. Moreover, re-introduction of HDAC7 suppressed crucial functions of macrophages, such as the ability to phagocytose bacteria and to respond to endotoxin by expressing major pro-inflammatory cytokines. To gain insight into the molecular mechanisms mediating HDAC7 repression in pre-B cells, we undertook co-immunoprecipitation and chromatin immunoprecipitation experimental approaches. We found that HDAC7 specifically interacted with the transcription factor MEF2C in pre-B cells and was recruited to MEF2 binding sites located at the promoters of genes critical for macrophage function. Thus, in B cells HDAC7 is a transcriptional repressor of undesirable genes. Our findings uncover a novel role for HDAC7 in maintaining the identity of a particular cell type by silencing lineage-inappropriate genes

Co-Depletion of Cathepsin B and uPAR Induces G0/G1 Arrest in Glioma via FOXO3a Mediated p27Kip1 Upregulation

Cathepsin B and urokinase plasminogen activator receptor (uPAR) are both known to be overexpressed in gliomas. Our previous work and that of others strongly suggest a relationship between the infiltrative phenotype of glioma and the expression of cathepsin B and uPAR. Though their role in migration and adhesion are well studied the effect of these molecules on cell cycle progression has not been thoroughly examined.Cathepsin B and uPAR single and bicistronic siRNA plasmids were used to downregulate these molecules in SNB19 and U251 glioma cells. FACS analysis and BrdU incorporation assay demonstrated G0/G1 arrest and decreased proliferation with the treatments, respectively. Immunoblot and immunocyto analysis demonstrated increased expression of p27(Kip1) and its nuclear localization with the knockdown of cathepsin B and uPAR. These effects could be mediated by alphaVbeta3/PI3K/AKT/FOXO pathway as observed by the decreased alphaVbeta3 expression, PI3K and AKT phosphorylation accompanied by elevated FOXO3a levels. These results were further confirmed with the increased expression of p27(Kip1) and FOXO3a when treated with Ly294002 (10 microM) and increased luciferase expression with the siRNA and Ly294002 treatments when the FOXO binding promoter region of p27(Kip1) was used. Our treatment also reduced the expression of cyclin D1, cyclin D2, p-Rb and cyclin E while the expression of Cdk2 was unaffected. Of note, the Cdk2-cyclin E complex formation was reduced significantly.Our study indicates that cathepsin B and uPAR knockdown induces G0/G1 arrest by modulating the PI3K/AKT signaling pathway and further increases expression of p27(Kip1) accompanied by the binding of FOXO3a to its promoter. Taken together, our findings provide molecular mechanism for the G0/G1 arrest induced by the downregulation of cathepsin B and uPAR in SNB19 and U251 glioma cells

STATegra, a comprehensive multi-omics dataset of B-cell differentiation in mouse

Multi-omics approaches use a diversity of high-throughput technologies to profile the different molecular layers of living cells. Ideally, the integration of this information should result in comprehensive systems models of cellular physiology and regulation. However, most multi-omics projects still include a limited number of molecular assays and there have been very few multi-omic studies that evaluate dynamic processes such as cellular growth, development and adaptation. Hence, we lack formal analysis methods and comprehensive multi-omics datasets that can be leveraged to develop true multi-layered models for dynamic cellular systems. Here we present the STATegra multi-omics dataset that combines measurements from up to 10 different omics technologies applied to the same biological system, namely the well-studied mouse pre-B-cell differentiation. STATegra includes high-throughput measurements of chromatin structure, gene expression, proteomics and metabolomics, and it is complemented with single-cell data. To our knowledge, the STATegra collection is the most diverse multi-omics dataset describing a dynamic biological system

DNA methylation signal has a major role in the response of human breast cancer cells to the microenvironment

International audienceBreast cancer-associated fibroblasts (CAFs) have a crucial role in tumor initiation, metastasis and therapeutic resistance by secreting various growth factors, cytokines, protease and extracellular matrix components. Soluble factors secreted by CAFs are involved in many pathways including inflammation, metabolism, proliferation and epigenetic modulation, suggesting that CAF-dependent reprograming of cancer cells affects a large set of genes. This paracrine signaling has an important role in tumor progression, thus deciphering some of these processes could lead to relevant discoveries with subsequent clinical implications. Here, we investigated the mechanisms underlying the changes in gene expression patterns associated with the cross-talk between breast cancer cells and the stroma. From RNAseq data obtained from breast cancer cell lines grown in presence of CAF-secreted factors, we identified 372 upregulated genes, exhibiting an expression level positively correlated with the stromal content of breast cancer specimens. Furthermore, we observed that gene expression changes were not mediated through significant DNA methylation changes. Nevertheless, CAF-secreted factors but also stromal content of the tumors remarkably activated specific genes characterized by a DNA methylation pattern: hypermethylation at transcription start site and shore regions. Experimental approaches (inhibition of DNA methylation, knockdown of methyl-CpG-binding domain protein 2 and chromatin immunoprecipitation assays) indicated that this set of genes was epigenetically controlled. These data elucidate the importance of epigenetics marks in the cancer cell reprogramming induced by stromal cell and indicated that the interpreters of the DNA methylation signal have a major role in the response of the cancer cells to the microenvironment

The DNA methylation Profile of Undifferentiated Arthritis Patients Anticipates their Subsequent Differentiation to Rheumatoid Arthritis

Objective The term "undifferentiated arthritis (UA)" is used to refer to all cases of arthritis that do not fit a specific diagnosis. A significant percentage of UA patients progress to rheumatoid arthritis (RA), others to a different definite rheumatic disease, and the rest undergo spontaneous remission. Therapeutic intervention in patients with UA can delay or halt disease progression and its long-term consequences. It is therefore of inherent interest to identify those UA patients with a high probability of progressing to RA who would benefit from early appropriate therapy. This study was undertaken to investigate whether alterations in the DNA methylation profiles of immune cells may provide information on the genetically or environmentally determined status of patients and potentially discriminate between disease subtypes. Methods We performed DNA methylation profiling of a UA patient cohort, in which progression to RA occurred for a significant proportion of the patients. Results We found differential DNA methylation in UA patients compared to healthy controls. Most importantly, our analysis identified a DNA methylation signature characteristic of those UA cases that differentiated to RA. We demonstrated that the methylome of peripheral mononuclear cells can be used to anticipate the evolution of UA to RA, and that this methylome is associated with a number of inflammatory pathways and transcription factors. Finally, we designed a machine learning strategy for DNA methylation-based classification that predicts the differentiation of UA toward RA. Conclusion Our findings indicate that DNA methylation profiling provides a good predictor of UA-to-RA progression to anticipate targeted treatments and improve clinical management.Pathophysiology and treatment of rheumatic disease

TET2-and TDG-mediated changes are required for the acquisition of distinct histone modifications in divergent terminal differentiation of myeloid cells

Instituto de Salud Carlos III, an organisation of the Ministerio de Economía y Competitividad, and cofunding by FEDER funds/European Regional Development Fund (ERDF)—a way to build Europe [SAF2014-55942-R]; Multiple Myeloma Research Foundation (MMRF); Asociación Española Contra el Cáncer (AECC) (to A.G.G.). Funding for open access charge: Instituto de Salud Carlos III, an organisation of the Ministerio de Economía y Competitividad, and cofunding by FEDER funds/European Regional Development Fund (ERDF)—a way to build Europe [SAF2014-55942-R]

Impaired CpG Demethylation in Common Variable Immunodeficiency Associates With B Cell Phenotype and Proliferation Rate

Common Variable Immunodeficiency (CVID) is characterized by impaired antibody production and poor terminal differentiation of the B cell compartment, yet its pathogenesis is still poorly understood. We first reported the occurrence of epigenetic alterations in CVID by high-throughput methylation analysis in CVID-discordant monozygotic twins. Data from a recent whole DNA methylome analysis throughout different stages of normal B cell differentiation allowed us to design a new experimental approach. We selected CpG sites for analysis based on two criteria: one, CpGs with potential association with the transcriptional status of relevant genes for B cell activation and differentiation; and two, CpGs that undergo significant demethylation from naive to memory B cells in healthy individuals. DNA methylation was analyzed by bisulfite pyrosequencing of specific CpG sites in sorted naive and memory B cell subsets from CVID patients and healthy donors. We observed impaired demethylation in two thirds of the selected CpGs in CVID memory B cells, in genes that govern B cell-specific processes or participate in B cell signaling. The degree of demethylation impairment associated with the extent of the memory B cell reduction. The impaired demethylation in such functionally relevant genes as AICDA in switched memory B cells correlated with a lower proliferative rate. Our new results reinforce the hypothesis of altered demethylation during B cell differentiation as a contributing pathogenic mechanism to the impairment of B cell function and maturation in CVID. In particular, deregulated epigenetic control of AICDA could play a role in the defective establishment of a post-germinal center B cell compartment in CVID.Transplantation and immunomodulatio