Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes

Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction1. There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity1,2. Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments.

Maximizing statistical power to detect differentially abundant cell states with scPOST

To estimate a study design's power to detect differential abundance, we require a framework that simulates many multi-sample single-cell datasets. However, current simulation methods are challenging for large-scale power analyses because they are computationally resource intensive and do not support easy simulation of multi-sample datasets. Current methods also lack modeling of important inter-sample variation, such as the variation in the frequency of cell states between samples that is observed in single-cell data. Thus, we developed single-cell POwer Simulation Tool (scPOST) to address these limitations and help investigators quickly simulate multi-sample single-cell datasets. Users may explore a range of effect sizes and study design choices (such as increasing the number of samples or cells per sample) to determine their effect on power, and thus choose the optimal study design for their planned experiments.

Efficient and precise single-cell reference atlas mapping with Symphony

Recent advances in single-cell technologies and integration algorithms make it possible to construct comprehensive reference atlases encompassing many donors, studies, disease states, and sequencing platforms. Much like mapping sequencing reads to a reference genome, it is essential to be able to map query cells onto complex, multimillion-cell reference atlases to rapidly identify relevant cell states and phenotypes. We present Symphony ( https://github.com/immunogenomics/symphony ), an algorithm for building large-scale, integrated reference atlases in a convenient, portable format that enables efficient query mapping within seconds. Symphony localizes query cells within a stable low-dimensional reference embedding, facilitating reproducible downstream transfer of reference-defined annotations to the query. We demonstrate the power of Symphony in multiple real-world datasets, including (1) mapping a multi-donor, multi-species query to predict pancreatic cell types, (2) localizing query cells along a developmental trajectory of fetal liver hematopoiesis, and (3) inferring surface protein expression with a multimodal CITE-seq atlas of memory T cells.

Fast, sensitive and accurate integration of single-cell data with Harmony

The emerging diversity of single-cell RNA-seq datasets allows for the full transcriptional characterization of cell types across a wide variety of biological and clinical conditions. However, it is challenging to analyze them together, particularly when datasets are assayed with different technologies, because biological and technical differences are interspersed. We present Harmony (https://github.com/immunogenomics/harmony), an algorithm that projects cells into a shared embedding in which cells group by cell type rather than dataset-specific conditions. Harmony simultaneously accounts for multiple experimental and biological factors. In six analyses, we demonstrate the superior performance of Harmony to previously published algorithms while requiring fewer computational resources. Harmony enables the integration of ~106 cells on a personal computer. We apply Harmony to peripheral blood mononuclear cells from datasets with large experimental differences, five studies of pancreatic islet cells, mouse embryogenesis datasets and the integration of scRNA-seq with spatial transcriptomics data.

Abstract 4910: Development of an antagonist to the TWEAK-Fn14 ligand-receptor interaction with enhanced efficacy/potency in glioblastoma cells

Glioblastoma multiforme (GBM) remains the most common and deadly primary brain tumor with minimal advances in therapeutic development for pharmacological treatment. Tumor resection followed by temozolomide (TMZ) and radiotherapy adds months to survival; however, tumor recurrence usually occurs. The fibroblast growth factor-inducible 14 (Fn14) receptor has been shown to be up-regulated in the GBM cells left behind after surgery and contributes to an invasive and pro-survival phenotype, providing a desirable molecule to target after removal of the primary tumor. Previously, L524-0366 was reported by our lab to be the first antagonist of Fn14 signaling; however, minimal efficacy/potency has limited this drug from progressing from a useful research tool to preclinical studies. Structure activity relationship (SAR) studies using the parent L524-0366 compound gave rise to K78, which was found to bind to Fn14 with enhanced affinity, while showing no binding to the structurally-related TNFα receptor. Furthermore, K78 was able to abate the downstream signaling effects initiated by the Fn14 ligand, tumor necrosis factor-like weak inducer of apoptosis (TWEAK), as well as sensitize GBM cells to the cytotoxic effects of TMZ. TWEAK-induced cellular migration was also mitigated with co-treatment of K78 in GBM cells, compared to a vehicle control. It is anticipated that further development of Fn14 antagonists will be of great importance for the advancement of GBM patient treatment and warrant further investigation as primary and combination therapy, especially for the prevention of recurrent disease.

Citation Format: Bryan Harder, Chris Sereduk, Harshil Dhruv, Nghia Millard, Anthony Kim, Jeffrey Winkles, Graeme Woodworth, Holly Yin, Nhan L. Tran. Development of an antagonist to the TWEAK-Fn14 ligand-receptor interaction with enhanced efficacy/potency in glioblastoma cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4910.

Abstract 3462: EGFRvIII-Stat5 signaling enhances glioblastoma cell invasion

Glioblastoma Multiforme (GBM) is the most common malignant brain tumor in adults. Most GBM patients succumb to the disease less than one-year post diagnosis due to the highly invasive nature of the tumor, which prevents complete surgical resection and gives rise to tumor recurrence. The invasive phenotype also confers radio and chemoresistant properties to the tumor cells; therefore, there is a need to develop new therapeutics that target drivers of GBM invasion. Amplification of EGFR is observed in over 50% of GBM tumors, of which half concurrently overexpress the variant EGFRvIII, and expression of both receptors confers a worse prognosis. EGFR and EGFRvIII cooperate to promote tumor progression and invasion, in part, through activation of the Stat-signaling pathway. Here we report that EGFRvIII activates Stat5 and GBM invasion, in part, by inducing the expression of a previously established mediator of glioma cell invasion and survival, fibroblast growth factor-inducible 14 (Fn14). EGFRvIII-mediated induction of Fn14 expression is dependent upon Stat5 and requires activation of Src, whereas EGFR regulation of Fn14 is dependent upon MEK/ERK-Stat3 activation. Notably, treatment of EGFRvIII expressing GBM cells with the FDA approved Stat5 inhibitor pimozide blocked Stat5 phosphorylation, Fn14 expression, and cell migration. Since EGFR inhibitors display limited therapeutic efficacy in GBM patients, we hypothesize that the EGFRvIII-Stat5-Fn14 signaling pathway represents a node of vulnerability in the invasive GB cell population and that targeting critical effectors in this pathway will limit GBM tumor dispersion, mitigate therapeutic resistance, and increase survival.

Citation Format: Alison Roos, Harshil D. Dhruv, Sen Peng, Landon J. Inge, Serdar Tuncali, Michael Pineda, Nghia Millard, Jeffrey A. Winkles, Joseph C. Loftus, Nhan L. Tran. EGFRvIII-Stat5 signaling enhances glioblastoma cell invasion [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3462.

EGFRvIII-Stat5 Signaling Enhances Glioblastoma Cell Migration and Survival

Glioblastoma multiforme (GBM) is the most common brain malignancies in adults. Most GBM patients succumb to the disease less than 1 year after diagnosis due to the highly invasive nature of the tumor, which prevents complete surgical resection and gives rise to tumor recurrence. The invasive phenotype also confers radioresistant and chemoresistant properties to the tumor cells; therefore, there is a critical need to develop new therapeutics that target drivers of GBM invasion. Amplification of EGFR is observed in over 50% of GBM tumors, of which half concurrently overexpress the variant EGFRvIII, and expression of both receptors confers a worse prognosis. EGFR and EGFRvIII cooperate to promote tumor progression and invasion, in part, through activation of the Stat signaling pathway. Here, it is reported that EGFRvIII activates Stat5 and GBM invasion by inducing the expression of a previously established mediator of glioma cell invasion and survival: fibroblast growth factor-inducible 14 (Fn14). EGFRvIII-mediated induction of Fn14 expression is Stat5 dependent and requires activation of Src, whereas EGFR regulation of Fn14 is dependent upon Src-MEK/ERK-Stat3 activation. Notably, treatment of EGFRvIII-expressing GBM cells with the FDA-approved Stat5 inhibitor pimozide blocked Stat5 phosphorylation, Fn14 expression, and cell migration and survival. Because EGFR inhibitors display limited therapeutic efficacy in GBM patients, the EGFRvIII-Stat5-Fn14 signaling pathway represents a node of vulnerability in the invasive GBM cell populations.Implications: Targeting critical effectors in the EGFRvIII-Stat5-Fn14 pathway may limit GBM tumor dispersion, mitigate therapeutic resistance, and increase survival. Mol Cancer Res; 16(7); 1185-95. ©2018 AACR.

Identification of aurintricarboxylic acid as a selective inhibitor of the TWEAK-Fn14 signaling pathway in glioblastoma cells

The survival of patients diagnosed with glioblastoma (GBM), the most deadly form of brain cancer, is compromised by the proclivity for local invasion into the surrounding normal brain, which prevents complete surgical resection and contributes to therapeutic resistance. Tumor necrosis factor-like weak inducer of apoptosis (TWEAK), a member of the tumor necrosis factor (TNF) superfamily, can stimulate glioma cell invasion and survival via binding to fibroblast growth factor-inducible 14 (Fn14) and subsequent activation of the transcription factor NF-κB. To discover small molecule inhibitors that disrupt the TWEAK-Fn14 signaling axis, we utilized a cell-based drug-screening assay using HEK293 cells engineered to express both Fn14 and a NF-κB-driven firefly luciferase reporter protein. Focusing on the LOPAC1280 library of 1280 pharmacologically active compounds, we identified aurintricarboxylic acid (ATA) as an agent that suppressed TWEAK-Fn14-NF-κB dependent signaling, but not TNFα-TNFR-NF-κB driven signaling. We demonstrated that ATA repressed TWEAK-induced glioma cell chemotactic migration and invasion via inhibition of Rac1 activation but had no effect on cell viability or Fn14 expression. In addition, ATA treatment enhanced glioma cell sensitivity to both the chemotherapeutic agent temozolomide (TMZ) and radiation-induced cell death. In summary, this work reports a repurposed use of a small molecule inhibitor that targets the TWEAK-Fn14 signaling axis, which could potentially be developed as a new therapeutic agent for treatment of GBM patients.

TRADITIONAL CANISTER-BASED OPEN WASTE MANAGEMENT SYSTEM VERSUS CLOSED SYSTEM: HAZARDOUS EXPOSURE PREVENTION AND OPERATING THEATRE STAFF SATISFACTION

INTRODUCTION

Exposure to blood and body fluids is a major concern to health care professionals working in operating rooms (ORs). Thus, it is essential that hospitals use fluid waste management systems that minimise risk to staff, while maximising efficiency.

METHOD

The current study compared the utility of a 'closed' system with a traditional canister-based 'open' system in the OR in a private hospital setting.

RESULTS

A total of 30 arthroscopy, urology, and orthopaedic cases were observed. The closed system was used in five, four, and six cases, respectively and the open system was used in nine, two, and four cases, respectively. The average number of opportunities for staff to be exposed to hazardous fluids were fewer for the closed system when compared to the open during arthroscopy and urology procedures. The open system required nearly 3.5 times as much staff time for set-up, maintenance during procedures, and post-procedure disposal of waste. Theatre staff expressed greater satisfaction with the closed system than with the open.

CONCLUSION

In conclusion, compared with the open system, the closed system offers a less hazardous and more efficient method of disposing of fluid waste generated in the OR.

Spatially complex distribution of dissolved manganese in a fjord as revealed by high-resolution in situ sensing using the autonomous underwater vehicle Autosub

Loch Etive is a fjordic system on the west coast of Scotland. The deep waters of the upper basin are periodically isolated, and during these periods oxygen is lost through benthic respiration and concentrations of dissolved manganese increase. In April 2000 the autonomous underwater vehicle (AUV) Autosub was fitted with an in situ dissolved manganese analyzer and was used to study the spatial variability of this element together with oxygen, salinity, and temperature throughout the basin. Six along-loch transects were completed at either constant height above the seafloor or at constant depth below the surface. The ca. 4000 in situ 10-s-average dissolved Mn (Mnd) data points obtained provide a new quasi-synoptic and highly detailed view of the distribution of manganese in this fjordic environment not possible using conventional (water bottle) sampling. There is substantial variability in concentrations (<25 to >600 nM) and distributions of Mnd. Surface waters are characteristically low in Mnd reflecting mixing of riverine and marine end-member waters, both of which are low in Mnd. The deeper waters are enriched in Mnd, and as the water column always contains some oxygen, this must reflect primarily benthic inputs of reduced dissolved Mn. However, this enrichment of Mnd is spatially very variable, presumably as a result of variability in release of Mn coupled with mixing of water in the loch and removal processes. This work demonstrates how AUVs coupled with chemical sensors can reveal substantial small-scale variability of distributions of chemical species in coastal environments that would not be resolved by conventional sampling approaches. Such information is essential if we are to improve our understanding of the nature and significance of the underlying processes leading to this variability.