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22 result(s) for "Casement, John"
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To Break or Not to Break: The Role of TOP2B in Transcription
Transcription and its regulation pose challenges related to DNA torsion and supercoiling of the DNA template. RNA polymerase tracking the helical groove of the DNA introduces positive helical torsion and supercoiling upstream and negative torsion and supercoiling behind its direction of travel. This can inhibit transcriptional elongation and other processes essential to transcription. In addition, chromatin remodeling associated with gene activation can generate or be hindered by excess DNA torsional stress in gene regulatory regions. These topological challenges are solved by DNA topoisomerases via a strand-passage reaction which involves transiently breaking and re-joining of one (type I topoisomerases) or both (type II topoisomerases) strands of the phosphodiester backbone. This review will focus on one of the two mammalian type II DNA topoisomerase enzymes, DNA topoisomerase II beta (TOP2B), that have been implicated in correct execution of developmental transcriptional programs and in signal-induced transcription, including transcriptional activation by nuclear hormone ligands. Surprisingly, several lines of evidence indicate that TOP2B-mediated protein-free DNA double-strand breaks are involved in signal-induced transcription. We discuss the possible significance and origins of these DSBs along with a network of protein interaction data supporting a variety of roles for TOP2B in transcriptional regulation.
TOP2B Is Required to Maintain the Adrenergic Neural Phenotype and for ATRA-Induced Differentiation of SH-SY5Y Neuroblastoma Cells
The neuroblastoma cell line SH-SY5Y is widely used to study retinoic acid (RA)-induced gene expression and differentiation and as a tool to study neurodegenerative disorders. SH-SY5Y cells predominantly exhibit adrenergic neuronal properties, but they can also exist in an epigenetically interconvertible alternative state with more mesenchymal characteristics; as a result, these cells can be used to study gene regulation circuitry controlling neuroblastoma phenotype. Using a combination of pharmacological inhibition and targeted gene inactivation, we have probed the requirement for DNA topoisomerase IIB (TOP2B) in RA-induced gene expression and differentiation and in the balance between adrenergic neuronal versus mesenchymal transcription programmes. We found that expression of many, but not all genes that are rapidly induced by ATRA in SH-SY5Y cells was significantly reduced in the TOP2B null cells; these genes include BCL2 , CYP26A1 , CRABP2 , and NTRK2 . Comparing gene expression profiles in wild-type versus TOP2B null cells, we found that long genes and genes expressed at a high level in WT SH-SY5Y cells were disproportionately dependent on TOP2B. Notably, TOP2B null SH-SY5Y cells upregulated mesenchymal markers vimentin ( VIM ) and fibronectin ( FN1 ) and components of the NOTCH signalling pathway. Enrichment analysis and comparison with the transcription profiles of other neuroblastoma-derived cell lines supported the conclusion that TOP2B is required to fully maintain the adrenergic neural-like transcriptional signature of SH-SY5Y cells and to suppress the alternative mesenchymal epithelial-like epigenetic state.
Comorbidities in the UK Primary Sjögren’s Syndrome Registry
Primary Sjögren's Syndrome (PSS) is a chronic disease characterised by symptoms of oral and ocular dryness, pain, fatigue, anxiety and depression. PSS patients can be subclassified by the pattern of severity of these five key symptoms using the Newcastle Sjögren's Stratification Tool (NSST). Although PSS is often associated with one or more comorbidities, the relationship between comorbidities, polypharmacy, and PSS symptom burden is unclear. Using data from the UK Primary Sjögren's Syndrome Registry (UKPSSR) we describe the landscape of polypharmacy and comorbidities in PSS. The UKPSSR is research biobank of clinically well-defined PSS patients where clinical, demographic, comorbidities and concomitant medications data are recorded. Patients were subclassified into the four NSST subgroups: Low Symptom Burden (LSB), High Symptom Burden (HSB), Dryness Dominated Fatigue (DDF) and Pain Dominated Fatigue (PDF). Group analyses of comorbid conditions and polypharmacy scores were performed. Comorbidity and Polypharmacy Scores (CPS) were modelled as a function of age, sex, symptom duration, body mass index (BMI), current immunosuppressant and hydroxychloroquine prescriptions and NSST subgroup. There were marked differences in the number and the nature of comorbidities associated with the NSST subgroups. LSB and DDF patients were characterized by fewer comorbidities and medications. In contrast, HSB and PDF patients were associated with more comorbidities and were more likely to be prescribed multiple medications. Group analysis shows that HSB patients are more closely associated with peripheral vascular disease and infection whereas the PDF patients were associated with cardiovascular disease and gastrointestinal comorbidities. Comorbidity and polypharmacy scores increase with age and BMI regardless of symptom subgroup and symptom duration. In addition, the longer the reported symptom duration the higher the associated comorbidities and polypharmacy scores. Comorbid conditions are more prevalent in some subgroups of the PSS cohort but increase with age and BMI across the entire cohort. It is unclear from these data whether specific comorbid conditions are a consequence of PSS or represent shared aetiology or pathogenetic susceptibility. Regardless, these findings may have implications for disease management and clinical trial design.
Epigenome-wide analysis across the development span of pediatric acute lymphoblastic leukemia: backtracking to birth
Background Cancer is the leading cause of disease-related mortality in children. Causes of leukemia, the most common form, are largely unknown. Growing evidence points to an origin in-utero , when global redistribution of DNA methylation occurs driving tissue differentiation. Methods Epigenome-wide DNA methylation was profiled in surrogate (blood) and target (bone marrow) tissues at birth, diagnosis, remission and relapse of pediatric pre-B acute lymphoblastic leukemia (pre-B ALL) patients. Double-blinded analyses was performed between prospective cohorts extending from birth to diagnosis and retrospective studies backtracking from clinical disease to birth. Validation was carried out using independent technologies and populations. Results The imprinted and immuno-modulating VTRNA2-1 was hypermethylated (FDR<0.05) at birth in nested cases relative to controls in all tested populations (totaling 317 cases and 483 controls), including European and Hispanic ancestries. VTRNA2-1 methylation was stable over follow-up years after birth and across surrogate, target and other tissues ( n =5,023 tissues; 30 types). When profiled in leukemic tissues from two clinical cohorts (totaling 644 cases), VTRNA2-1 methylation exhibited higher levels at diagnosis relative to controls, it reset back to normal levels at remission, and then re-increased to above control levels at relapse. Hypermethylation was significantly associated with worse pre-B ALL patient survival and with reduced VTRNA2-1 expression ( n =2,294 tissues; 26 types), supporting a functional and translational role for VTRNA2-1 methylation. Conclusion This study provides proof-of-concept to detect at birth epigenetic precursors of pediatric pre-B ALL. These alterations were reproducible with different technologies, in three continents and in two ethnicities, and can offer biomarkers for early detection and prognosis as well as actionable targets for therapy. Key points • Precursors of pediatric acute lymphoblastic leukemia may be of epigenetic origin, detectable since birth and affecting patient prognosis. • These epigenetic precursors can be robust over several years and across several populations, ethnicities and surrogate and target tissues.
Choice of Differentiation Media Significantly Impacts Cell Lineage and Response to CFTR Modulators in Fully Differentiated Primary Cultures of Cystic Fibrosis Human Airway Epithelial Cells
In vitro cultures of primary human airway epithelial cells (hAECs) grown at air–liquid interface have become a valuable tool to study airway biology under normal and pathologic conditions, and for drug discovery in lung diseases such as cystic fibrosis (CF). An increasing number of different differentiation media, are now available, making comparison of data between studies difficult. Here, we investigated the impact of two common differentiation media on phenotypic, transcriptomic, and physiological features of CF and non-CF epithelia. Cellular architecture and density were strongly impacted by the choice of medium. RNA-sequencing revealed a shift in airway cell lineage; one medium promoting differentiation into club and goblet cells whilst the other enriched the growth of ionocytes and multiciliated cells. Pathway analysis identified differential expression of genes involved in ion and fluid transport. Physiological assays (intracellular/extracellular pH, Ussing chamber) specifically showed that ATP12A and CFTR function were altered, impacting pH and transepithelial ion transport in CF hAECs. Importantly, the two media differentially affected functional responses to CFTR modulators. We argue that the effect of growth conditions should be appropriately determined depending on the scientific question and that our study can act as a guide for choosing the optimal growth medium for specific applications.
Significant Variations in Double-Stranded RNA Levels in Cultured Skin Cells
Endogenous double-stranded RNA has emerged as a potent stimulator of innate immunity. Under physiological conditions, endogenous dsRNA is maintained in the cell nucleus or the mitochondria; however, if protective mechanisms are breached, it leaches into the cytoplasm and triggers immune signaling pathways. Ectopic activation of innate immune pathways is associated with various diseases and senescence and can trigger apoptosis. Hereby, the level of cytoplasmic dsRNA is crucial. We have enriched dsRNA from two melanoma cell lines and primary dermal fibroblasts, including a competing probe, and analyzed the dsRNA transcriptome using RNA sequencing. There was a striking difference in read counts between the cell lines and the primary cells, and the effect was confirmed by northern blotting and immunocytochemistry. Both mitochondria (10–20%) and nuclear transcription (80–90%) contributed significantly to the dsRNA transcriptome. The mitochondrial contribution was lower in the cancer cells compared to fibroblasts. The expression of different transposable element families was comparable, suggesting a general up-regulation of transposable element expression rather than stimulation of a specific sub-family. Sequencing of the input control revealed minor differences in dsRNA processing pathways with an upregulation of oligoadenylate synthase and RNP125 that negatively regulates the dsRNA sensors RIG1 and MDA5. Moreover, RT-qPCR, Western blotting, and immunocytochemistry confirmed the relatively minor adaptations to the hugely different dsRNA levels. As a consequence, these transformed cell lines are potentially less tolerant to interventions that increase the formation of endogenous dsRNA.
Stability of symptom-based subtypes in Sjogren’s disease
ObjectivesThe Newcastle Sjogren’s Stratification Tool (NSST) stratifies Sjogren’s disease patients into four subtypes. Understanding the stability of the subtypes is vital if symptom-based stratification is to be more broadly adopted. In this study, we stratify patients longitudinally to understand how symptom-based subtypes vary over time and factors influencing subtype change.Methods274 patients from the United Kingdom Primary Sjögren’s Syndrome Registry (UKPSSR) with data permitting NSST subtype assignment from two study visits were included. The French Assessment of Systemic Signs and Evolution of Sjogren’s Syndrome (ASSESS) cohort (n=237) acted as an independent comparator. Group analyses of significant differences were performed, with logistic regression models used to assess covariates of subtype stability.ResultsUKPSSR and ASSESS cohorts showed a broadly similar proportion of subjects in each subtype and similar baseline clinical characteristics except body mass index (BMI). Several baseline characteristics differ significantly between the subtypes, most notably anti-Ro status and BMI. Subtype membership was reasonably stable in both cohorts with 60% and 57% retaining subtype. The high-symptom burden subtype was the most stable over time with 70% and 67% retaining subtype. Higher baseline probability score was the greatest predictor of subtype stability with higher C4 levels, antidepressant use, and a higher CCI score also predicting increased stability.ConclusionNSST subtype membership remains stable over time in a large proportion of patients. When subtype transition is associated with factors at baseline, it is most strongly associated with an uncertain subtype allocation. Our findings support the hypothesis that symptom-based subtypes reflect genuine pathobiological endotypes and therefore maybe important to consider in trial design and clinical management.
Transcriptomic profiling and machine learning uncover gene signatures of psoriasis endotypes and disease severity
Background Despite increased understanding of psoriasis pathogenesis, molecular classification of clinical phenotypes and disease severity is poorly defined. Knowledge gaps include whether molecular endotypes of psoriasis underlie distinct clinical phenotypes and the positive and negative molecular regulators of disease severity across tissue compartments. Methods We performed comprehensive RNA sequencing of skin and blood (n = 718) from prospectively-recruited, deeply-phenotyped discovery and replication cohorts of 146 subjects with moderate-to-severe chronic plaque psoriasis initiating TNF-inhibitor (adalimumab) or IL-12/23-inhibitor (ustekinumab) therapy. Results Here we show, using two complementary dimensionality reduction methods, that co-expressed gene modules and factors within skin and blood are significantly associated with psoriasis phenotypes and disease severity. We identify a 14-gene signature negatively associated with BMI in nonlesional skin and with disease severity in lesional skin. Genotype integration reveals that HLA-DQA1*01 and HLA-DRB1*15 genotypes are positively associated with baseline psoriasis severity. Using explainable machine learning models, we define two disease severity-associated gene modules in lesional skin - one positive, one negatively-associated - and a 9-gene signature in lesional skin predictive of disease severity. Disease severity signatures in blood are only seen following adalimumab exposure, suggesting greater systemic impact of adalimumab compared to ustekinumab, in line with its side effect profile. In contrast, a gene signature in blood linked to HLA-C*06:02 status is independent of disease severity or drug. Conclusions These findings delineate gene-environmental and genetic effects on the psoriasis transcriptome linked to disease severity. Plain language summary Psoriasis is a common and debilitating skin disease, linked to other inflammatory conditions. A lot is known about what causes psoriasis and the factors that influence it, but doctors still cannot offer personalised treatments. This is because it has been difficult to understand what makes psoriasis more or less severe, why people respond differently to treatment, or why some people develop related diseases. To help address this, we collected skin and blood samples and personal information from people with severe psoriasis across the United Kingdom. Using computer-based methods, we found shared biological processes that link the disease with obesity and help predict its severity. Rider, Grantham, Smith, Watson et al. integrate multiomic data from patients with psoriasis using dimensionality reduction and machine learning techniques. This approach identifies biological relationships between genetic background, clinical features and disease severity, providing insight into disease variability across individuals.
Examining the biological pathways underlying clinical heterogeneity in Sjogren's syndrome: proteomic and network analysis
Stratification approaches are vital to address clinical heterogeneity in Sjogren's syndrome (SS). We previously described that the Newcastle Sjogren's Stratification Tool (NSST) identified four distinct clinical subtypes of SS. We performed proteomic and network analysis to analyse the underlying pathobiology and highlight potential therapeutic targets for different SS subtypes. We profiled serum proteins using O-link technology of 180 SS subjects. We used 5 O-link proteomics panels which included a total of 454 unique proteins. Network reconstruction was performed using the ARACNE algorithm, with differential expression estimates overlaid on these networks to reveal the key subnetworks of differential expression. Furthermore, data from a phase III trial of tocilizumab in SS were reanalysed by stratifying patients at baseline using NSST. Our analysis highlights differential expression of chemokines, cytokines and the major autoantigen TRIM21 between the SS subtypes. Furthermore, we observe differential expression of several transcription factors associated with energy metabolism and redox balance namely APE1/Ref-1, FOXO1, TIGAR and BACH1. The differentially expressed proteins were inter-related in our network analysis, supporting the concept that distinct molecular networks underlie the clinical subtypes of SS. Stratification of patients at baseline using NSST revealed improvement of fatigue score only in the subtype expressing the highest levels of serum IL-6. Our data provide clues to the pathways contributing to the glandular and non-glandular manifestations of SS and to potential therapeutic targets for different SS subtypes. In addition, our analysis highlights the need for further exploration of altered metabolism and mitochondrial dysfunction in the context of SS subtypes.
Identification of ITIAM1/I as a Potential Synthetic-Lethal-like Gene in a Defined Subset of Hepatocellular Carcinoma
Hepatocellular carcinoma (HCC), the most common type of liver cancer, has very poor outcomes. Current therapies often have low efficacy and significant toxicities. Thus, there is a critical need for the development of novel therapeutic approaches for HCC. We have developed a novel bioinformatics pipeline, which integrates genome-wide DNA methylation and gene expression data, to identify genes required for the survival of specific molecular cancer subgroups but not normal cells. Targeting these genes may induce cancer-specific \"synthetic lethality\". Initially, five potential HCC molecular subgroups were identified based on global DNA methylation patterns. Subgroup-2 exhibited the most unique methylation profile and two candidate subtype-specific vulnerability or SL-like genes were identified for this subgroup, including TIAM1, a guanine nucleotide exchange factor encoding gene known to activate Rac1 signalling. siRNA targeting TIAM1 inhibited cell proliferation in TIAM1-positive (subgroup-2) HCC cell lines but had no effect on the normal hepatocyte HHL5 cell line. Furthermore, TIAM1-positive/subgroup-2 cell lines were significantly more sensitive to the TIAM1/RAC1 inhibitor NSC23766 compared with TIAM1-negative HCC lines or the normal HHL5 cell line. The results are consistent with a synthetic lethal role for TIAM1 in a methylation-defined HCC subgroup and suggest it may be a viable therapeutic target in this subset of HCC patients.