The biased apelin receptor agonist, MM07, reverses Sugen/hypoxia-induced pulmonary arterial hypertension as effectively as the endothelin antagonist macitentan.

Introduction: Pulmonary arterial hypertension (PAH) is characterised by endothelial dysfunction and pathological vascular remodelling, resulting in the occlusion of pulmonary arteries and arterioles, right ventricular hypertrophy, and eventually fatal heart failure. Targeting the apelin receptor with the novel, G protein-biased peptide agonist, MM07, is hypothesised to reverse the developed symptoms of elevated right ventricular systolic pressure and right ventricular hypertrophy. Here, the effects of MM07 were compared with the clinical standard-of-care endothelin receptor antagonist macitentan. Methods: Male Sprague-Dawley rats were randomised and treated with either normoxia/saline, or Sugen/hypoxia (SuHx) to induce an established model of PAH, before subsequent treatment with either saline, macitentan (30 mg/kg), or MM07 (10 mg/kg). Rats were then anaesthetised and catheterised for haemodynamic measurements, and tissues collected for histopathological assessment. Results: The SuHx/saline group presented with significant increases in right ventricular hypertrophy, right ventricular systolic pressure, and muscularization of pulmonary arteries compared to normoxic/saline controls. Critically, MM07 was as at least as effective as macitentan in significantly reversing detrimental structural and haemodynamic changes after 4 weeks of treatment. Discussion: These results support the development of G protein-biased apelin receptor agonists with improved pharmacokinetic profiles for use in human disease.

Regulation of blood-brain barrier integrity by microbiome-associated methylamines and cognition by trimethylamine N-oxide.

BACKGROUND: Communication between the gut microbiota and the brain is primarily mediated via soluble microbe-derived metabolites, but the details of this pathway remain poorly defined. Methylamines produced by microbial metabolism of dietary choline and L-carnitine have received attention due to their proposed association with vascular disease, but their effects upon the cerebrovascular circulation have hitherto not been studied. RESULTS: Here, we use an integrated in vitro/in vivo approach to show that physiologically relevant concentrations of the dietary methylamine trimethylamine N-oxide (TMAO) enhanced blood-brain barrier (BBB) integrity and protected it from inflammatory insult, acting through the tight junction regulator annexin A1. In contrast, the TMAO precursor trimethylamine (TMA) impaired BBB function and disrupted tight junction integrity. Moreover, we show that long-term exposure to TMAO protects murine cognitive function from inflammatory challenge, acting to limit astrocyte and microglial reactivity in a brain region-specific manner. CONCLUSION: Our findings demonstrate the mechanisms through which microbiome-associated methylamines directly interact with the mammalian BBB, with consequences for cerebrovascular and cognitive function. Video abstract.

G392E neuroserpin causing the dementia FENIB is secreted from cells but is not synaptotoxic.

Familial encephalopathy with neuroserpin inclusion bodies (FENIB) is a progressive neurodegenerative disease caused by point mutations in the gene for neuroserpin, a serine protease inhibitor of the nervous system. Different mutations are known that are responsible for mutant neuroserpin polymerization and accumulation as inclusion bodies in many cortical and subcortical neurons, thereby leading to cell death, dementia and epilepsy. Many efforts have been undertaken to elucidate the molecular pathways responsible for neuronal death. Most investigations have concentrated on analysis of intracellular mechanisms such as endoplasmic reticulum (ER) stress, ER-associated protein degradation (ERAD) and oxidative stress. We have generated a HEK-293 cell model of FENIB by overexpressing G392E-mutant neuroserpin and in this study we examine trafficking and toxicity of this polymerogenic variant. We observed that a small fraction of mutant neuroserpin is secreted via the ER-to-Golgi pathway, and that this release can be pharmacologically regulated. Overexpression of the mutant form of neuroserpin did not stimulate cell death in the HEK-293 cell model. Finally, when treating primary hippocampal neurons with G392E neuroserpin polymers, we did not detect cytotoxicity or synaptotoxicity. Altogether, we report here that a polymerogenic mutant form of neuroserpin is secreted from cells but is not toxic in the extracellular milieu.

Extraction and Integration of Genetic Networks from Short-Profile Omic Data Sets.

Mass spectrometry technologies are widely used in the fields of ionomics and metabolomics to simultaneously profile the intracellular concentrations of, e.g., amino acids or elements in genome-wide mutant libraries. These molecular or sub-molecular features are generally non-Gaussian and their covariance reveals patterns of correlations that reflect the system nature of the cell biochemistry and biology. Here, we introduce two similarity measures, the Mahalanobis cosine and the hybrid Mahalanobis cosine, that enforce information from the empirical covariance matrix of omics data from high-throughput screening and that can be used to quantify similarities between the profiled features of different mutants. We evaluate the performance of these similarity measures in the task of inferring and integrating genetic networks from short-profile ionomics/metabolomics data through an analysis of experimental data sets related to the ionome and the metabolome of the model organism S. cerevisiae. The study of the resulting ionome-metabolome Saccharomyces cerevisiae multilayer genetic network, which encodes multiple omic-specific levels of correlations between genes, shows that the proposed measures can provide an alternative description of relations between biological processes when compared to the commonly used Pearson's correlation coefficient and have the potential to guide the construction of novel hypotheses on the function of uncharacterised genes.

Consequences of Lipid Remodeling of Adipocyte Membranes Being Functionally Distinct from Lipid Storage in Obesity.

Obesity is a complex disorder where the genome interacts with diet and environmental factors to ultimately influence body mass, composition, and shape. Numerous studies have investigated how bulk lipid metabolism of adipose tissue changes with obesity and, in particular, how the composition of triglycerides (TGs) changes with increased adipocyte expansion. However, reflecting the analytical challenge posed by examining non-TG lipids in extracts dominated by TGs, the glycerophospholipid composition of cell membranes has been seldom investigated. Phospholipids (PLs) contribute to a variety of cellular processes including maintaining organelle functionality, providing an optimized environment for membrane-associated proteins, and acting as pools for metabolites (e.g. choline for one-carbon metabolism and for methylation of DNA). We have conducted a comprehensive lipidomic study of white adipose tissue in mice which become obese either through genetic modification (ob/ob), diet (high fat diet), or a combination of the two, using both solid phase extraction and ion mobility to increase coverage of the lipidome. Composition changes in seven classes of lipids (free fatty acids, diglycerides, TGs, phosphatidylcholines, lyso-phosphatidylcholines, phosphatidylethanolamines, and phosphatidylserines) correlated with perturbations in one-carbon metabolism and transcriptional changes in adipose tissue. We demonstrate that changes in TGs that dominate the overall lipid composition of white adipose tissue are distinct from diet-induced alterations of PLs, the predominant components of the cell membranes. PLs correlate better with transcriptional and one-carbon metabolism changes within the cell, suggesting that the compositional changes that occur in cell membranes during adipocyte expansion have far-reaching functional consequences. Data are available at MetaboLights under the submission number: MTBLS1775.

Metabolic Fingerprinting Links Oncogenic PIK3CA with Enhanced Arachidonic Acid-Derived Eicosanoids.

Oncogenic transformation is associated with profound changes in cellular metabolism, but whether tracking these can improve disease stratification or influence therapy decision-making is largely unknown. Using the iKnife to sample the aerosol of cauterized specimens, we demonstrate a new mode of real-time diagnosis, coupling metabolic phenotype to mutant PIK3CA genotype. Oncogenic PIK3CA results in an increase in arachidonic acid and a concomitant overproduction of eicosanoids, acting to promote cell proliferation beyond a cell-autonomous manner. Mechanistically, mutant PIK3CA drives a multimodal signaling network involving mTORC2-PKCζ-mediated activation of the calcium-dependent phospholipase A2 (cPLA2). Notably, inhibiting cPLA2 synergizes with fatty acid-free diet to restore immunogenicity and selectively reduce mutant PIK3CA-induced tumorigenicity. Besides highlighting the potential for metabolic phenotyping in stratified medicine, this study reveals an important role for activated PI3K signaling in regulating arachidonic acid metabolism, uncovering a targetable metabolic vulnerability that largely depends on dietary fat restriction. VIDEO ABSTRACT.

Validating the validation: reanalyzing a large-scale comparison of deep learning and machine learning models for bioactivity prediction.

Machine learning methods may have the potential to significantly accelerate drug discovery. However, the increasing rate of new methodological approaches being published in the literature raises the fundamental question of how models should be benchmarked and validated. We reanalyze the data generated by a recently published large-scale comparison of machine learning models for bioactivity prediction and arrive at a somewhat different conclusion. We show that the performance of support vector machines is competitive with that of deep learning methods. Additionally, using a series of numerical experiments, we question the relevance of area under the receiver operating characteristic curve as a metric in virtual screening. We further suggest that area under the precision-recall curve should be used in conjunction with the receiver operating characteristic curve. Our numerical experiments also highlight challenges in estimating the uncertainty in model performance via scaffold-split nested cross validation.

The G Protein Biased Small Molecule Apelin Agonist CMF-019 is Disease Modifying in Endothelial Cell Apoptosis In Vitro and Induces Vasodilatation Without Desensitisation In Vivo.

Signaling through the apelin receptor is beneficial for a number of diseases including pulmonary arterial hypertension. The endogenous small peptides, apelin and elabela/toddler, are downregulated in pulmonary arterial hypertension but are not suitable for exogenous administration owing to a lack of bioavailability, proteolytic instability and susceptibility to renal clearance. CMF-019, a small molecule apelin agonist that displays strong bias towards G protein signaling over ß-arrestin (∼400 fold), may be more suitable. This study demonstrates that in addition to being a positive inotrope, CMF-019 caused dose-dependent vasodilatation in vivo (50 nmol 4.16 ± 1.18 mmHg, **p < 0.01; 500 nmol 6.62 ± 1.85 mmHg, **p < 0.01), without receptor desensitization. Furthermore, CMF-019 rescues human pulmonary artery endothelial cells from apoptosis induced by tumor necrosis factor α and cycloheximide (5.66 ± 0.97%, **p < 0.01) by approximately 50% of that observable with rhVEGF (11.59 ± 1.85%, **p < 0.01), suggesting it has disease-modifying potential in vitro. CMF-019 displays remarkable bias at the apelin receptor for a small molecule and importantly recapitulates all aspects of the cardiovascular responses to the endogenous ligand, [Pyr1]apelin-13, in vivo. Additionally, it is able to protect human pulmonary artery endothelial cells from apoptosis, suggesting that the beneficial effects observed with apelin agonists extend beyond hemodynamic alleviation and address disease etiology itself. These findings support CMF-019 as a G protein biased small molecule apelin agonist in vitro and in vivo that could form the basis for the design of novel therapeutic agents in chronic diseases, such as, pulmonary arterial hypertension.

Apelin peptides linked to anti-serum albumin domain antibodies retain affinity in vitro and are efficacious receptor agonists in vivo.

The apelin receptor is a potential target in the treatment of heart failure and pulmonary arterial hypertension where levels of endogenous apelin peptides are reduced but significant receptor levels remain. Our aim was to characterise the pharmacology of a modified peptide agonist, MM202, designed to have high affinity for the apelin receptor and resistance to peptidase degradation and linked to an anti-serum albumin domain antibody (AlbudAb) to extend half-life in the blood. In competition, binding experiments in human heart MM202-AlbudAb (pKi  = 9.39 ± 0.09) bound with similar high affinity as the endogenous peptides [Pyr1 ]apelin-13 (pKi  = 8.83 ± 0.06) and apelin-17 (pKi  = 9.57 ± 0.08). [Pyr1 ]apelin-13 was tenfold more potent in the cAMP (pD2  = 9.52 ± 0.05) compared to the ß-arrestin (pD2  = 8.53 ± 0.03) assay, whereas apelin-17 (pD2  = 10.31 ± 0.28; pD2  = 10.15 ± 0.13, respectively) and MM202-AlbudAb (pD2  = 9.15 ± 0.12; pD2  = 9.26 ± 0.03, respectively) were equipotent in both assays, with MM202-AlbudAb tenfold less potent than apelin-17. MM202-AlbudAb bound to immobilised human serum albumin with high affinity (pKD  = 9.02). In anaesthetised, male Sprague Dawley rats, MM202-AlbudAb (5 nmol, n = 15) significantly reduced left ventricular systolic pressure by 6.61 ± 1.46 mm Hg and systolic arterial pressure by 14.12 ± 3.35 mm Hg and significantly increased cardiac contractility by 533 ± 170 mm Hg/s, cardiac output by 1277 ± 190 RVU/min, stroke volume by 3.09 ± 0.47 RVU and heart rate by 4.64 ± 2.24 bpm. This study demonstrates that conjugating an apelin mimetic peptide to the AlbudAb structure retains receptor and in vivo activity and may be a new strategy for development of apelin peptides as therapeutic agents.

A Bone Morphogenetic Protein (BMP)-derived Peptide Based on the Type I Receptor-binding Site Modifies Cell-type Dependent BMP Signalling.

Bone morphogenetic proteins (BMPs) are multifunctional cytokines of the transforming growth factor ß (TGFß) superfamily with potential therapeutic applications due to their broad biological functionality. Designing BMP mimetics with specific activity will contribute to the translational potential of BMP-based therapies. Here, we report a BMP9 peptide mimetic, P3, designed from the type I receptor binding site, which showed millimolar binding affinities for the type I receptor activin receptor like kinase 1 (ALK1), ALK2 and ALK3. Although showing no baseline activity, P3 significantly enhanced BMP9-induced Smad1/5 phosphorylation as well as ID1, BMPR2, HEY1 and HEY2 gene expression in pulmonary artery endothelial cells (hPAECs), and this activity is dependent on its alpha helix propensity. However, in human dermal microvascular endothelial cells, P3 did not affect BMP9-induced Smad1/5 phosphorylation, but potently inhibited ALK3-dependent BMP4-induced Smad1/5 phosphorylation and gene expression. In C2C12 mouse myoblast cells, P3 had no effect on BMP9-induced osteogenic signalling, which is primarily mediated by ALK2. Interestingly, a previously published peptide from the knuckle region of BMP9 was found to inhibit BMP4-induced Smad1/5 phosphorylation. Together, our data identify a BMP9-derived peptide that can selectively enhance ALK1-mediated BMP9 signalling in hPAECs and modulate BMP9 and BMP4 signalling in a cell type-specific manner.

International Union of Basic and Clinical Pharmacology. CVII. Structure and Pharmacology of the Apelin Receptor with a Recommendation that Elabela/Toddler Is a Second Endogenous Peptide Ligand.

The predicted protein encoded by the APJ gene discovered in 1993 was originally classified as a class A G protein-coupled orphan receptor but was subsequently paired with a novel peptide ligand, apelin-36 in 1998. Substantial research identified a family of shorter peptides activating the apelin receptor, including apelin-17, apelin-13, and [Pyr1]apelin-13, with the latter peptide predominating in human plasma and cardiovascular system. A range of pharmacological tools have been developed, including radiolabeled ligands, analogs with improved plasma stability, peptides, and small molecules including biased agonists and antagonists, leading to the recommendation that the APJ gene be renamed APLNR and encode the apelin receptor protein. Recently, a second endogenous ligand has been identified and called Elabela/Toddler, a 54-amino acid peptide originally identified in the genomes of fish and humans but misclassified as noncoding. This precursor is also able to be cleaved to shorter sequences (32, 21, and 11 amino acids), and all are able to activate the apelin receptor and are blocked by apelin receptor antagonists. This review summarizes the pharmacology of these ligands and the apelin receptor, highlights the emerging physiologic and pathophysiological roles in a number of diseases, and recommends that Elabela/Toddler is a second endogenous peptide ligand of the apelin receptor protein.

The structural basis for membrane assembly of immunoreceptor signalling complexes.

Immunoreceptors are TM complexes that consist of separate ligand-binding and signal-transducing modules. Mounting evidence suggests that interactions with the local environment may influence the architecture of these TM domains, which assemble via crucial sets of conserved ionisable residues, and also control the peripheral association of immunoreceptor tyrosine-based activation motifs (ITAMs) whose phosphorylation triggers cytoplasmic signalling cascades. We now report a molecular dynamics (MD) simulation study of the archetypal T cell receptor (TCR) and its cluster of differentiation 3 (CD3) signalling partners, along with the analogous DNAX-activation protein of 12 kDa (DAP12)/natural killer group 2C (NKG2C) complex. Based on > 15 µs of explicitly solvated, atomic-resolution sampling, we explore molecular aspects of immunoreceptor complex stability in different functionally relevant states. A novel alchemical approach is used to simulate the cytoplasmic CD3ε tail at different depths within lipid bilayer models, revealing that the conformation and cytoplasmic exposure of ITAMs are highly sensitive to local enrichment by different lipid species and to phosphorylation. Furthermore, simulations of the TCR and DAP12 TM domains in various states of oligomerisation suggest that, during the early stages of assembly, stable membrane insertion is facilitated by the interfacial lipid/solvent environment and/or partial ionisation of charged residues. Collectively, our results indicate that the architecture and mechanisms of signal transduction in immunoreceptor complexes are tightly regulated by interactions with the microenvironment.

The nPYc-Toolbox, a Python module for the pre-processing, quality-control and analysis of metabolic profiling datasets.

SUMMARY: As large-scale metabolic phenotyping studies become increasingly common, the need for systemic methods for pre-processing and quality control (QC) of analytical data prior to statistical analysis has become increasingly important, both within a study, and to allow meaningful inter-study comparisons. The nPYc-Toolbox provides software for the import, pre-processing, QC and visualization of metabolic phenotyping datasets, either interactively, or in automated pipelines. AVAILABILITY AND IMPLEMENTATION: The nPYc-Toolbox is implemented in Python, and is freely available from the Python package index https://pypi.org/project/nPYc/, source is available at https://github.com/phenomecentre/nPYc-Toolbox. Full documentation can be found at http://npyc-toolbox.readthedocs.io/ and exemplar datasets and tutorials at https://github.com/phenomecentre/nPYc-toolbox-tutorials.

Colocalization Features for Classification of Tumors Using Desorption Electrospray Ionization Mass Spectrometry Imaging.

Supervised modeling of mass spectrometry imaging (MSI) data is a crucial component for the detection of the distinct molecular characteristics of cancerous tissues. Currently, two types of supervised analyses are mainly used on MSI data: pixel-wise segmentation of sample images and whole-sample-based classification. A large number of mass spectra associated with each MSI sample can represent a challenge for designing models that simultaneously preserve the overall molecular content while capturing valuable information contained in the MSI data. Furthermore, intensity-related batch effects can introduce biases in the statistical models. Here we introduce a method based on ion colocalization features that allows the classification of whole tissue specimens using MSI data, which naturally preserves the spatial information associated the with the mass spectra and is less sensitive to possible batch effects. Finally, we propose data visualization strategies for the inspection of the derived networks, which can be used to assess whether the correlation differences are related to coexpression/suppression or disjoint spatial localization patterns and can suggest hypotheses based on the underlying mechanisms associated with the different classes of analyzed samples.

A novel cyclic biased agonist of the apelin receptor, MM07, is disease modifying in the rat monocrotaline model of pulmonary arterial hypertension.

BACKGROUND AND PURPOSE: Apelin is an endogenous vasodilatory and inotropic peptide that is down-regulated in human pulmonary arterial hypertension, although the density of the apelin receptor is not significantly attenuated. We hypothesised that a G protein-biased apelin analogue MM07, which is more stable than the endogenous apelin peptide, may be beneficial in this condition with the advantage of reduced ß-arrestin-mediated receptor internalisation with chronic use. EXPERIMENTAL APPROACH: Male Sprague-Dawley rats received either monocrotaline to induce pulmonary arterial hypertension or saline and then daily i.p. injections of either MM07 or saline for 21 days. The extent of disease was assessed by right ventricular catheterisation, cardiac MRI, and histological analysis of the pulmonary vasculature. The effect of MM07 on signalling, proliferation, and apoptosis of human pulmonary artery endothelial cells was investigated. KEY RESULTS: MM07 significantly reduced the elevation of right ventricular systolic pressure and hypertrophy induced by monocrotaline. Monocrotaline-induced changes in cardiac structure and function, including right ventricular end-systolic and end-diastolic volumes, ejection fraction, and left ventricular end-diastolic volume, were attenuated by MM07. MM07 also significantly reduced monocrotaline-induced muscularisation of small pulmonary blood vessels. MM07 stimulated endothelial NOS phosphorylation and expression, promoted proliferation, and attenuated apoptosis of human pulmonary arterial endothelial cells in vitro. CONCLUSION AND IMPLICATIONS: Our findings suggest that chronic treatment with MM07 is beneficial in this animal model of pulmonary arterial hypertension by addressing disease aetiology. These data support the development of G protein-biased apelin receptor agonists with improved pharmacokinetic profiles for use in human disease.

SPUTNIK: an R package for filtering of spatially related peaks in mass spectrometry imaging data.

Summary: SPUTNIK is an R package consisting of a series of tools to filter mass spectrometry imaging peaks characterized by a noisy or unlikely spatial distribution. SPUTNIK can produce mass spectrometry imaging datasets characterized by a smaller but more informative set of peaks, reduce the complexity of subsequent multi-variate analysis and increase the interpretability of the statistical results. Availability and implementation: SPUTNIK is freely available online from CRAN repository and at https://github.com/paoloinglese/SPUTNIK. The package is distributed under the GNU General Public License version 3 and is accompanied by example files and data. Supplementary information: Supplementary data are available at Bioinformatics online.

Structure-based design of allosteric calpain-1 inhibitors populating a novel bioactivity space.

Dimeric calpains constitute a promising therapeutic target for many diseases such as cardiovascular, neurodegenerative and ischaemic disease. The discovery of selective calpain inhibitors, however, has been extremely challenging. Previously, allosteric inhibitors of calpains, such as PD150606, which included a specific α-mercaptoacrylic acid sub-structure, were reported to bind to the penta-EF hand calcium binding domain, PEF(S) of calpain. Although these are selective to calpains over other cysteine proteases, their mode of action has remained elusive due to their ability to inhibit the active site domain with and without the presence of PEF(S), with similar potency. These findings have led to the question of whether the inhibitory response can be attributed to an allosteric mode of action or alternatively to inhibition at the active site. In order to address this problem, we report a structure-based virtual screening protocol as a novel approach for the discovery of PEF(S) binders that populate a novel chemical space. We have identified compound 1, Vidupiprant, which is shown to bind to the PEF(S) domain by the TNS displacement method, and it exhibited specificity in its allosteric mode of inhibition. Compound 1 inhibited the full-length calpain-1 complex with a higher potency (IC50 = 7.5 µM) than the selective, cell-permeable non-peptide calpain inhibitor, PD150606 (IC50 = 19.3 µM), where the latter also inhibited the active site domain in the absence of PEF(S) (IC50 = 17.8 µM). Hence the method presented here has identified known compounds with a novel allosteric mechanism for the inhibition of calpain-1. We show for the first time that the inhibition of enzyme activity can be attributed to an allosteric mode of action, which may offer improved selectivity and a reduced side-effects profile.

Microbiome-host systems interactions: protective effects of propionate upon the blood-brain barrier.

BACKGROUND: Gut microbiota composition and function are symbiotically linked with host health and altered in metabolic, inflammatory and neurodegenerative disorders. Three recognised mechanisms exist by which the microbiome influences the gut-brain axis: modification of autonomic/sensorimotor connections, immune activation, and neuroendocrine pathway regulation. We hypothesised interactions between circulating gut-derived microbial metabolites, and the blood-brain barrier (BBB) also contribute to the gut-brain axis. Propionate, produced from dietary substrates by colonic bacteria, stimulates intestinal gluconeogenesis and is associated with reduced stress behaviours, but its potential endocrine role has not been addressed. RESULTS: After demonstrating expression of the propionate receptor FFAR3 on human brain endothelium, we examined the impact of a physiologically relevant propionate concentration (1 µM) on BBB properties in vitro. Propionate inhibited pathways associated with non-specific microbial infections via a CD14-dependent mechanism, suppressed expression of LRP-1 and protected the BBB from oxidative stress via NRF2 (NFE2L2) signalling. CONCLUSIONS: Together, these results suggest gut-derived microbial metabolites interact with the BBB, representing a fourth facet of the gut-brain axis that warrants further attention.

Pharmacological targeting of apelin impairs glioblastoma growth.

Glioblastoma are highly aggressive brain tumours that are associated with an extremely poor prognosis. Within these tumours exists a subpopulation of highly plastic self-renewing cancer cells that retain the ability to expand ex vivo as tumourspheres, induce tumour growth in mice, and have been implicated in radio- and chemo-resistance. Although their identity and fate are regulated by external cues emanating from endothelial cells, the nature of such signals remains unknown. Here, we used a mass spectrometry proteomic approach to characterize the factors released by brain endothelial cells. We report the identification of the vasoactive peptide apelin as a central regulator for endothelial-mediated maintenance of glioblastoma patient-derived cells with stem-like properties. Genetic and pharmacological targeting of apelin cognate receptor abrogates apelin- and endothelial-mediated expansion of glioblastoma patient-derived cells with stem-like properties in vitro and suppresses tumour growth in vivo. Functionally, selective competitive antagonists of apelin receptor were shown to be safe and effective in reducing tumour expansion and lengthening the survival of intracranially xenografted mice. Therefore, the apelin/apelin receptor signalling nexus may operate as a paracrine signal that sustains tumour cell expansion and progression, suggesting that apelin is a druggable factor in glioblastoma.

Deep learning and 3D-DESI imaging reveal the hidden metabolic heterogeneity of cancer.

Visual inspection of tumour tissues does not reveal the complex metabolic changes that differentiate cancer and its sub-types from healthy tissues. Mass spectrometry imaging, which quantifies the underlying chemistry, represents a powerful tool for the molecular exploration of tumour tissues. A 3-dimensional topological description of the chemical properties of the tumour permits the formulation of hypotheses about the biological composition and interactions and the possible causes of its heterogeneous structure. The large amount of information contained in such datasets requires powerful tools for its analysis, visualisation and interpretation. Linear methods for unsupervised dimensionality reduction, such as PCA, are inadequate to capture the complex non-linear relationships present in these data. For this reason, a deep unsupervised neural network based technique, parametric t-SNE, is adopted to map a 3D-DESI-MS dataset from a human colorectal adenocarcinoma biopsy onto a 2-dimensional manifold. This technique allows the identification of clusters not visible with linear methods. The unsupervised clustering of the tumour tissue results in the identification of sub-regions characterised by the abundance of identified metabolites, making possible the formulation of hypotheses to account for their significance and the underlying biological heterogeneity in the tumour.