Anti-tumour effects of a specific anti-ADAM17 antibody in an ovarian cancer model in vivo.

ADAM 17 (TNF-α converting enzyme, TACE) is a potential target for cancer therapy, but the small molecule inhibitors reported to date are not specific to this ADAM family member. This membrane-bound metalloproteinase is responsible for ectodomain shedding of pathologically significant substrates including TNF-α and EGFR ligands. The aim of this study was to evaluate the pharmacokinetics, pharmacodynamics and anti-tumour efficacy of the first specific inhibitor, an anti-human ADAM17 IgG antibody, clone D1(A12). We used intraperitoneal xenografts of the human ovarian cancer cell line IGROV1-Luc in Balb/c nude mice, chosen because it was previously reported that growth of these xenografts is inhibited by knock-down of TNF-α. In vitro, 200 nM D1(A12) inhibited shedding of ADAM17 substrates TNF-α, TNFR1-α, TGF-α, amphiregulin (AREG), HB-EGF and IL-6Rα, from IGROV1-Luc cells, (4.7 nM IC(50) for TNF-α shedding). In IGROV1-Luc xenografts in vivo, D1(A12) IgG showed pharmacokinetic properties suitable for efficacy studies, with a single i.p. dose of 10 mg/kg D1(A12) sufficient to maintain IgG plasma and ascites fluid concentrations above 100 nM for more than 7 days. The plasma half life was 8.6 days. Next, an efficacy study was performed, dosing D1(A12) or anti-human TNF-α antibody infliximab at 10 mg/kg q7d, quantifying IGROV1-Luc tumour burden by bioluminescence. D1(A12) IgG showed a significant reduction in tumour growth (p = 0.005), 56% of vehicle control. Surprisingly, D1(A12) did not reduce the concentration of circulating human TNF-α, suggesting that another enzyme may compensate for inhibition of ADAM17 in vivo (but not in vitro). However, D1(A12) did show clear pharmacodynamic effects in the mice, with significant inhibition of shedding from tumour of ADAM17 substrates TNFR1-α, AREG, and TGF-α (4-15-fold reductions, p<0.0001 for all three). Thus, D1(A12) has anti-ADAM17 activity in vivo, inhibits shedding of EGFR ligands and has potential for use in EGF ligand-dependent tumours

Directed Scattering for Knowledge Graph-based Cellular Signaling Analysis

Directed graphs are a natural model for many phenomena, in particular scientific knowledge graphs such as molecular interaction or chemical reaction networks that define cellular signaling relationships. In these situations, source nodes typically have distinct biophysical properties from sinks. Due to their ordered and unidirectional relationships, many such networks also have hierarchical and multiscale structure. However, the majority of methods performing node- and edge-level tasks in machine learning do not take these properties into account, and thus have not been leveraged effectively for scientific tasks such as cellular signaling network inference. We propose a new framework called Directed Scattering Autoencoder (DSAE) which uses a directed version of a geometric scattering transform, combined with the non-linear dimensionality reduction properties of an autoencoder and the geometric properties of the hyperbolic space to learn latent hierarchies. We show this method outperforms numerous others on tasks such as embedding directed graphs and learning cellular signaling networks.Comment: 5 pages, 3 figure

SIGNAL-seq:Multimodal Single-cell Inter- and Intra-cellular Signalling Analysis

We present SIGNAL-seq (Split-pool Indexing siG-Nalling AnaLysis by sequencing): a multiplexed splitpool combinatorial barcoding method that simultaneously measures RNA and post-translational modifications (PTMs) in fixed single cells from 3D models. SIGNAL-seq PTM measurements are equivalent to mass cytometry and RNA gene detection is analogous to split-pool barcoding scRNA-seq. By measuring both mRNA ligand-receptor pairs and PTMs in single cells, SIGNAL-seq can simultaneously uncover inter- and intra-cellular regulation of tumour microenvironment plasticity

Proteomics profiling of interactome dynamics by colocalisation analysis (COLA)

Localisation and protein function are intimately linked in eukaryotes, as proteins are localised to specific compartments where they come into proximity of other functionally relevant proteins. Significant co-localisation of two proteins can therefore be indicative of their functional association. We here present COLA, a proteomics based strategy coupled with a bioinformatics framework to detect protein–protein co-localisations on a global scale. COLA reveals functional interactions by matching proteins with significant similarity in their subcellular localisation signatures. The rapid nature of COLA allows mapping of interactome dynamics across different conditions or treatments with high precision.Cancer Research UK; BBSRC

The Autism - Tics, AD/HD and other Comorbidities inventory (A-TAC): further validation of a telephone interview for epidemiological research

<p>Abstract</p> <p>Background</p> <p>Reliable, valid, and easy-to-administer instruments to identify possible caseness and to provide proxies for clinical diagnoses are needed in epidemiological research on child and adolescent mental health.</p> <p>The aim of this study is to provide further validity data for a parent telephone interview focused on Autism - Tics, Attention-deficit/hyperactivity disorder (AD/HD), and other Comorbidities (A-TAC), for which reliability and preliminary validation data have been previously reported.</p> <p>Methods</p> <p>Parents of 91 children clinically diagnosed at a specialized Child Neuropsychiatric Clinic, 366 control children and 319 children for whom clinical diagnoses had been previously assigned were interviewed by the A-TAC over the phone. Interviewers were blind to clinical information. Different scores from the A-TAC were compared to the diagnostic outcome.</p> <p>Results</p> <p>Areas under ROC curves for interview scores as predictors of clinical diagnoses were around 0.95 for most disorders, including autism spectrum disorders (ASDs), attention deficit/hyperactivity disorder (AD/HD), tic disorders, developmental coordination disorders (DCD) and learning disorders, indicating excellent screening properties. Screening cut-off scores with sensitivities above 0.90 (0.95 for ASD and AD/HD) were established for most conditions, as well as cut-off scores to identify proxies to clinical diagnoses with specificities above 0.90 (0.95 for ASD and AD/HD).</p> <p>Conclusions</p> <p>The previously reported validity of the A-TAC was supported by this larger replication study using broader scales from the A-TAC-items and a larger number of diagnostic categories. Short versions of algorithms worked as well as larger. Different cut-off levels for screening versus identifying proxies for clinical diagnoses are warranted. Data on the validity for mood problems and oppositional defiant/conduct problems are still lacking. Although the A-TAC is principally intended for epidemiological research and general investigations, the instrument may be useful as a tool to collect information in clinical practice as well.</p

Pan-cancer deconvolution of tumour composition using DNA methylation

The nature and extent of immune cell infiltration into solid tumours are key determinants of therapeutic response. Here, using a DNA methylation-based approach to tumour cell fraction deconvolution, we report the integrated analysis of tumour composition and genomics across a wide spectrum of solid cancers. Initially studying head and neck squamous cell carcinoma, we identify two distinct tumour subgroups: ‘immune hot’ and ‘immune cold’, which display differing prognosis, mutation burden, cytokine signalling, cytolytic activity and oncogenic driver events. We demonstrate the existence of such tumour subgroups pan-cancer, link clonal-neoantigen burden to cytotoxic T-lymphocyte infiltration, and show that transcriptional signatures of hot tumours are selectively engaged in immunotherapy responders. We also find that treatment-naive hot tumours are markedly enriched for known immune-resistance genomic alterations, potentially explaining the heterogeneity of immunotherapy response and prognosis seen within this group. Finally, we define a catalogue of mediators of active antitumour immunity, deriving candidate biomarkers and potential targets for precision immunotherapy

Cell-specific labeling enzymes for analysis of cell-cell communication in continuous co-culture.

We report the orthologous screening, engineering, and optimization of amino acid conversion enzymes for cell-specific proteomic labeling. Intracellular endoplasmic-reticulum-anchored Mycobacterium tuberculosis diaminopimelate decarboxylase (DDC(M.tub)(-KDEL)) confers cell-specific meso-2,6-diaminopimelate-dependent proliferation to multiple eukaryotic cell types. Optimized lysine racemase (Lyr(M37-KDEL)) supports D-lysine specific proliferation and efficient cell-specific isotopic labeling. When ectopically expressed in discrete cell types, these enzymes confer 90% cell-specific isotopic labeling efficiency after 10 days of co-culture. Moreover, DDC(M.tub)(-KDEL) and Lyr(M37-KDEL) facilitate equally high cell-specific labeling fidelity without daily media exchange. Consequently, the reported novel enzyme pairing can be used to study cell-specific signaling in uninterrupted, continuous co-cultures. Demonstrating the importance of increased labeling stability for addressing novel biological questions, we compare the cell-specific phosphoproteome of fibroblasts in direct co-culture with epithelial tumor cells in both interrupted (daily media exchange) and continuous (no media exchange) co-cultures. This analysis identified multiple cell-specific phosphorylation sites specifically regulated in the continuous co-culture. Given their applicability to multiple cell types, continuous co-culture labeling fidelity, and suitability for long-term cell–cell phospho-signaling experiments, we propose DDC(M.tub)(-KDEL) and Lyr(M37-KDEL) as excellent enzymes for cell-specific labeling with amino acid precursors

Inhibition of shedding of ADAM17 substrates by D1(A12) and infiximab.

<p>Concentrations of the cleaved products of ADAM17 substrates in plasma and ascites fluid at the endpoint (day 33), as measured by ELISA. Horizontal bars represent the mean and standard deviation. Asterisks show the groups significantly different (P<0.05) from the PBS control group in the same fluid type.</p

Distribution of D1(A12) and infliximab IgG <i>in vivo</i> at the end of the efficacy study.

<p>Samples were taken at endpoint (day 33), 20 hours after the final antibody dose. (A) Concentrations in plasma and ascites fluid. Horizontal bars represent the mean and standard deviation. (B) Concentrations in homogenates of tissue from tumour in pancreas and omentum. (C) Immunohistochemistry to detect human IgG in IGROV1-Luc tumour and liver. Top: mouse ID 901, treated with D1(A12), with an arrow marking the position of a blood vessel; middle: mouse ID 903, treated with infliximab; bottom: mouse ID 902, treated with vehicle. Images were taken at 20X magnification.</p