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Epithelial-to-mesenchymal transition (EMT)-inducing transcription factors (TF) are well known for their ability to induce mesenchymal states associated with increased migratory and invasive properties. Unexpectedly, nuclear expression of the EMT-TF ZEB2 in human primary melanoma has been shown to correlate with reduced invasion. We report here that ZEB2 is required for outgrowth for primary melanomas and metastases at secondary sites. Ablation of Zeb2 hampered outgrowth of primary melanomas in vivo, whereas ectopic expression enhanced proliferation and growth at both primary and secondary sites. Gain of Zeb2 expression in pulmonary-residing melanoma cells promoted the development of macroscopic lesions. In vivo fate mapping made clear that melanoma cells undergo a conversion in state where ZEB2 expression is replaced by ZEB1 expression associated with gain of an invasive phenotype. These findings suggest that reversible switching of the ZEB2/ZEB1 ratio enhances melanoma metastatic dissemination.Significance:ZEB2 function exerts opposing behaviors in melanoma by promoting proliferation and expansion and conversely inhibiting invasiveness, which could be of future clinical relevance.

Supplementary Figures. Supplementary Figure S1: Zeb2-wildtype cells outcompete Zeb2-negative cells in terms of expansion and differentiation. Supplementary Figure S2: Zeb2 does not accelerate melanoma development on a p53-wildtype background. Supplementary Figure S3: ZEB2 affects the phenotypical switch between proliferation and invasion in mouse and human melanoma cells. Supplementary Figure S4: ZEB2 affects the phenotypical switch between proliferation and invasion in human melanoma. Supplementary Figure S5: TGF-ß treatment mediates the switch from ZEB2 to ZEB1 and induces an invasive gene signature.

Supplementary materials and methods

Supplementary Figures 1-6. Suppl. Fig. 1. Mel-ILP induces release of certain cytokines, however does not affect infiltration of immune cells into tumor bed. Suppl. Fig. 2. Melphalan induces apoptosis of melanoma cells. Suppl. Fig. 3 Melphalan induces exposure of danger signals. Suppl. Fig. 4. Dying human melanoma cells induce danger signaling-independent in vitro stimulation of immune cells. Suppl. Fig. 5. In vitro treated melanoma cells do not strongly activate NK cells. Suppl. Fig. 6. (A) The phenotypic maturation of murine iDCs (B) Effect of antibodybased elimination of CD4+ and CD8+ cells in prophylactic mice vaccination experiment

Supplementary Tables 1-3. Supplementary Table 1. Meta-data analysis of clinical response to melphalan-based isolated limbtreatment procedures in melanoma patients. Supplementary Table 2. Meta-data analysis of clinical response to melphalan/TNF or Mel/TNF/IFNγ combination therapies for isolated limb-treatment procedures in melanoma patients. Supplementary Table 3. Follow up information about the patients whose tumour samples were used for analysis of infiltration of immune cells and expression levels of cytokines.

Systemic chemotherapy generally has been considered immunosuppressive, but it has become evident that certain chemotherapeutic drugs elicit immunogenic danger signals in dying cancer cells that can incite protective antitumor immunity. In this study, we investigated whether locoregionally applied therapies, such as melphalan, used in limb perfusion for melanoma (Mel-ILP) produce related immunogenic effects. In human melanoma biopsies, Mel-ILP treatment upregulated IL1B, IL8, and IL6 associated with their release in patients' locoregional sera. Although induction of apoptosis in melanoma cells by melphalan in vitro did not elicit threshold levels of endoplasmic reticulum and reactive oxygen species stress associated with danger signals, such as induction of cell-surface calreticulin, prophylactic immunization and T-cell depletion experiments showed that melphalan administration in vivo could stimulate a CD8+ T cell–dependent protective antitumor response. Interestingly, the vaccination effect was potentiated in combination with exogenous calreticulin, but not tumor necrosis factor, a cytokine often combined with Mel-ILP. Our results illustrate how melphalan triggers inflammatory cell death that can be leveraged by immunomodulators such as the danger signal calreticulin. Cancer Res; 75(8); 1603–14. ©2015 AACR.

Although melanoma is notorious for its high degree of heterogeneity and plasticity1,2, the origin and magnitude of cell-state diversity remains poorly understood. Equally, it is unclear whether growth and metastatic dissemination are supported by overlapping or distinct melanoma subpopulations. Here, by combining mouse genetics, single-cell and spatial transcriptomics, lineage tracing and quantitative modelling, we provide evidence of a hierarchical model of tumour growth that mirrors the cellular and molecular logic underlying the cell-fate specification and differentiation of the embryonic neural crest. We show that tumorigenic competence is associated with a spatially localized perivascular niche, a phenotype acquired through an intercellular communication pathway established by endothelial cells. Consistent with a model in which only a fraction of cells are fated to fuel growth, temporal single-cell tracing of a population of melanoma cells with a mesenchymal-like state revealed that these cells do not contribute to primary tumour growth but, instead, constitute a pool of metastatic initiating cells that switch cell identity while disseminating to secondary organs. Our data provide a spatially and temporally resolved map of the diversity and trajectories of melanoma cell states and suggest that the ability to support growth and metastasis are limited to distinct pools of cells. The observation that these phenotypic competencies can be dynamically acquired after exposure to specific niche signals warrant the development of therapeutic strategies that interfere with the cancer cell reprogramming activity of such microenvironmental cues.

Joint profiling of chromatin accessibility and gene expression of individual cells provides an opportunity to decipher enhancer-driven gene regulatory networks (eGRN). Here we present a new method for the inference of eGRNs, called SCENIC+. SCENIC+ predicts genomic enhancers along with candidate upstream transcription factors (TF) and links these enhancers to candidate target genes. Specific TFs for each cell type or cell state are predicted based on the concordance of TF binding site accessibility, TF expression, and target gene expression. To improve both recall and precision of TF identification, we curated and clustered more than 40,000 position weight matrices that we could associate with 1,553 human TFs. We validated and benchmarked each of the SCENIC+ components on diverse data sets from different species, including human peripheral blood mononuclear cell types, ENCODE cell lines, human melanoma cell states, and Drosophila retinal development. Next, we exploit SCENIC+ predictions to study conserved TFs, enhancers, and GRNs between human and mouse cell types in the cerebral cortex. Finally, we provide new capabilities that exploit the inferred eGRNs to study the dynamics of gene regulation along differentiation trajectories; to map regulatory activities onto tissues using spatial omics data; and to predict the effect of TF perturbations on cell state. SCENIC+ provides critical insight into gene regulation, starting from multiome atlases of scATAC-seq and scRNA-seq. The SCENIC+ suite is available as a set of Python modules at https://scenicplus.readthedocs.io.

in press

Melanoma cells can switch between a melanocytic and a mesenchymal-like state. Scattered evidence indicates that additional intermediate state(s) may exist. Here, to search for such states and decipher their underlying gene regulatory network (GRN), we studied 10 melanoma cultures using single-cell RNA sequencing (RNA-seq) as well as 26 additional cultures using bulk RNA-seq. Although each culture exhibited a unique transcriptome, we identified shared GRNs that underlie the extreme melanocytic and mesenchymal states and the intermediate state. This intermediate state is corroborated by a distinct chromatin landscape and is governed by the transcription factors SOX6, NFATC2, EGR3, ELF1 and ETV4. Single-cell migration assays confirmed the intermediate migratory phenotype of this state. Using time-series sampling of single cells after knockdown of SOX10, we unravelled the sequential and recurrent arrangement of GRNs during phenotype switching. Taken together, these analyses indicate that an intermediate state exists and is driven by a distinct and stable 'mixed' GRN rather than being a symbiotic heterogeneous mix of cells. ispartof: NATURE CELL BIOLOGY vol:22 issue:8 pages:986-+ ispartof: location:England status: published

Epithelial-to-mesenchymal transition (EMT)-inducing transcription factors (TF) are well known for their ability to induce mesenchymal states associated with increased migratory and invasive properties. Unexpectedly, nuclear expression of the EMT-TF ZEB2 in human primary melanoma has been shown to correlate with reduced invasion. We report here that ZEB2 is required for outgrowth for primary melanomas and metastases at secondary sites. Ablation of Zeb2 hampered outgrowth of primary melanomas in vivo, whereas ectopic expression enhanced proliferation and growth at both primary and secondary sites. Gain of Zeb2 expression in pulmonary-residing melanoma cells promoted the development of macroscopic lesions. In vivo fate mapping made clear that melanoma cells undergo a conversion in state where ZEB2 expression is replaced by ZEB1 expression associated with gain of an invasive phenotype. These findings suggest that reversible switching of the ZEB2/ZEB1 ratio enhances melanoma metastatic dissemination. Significance: ZEB2 function exerts opposing behaviors in melanoma by promoting proliferation and expansion and conversely inhibiting invasiveness, which could be of future clinical relevance.

Single-cell RNA-seq and single-cell assay for transposase-accessible chromatin (ATAC-seq) technologies are used extensively to create cell type atlases for a wide range of organisms, tissues, and disease processes. To increase the scale of these atlases, lower the cost and pave the way for more specialized multiome assays, custom droplet microfluidics may provide solutions complementary to commercial setups. We developed HyDrop, a flexible and open-source droplet microfluidic platform encompassing three protocols. The first protocol involves creating dissolvable hydrogel beads with custom oligos that can be released in the droplets. In the second protocol, we demonstrate the use of these beads for HyDrop-ATAC, a low-cost noncommercial scATAC-seq protocol in droplets. After validating HyDrop-ATAC, we applied it to flash-frozen mouse cortex and generated 7996 high-quality single-cell chromatin accessibility profiles in a single run. In the third protocol, we adapt both the reaction chemistry and the capture sequence of the barcoded hydrogel bead to capture mRNA, and demonstrate a significant improvement in throughput and sensitivity compared to previous open-source droplet-based scRNA-seq assays (Drop-seq and inDrop). Similarly, we applied HyDrop-RNA to flash-frozen mouse cortex and generated 9508 single-cell transcriptomes closely matching reference single-cell gene expression data. Finally, we leveraged HyDrop-RNA's high capture rate to analyze a small population of fluorescence-activated cell sorted neurons from theScientists are now able to determine the order of chemical blocks, or nucleic acids, that make up the genetic code. These sequencing tools can be used to identify which genes are active within a biological sample. They do this by extracting and analysing open chromatin (regions of DNA that are accessible to the cell’s machinery), or sequences of RNA (the molecular templates cells use to translate genes into working proteins). Initially, most sequencing tools could only provide an ‘averaged-out’ profile of the genes activated in bulk pieces of tissue which contain multiple types of cell. However, advances in technology have led to new methods that can extract and analyse open chromatin or RNA from individual cells. First, the cells are separated, via a technique called microfluidics, into tiny droplets of water along with a single bead that carries a unique barcode. The cell is then broken apart inside the droplet and the barcode within the bead gets released and attaches itself to the genetic material extracted from the cell. All the genetic material inside the droplets is then pooled together and sequenced. Researchers then use the barcode tags to identify which bits of RNA or DNA belong to each cell. Single-cell sequencing has many advantages, including being able to pinpoint precise genetic differences between healthy and abnormal cells, and to create cell atlases of whole organisms, tissues and microbial communities. But existing methods for extracting chromatin are very expensive, and there were no openly available tools for processing thousands of cells at speed. Furthermore, while several single-cell RNA sequencing tools are already freely available, they are not very sensitive or practical to use. Here, De Rop et al. have developed a new open-source platform called HyDrop that overcomes these barriers. The method entails a new type of barcoded bead and optimised elements of existing microfluidics protocols using open-source reagents. These changes created a more user-friendly workflow and increased sensitivity of sequencing at no additional cost. De Rop et al. used their new platform to screen the RNA and open chromatin of thousands of individuals cells from the brains of mice and flies. HyDrop outperformed other open-source methods when working in RNA-sequencing mode. It also provides the first open-source tool for sequencing open chromatin in single cells. Further improvements are expected as researchers tweak the platform, which for now provides an affordable alternative to existing methods.

Objective. We present a framework to objectively test and compare stimulation artefact removal techniques in the context of neural spike sorting. Approach. To this end, we used realistic hybrid ground-truth spiking data, with superimposed artefacts from in vivo recordings. We used the framework to evaluate and compare several techniques: blanking, template subtraction by averaging, linear regression, and a multi-channel Wiener filter (MWF). Main results. Our study demonstrates that blanking and template subtraction result in a poorer spike sorting performance than linear regression and MWF, while the latter two perform similarly. Finally, to validate the conclusions found from the hybrid evaluation framework, we also performed a qualitative analysis on in vivo recordings without artificial manipulations. Significance. Our framework allows direct quantification of the impact of the residual artefact on the spike sorting accuracy, thereby allowing for a more objective and more relevant comparison compared to indirect signal quality metrics that are estimated from the signal statistics. Furthermore, the availability of a ground truth in the form of single-unit spiking activity also facilitates a better estimation of such signal quality metrics.

Genomic sequence variation within enhancers and promoters can have a significant impact on the cellular state and phenotype. However, sifting through the millions of candidate variants in a personal genome or a cancer genome, to identify those that impact cis-regulatory function, remains a major challenge. Interpretation of noncoding genome variation benefits from explainable artificial intelligence to predict and interpret the impact of a mutation on gene regulation. Here we generate phased whole genomes with matched chromatin accessibility, histone modifications, and gene expression for 10 melanoma cell lines. We find that training a specialized deep learning model, called DeepMEL2, on melanoma chromatin accessibility data can capture the various regulatory programs of the melanocytic and mesenchymal-like melanoma cell states. This model outperforms motif-based variant scoring, as well as more generic deep learning models. We detect hundreds to thousands of allele-specific chromatin accessibility variants (ASCAVs) in each melanoma genome, of which 15%–20% can be explained by gains or losses of transcription factor binding sites. A considerable fraction of ASCAVs are caused by changes in AP-1 binding, as confirmed by matched ChIP-seq data to identify allele-specific binding of JUN and FOSL1. Finally, by augmenting the DeepMEL2 model with ChIP-seq data for GABPA, the TERT promoter mutation, as well as additional ETS motif gains, can be identified with high confidence. In conclusion, we present a new integrative genomics approach and a deep learning model to identify and interpret functional enhancer mutations with allelic imbalance of chromatin accessibility and gene expression., SCOPUS: ar.j, info:eu-repo/semantics/published

BNIP3 is a mitophagy receptor with context‐dependent roles in cancer, but whether and how it modulates melanoma growth in vivo remains unknown. Here, we found that elevated BNIP3 levels correlated with poorer melanoma patient’s survival and depletion of BNIP3 in B16‐F10 melanoma cells compromised tumor growth in vivo. BNIP3 depletion halted mitophagy and enforced a PHD2‐mediated downregulation of HIF‐1α and its glycolytic program both in vitro and in vivo. Mechanistically, we found that BNIP3‐deprived melanoma cells displayed increased intracellular iron levels caused by heightened NCOA4‐mediated ferritinophagy, which fostered PHD2‐mediated HIF‐1α destabilization. These effects were not phenocopied by ATG5 or NIX silencing. Restoring HIF‐1α levels in BNIP3‐depleted melanoma cells rescued their metabolic phenotype and tumor growth in vivo, but did not affect NCOA4 turnover, underscoring that these BNIP3 effects are not secondary to HIF‐1α. These results unravel an unexpected role of BNIP3 as upstream regulator of the pro‐tumorigenic HIF‐1α glycolytic program in melanoma cells., Mitophagy receptor BNIP3 facilitates skin cancer by supporting HIF1‐1α protein stability.

We present cisTopic, a probabilistic framework used to simultaneously discover coaccessible enhancers and stable cell states from sparse single-cell epigenomics data ( http://github.com/aertslab/cistopic ). Using a compendium of single-cell ATAC-seq datasets from differentiating hematopoietic cells, brain and transcription factor perturbations, we demonstrate that topic modeling can be exploited for robust identification of cell types, enhancers and relevant transcription factors. cisTopic provides insight into the mechanisms underlying regulatory heterogeneity in cell populations. As an unsupervised Bayesian framework, cisTopic classifies regions in scATAC-seq data into regulatory topics, which are used for clustering.

Background & Aims: Obesity-associated inflammation is a key player in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). However, the role of macrophage scavenger receptor 1 (MSR1, CD204) remains incompletely understood. Methods: A total of 170 NAFLD liver biopsies were processed for transcriptomic analysis and correlated with clinicopathological features. Msr1(-/-) and wild-type mice were subjected to a 16-week high-fat and high-cholesterol diet. Mice and ex vivo human liver slices were treated with a monoclonal antibody against MSR1. Genetic susceptibility was assessed using genome-wide association study data from 1,483 patients with NAFLD and 430,101 participants of the UK Biobank. Results: MSR1 expression was associated with the occurrence of hepatic lipid-laden foamy macrophages and correlated with the degree of steatosis and steatohepatitis in patients with NAFLD. Mice lacking Msr1 were protected against diet-induced metabolic disorder, showing fewer hepatic foamy macrophages, less hepatic inflammation, improved dyslipidaemia and glucose tolerance, and altered hepatic lipid metabolism. Upon induction by saturated fatty acids, MSR1 induced a pro-inflammatory response via the JNK signalling pathway. In vitro blockade of the receptor prevented the accumulation of lipids in primary macrophages which inhibited the switch towards a proinflammatory phenotype and the release of cytokines such as TNF-alpha Targeting MSR1 using monoclonal antibody therapy in an obesity-associated NAFLD mouse model and human liver slices resulted in the prevention of foamy macrophage formation and inflammation. Moreover, we identified that rs41505344, a polymorphism in the upstream transcriptional region of MSR1, was associated with altered serum triglycerides and aspartate aminotransferase levels in a cohort of over 400,000 patients. Conclusions: Taken together, our data suggest that MSR1 plays a critical role in lipid-induced inflammation and could thus be a potential therapeutic target for the treatment of NAFLD. Lay summary: Non-alcoholic fatty liver disease (NAFLD) is a chronic disease primarily caused by excessive consumption of fat and sugar combined with a lack of exercise or a sedentary lifestyle. Herein, we show that the macrophage scavenger receptor MSR1, an innate immune receptor, mediates lipid uptake and accumulation in Kupffer cells, resulting in liver inflammation and thereby promoting the progression of NAFLD in humans and mice. (C) 2021 The Authors. Published by Elsevier B.V. on behalf of European Association for the Study of the Liver. Funding Agencies|EPoS (Elucidating Pathways of Steatohepatitis) consortium - Horizon 2020 Framework Program of the European Union [634413]; LITMUS (Liver Investigation: Testing Marker Utility in Steatohepatitis) consortium - Innovative Medicines Initiative (IMI2) Program of the European Union from the EU Horizon 2020 programme [777377]; EFPIA; Newcastle NIHR Biomedical Research Centre; Newcastle University; Wellcome Trust [215542/Z/19/Z]; Knut och Alice Wallenberg Foundation Wallenberg Centre for molecular and translational medicine; University of Gothenburg, Sweden; Ake Wirbergs Research [M18-0121]; Cancerfonfen [19 0352 Pj]; Belgian Federal Science Policy Office (Interuniversity Attraction Poles Program) grant [Network P7/83-HEPRO2]; Rosetrees Trust; Flemish Cancer Society Kom op tegen Kanker; Belgian Cancer Society Stichting tegen Kanker

Deciphering the genomic regulatory code of enhancers is a key challenge in biology because this code underlies cellular identity. A better understanding of how enhancers work will improve the interpretation of noncoding genome variation and empower the generation of cell type-specific drivers for gene therapy. Here, we explore the combination of deep learning and cross-species chromatin accessibility profiling to build explainable enhancer models. We apply this strategy to decipher the enhancer code in melanoma, a relevant case study owing to the presence of distinct melanoma cell states. We trained and validated a deep learning model, called DeepMEL, using chromatin accessibility data of 26 melanoma samples across six different species. We show the accuracy of DeepMEL predictions on the CAGI5 challenge, where it significantly outperforms existing models on the melanoma enhancer of IRF4 Next, we exploit DeepMEL to analyze enhancer architectures and identify accurate transcription factor binding sites for the core regulatory complexes in the two different melanoma states, with distinct roles for each transcription factor, in terms of nucleosome displacement or enhancer activation. Finally, DeepMEL identifies orthologous enhancers across distantly related species, where sequence alignment fails, and the model highlights specific nucleotide substitutions that underlie enhancer turnover. DeepMEL can be used from the Kipoi database to predict and optimize candidate enhancers and to prioritize enhancer mutations. In addition, our computational strategy can be applied to other cancer or normal cell types. ispartof: GENOME RESEARCH vol:30 issue:12 ispartof: location:United States status: published

Spike sorting is the process of retrieving the spike times of individual neurons that are present in an extracellular neural recording. Over the last decades, many spike sorting algorithms have been published. In an effort to guide a user towards a specific spike sorting algorithm, given a specific recording setting (i.e., brain region and recording device), we provide an open-source graphical tool for the generation of hybrid ground-truth data in Python. Hybrid ground-truth data is a data-driven modelling paradigm in which spikes from a single unit are moved to a different location on the recording probe, thereby generating a virtual unit of which the spike times are known. The tool enables a user to efficiently generate hybrid ground-truth datasets and make informed decisions between spike sorting algorithms, fine-tune the algorithm parameters towards the used recording setting, or get a deeper understanding of those algorithms. ispartof: Neuroinformatics vol:19 issue:1 pages:141-158 ispartof: location:United States status: published

When inserting an electrode array in the brain, its electrodes will record so-called ’spikes’ which are generated by the neurons in the neighbourhood of the array. Spike sorting is the process of detecting and assigning these recorded spikes to their putative neurons. Many spike sorting pipelines rely on a clustering algorithm that groups the spikes coming from the same neuron in a pre-defined feature space. However, classical spike sorting algorithms fail when spike overlap, i.e., the near-simultaneous occurrence of two or more spikes from different neurons, is present in the recording. In such cases, the overlapping spikes segment ends up in a seemingly random position in the feature space and is not assigned to the correct cluster. This problem has been addressed before by extending the sorting algorithm with a template matching post-processor. In this work, a novel approach is presented to resolve spike overlap directly in the feature space. To this end, a neural network feature map is presented, that generates spike embeddings (feature vectors) that behave as a linear superposition in the feature space in the case of spike overlap. Its performance is quantified on semi-synthetic data obtained through a data augmentation procedure applied to real neural recordings.

In melanoma, the lymphocytic infiltrate is a prognostic parameter classified morphologically in “brisk”, “non-brisk” and “absent”. The meaning of “brisk” is “active, energetic”, implying a functional connotation which has never been proved. Recently, it has been shown that not all brisk infiltrates have a good prognosis, that lymphocytic populations can be very heterogeneous, and that anti-PD-1 immunotherapy supports activated T cells. Here, we characterize the immune landscape in primary melanoma by high-dimensional single cell multiplex analysis in tissue sections (MILAN technique) followed by image analysis, RT-PCR and shotgun proteomics. We observed that the brisk and non-brisk patterns of tumor infiltrating lymphocytes (TILs) in primary melanoma are heterogeneous functional categories that can be further sub-classified according to the functional status of their lymphocytes as active, transitional or exhausted. We found that only activation of TILs correlates with spontaneous regression, and that the good prognosis of melanomas with a brisk pattern could be due to the fact that in these case the Tcy that are in contact with the melanoma cells are still active, and consequently the melanoma is still under immune control at the moment of surgical excision. The main inflammatory cell subpopulations that are present in the microenvironment associated with activation and exhaustion and their spatial relationships are described using neighbourhood analysis. Finally, we show a bioinformatic pipeline that, starting from common immunofluorescence stainings, can transform the tissue into a digitalized image, which represents the starting point for multiple deeper levels of analysis.

Despite the introduction of novel targeted therapies, chemotherapy still remains the primary treatment for metastatic melanoma in poorly funded healthcare environments or in case of disease relapse, with no reliable molecular markers for progression-free survival (PFS) available. As chemotherapy primarily eliminates cancer cells by apoptosis, we here evaluated if the expression of key apoptosis regulators (Bax, Bak, Bcl-2, Bcl-xL, Smac, Procaspase-9, Apaf-1, Procaspase-3 and XIAP) allows prognosticating PFS in stage III/IV melanoma patients. Following antibody validation, marker expression was determined by automated and manual scoring of immunohistochemically stained tissue microarrays (TMAs) constructed from treatment-naive metastatic melanoma biopsies. Interestingly and counter-intuitively, low expression of the pro-apoptotic proteins Bax, Bak and Smac indicated better prognosis (log-rank p 12 months) on a case-by-case basis (area under the receiver operating characteristic curve (ROC AUC) = 0.79). Taken together, our results therefore suggest that Bax, Bak and Smac jointly define a signature with potential clinical utility in chemotherapy-treated metastatic melanoma. ispartof: CELL DEATH & DISEASE vol:11 issue:2 ispartof: location:England status: published

Obesity-associated inflammation is a key player in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). However, the exact mechanisms remain incompletely understood. Here we demonstrate that macrophage scavenger receptor 1 (MSR1, CD204) expression is associated with the occurrence of hepatic lipid-laden foamy macrophages and correlates with the degree of steatosis and steatohepatitis in a cohort of 170 NAFLD patients. Mice lacking Msr1 are protected against high fat-cholesterol diet (HFD)-induced metabolic disorder, showing fewer hepatic lipid-laden foamy macrophages, less hepatic inflammation, improved dyslipidemia and glucose tolerance, while showing a change in hepatic lipid metabolism. We show that MSR1 induces a pro-inflammatory response via the JNK signaling pathway upon triggering by saturated fatty acids. In vitro blockade of the receptor prevented the accumulation of lipids in primary macrophages which inhibited the switch towards a pro-inflammatory phenotype and the release of cytokines such as TNFa. Targeting MSR1 using monoclonal antibody therapy in an obesity-associated NAFLD mouse model and ex vivo human liver slices resulted in the prevention of foamy macrophage formation and liver inflammation. Moreover, we identified that rs41505344, a polymorphism in the upstream transcriptional region of MSR1, was associated with altered serum triglycerides and aspartate transaminase levels in a cohort of over 400,000 patients. Taken together, our data suggest a critical role for MSR1 in lipid homeostasis and a potential therapeutic target for the treatment of NAFLD.One Sentence SummaryThe immunometabolic role of MSR1 in human NAFLD.

Genomic enhancers form the central nodes of gene regulatory networks by harbouring combinations of transcription factor binding sites. Deciphering the combinatorial code by which these binding sites are assembled within enhancers is indispensable to understand their regulatory involvement in establishing a cell’s phenotype, especially within biological systems with dysregulated gene regulatory networks, such as melanoma. In order to unravel the enhancer logic of the two most common melanoma cell states, namely the melanocytic and mesenchymal-like state, we combined comparative epigenomics with machine learning. By profiling chromatin accessibility using ATAC-seq on a cohort of 27 melanoma cell lines across six different species, we demonstrate the conservation of the two main melanoma states and their underlying master regulators. To perform an in-depth analysis of the enhancer architecture, we trained a deep neural network, called DeepMEL, to classify melanoma enhancers not only in the human genome, but also in other species. DeepMEL revealed the presence, organisation and positional specificity of important transcription factor binding sites. Together, this extensive analysis of the melanoma enhancer code allowed us to propose the concept of a core regulatory complex binding to melanocytic enhancers, consisting of SOX10, TFAP2A, MITF and RUNX, and to disentangle their individual roles in regulating enhancer accessibility and activity.

Brief AbstractPrioritization of non-coding genome variation benefits from explainable AI to predict and interpret the impact of a mutation on gene regulation. Here we apply a specialized deep learning model to phased melanoma genomes and identify functional enhancer mutations with allelic imbalance of chromatin accessibility and gene expression.

Although single-cell RNA-seq is revolutionizing biology, data interpretation remains a challenge. We present SCENIC for the simultaneous reconstruction of gene regulatory networks and identification of cell states. We apply SCENIC to a compendium of single-cell data from tumors and brain, and demonstrate that the genomic regulatory code can be exploited to guide the identification of transcription factors and cell states. SCENIC provides critical biological insights into the mechanisms driving cellular heterogeneity.

Human hepatocellular carcinomas (HCCs) expressing the biliary/hepatic progenitor cell marker keratin 19 (K19) have been linked with a poor prognosis and exhibit an increase in platelet-derived growth factor receptor α (PDGFRα) and laminin beta 1 (LAMB1) expression. PDGFRα has been reported to induce de novo synthesis of LAMB1 protein in a Sjogren syndrome antigen B (La/SSB)-dependent manner in a murine metastasis model. However, the role of this cascade in human HCC remains unclear. This study focused on the functional role of the PDGFRα-La/SSB-LAMB1 pathway and its molecular link to K19 expression in human HCC. In surgical HCC specimens from a cohort of 136 patients, PDGFRα expression correlated with K19 expression, microvascular invasion and metastatic spread. In addition, PDGFRα expression in pre-operative needle biopsy specimens predicted poor overall survival during a 5-year follow-up period. Consecutive histological staining demonstrated that the signaling components of the PDGFRα-La/SSB-LAMB1 pathway were strongly expressed at the invasive front. K19-positive HCC cells displayed high levels of α2β1 integrin (ITG) receptor, both in vitro and in vivo. In vitro activation of PDGFRα signaling triggered the translocation of nuclear La/SSB into the cytoplasm, enhanced the protein synthesis of LAMB1 by activating its internal ribosome entry site, which in turn led to increased secretion of laminin-111. This effect was abrogated by the PDGFRα-specific inhibitor crenolanib. Importantly LAMB1 stimulated ITG-dependent focal adhesion kinase/Src proto-oncogene non-receptor tyrosine kinase signaling. It also promoted the ITG-specific downstream target Rho-associated coiled-coil containing protein kinase 2, induced K19 expression in an autocrine manner, invadopodia formation and cell invasion. Finally, we showed that the knockdown of LAMB1 or K19 in subcutaneous xenograft mouse models resulted in significant loss of cells invading the surrounding stromal tissue and reduced HepG2 colonization into lung and liver after tail vein injection. The PDGFRα-LAMB1 pathway supports tumor progression at the invasive front of human HCC through K19 expression.Oncogene advance online publication, 7 August 2017; doi:10.1038/onc.2017.260. ispartof: Oncogene vol:36 issue:47 pages:6605-6616 ispartof: location:England status: published

Background Cutaneous melanoma is the deadliest skin cancer, with an increasing incidence and mortality rate. Currently, staging of patients with primary melanoma is performed using histological biomarkers such as tumor thickness and ulceration. As disruption of the epigenomic landscape is recognized as a widespread feature inherent in tumor development and progression, we aimed to identify novel biomarkers providing additional clinical information over current factors using unbiased genome-wide DNA methylation analyses. Methods We performed a comprehensive DNA methylation analysis during all progression stages of melanoma using Infinium HumanMethylation450 BeadChips on a discovery cohort of benign nevi (n = 14) and malignant melanoma from both primary (n = 33) and metastatic (n = 28) sites, integrating the DNA methylome with gene expression data. We validated the discovered biomarkers in three independent validation cohorts by pyrosequencing and immunohistochemistry. Results We identified and validated biomarkers for, and pathways involved in, melanoma development (e.g., HOXA9 DNA methylation) and tumor progression (e.g., TBC1D16 DNA methylation). In addition, we determined a prognostic signature with potential clinical applicability and validated PON3 DNA methylation and OVOL1 protein expression as biomarkers with prognostic information independent of tumor thickness and ulceration. Conclusions Our data underscores the importance of epigenomic regulation in triggering metastatic dissemination through the inactivation of central cancer-related pathways. Inactivation of cell-adhesion and differentiation unleashes dissemination, and subsequent activation of inflammatory and immune system programs impairs anti-tumoral defense pathways. Moreover, we identify several markers of tumor development and progression previously unrelated to melanoma, and determined a prognostic signature with potential clinical utility. Electronic supplementary material The online version of this article (doi:10.1186/s12916-017-0851-3) contains supplementary material, which is available to authorized users.

Melanoma is notorious for its cellular heterogeneity, which is at least partly due to its ability to transition between alternate cell states. Similarly to EMT, melanoma cells with a melanocytic phenotype can switch to a mesenchymal-like phenotype. However, scattered emerging evidence indicates that additional, intermediate state(s) may exist. In order to search for such new melanoma states and decipher their underlying gene regulatory network (GRN), we extensively studied ten patient-derived melanoma cultures by single-cell RNA-seq of >39,000 cells. Although each culture exhibited a unique transcriptome, we identified shared gene regulatory networks that underlie the extreme melanocytic and mesenchymal cell states, as well as one (stable) intermediate state. The intermediate state was corroborated by a distinct open chromatin landscape and governed by the transcription factors EGR3, NFATC2, and RXRG. Single-cell migration assays established that this “transition” state exhibits an intermediate migratory phenotype. Through a dense time-series sampling of single cells and dynamic GRN inference, we unraveled the sequential and recurrent arrangement of transcriptional programs at play during phenotype switching that ultimately lead to the mesenchymal cell state. We provide the scRNA-Seq data with 39,263 melanoma cells on our SCope platform and the ATAC-seq data on a UCSC hub to jointly serve as a resource for the melanoma field. Together, this exhaustive analysis of melanoma cell state diversity indicates that additional states exists between the two extreme melanocytic and mesenchymal-like states. The GRN we identified may serve as a new putative target to prevent the switch to mesenchymal cell state and thereby, acquisition of metastatic and drug resistant potential.

OBJECTIVE: The process of grouping neuronal spikes in an extracellular recording according to their neuronal sources, is generally referred to as spike sorting. Currently, the use of spike sorting is mainly limited to an offline usage, where spikes are sorted after the data acquisition has been completed. In this paper, we propose a discriminative template matching algorithm for threshold-based spike sorting on high-density extracellular data. Such threshold-based spike sorting has a low and deterministic algorithmic delay, allowing for fast online spike sorting. APPROACH: At its core, threshold-based spike sorting is driven by linear filters. The proposed discriminative template matching filter design algorithm optimizes the output signal-to-peak-interference ratio in a data-driven fashion, assuming the template of the target spike is available. The latter allows the filter to suppress the spikes of interfering neurons and to resolve spike overlap. The data-driven filter design algorithm requires only templates of the target neurons of interest, which can be retrieved, e.g. through a prior clustering on an initial recording. MAIN RESULTS: The proposed discriminative template matching filters are validated on in vivo ground truth data and are shown to provide single-unit activity with good accuracy using a simple thresholding operation on the filter outputs. SIGNIFICANCE: The low algorithmic complexity allows for computationally cheap and fast spike sorting. Also the proposed filters are guaranteed to be stable and have a deterministic delay. These characteristics make the proposed filter design method a valuable building block for online spike sorting, thereby enabling unit activity-based real-time and closed-loop experiments for high-density neural recordings. ispartof: Journal of Neural Engineering vol:15 issue:5 ispartof: location:England status: published

Malignant melanoma is one of the most aggressive cancers. Several new therapeutic strategies that focus on immuno- and/or targeted therapy have been developed, which have entered clinical trials or already been approved. This review provides an update on prognostic and predictive biomarkers in melanoma that may be used to improve the clinical management of patients. Prognostic markers include conventional histopathological characteristics, chromosomal aberrations, gene expression patterns and miRNA profiles. There is a trend towards multi-marker assays and whole-genome molecular screening methods to determine the prognosis of individual patients. Predictive biomarkers, including targeted components of signal transduction, developmental or transcriptional pathways, can be used to determine patient response towards a particular treatment or combination thereof. The rapid evolution of sequencing technologies and multi-marker screening will change the spectrum of patients who become candidates for therapeutic agents, and in addition create new ethical and regulatory challenges.

Ductular reaction (DR) represents the activation of hepatic progenitor cells (HPCs) and has been associated with features of advanced chronic liver disease; yet it is not clear whether these cells contribute to disease progression and how the composition of their micro-environment differs depending on the aetiology. This study aimed to identify HPC-associated signalling pathways relevant in different chronic liver diseases using a high-throughput sequencing approach. DR/HPCs were isolated using laser microdissection from patient samples diagnosed with HCV or primary sclerosing cholangitis (PSC), as models for hepatocellular or biliary regeneration. Key signals were validated at the protein level for a cohort of 56 patients (20 early and 36 advanced stage). In total, 330 genes were significantly differentially expressed between the HPCs in HCV and PSC. Recruitment and homing of inflammatory cells were distinctly different depending on the aetiology. HPCs in PSC were characterised by a response to oxidative stress (e.g. JUN, VNN1) and neutrophil-attractant chemokines (CXCL5, CXCL6, IL-8), whereas HPCs in HCV were identified by T- and B-lymphocyte infiltration. Moreover, we found that communication between HPCs and macrophages was aetiology driven. In PSC, a high frequency of CCL28-positive macrophages was observed in the portal infiltrate, already in early disease in the absence of advanced fibrosis, while in HCV, HPCs showed a strong expression of the macrophage scavenger receptor MARCO. Interestingly, DR/HPCs in PSC showed more deposition of ECM (e.g. FN1, LAMC2, collagens) compared to HCV, where an increase of pro-invasive genes (e.g. PDGFRA, IGF2) was observed. Additionally, endothelial cells in the vicinity of DR/HPCs showed differential immunopositivity (e.g. IGF2 and INHBA expression). In conclusion, our data shine light on the role of DR/HPCs in immune signalling, fibrogenesis and angiogenesis in chronic liver disease. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. ispartof: JOURNAL OF PATHOLOGY vol:248 issue:1 pages:66-76 ispartof: location:England status: published

Single-cell epigenomics provides new opportunities to decipher genomic regulatory programs from heterogeneous samples and dynamic processes. We present a probabilistic framework called cisTopic, to simultaneously discover “cis-regulatory topics” and stable cell states from sparse single-cell epigenomics data. After benchmarking cisTopic on single-cell ATAC-seq data, single-cell DNA methylation data, and semi-simulated single-cell ChIP-seq data, we use cisTopic to predict regulatory programs in the human brain and validate these by aligning them with co-expression networks derived from single-cell RNA-seq data. Next, we performed a time-series single-cell ATAC-seq experiment after SOX10 perturbations in melanoma cultures, where cisTopic revealed dynamic regulatory topics driven by SOX10 and AP-1. Finally, machine learning and enhancer modelling approaches allowed to predict cell type specific SOX10 and SOX9 binding sites based on topic specific co-regulatory motifs. cisTopic is available as an R/Bioconductor package at http://github.com/aertslab/cistopic.