Search

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.

Understanding how enhancers drive cell-type specificity and efficiently identifying them is essential for the development of innovative therapeutic strategies. In melanoma, the melanocytic (MEL) and the mesenchymal-like (MES) states present themselves with different responses to therapy, making the identification of specific enhancers highly relevant. Using massively parallel reporter assays (MPRAs) in a panel of patient-derived melanoma lines (MM lines), we set to identify and decipher melanoma enhancers by first focusing on regions with state-specific H3K27 acetylation close to differentially expressed genes. An in-depth evaluation of those regions was then pursued by investigating the activity of overlapping ATAC-seq peaks along with a full tiling of the acetylated regions with 190 bp sequences. Activity was observed in more than 60% of the selected regions, and we were able to precisely locate the active enhancers within ATAC-seq peaks. Comparison of sequence content with activity, using the deep learning model DeepMEL2, revealed that AP-1 alone is responsible for the MES enhancer activity. In contrast, SOX10 and MITF both influence MEL enhancer function with SOX10 being required to achieve high levels of activity. Overall, our MPRAs shed light on the relationship between long and short sequences in terms of their sequence content, enhancer activity, and specificity across melanoma cell states. ispartof: ELIFE vol:10 ispartof: location:England status: published

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.

Spike sorting is the process of assigning neural spikes in an extracellular brain recording to their putative neurons. Optimal pre-whitened template matching filters that are used in spike sorting typically suffer from ill-conditioning. In this paper, we investigate the origin of this ill-conditioning and the way in which it influences the resulting filters. Two data-driven subspace regularization approaches are proposed, and those are shown to outperform a regularization approach used in recent literature. The comparison of the methods is based on ground truth data that are recorded in-vivo. ispartof: pages:4376-4379 ispartof: 2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) vol:2019 pages:4376-4379 ispartof: 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) location:Berlin, Germany date:23 Jul - 27 Jul 2019 status: published

© 2019 IEEE. An innovative filter design method is proposed for threshold-based spike sorting of high-density neural recordings. Threshold-based spike sorting is the process of assigning each detected spike in an extracellular recording to its putative neuron, using only linear filters and simple thresholding operations. The low computational complexity of threshold-based spike sorting makes it interesting for real-time (hardware) implementations with potential applications in the field of brain-machine interfaces. The proposed method extends our earlier work on discriminative template matching and avoids the need for a prior heuristic definition of an interference covariance matrix. A new optimal filter design objective function is proposed, which automatically selects interference-dominated signal segments based on the output signal of the filter under design. This new method leads to filters that are signal-to-peak-interference ratio (SPIR) optimal. The method is validated on ground truth data recorded in-vivo. ispartof: pages:247-250 ispartof: International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering vol:2019-March pages:247-250 ispartof: 9th International IEEE/EMBS Conference on Neural Engineering (NER) location:San Francisco, USA date:20 Mar - 23 Mar 2019 status: published

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.

Transcriptional enhancers function as docking platforms for combinations of transcription factors (TFs) to control gene expression. How enhancer sequences determine nucleosome occupancy, TF recruitment and transcriptional activation in vivo remains unclear. Using ATAC–seq across a panel of Drosophila inbred strains, we found that SNPs affecting binding sites of the TF Grainy head (Grh) causally determine the accessibility of epithelial enhancers. We show that deletion and ectopic expression of Grh cause loss and gain of DNA accessibility, respectively. However, although Grh binding is necessary for enhancer accessibility, it is insufficient to activate enhancers. Finally, we show that human Grh homologs—GRHL1, GRHL2 and GRHL3—function similarly. We conclude that Grh binding is necessary and sufficient for the opening of epithelial enhancers but not for their activation. Our data support a model positing that complex spatiotemporal expression patterns are controlled by regulatory hierarchies in which pioneer factors, such as Grh, establish tissue-specific accessible chromatin landscapes upon which other factors can act. ispartof: NATURE GENETICS vol:50 issue:7 pages:1011-1020 ispartof: location:United States status: published

Identification and functional validation of oncogenic drivers are essential steps toward advancing cancer precision medicine. Here, we have presented a comprehensive analysis of the somatic genomic landscape of the widely used BRAFV600E- and NRASQ61K-driven mouse models of melanoma. By integrating the data with publically available genomic, epigenomic, and transcriptomic information from human clinical samples, we confirmed the importance of several genes and pathways previously implicated in human melanoma, including the tumor-suppressor genes phosphatase and tensin homolog (PTEN), cyclin dependent kinase inhibitor 2A (CDKN2A), LKB1, and others. Importantly, this approach also identified additional putative melanoma drivers with prognostic and therapeutic relevance. Surprisingly, one of these genes encodes the tyrosine kinase FES. Whereas FES is highly expressed in normal human melanocytes, FES expression is strongly decreased in over 30% of human melanomas. This downregulation correlates with poor overall survival. Correspondingly, engineered deletion of Fes accelerated tumor progression in a BRAFV600E-driven mouse model of melanoma. Together, these data implicate FES as a driver of melanoma progression and demonstrate the potential of cross-species oncogenomic approaches combined with mouse modeling to uncover impactful mutations and oncogenic driver alleles with clinical importance in the treatment of human cancer. ispartof: JOURNAL OF CLINICAL INVESTIGATION vol:127 issue:6 pages:2310-2325 ispartof: location:United States status: published

Single-cell RNA-seq allows building cell atlases of any given tissue and infer the dynamics of cellular state transitions during developmental or disease trajectories. Both the maintenance and transitions of cell states are encoded by regulatory programs in the genome sequence. However, this regulatory code has not yet been exploited to guide the identification of cellular states from single-cell RNA-seq data. Here we describe a computational resource, called SCENIC (Single Cell rEgulatory Network Inference and Clustering), for the simultaneous reconstruction of gene regulatory networks (GRNs) and the identification of stable cell states, using single-cell RNA-seq data. SCENIC outperforms existing approaches at the level of cell clustering and transcription factor identification. Importantly, we show that cell state identification based on GRNs is robust towards batch-effects and technical-biases. We applied SCENIC to a compendium of single-cell data from the mouse and human brain and demonstrate that the proper combinations of transcription factors, target genes, enhancers, and cell types can be identified. Moreover, we used SCENIC to map the cell state landscape in melanoma and identified a gene regulatory network underlying a proliferative melanoma state driven by MITF and STAT and a contrasting network controlling an invasive state governed by NFATC2 and NFIB. We further validated these predictions by showing that two transcription factors are predominantly expressed in early metastatic sentinel lymph nodes. In summary, SCENIC is the first method to analyze scRNA-seq data using a network-centric, rather than cell-centric approach. SCENIC is generic, easy to use, and flexible, and allows for the simultaneous tracing of genomic regulatory programs and the mapping of cellular identities emerging from these programs. Availability: SCENIC is available as an R workflow based on three new R/Bioconductor packages: GENIE3, RcisTarget and AUCell. As scalable alternative to GENIE3, we also provide GRNboost, paving the way towards the network analysis across millions of single cells.

More insight into the biological fundamentals of leukocyte platelet-rich fibrin (L-PRF) guided healing is necessary to recommend its application, in particular in deficient bone sites that need to support implants. This study investigated the short-term bone healing effect of L-PRF treatment in cylindrical non-critical sized bone defects with 3 mm diameter and 6 mm depth in tibiae of 18 adult male New Zealand White rabbits. After a randomization process, 96 bone defects were prepared and half of them were filled with a L-PRF membrane, while untreated defects in the opposite tibia served as control group. The rabbits were euthanized after 7, 14 or 28 days of healing. The bone healing of the cortical and medullary areas was investigated by micro-CT, while the expression of molecular markers (RUNX2, VEGFA, COL1A2 and BMP2) was assessed by qRT-PCR. Treatment with L-PRF did not affect the micro-structural bone characteristics of the repaired bone tissue, except for a decrease in the trabecular connectivity at the cortical level after 14 days of healing. At this time, RUNX2 and VEGFA mRNA levels were significantly lower in the treated defects. L-PRF membranes thus had a temporary negative influence on the bone microarchitecture (Tb.Pf) and on the RUNX2 and VEGFA expression during early bone healing. Overall, L-PRF treatment did not enhance bone regeneration in these non-critical size defects after 28 days. ispartof: Scientific Reports vol:7 ispartof: location:England status: published

Male gender is independently and significantly associated with poor prognosis in melanoma of all clinical stages. The biological underpinnings of this sex difference remain largely unknown, but we hypothesized that gene expression from gonosomes (sex chromosomes) might play an important role. We demonstrate that loss of the inactivated X chromosome in melanomas arising in females is strongly associated with poor distant metastasis-free survival, suggesting a dosage benefit from two X chromosomes. The gonosomal protein phosphatase 2 regulatory subunit B, beta (PPP2R3B) gene is located on the pseudoautosomal region (PAR) of the X chromosome in females and the Y chromosome in males. We observed that, despite its location on the PAR that predicts equal dosage across genders, PPP2R3B expression was lower in males than in females and was independently correlated with poor clinical outcome. PPP2R3B codes for the PR70 protein, a regulatory substrate-recognizing subunit of protein phosphatase 2A. PR70 decreased melanoma growth by negatively interfering with DNA replication and cell cycle progression through its role in stabilizing the cell division cycle 6 (CDC6)-chromatin licensing and DNA replication factor 1 (CDT1) interaction, which delays the firing of origins of DNA replication. Hence, PR70 functionally behaves as an X-linked tumor suppressor gene.

Increasing evidence suggests that cancer cells highjack developmental programs for disease initiation and progression. Melanoma arises from melanocytes that originate during development from neural crest stem cells (NCSCs). Here, we identified the transcription factor Yin Yang 1 (Yy1) as an NCSCs regulator. Conditional deletion of Yy1 in NCSCs resulted in stage-dependent hypoplasia of all major neural crest derivatives due to decreased proliferation and increased cell death. Moreover, conditional ablation of one Yy1 allele in a melanoma mouse model prevented tumorigenesis, indicating a particular susceptibility of melanoma cells to reduced Yy1 levels. Combined RNA sequencing (RNA-seq), chromatin immunoprecipitation (ChIP)-seq, and untargeted metabolomics demonstrated that YY1 governs multiple metabolic pathways and protein synthesis in both NCSCs and melanoma. In addition to directly regulating a metabolic gene set, YY1 can act upstream of MITF/c-MYC as part of a gene regulatory network controlling metabolism. Thus, both NCSC development and melanoma formation depend on an intricate YY1-controlled metabolic program. ispartof: CELL STEM CELL vol:24 issue:4 pages:637-+ ispartof: location:United States status: published

Gene regulatory networks determine cellular identity. In cancer, aberrations of gene networks are caused by driver mutations that often affect transcription factors and chromatin modifiers. Nevertheless, gene transcription in cancer follows the same cis-regulatory rules as normal cells, and cancer cells have served as convenient model systems to study transcriptional regulation. Tumours often show regulatory heterogeneity, with subpopulations of cells in different transcriptional states, which has important therapeutic implications. Here, we review recent experimental and computational techniques to reverse engineer cancer gene networks using transcriptome and epigenome data. New algorithms, data integration strategies, and increasing amounts of single cell genomics data provide exciting opportunities to model dynamic regulatory states at unprecedented resolution. publisher: Elsevier articletitle: Decoding transcriptional states in cancer journaltitle: Current Opinion in Genetics & Development articlelink: http://dx.doi.org/10.1016/j.gde.2017.01.003 content_type: article copyright: © 2017 Published by Elsevier Ltd. ispartof: CURRENT OPINION IN GENETICS & DEVELOPMENT vol:43 pages:82-92 ispartof: location:England status: published

Background: Tumour budding, described as the presence of single cells or small clusters of up to five tumour cells at the invasive margin, is established as a prognostic marker in colorectal carcinoma. In the present study, we aimed to investigate the molecular signature of tumour budding cells and the corresponding tumour bulk. Methods: Tumour bulk and budding areas were microdissected and processed for RNA-sequencing. As little RNA was obtained from budding cells, a special low-input mRNA library preparation protocol was used. Gene expression profiles of budding as compared with tumour bulk were investigated for established EMT signatures, consensus molecular subtype (CMS), gene set enrichment and pathway analysis. Results: A total of 296 genes were differentially expressed with an FDR

Background & Aims Cancer stem cells (CSCs) are thought to be persistent in tumours due to their chemoresistance and to cause relapse and metastasis. Hepatic carcinomas displaying hepatic progenitor cell (HPC) features have been associated with a poor prognosis, though it remains unclear how CSCs relate to these different histological subtypes. Methods Candidate CSCs were isolated using the side population (SP) technique from primary tissue samples diagnosed as keratin(K)19-negative or -positive hepatocellular carcinoma (HCC) or as combined hepatocellular/cholangiocarcinoma and analysed for gene and protein expression. The effect of laminin-332 was analysed in vitro by using HCC cell lines and in vivo using a xenograft mouse model. Results The size of the SP correlated with the degree of HPC features found in human hepatic cancer, and also showed an elevated mRNA expression of biliary/HPC markers and the extracellular matrix marker LAMC2 , the gene encoding the laminin γ2-chain. Immunopositivity for the γ2-chain of laminin-332 was seen in the extracellular matrix surrounding small HPC-like tumour cells with a low proliferation rate. In vitro , laminin-332 increased K19 expression, phosphorylated mTOR and decreased phospho-histone H3 expression, indicating reduced cell mitosis. The effect of laminin-332 was enhanced upon mTORC1 inhibition and diminished when inhibiting mTORC1+C2. Resistance to doxorubicin and sorafenib treatment, and the SP fraction increased in the coated condition. In vivo , laminin-332 reduced tumour growth and sustained K19 expression. Conclusions In this study we identified a prominent role for laminin-332 as part of the specialised CSC niche in maintaining and supporting cell ‘stemness', which leads to chemoresistance and quiescence.

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.

Purpose Fuchs' endothelial corneal dystrophy (FECD) is a degenerative eye disorder affecting 4% of Americans older than 40. It is the leading indication for corneal endothelial (CE) transplantation for which there is a global donor shortage. This study aimed to gain further insight into the pathophysiology of FECD and identify targets for nonsurgical therapy. Methods CE from patients with late-onset FECD was compared with that of normal controls using microarray expression analysis (n = 4 FECD, n = 4 normal), reverse transcriptase quantitative PCR (n = 9 FECD, n = 8 normal), and immunohistology (n = 55 FECD, n = 15 normal). Results This led to the identification of circulating fibrocytes and their dendritic derivatives in all examined CE samples with FECD (in all clinical stages of symptomatic FECD and independent of prior cataract surgery). These cells were not present in normal CE. In this study we characterize their morphology, protein expression profile, number, and localization within the CE layer of patients with FECD. Conclusions Circulating fibrocytes and their dendritic derivatives are a new aspect of FECD that deserves further investigation. Because they are known to cause fibrosis in a variety of organs, they may play a similar role in FECD and might be a valuable target for nonsurgical therapy.

International audience; Focal amplifications of chromosome 3p13-3p14 occur in about 10% of melanomas and are associated with a poor prognosis. The melanoma-specific oncogene MITF resides at the epicentre of this amplicon. However, whether other loci present in this amplicon also contribute to melanomagenesis is unknown. Here we show that the recently annotated long non-coding RNA (lncRNA) gene SAMMSON is consistently co-gained with MITF. In addition, SAMMSON is a target of the lineage-specific transcription factor SOX10 and its expression is detectable in more than 90% of human melanomas. Whereas exogenous SAMMSON increases the clonogenic potential in trans, SAMMSON knockdown drastically decreases the viability of melanoma cells irrespective of their transcriptional cell state and BRAF, NRAS or TP53 mutational status. Moreover, SAMMSON targeting sensitizes melanoma to MAPK-targeting therapeutics both in vitro and in patient-derived xenograft models. Mechanistically, SAMMSON interacts with p32, a master regulator of mitochondrial homeostasis and metabolism, to increase its mitochondrial targeting and pro-oncogenic function. Our results indicate that silencing of the lineage addiction oncogene SAMMSON disrupts vital mitochondrial functions in a cancer-cell-specific manner; this silencing is therefore expected to deliver highly effective and tissue-restricted anti-melanoma therapeutic responses.

Contains fulltext : 171198.pdf (Publisher’s version ) (Closed access) Melanoma is not only one of the most immunogenic cancers but also one of the most effective cancers at subverting host immunity. The role of T lymphocytes in tumor immunity has been extensively studied in melanoma, whereas less is known about the importance of B lymphocytes. The effects of plasma cells (PCs), in particular, are still obscure. The aim of this study was to characterize pathological features and clinical outcome of primary cutaneous melanomas associated with PCs. Moreover, we investigated the origins of the melanoma-associated PCs. Finally, we studied the outcome of patients with primary melanomas with PCs. We reviewed 710 melanomas to correlate the presence of PCs with histological prognostic markers. Immunohistochemistry for CD138 and heavy and light chains was performed in primary melanomas (PM) and in loco-regional lymph nodes (LN), both metastatic and not metastatic. In three PM and nine LN with frozen material, VDJ-rearrangement was analyzed by Gene Scan Analysis. Survival analysis was performed on a group of 85 primary melanomas >2 mm in thickness. Forty-one cases (3.7%) showed clusters/sheets of PCs. PC-rich melanomas occurred at an older age and were thicker, more often ulcerated and more mitotically active (P