Energy Metabolism, Metabolite, and Inflammatory Profiles in Human Ex Vivo Adipose Tissue Are Influenced by Obesity Status, Metabolic Dysfunction, and Treatment Regimes in Patients with Oesophageal Adenocarcinoma

Oesophageal adenocarcinoma (OAC) is a poor prognosis cancer with limited response rates to current treatment modalities and has a strong link to obesity. To better elucidate the role of visceral adiposity in this disease state, a full metabolic profile combined with analysis of secreted pro-inflammatory cytokines, metabolites, and lipid profiles were assessed in human ex vivo adipose tissue explants from obese and non-obese OAC patients. These data were then related to extensive clinical data including obesity status, metabolic dysfunction, previous treatment exposure, and tumour regression grades. Real-time energy metabolism profiles were assessed using the seahorse technology. Adipose explant conditioned media was screened using multiplex ELISA to assess secreted levels of 54 pro-inflammatory mediators. Targeted secreted metabolite and lipid profiles were analysed using Ultra-High-Performance Liquid Chromatography coupled with Mass Spectrometry. Adipose tissue explants and matched clinical data were collected from OAC patients (n = 32). Compared to visceral fat from non-obese patients (n = 16), visceral fat explants from obese OAC patients (n = 16) had significantly elevated oxidative phosphorylation metabolism profiles and an increase in Eotaxin-3, IL-17A, IL-17D, IL-3, MCP-1, and MDC and altered secretions of glutamine associated metabolites. Adipose explants from patients with metabolic dysfunction correlated with increased oxidative phosphorylation metabolism, and increases in IL-5, IL-7, SAA, VEGF-C, triacylglycerides, and metabolites compared with metabolically healthy patients. Adipose explants generated from patients who had previously received neo-adjuvant chemotherapy (n = 14) showed elevated secretions of pro-inflammatory mediators, IL-12p40, IL-1α, IL-22, and TNF-β and a decreased expression of triacylglycerides. Furthermore, decreased secreted levels of triacylglycerides were also observed in the adipose secretome of patients who received the chemotherapy-only regimen FLOT compared with patients who received no neo-adjuvant treatment or chemo-radiotherapy regimen CROSS. For those patients who showed the poorest response to currently available treatments, their adipose tissue was associated with higher glycolytic metabolism compared to patients who had good treatment responses. This study demonstrates that the adipose secretome in OAC patients is enriched with mediators that could prime the tumour microenvironment to aid tumour progression and attenuate responses to conventional cancer treatments, an effect which appears to be augmented by obesity and metabolic dysfunction and exposure to different treatment regimes

Facile discovery of surrogate cytokine agonists

Cytokines are powerful immune modulators that initiate signaling through receptor dimerization, but natural cytokines have structural limitations as therapeutics. We present a strategy to discover cytokine surrogate agonists by using modular ligands that exploit induced proximity and receptor dimer geometry as pharmacological metrics amenable to high-throughput screening. Using VHH and scFv to human interleukin-2/15, type-I interferon, and interleukin-10 receptors, we generated combinatorial matrices of single-chain bispecific ligands that exhibited diverse spectrums of functional activities, including potent inhibition of SARS-CoV-2 by surrogate interferons. Crystal structures of IL-2R:VHH complexes revealed that variation in receptor dimer geometries resulted in functionally diverse signaling outputs. This modular platform enabled engineering of surrogate ligands that compelled assembly of an IL-2R/IL-10R heterodimer, which does not naturally exist, that signaled through pSTAT5 on T and natural killer (NK) cells. This “cytokine med-chem” approach, rooted in principles of induced proximity, is generalizable for discovery of diversified agonists for many ligand-receptor systems

Hypergraph models of biological networks to identify genes critical to pathogenic viral response

Background: Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems. Hypergraphs are generalizations of graphs that naturally model multi-way relationships and have shown promise in modeling systems such as protein complexes and metabolic reactions. In this paper we seek to understand how hypergraphs can more faithfully identify, and potentially predict, important genes based on complex relationships inferred from genomic expression data sets. Results: We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges represent significantly perturbed genes, and vertices represent individual biological samples with specific experimental conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality. Conclusions: Our results demonstrate the utility of using hypergraphs to represent complex biological systems and highlight central important responses in common to a variety of highly pathogenic viruses

A review of inferior vena cava filters

The care of patients with venous thromboembolism (VTE) is delivered via a multidisciplinary team. The primary treatment for VTE is anticoagulation; however, placement of filter devices in the inferior vena cava (IVC) to prevent embolisation of deep venous thrombosis (DVT) is a well-established secondary treatment option. Many controversies remain regarding utilisation and management of filters. </p

Multi-Modal Imaging with a Toolbox of Influenza AReporter Viruses

Reporter viruses are useful probes for studying multiple stages of the viral life cycle. Here we describe an expanded toolbox of fluorescent and bioluminescent influenza A reporter viruses. The enhanced utility of these tools enabled kinetic studies of viral attachment, infection, and co-infection. Multi-modal bioluminescence and positron emission tomography–computed tomography (PET/CT) imaging of infected animals revealed that antiviral treatment reduced viral load, dissemination, and inflammation. These new technologies and applications will dramatically accelerate in vitro and in vivo influenza virus studies