Search

Objective Rheumatoid arthritis (RA) fibroblast-like synoviocytes (FLS) derived from hip and knee have distinctive DNA methylation and transcriptome patterns in interleukin (IL)-6 signaling and Janus kinase (JAK)-signal transducers and activators of transcription (STAT) pathways. To determine the functional effects of these joint-specific signatures, we evaluated how RA hip and knee FLS differ in their response to IL-6. Methods Hip or knee RA FLS were obtained after arthroplasty. Previously published datasets on epigenetic landscape of FLS were mined to identify joint-specific IL-6-related epigenomic differences. RNA sequencing was performed on five RA hip and five knee FLS treated with or without IL-6. Differential gene expression was determined using edgeR software. STAT3 phosphorylation was measured using bead assays. Sensitivity to tofacitinib was evaluated by measuring CCL2 inhibition using quantitative polymerase chain reaction. Results Assay for Transposase-Accessible Chromatin sequencing and histone chromatin immunoprecipitation sequencing datasets from RA FLS were analyzed to identify epigenomic differences between hip and knee. Differential chromatin accessibility was associated with IL-6,IL-6R, and JAK1 genes. H3K27ac was also differentially marked at other JAK-STAT-related genes, including STAT3-STAT5A region. Principal component analysis of RNA sequencing data confirmed segregation between RA hip and knee FLS under basal conditions, that persisted following IL-6 treatment. STAT3 phosphorylation after IL-6 was significantly higher in knee than hip FLS and was highly correlated with JAK1 protein levels. Knee FLS were less sensitive to the JAK inhibitor tofacitinib than hip FLS. Conclusion RA hip and knee FLS have distinct transcriptomes, epigenetic marks, and STAT3 activation patterns in the IL-6 pathway. These joint-specific differences might contribute to a differential clinical response in individual joints to targeted therapies such as JAK inhibitors.

The LIM and SH3 domain protein 1 (Lasp1) was originally cloned from metastatic breast cancer and characterised as an adaptor molecule associated with tumourigenesis and cancer cell invasion. However, the regulation of Lasp1 and its function in the aggressive transformation of cells is unclear. Here we use integrative epigenomic profiling of invasive fibroblast-like synoviocytes (FLS) from patients with rheumatoid arthritis (RA) and from mouse models of the disease, to identify Lasp1 as an epigenomically co-modified region in chronic inflammatory arthritis and a functionally important binding partner of the Cadherin-11/β-Catenin complex in zipper-like cell-to-cell contacts. In vitro, loss or blocking of Lasp1 alters pathological tissue formation, migratory behaviour and platelet-derived growth factor response of arthritic FLS. In arthritic human TNF transgenic mice, deletion of Lasp1 reduces arthritic joint destruction. Therefore, we show a function of Lasp1 in cellular junction formation and inflammatory tissue remodelling and identify Lasp1 as a potential target for treating inflammatory joint disorders associated with aggressive cellular transformation., Fibroblast-like synoviocytes are important mediators of joint pathology in rheumatoid arthritis (RA). Here the authors show that Lasp1 is epigenetically regulated and highly expressed by these cells in RA and its deletion can limit joint pathology in a mouse model of inflammatory arthritis.

PTPRS-targeted FLS-directed therapy synergizes with TNF inhibition in therapy of arthritis., Fibroblast-like synoviocytes (FLS) are joint-lining cells that promote rheumatoid arthritis (RA) pathology. Current disease-modifying antirheumatic agents (DMARDs) operate through systemic immunosuppression. FLS-targeted approaches could potentially be combined with DMARDs to improve control of RA without increasing immunosuppression. Here, we assessed the potential of immunoglobulin-like domains 1 and 2 (Ig1&2), a decoy protein that activates the receptor tyrosine phosphatase sigma (PTPRS) on FLS, for RA therapy. We report that PTPRS expression is enriched in synovial lining RA FLS and that Ig1&2 reduces migration of RA but not osteoarthritis FLS. Administration of an Fc-fusion Ig1&2 attenuated arthritis in mice without affecting innate or adaptive immunity. Furthermore, PTPRS was down-regulated in FLS by tumor necrosis factor (TNF) via a phosphatidylinositol 3-kinase–mediated pathway, and TNF inhibition enhanced PTPRS expression in arthritic joints. Combination of ineffective doses of TNF inhibitor and Fc-Ig1&2 reversed arthritis in mice, providing an example of synergy between FLS-targeted and immunosuppressive DMARD therapies.

ObjectiveWe aimed to understand the role of the tyrosine phosphatase PTPN14—which in cancer cells modulates the Hippo pathway by retaining YAP in the cytosol—in fibroblast-like synoviocytes (FLS) from patients with rheumatoid arthritis (RA).MethodsGene/protein expression levels were measured by quantitative PCR and/or Western blotting. Gene knockdown in RA FLS was achieved using antisense oligonucleotides. The interaction between PTPN14 and YAP was assessed by immunoprecipitation. The cellular localisation of YAP and SMAD3 was examined via immunofluorescence. SMAD reporter studies were carried out in HEK293T cells. The RA FLS/cartilage coimplantation and passive K/BxN models were used to examine the role of YAP in arthritis.ResultsRA FLS displayed overexpression of PTPN14 when compared with FLS from patients with osteoarthritis (OA). PTPN14 knockdown in RA FLS impaired TGFβ-dependent expression of MMP13 and potentiation of TNF signalling. In RA FLS, PTPN14 formed a complex with YAP. Expression of PTPN14 or nuclear YAP—but not of a non-YAP-interacting PTPN14 mutant—enhanced SMAD reporter activity. YAP promoted TGFβ-dependent SMAD3 nuclear localisation in RA FLS. Differences in epigenetic marks within Hippo pathway genes, including YAP, were found between RA FLS and OA FLS. Inhibition of YAP reduced RA FLS pathogenic behaviour and ameliorated arthritis severity.ConclusionIn RA FLS, PTPN14 and YAP promote nuclear localisation of SMAD3. YAP enhances a range of RA FLS pathogenic behaviours which, together with epigenetic evidence, points to the Hippo pathway as an important regulator of RA FLS behaviour.

DNA methylation is an important epigenetic mark but how its locus-specificity is decided in relation to DNA sequence is not fully understood. Here, we have analyzed 34 diverse whole-genome bisulfite sequencing datasets in human and identified 313 motifs, including 92 and 221 associated with methylation (methylation motifs, MMs) and unmethylation (unmethylation motifs, UMs), respectively. The functionality of these motifs is supported by multiple lines of evidence. First, the methylation levels at the MM and UM motifs are respectively higher and lower than the genomic background. Second, these motifs are enriched at the binding sites of methylation modifying enzymes including DNMT3A and TET1, indicating their possible roles of recruiting these enzymes. Third, these motifs significantly overlap with “somatic QTLs” (quantitative trait loci) of methylation and expression. Fourth, disruption of these motifs by mutation is associated with significantly altered methylation level of the CpGs in the neighbor regions. Furthermore, these motifs together with somatic mutations are predictive of cancer subtypes and patient survival. We revealed some of these motifs were also associated with histone modifications, suggesting a possible interplay between the two types of epigenetic modifications. We also found some motifs form feed forward loops to contribute to DNA methylation dynamics.

The integration of genomic and DNA methylation data has been demonstrated as a powerful strategy in understanding cancer mechanisms and identifying therapeutic targets. The TCGA consortium has mapped DNA methylation in thousands of cancer samples using Illumina Infinium Human Methylation 450 K BeadChip (Illumina 450 K array) that only covers about 1.5% of CpGs in the human genome. Therefore, increasing the coverage of the DNA methylome would significantly leverage the usage of the TCGA data. Here, we present a new model called EAGLING that can expand the Illumina 450 K array data 18 times to cover about 30% of the CpGs in the human genome. We applied it to analyze 13 cancers in TCGA. By integrating the expanded methylation, gene expression, and somatic mutation data, we identified the genes showing differential patterns in each of the 13 cancers. Many of the triple-evidenced genes identified in majority of the cancers are biomarkers or potential biomarkers. Pan-cancer analysis also revealed the pathways in which the triple-evidenced genes are enriched, which include well known ones as well as new ones, such as axonal guidance signaling pathway and pathways related to inflammatory processing or inflammation response. Triple-evidenced genes, particularly TNXB, RRM2, CELSR3, SLC16A3, FANCI, MMP9, MMP11, SIK1, and TRIM59 showed superior predictive power in both tumor diagnosis and prognosis. These results have demonstrated that the integrative analysis using the expanded methylation data is powerful in identifying critical genes/pathways that may serve as new therapeutic targets.

Background Recently, measurement of RNA at single cell resolution has yielded surprising insights. Methods for single-cell RNA sequencing (scRNA-seq) have received considerable attention, but the broad reliability of single cell methods and the factors governing their performance are still poorly known. Results Here, we conducted a large-scale control experiment to assess the transfer function of three scRNA-seq methods and factors modulating the function. All three methods detected greater than 70% of the expected number of genes and had a 50% probability of detecting genes with abundance greater than 2 to 4 molecules. Despite the small number of molecules, sequencing depth significantly affected gene detection. While biases in detection and quantification were qualitatively similar across methods, the degree of bias differed, consistent with differences in molecular protocol. Measurement reliability increased with expression level for all methods and we conservatively estimate measurements to be quantitative at an expression level greater than ~5–10 molecules. Conclusions Based on these extensive control studies, we propose that RNA-seq of single cells has come of age, yielding quantitative biological information. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3300-3) contains supplementary material, which is available to authorized users.

Single-nucleus gene expression Identifying the genes expressed at the level of a single cell nucleus can better help us understand the human brain. Blue et al. developed a single-nuclei sequencing technique, which they applied to cells in classically defined Brodmann areas from a postmortem brain. Clustering of gene expression showed concordance with the area of origin and defining 16 neuronal subtypes. Both excitatory and inhibitory neuronal subtypes show regional variations that define distinct cortical areas and exhibit how gene expression clusters may distinguish between distinct cortical areas. This method opens the door to widespread sampling of the genes expressed in a diseased brain and other tissues of interest. Science , this issue p. 1586

Recently, measurement of RNA at single cell resolution has yielded surprising insights. Methods for single-cell RNA sequencing (scRNA-seq) have received considerable attention, but the broad reliability of single cell methods and the factors governing their performance are still poorly known. Here, we conducted a large-scale control experiment to assess the transfer function of three scRNA-seq methods and factors modulating the function. All three methods detected greater than 70% of the expected number of genes and had a 50% probability of detecting genes with abundance greater than 2 to 4 molecules. Despite the small number of molecules, sequencing depth significantly affected gene detection. While biases in detection and quantification were qualitatively similar across methods, the degree of bias differed, consistent with differences in molecular protocol. Measurement reliability increased with expression level for all methods and we conservatively estimate the measurement transfer functions to be linear above ~5-10 molecules. Based on these extensive control studies, we propose that RNA-seq of single cells has come of age, yielding quantitative biological information.