Search

Background/Aims The use of tumour necrosis factor inhibitors (TNFi) has advanced the clinical management of rheumatoid arthritis (RA). However, only 30-40% of patients who receive initial treatment with a TNFi experience a beneficial response. The discovery of reliable biomarkers of TNFi response is, therefore, a priority. Whilst T-cell dysfunction is documented in RA pathophysiology, T-cell involvement in TNFi treatment response is unclear. We aimed to phenotype peripheral blood-derived T-cells in RA patients over a number of time-points through the first 12-weeks of TNFi treatment; and to apply a cluster-free association testing method developed on single-cell CITE-seq data—co-varying neighbourhood analysis (CNA)—to high-dimensional single-cell CyTOF data. Methods 16 TNFi-naïve RA patients commenced treatment with a TNFi (10 on Adalimumab, 6 on Etanercept) and peripheral blood samples were collected at 6-7 time-points between pre-treatment and 12-weeks. Peripheral blood mononuclear cells were extracted, and stained with a 35-marker CyTOF panel. Treatment response was classified using the EULAR response criteria, and patients were characterised as good, moderate or non-responders. Data were cleaned in FlowJo and analysed using both i) a cluster-based approach, where data were clustered into 12 populations, and linear mixed models were fitted per cluster to test for significant differences in population abundance and ii) a cluster-free approach called CNA where association testing is purely data-driven. Both analyses controlled for age, sex, type of TNFi and TNFi concentration. Results Cluster-based analysis showed at 12-weeks, 1 of the 12 clusters (CD4+CD39+HLA-DR+) significantly increased in abundance in the non-responder cohort compared to the good and moderate responders (adjusted p = 0.037). Interestingly, HLA-DR and CD39 genetic effects have previously been associated with TNFi response. No significant differences were observed with CNA. Conclusion These results demonstrate that significant differences in T-cell abundance can be seen as early as 12-weeks after commencing treatment with a TNFi. Validation of these findings is required before the predictive value of this T-cell population can be tested. Disclosure M.A. Sutcliffe: None. S. Ling: None. A. Banyard: None. L. Rumker: None. S. Viatte: None. A. Morris: None. A. Barton: None. S. Raychaudhuri: None. D. Plant: None.

Gemcitabine (dFdC) is a common treatment for pancreatic cancer; however, it is thought that treatment may fail because tumor stroma prevents drug distribution to tumor cells. Gemcitabine is a pro-drug with active metabolites generated intracellularly; therefore, visualizing the distribution of parent drug as well as its metabolites is important. A multimodal imaging approach was developed using spatially coregistered mass spectrometry imaging (MSI), imaging mass cytometry (IMC), multiplex immunofluorescence microscopy (mIF), and hematoxylin and eosin (H&E) staining to assess the local distribution and metabolism of gemcitabine in tumors from a genetically engineered mouse model of pancreatic cancer (KPC) allowing for comparisons between effects in the tumor tissue and its microenvironment. Mass spectrometry imaging (MSI) enabled the visualization of the distribution of gemcitabine (100 mg/kg), its phosphorylated metabolites dFdCMP, dFdCDP and dFdCTP, and the inactive metabolite dFdU. Distribution was compared to small-molecule ATR inhibitor AZD6738 (25 mg/kg), which was codosed. Gemcitabine metabolites showed heterogeneous distribution within the tumor, which was different from the parent compound. The highest abundance of dFdCMP, dFdCDP, and dFdCTP correlated with distribution of endogenous AMP, ADP, and ATP in viable tumor cell regions, showing that gemcitabine active metabolites are reaching the tumor cell compartment, while AZD6738 was located to nonviable tumor regions. The method revealed that the generation of active, phosphorylated dFdC metabolites as well as treatment-induced DNA damage primarily correlated with sites of high proliferation in KPC PDAC tumor tissue, rather than sites of high parent drug abundance.

Context One risk factor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is postulated to be vitamin D deficiency. To better understand the role of vitamin D deficiency in the disease course of COVID-19, we undertook a retrospective case-control study in North West England. Objective To examine whether hospitalization with COVID-19 is more prevalent in individuals with lower vitamin D levels. Methods The study included individuals with test results for serum 25-hydroxyvitamin D (25[OH]D) between April 1, 2020, and January 29, 2021, from 2 districts in North West England. The last 25(OH)D level in the previous 12 months was categorized as “deficient” if less than 25 nmol/L and “insufficient” if 25 to 50 nmol/L. Results The study included 80 670 participants. Of these, 1808 were admitted to the hospital with COVID-19, of whom 670 died. In a primary cohort, median serum 25(OH)D in nonhospitalized participants with COVID-19 was 50.0 nmol/L (interquartile range [IQR], 34.0-66.7) vs 35.0 nmol/L (IQR, 21.0-57.0) in those admitted with COVID-19 (P Conclusion Vitamin D deficiency is associated with higher risk of COVID-19 hospitalization. Widespread measurement of serum 25(OH)D and treatment of insufficiency or deficiency may reduce this risk.

The tetracycline (TC) in water has led to serious concern. Graphitic carbon nitride (g-C3N4) photocatalysts were produced via copolymerization of mono-benzene ring-mediated precursors (urea, melamine, and dicyandiamide) involving salicylic acid (SA) for TC degradation. The SA-modified g-C3N4 samples showed improved visible-light absorbance, transfer and separation of photogenerated electrons, and prospective photocatalytic application in TC degradation. As a result, the optimal SA-modified g-C3N4 (2 wt% of SA) using urea (CNU-SA-2) showed 2 times higher TC degradation than that of pristine g-C3N4. The process of TC degradation was evaluated by the reduction of antibacterial activity and extensively studied by varying the types of TC, initial pH values, co-existing anions, and natural organic materials. In addition, the catalyst could be reused for at least four cycles, indicating good reusability. The main active species were revealed to be h+ and ·O2− by scavenging experiments and electron spin resonance. The CNU-SA-2 photocatalyst and TC intermediates during degradation had no adverse impact on zebrafish embryos. This work could provide a design strategy and a perspective on the practical application of g-C3N4-based photocatalysts for the treatment of wastewater containing antibiotics.

Methotrexate (MTX) is a common first-line treatment for new-onset rheumatoid arthritis (RA). However, MTX is ineffective for 30–40% of patients and there is no way to know which patients might benefit. Here, we built statistical models based on serum lipid levels measured at two time-points (pre-treatment and following 4 weeks on-drug) to investigate if MTX response (by 6 months) could be predicted. Patients about to commence MTX treatment for the first time were selected from the Rheumatoid Arthritis Medication Study (RAMS). Patients were categorised as good or non-responders following 6 months on-drug using EULAR response criteria. Serum lipids were measured using ultra‐performance liquid chromatography–mass spectrometry and supervised machine learning methods (including regularized regression, support vector machine and random forest) were used to predict EULAR response. Models including lipid levels were compared to models including clinical covariates alone. The best performing classifier including lipid levels (assessed at 4 weeks) was constructed using regularized regression (ROC AUC 0.61 ± 0.02). However, the clinical covariate based model outperformed the classifier including lipid levels when either pre- or on-treatment time-points were investigated (ROC AUC 0.68 ± 0.02). Pre- or early-treatment serum lipid profiles are unlikely to inform classification of MTX response by 6 months with performance adequate for use in RA clinical management.

Imaging mass cytometry (IMC) offers the opportunity to image metal- and heavy halogen-containing xenobiotics in a highly multiplexed experiment with other immunochemistry-based reagents to distinguish uptake into different tissue structures or cell types. However, in practice, many xenobiotics are not amenable to this analysis, as any compound which is not bound to the tissue matrix will delocalize during aqueous sample-processing steps required for IMC analysis. Here, we present a strategy to perform IMC experiments on a water-soluble polysarcosine-modified dendrimer drug-delivery system (S-Dends). This strategy involves two consecutive imaging acquisitions on the same tissue section using the same instrumental platform, an initial laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MSI) experiment followed by tissue staining and a standard IMC experiment. We demonstrated that settings can be found for the initial ablation step that leave sufficient residual tissue for subsequent antibody staining and visualization. This workflow results in lateral resolution for the S-Dends of 2 μm followed by imaging of metal-tagged antibodies at 1 μm.

Isu komitmen guru rendah sering berlaku dan saling berhubung kait dengan amalan transformasional pengetua. Guru yang berkomited rendah akan menunjukkan tingkah laku negatif dan kurang proaktif terhadap sekolah. Kajian ini bertujuan untuk mengenal pasti hubungan antara tahap amalan kepimpinan transformasional pengetua dengan komitmen guru di sekolah menengah daerah Subis, Sarawak. Kajian ini menggunakan reka bentuk tinjauan dan pendekatan kuantitatif. Borang soal selidik digunakan untuk mengumpul data. Seramai 169 orang responden daripada 295 orang guru telah dipilih sebagai sampel kajian. Data dianalisis menggunakan statistik deskriptif dan inferensi. Dapatan kajian mendapati bahawa tahap kepimpinan transformasional pengetua berada pada tahap yang tinggi (min = 3.80; s.p. = 0.601) manakala tahap komitmen guru juga berada pada tahap yang tinggi (min = 3.72; s.p. = 0.604). Amalan kepimpinan transformasional pengetua mempunyai hubungan yang signifikan dengan komitmen guru di SMK daerah Subis, Sarawak (r = 0.586, p < 0.01). Secara keseluruhannya, dapatan kajian menunjukkan hubungan antara amalan kepimpinan transformasional pengetua mengikut persepsi guru dan komitmen guru di SMK daerah Subis, Sarawak adalah kuat. Implikasinya kajian ini dilaksanakan dan diharapkan dapat mengisi jurang yang tidak dikaji dan melihat sejauh mana kepimpinan transformasional meningkatkan komitmen guru. Pengetua boleh mempersiapkan diri dengan info gaya kepimpinan transformasional dan mendapatkan latihan secara teori dan praktikal dalam bidang kepimpinan.

Clinical tissue specimens are often unscreened, and preparation of tissue sections for analysis by mass spectrometry imaging (MSI) can cause aerosolization of particles potentially carrying an infectious load. We here present a decontamination approach based on ultraviolet-C (UV-C) light to inactivate clinically relevant pathogens such as herpesviridae, papovaviridae human immunodeficiency virus, or SARS-CoV-2, which may be present in human tissue samples while preserving the biodistributions of analytes within the tissue. High doses of UV-C required for high-level disinfection were found to cause oxidation and photodegradation of endogenous species. Lower UV-C doses maintaining inactivation of clinically relevant pathogens to a level of increased operator safety were found to be less destructive to the tissue metabolome and xenobiotics. These doses caused less alterations of the tissue metabolome and allowed elucidation of the biodistribution of the endogenous metabolites. Additionally, we were able to determine the spatially integrated abundances of the ATR inhibitor ceralasertib from decontaminated human biopsies using desorption electrospray ionization-MSI (DESI-MSI).

The limited availability of human kidney biopsies to study acute kidney injury (AKI) has restricted the development of effective therapies for this condition. Here, we validate the use of deceased transplant organ donor kidneys to study human AKI and characterized the multi-omics and immune landscape of human AKI kidneys. We demonstrate that changes in kidney injury and inflammatory markers following AKI in deceased transplant donors are similar to that of mouse kidney ischemia-reperfusion injury. Integrated transcriptomic and metabolomic analysis of human kidneys shows upregulated renal arachidonic acid metabolism following AKI, a pathway speculated to be linked to the ceramide accumulation detected in these kidneys. Markers of T and B lymphocytes, and macrophages were upregulated in AKI kidneys. Interestingly, we show upregulated renal cytoplasmic phospholipase A2 (cPLA2) levels in AKI kidneys, and the inhibition of this enzyme reduced injury and inflammation in vitro, findings that have potentially important therapeutic implications.

AZD0156 is a potent and selective, bioavailable inhibitor of ataxia-telangiectasia mutated (ATM) protein, a signaling kinase involved in the DNA damage response. We present preclinical data demonstrating abrogation of irradiation-induced ATM signaling by low doses of AZD0156, as measured by phosphorylation of ATM substrates. AZD0156 is a strong radiosensitizer in vitro, and using a lung xenograft model, we show that systemic delivery of AZD0156 enhances the tumor growth inhibitory effects of radiation treatment in vivo. Because ATM deficiency contributes to PARP inhibitor sensitivity, preclinically, we evaluated the effect of combining AZD0156 with the PARP inhibitor olaparib. Using ATM isogenic FaDu cells, we demonstrate that AZD0156 impedes the repair of olaparib-induced DNA damage, resulting in elevated DNA double-strand break signaling, cell-cycle arrest, and apoptosis. Preclinically, AZD0156 potentiated the effects of olaparib across a panel of lung, gastric, and breast cancer cell lines in vitro, and improved the efficacy of olaparib in two patient-derived triple-negative breast cancer xenograft models. AZD0156 is currently being evaluated in phase I studies (NCT02588105).

Seropositivity for anti-citrullinated peptide antibodies (ACPA) in patients with rheumatoid arthritis (RA), a chronic autoimmune arthritis, is associated with worse long-term disease outcomes. ACPA is ubiquitously tested in RA patients, but other autoantibodies exist (in both citrullinated and non-citrullinated form) which may provide additional information on RA subtypes and/or treatment response. We used a multiplex bead-based assay of 376 autoantibodies to test associations between these autoantibodies and treatment response in RA patients. Clusters of patients with similar autoantibody expression were defined and cluster membership was associated with treatment response. Thirty-four autoantibodies were differentially expressed in RA patients compared with healthy controls; citrullinated vimentin was associated with treatment response. A selection of citrullinated autoantibodies was found to be associated with treatment response in a subanalysis of ACPA-negative RA patients. Finer ACPA specificities in ACPA-negative RA patients may be predictive of treatment response and could represent a rich vein of future study.

A more complete and holistic view on host-microbe interactions is needed to understand the physiological and cellular barriers that affect the efficacy of drug treatments and allow the discovery and development of new therapeutics. Here, we developed a multimodal imaging approach combining histopathology with mass spectrometry imaging (MSI) and same section imaging mass cytometry (IMC) to study the effects of

A more complete and holistic view on host-microbe interactions is needed to understand the physiological and cellular barriers that affect the efficacy of drug treatments and allow the discovery and development of new therapeutics. Here, we developed a multimodal imaging approach combining histopathology with mass spectrometry imaging (MSI) and same section imaging mass cytometry (IMC) to study the effects of Salmonella Typhimurium infection in the liver of a mouse model using the S. Typhimurium strains SL3261 and SL1344. This approach enables correlation of tissue morphology and specific cell phenotypes with molecular images of tissue metabolism. IMC revealed a marked increase in immune cell markers and localization in immune aggregates in infected tissues. A correlative computational method (network analysis) was deployed to find metabolic features associated with infection and revealed metabolic clusters of acetyl carnitines, as well as phosphatidylcholine and phosphatidylethanolamine plasmalogen species, which could be associated with pro-inflammatory immune cell types. By developing an IMC marker for the detection of Salmonella LPS, we were further able to identify and characterize those cell types which contained S. Typhimurium.

Two-dimensional (2D) graphitic carbon nitride (g-C

Osteosarcoma (OS) is the most common primary bone malignancy and largely effects adolescents and young adults, with 60% of patients under the age of 25. There are multiple cell models of OS described in vitro that express the specific genetic alterations of the sarcoma. In the work reported here, multiple mass spectrometry imaging (MSI) modalities were employed to characterise two aggregated cellular models of OS models formed using the MG63 and SAOS-2 cell lines. Phenotyping of the metabolite activity within the two OS aggregoid models was achieved and a comparison of the metabolite data with OS human tissue samples revealed relevant fatty acid and phospholipid markers. Although, annotations of these species require MS/MS analysis for confident identification of the metabolites. From the putative assignments however, it was suggested that the MG63 aggregoids are an aggressive tumour model that exhibited metastatic-like potential. Alternatively, the SAOS-2 aggregoids are more mature osteoblast-like phenotype that expressed characteristics of cellular differentiation and bone development. It was determined the two OS aggregoid models shared similarities of metabolic behaviour with different regions of OS human tissues, specifically of the higher metastatic grade.

Cardiac physiology and homeostasis are maintained by the interaction of multiple cell types, via both intra- and intercellular signaling pathways. Perturbations in these signaling pathways induced by oncology therapies can reduce cardiac function, ultimately leading to heart failure. As cancer survival increases, related cardiovascular complications are becoming increasingly prevalent, thus identifying the perturbations and cell signaling drivers of cardiotoxicity is increasingly important. Here, we discuss the homotypic and heterotypic cellular interactions that form the basis of intra- and intercellular cardiac signaling pathways, and how oncological agents disrupt these pathways, leading to heart failure. We also highlight the emerging systems biology techniques that can be applied, enabling a deeper understanding of the intra- and intercellular signaling pathways across multiple cell types associated with cardiovascular toxicity.

The worldwide pandemic of 2019 novel coronavirus disease (COVID-19) has posed the most substantial and severe public health issue for several generations, and therapeutic options have not yet been optimised. Vitamin D (in its &ldquo, parent&rdquo, form, cholecalciferol) has been proposed in the pharmacological management of COVID-19 by various sources. We aimed to determine whether COVID-19 mortality was affected by serum 25-hydroxyvitamin D (25(OH)D) levels, vitamin D status, or cholecalciferol therapy, and to elucidate any other predictors of COVID-19 mortality. Patients hospitalised with COVID-19 were opportunistically recruited from three UK hospitals, and their data were collected retrospectively. Logistic regression was used to determine any relationships between COVID-19 mortality and potential predictors, including 25(OH)D levels and cholecalciferol booster therapy. A total of 986 participants with COVID-19 were studied, of whom 151 (16.0%) received cholecalciferol booster therapy. In the primary cohort of 444 patients, cholecalciferol booster therapy was associated with a reduced risk of COVID-19 mortality, following adjustment for potential confounders (ORadj 0.13, 95% CI 0.05&ndash, 0.35, p &lt, 0.001). This finding was replicated in a validation cohort of 541 patients (ORadj 0.38, 95% CI 0.17&ndash, 0.84, p = 0.018). In this observational study, treatment with cholecalciferol booster therapy, regardless of baseline serum 25(OH)D levels, appears to be associated with a reduced risk of mortality in acute in-patients admitted with COVID-19. Further work with large population studies needs to be carried out to determine adequate serum 25(OH)D levels, as well as multi-dose clinical trials of cholecalciferol therapy to assess maximum efficacy.

Mass spectrometry imaging (MSI) is an established analytical tool capable of defining and understanding complex tissues by determining the spatial distribution of biological molecules. Three-dimensional (3D) cell culture models mimic the pathophysiological environment of in vivo tumors and are rapidly emerging as a valuable research tool. Here, multimodal MSI techniques were employed to characterize a novel aggregated 3D lung adenocarcinoma model, developed by the group to mimic the in vivo tissue. Regions of tumor heterogeneity and the hypoxic microenvironment were observed based on the spatial distribution of a variety of endogenous molecules. Desorption electrospray ionization (DESI)-MSI defined regions of a hypoxic core and a proliferative outer layer from metabolite distribution. Targeted metabolites (e.g., lactate, glutamine, and citrate) were mapped to pathways of glycolysis and the TCA cycle demonstrating tumor metabolic behavior. The first application of imaging mass cytometry (IMC) with 3D cell culture enabled single-cell phenotyping at 1 μm spatial resolution. Protein markers of proliferation (Ki-67) and hypoxia (glucose transporter 1) defined metabolic signaling in the aggregoid model, which complemented the metabolite data. Laser ablation inductively coupled plasma (LA-ICP)-MSI analysis localized endogenous elements including magnesium and copper, further differentiating the hypoxia gradient and validating the protein expression. Obtaining a large amount of molecular information on a complementary nature enabled an in-depth understanding of the biological processes within the novel tumor model. Combining powerful imaging techniques to characterize the aggregated 3D culture highlighted a future methodology with potential applications in cancer research and drug development.

A new tissue sample embedding and processing method is presented that provides downstream compatibility with numerous different histological, molecular biology, and analytical techniques. The methodology is based on the low temperature embedding of fresh frozen specimens into a hydrogel matrix composed of hydroxypropyl methylcellulose (HPMC) and polyvinylpyrrolidone (PVP) and sectioning using a cryomicrotome. The hydrogel was expected not to interfere with standard tissue characterization methods, histologically or analytically. We assessed the compatibility of this protocol with various mass spectrometric imaging methods including matrix-assisted laser desorption ionization (MALDI), desorption electrospray ionization (DESI) and secondary ion mass spectrometry (SIMS). We also demonstrated the suitability of the universal protocol for extraction based molecular biology techniques such as rt-PCR. The integration of multiple analytical modalities through this universal sample preparation protocol offers the ability to study tissues at a systems biology level and directly linking results to tissue morphology and cellular phenotype.

Background For patients with rheumatoid arthritis (RA), introduction of early, effective therapy has consistently been shown to improve long-term outcomes. Low-dose methotrexate (MTX) is commonly prescribed as first-line treatment for RA. However, MTX is not effective for a large minority of patients and there is currently no way to determine ahead of therapy which patients are most likely to benefit. Metabolomics and lipidomics are emerging approaches for studying patient stratification in RA and have the potential to identify disease processes that underpin treatment outcomes. Here we apply state-of-the-art machine learning algorithms to predict MTX treatment response, by testing serum lipid levels measured at two time-points (pre-treatment and following 4 weeks on drug) to predict MTX response by 6 months. Methods This study included patients from the Rheumatoid Arthritis Medication Study (RAMS), a UK multi-centre one-year prospective observational study investigating predictors of response to MTX in patients with RA. Since 2008, patients who are about to start MTX for the first time are asked to provide demographic and clinical data, as well as blood samples to permit DNA, RNA and serum-based biomarker studies. Patients about to commence MTX treatment were followed longitudinally and those categorised as good or non-responders following 6 months on-drug using EULAR response criteria were analysed. Serum lipid levels were measured at pre-treatment and following 4 weeks on drug using ultra-performance liquid chromatography tailored for complex lipid analysis, coupled to mass spectrometry. State-of-the-art supervised machine learning methods were then applied to predict EULAR response at 6 months. Models including lipid levels were compared to models including clinical covariates (including: MTX start dose, steroid use at inclusion, BMI, number of swollen joints, number of tender joints, CRP levels, patients’ assessment of their overall wellbeing, gender, age-at-inclusion, age-at-onset, disease duration, HAQ score and pre-treatment smoking habits). Results Following quality control, 3,366 features (1,060 in negatively-charged mode and 2,306 in positive mode) were available for analysis at pre-treatment and 4 weeks from 100 RA patients categorised as good (GR, n = 50) or poor (NR, n = 50) responders to MTX following 6 months on drug. The best model performance for the classifier including clinical covariates was observed using L1/L2-regularised logistic regression (ROC AUC 0.68 ± 0.02). However, the clinical covariate model outperformed the classifier including lipid levels when either pre- or on-treatment time-points were investigated (ROC AUC 0.61 ± 0.02). Conclusion These data do not support the utility of early treatment lipidomic monitoring in routine clinical practice in patients started on MTX for their RA. Disclosures M. Maciejewski: Shareholder/stock ownership; owns stock or stock options in Pfizer. C. Sands None. N. Nair None. S. Ling None. S. Verstappen None. K. Hyrich None. A. Barton None. D. Ziemek Shareholder/stock ownership; owns stock or stock options in Pfizer. M. Lewis None. D. Plant None.

DNA-dependent protein kinase (DNA-PK) is a critical player in the DNA damage response (DDR) and instrumental in the non-homologous end-joining pathway (NHEJ) used to detect and repair DNA double-strand breaks (DSBs). We demonstrate that the potent and highly selective DNA-PK inhibitor, AZD7648, is an efficient sensitizer of radiation- and doxorubicin-induced DNA damage, with combinations in xenograft and patient-derived xenograft (PDX) models inducing sustained regressions. Using ATM-deficient cells, we demonstrate that AZD7648, in combination with the PARP inhibitor olaparib, increases genomic instability, resulting in cell growth inhibition and apoptosis. AZD7648 enhanced olaparib efficacy across a range of doses and schedules in xenograft and PDX models, enabling sustained tumour regression and providing a clear rationale for its clinical investigation. Through its differentiated mechanism of action as an NHEJ inhibitor, AZD7648 complements the current armamentarium of DDR-targeted agents and has potential in combination with these agents to achieve deeper responses to current therapies., DNA-dependent protein kinase (DNA-PK) plays a major role in the DNA damage response upon double-strand break formation. Here, the authors show that the DNA-PK inhibitor AZD7648, enhances the activity of radiotherapy, chemotherapy and the PARP inhibitor olaparib in multiple mouse tumour models.

Methotrexate (MTX) is the first-line disease-modifying drug of choice in controlling active inflammation of the synovium that characterises rheumatoid arthritis, a chronic autoimmune inflammatory condition. However, many patients do not respond to treatment with MTX or cannot tolerate the medication. Pre-treatment characteristics that predict response to MTX are, therefore, of particular interest and potential clinical utility. Areas covered: This narrative review seeks to cover various genotypic and phenotypic characteristics that have been investigated as predictors of treatment response to MTX in RA. Ovid Medline searches (1946 to January 2018) were carried out for 'methotrexate' and 'rheumatoid arthritis', in combination with relevant terms. All papers identified were English language, with abstracts. Relevant references were also reviewed. Expert commentary: Despite the introduction of biologic medication and targeted therapies, MTX is likely to remain the mainstay of RA treatment, largely due to its much cheaper cost. Development of a multifactorial predictive algorithm for response to MTX may be of clinical utility, as well as routine MTX drug level testing to improve medication adherence and persistence.

Summary Immune-mediated inflammatory diseases (IMIDs) are characterized by dysregulation of the normal immune response, which leads to inflammation. Together, they account for a high disease burden in the population, given that they are usually chronic conditions with associated co-morbidities. Examples include systemic lupus erythematosus, rheumatoid arthritis, Crohn's disease and type 1 diabetes. Since the advent of genome-wide association studies, evidence of considerable genetic overlap in the loci predisposing to a wide range of IMIDs has emerged. Understanding the genetic risk and extent of genetic overlap between IMIDs may help to determine which genes control which aspects of the different diseases; it may identify potential novel therapeutic targets for a number of these conditions, and/or it may facilitate repurposing existing therapies developed originally for different conditions. The findings show that autoantibody-mediated autoimmune diseases cluster more closely with each other than autoantibody-negative diseases such as psoriasis, psoriatic arthritis, Crohn's disease and ankylosing spondylitis which, instead, form a seronegative genetic cluster. The genetic clustering largely mirrors the known response to existing biological therapies, but apparent anomalies in treatment response are discussed.

Intratumoral adenosine is a key immunosuppressive factor linked to poor prognosis and reduced efficacy of T cell checkpoint inhibitors. CD73 is an ectoenzyme and key node in the catabolic pathway responsible for sequential hydrolysis of extracellular ATP to adenosine. ATP is released from necrotic and damaged tumor cells; a phenomenon enhanced as consequence of cytotoxic chemotherapy or radiotherapy. A CD73 inhibiting human monoclonal IgG1-TM antibody, Oleclumab, is currently in phase 2 clinical development for treatment of patients with various solid tumors. The combination of CD73 inhibition with chemotherapy and T cell checkpoint inhibition was tested using two murine cancer models, CT26 (colorectal) or MCA205 (fibrosarcoma) implanted subcutaneously in BALB/c mice or C57BL/6 mice, respectively. Tumor bearing mice were treated with combinations of oxaliplatin and 5-fluorouracil and murine surrogate monoclonal antibodies for Oleclumab and Durvalumab (anti-PD-L1). CT26 implanted mice were also treated with the murine surrogate antibodies in the presence and absence of Docetaxel. In an attempt to define contribution of components, comparator groups received monotherapies and other iterations of the combination. Treatment with anti-CD73 and anti-PD-L1 antibodies, concomitantly with chemotherapy, resulted in improved tumor growth inhibition, plus increased proportions of complete tumor regression (P Citation Format: Jim Eyles, Amanda Watkins, Kristina Ilieva, Stef Mullins, Jude Anderton, Elena Galvani, Fabien Garcon, Kelli Ryan, Brajesh P. Kaistha, Andreas Dannhorn, Stephanie Ling, Tim Slidel, Gozde Kar, Alwin Schuller, Zachary A. Cooper, Kris Sachsenmeier, Nadia Luheshi, Rakesh Kumar, Robert W. Wilkinson. Efficacy and pharmacodynamic effect of anti-CD73/PD-L1 monoclonal antibodies in combination with chemotherapy: Observations from mouse tumor models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1584.

Background Sex hormones play important roles in teleost ovarian and testicular development. In zebrafish, ovarian differentiation appears to be dictated by an oocyte-derived signal via Cyp19a1a aromatase-mediated estrogen production. Androgens and aromatase inhibitors can induce female-to-male sex reversal, however, the mechanisms underlying gonadal masculinisation are poorly understood. We used histological analyses together with RNA sequencing to characterise zebrafish gonadal transcriptomes and investigate the effects of 17α-methyltestosterone on gonadal differentiation. Results At a morphological level, 17α-methyltestosterone (MT) masculinised gonads and accelerated spermatogenesis, and these changes were paralleled in masculinisation and de-feminisation of gonadal transcriptomes. MT treatment upregulated expression of genes involved in male sex determination and differentiation (amh, dmrt1, gsdf and wt1a) and those involved in 11-oxygenated androgen production (cyp11c1 and hsd11b2). It also repressed expression of ovarian development and folliculogenesis genes (bmp15, gdf9, figla, zp2.1 and zp3b). Furthermore, MT treatment altered epigenetic modification of histones in zebrafish gonads. Contrary to expectations, higher levels of cyp19a1a or foxl2 expression in control ovaries compared to MT-treated testes and control testes were not statistically significant during early gonad development (40 dpf). Conclusion Our study suggests that both androgen production and aromatase inhibition are important for androgen-induced gonadal masculinisation and natural testicular differentiation in zebrafish. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3915-z) contains supplementary material, which is available to authorized users.

Background RA patients who are ACPA-positive (ACPA+) are known to have worse prognosis. Less is known regarding predictors of treatment outcomes in ACPA-negative (ACPA-) patients. Objectives We investigated whether autoantibodies captured on a custom array were associated with response to therapy in ACPA- RA patients. Methods RA patients were recruited to either the Biologics in RA Genetics and Genomics Study Syndicate (BRAGGSS, starting adalimumab, established disease) or the RA Medication Study (RAMS, starting methotrexate, early disease). Serum samples were collected at pre-treatment and 3/6 months in BRAGGSS/RAMS, respectively. Treatment groups were pooled for analysis. ACPA was measured using a commercially available ELISA (Axis-Shield Diagnostics Ltd, Dundee, UK). Pre-treatment RA and healthy blood donor control (HC) serum samples were incubated on a bead-based assay (Luminex FlexMap 3D) containing 376 human protein antigens associated with autoimmune disease (39 in citrullinated (cit) form) to detect autoantibodies. Median fluorescence intensity (MFI) values were calculated for each autoantibody for RA and HC, then normalised and log2-transformed. The 95th percentile for each autoantibody in HC was used to determine whether an RA sample was positive/negative for that autoantibody. Proteins with Results 168 patients with RA were included in analysis (mean age 59.6 years, mean disease duration 14.3 years, 126 (75%) female patients, 90 (53.6%) ACPA+ patients). 34 autoantibodies were differentially expressed in RA patients, only one of which (TNF ligand superfamily member 13, TNFSF13) was lower than in HC. 29/34 autoantigens were in cit-form. In multivariate models of all differentially expressed autoantibodies, heterogeneous nuclear ribonucleoprotein A1 (HNRNPA1) was significantly associated with EULAR response (coefficient (coef) 0.7, 95% CI 0.1-1.3), and cit-vimentin (VIM) was significantly associated with poor EULAR response (ORadj 4.2, 95% CI 1.1-18.3) and reduced odds of good EULAR response (ORadj 0.2, 95% CI 0.1-0.8). ACPA remained the best predictor of treatment response. In a subanalysis of the 78 ACPA-patients, cit-cleavage and polyadenylation specificity factor subunit 6 (CPSF6) was significantly associated with worse DAS28 (coef (-1.8), 95% CI (-3.6)-(-0.1)). cit-DnaJ homolog subfamily B member 1 (DNAJB1) was significantly associated with DAS28 improvement (coef 2.2, 95% CI 0.6-3.8). No autoantibody was associated with EULAR response. Conclusion A subset of ACPA-patients have ACPA fine specificities not seen by a commercial assay. Larger ACPA profiling may provide additional information on treatment response. This requires validation with larger sample sizes and replication in an independent cohort. Reference [1] Ann Rheum Dis2013;72:844. 2. Arthritis Res Ther2016;18:235. Disclosure of Interests Stephanie Ling: None declared, Nisha Nair: None declared, Darren Plant: None declared, Hans-Dieter Zucht Employee of: Hans-Dieter Zucht is an employee of Protagen AG, Petra Budde Employee of: Petra Budde is an employee of Protagen AG, Peter Schulz-Knappe Shareholder of: Peter Schulz-Knappe is a shareholder of Protagen AG, Consultant for: Peter Schulz-Knappe is a consultant to Protagen AG, Employee of: Peter Schulz-Knappe was an employee of Protagen AG, MATURA Consortium: None declared, Anne Barton: None declared