ADAMTS12 is a stromal modulator in chronic liver disease.

Adamalysins, a family of metalloproteinases containing a disintegrin and metalloproteinases (ADAMs) and ADAM with thrombospondin motifs (ADAMTSs), belong to the matrisome and play important roles in various biological and pathological processes, such as development, immunity and cancer. Using a liver cancer dataset from the International Cancer Genome Consortium, we developed an extensive in silico screening that identified a cluster of adamalysins co-expressed in livers from patients with hepatocellular carcinoma (HCC). Within this cluster, ADAMTS12 expression was highly associated with recurrence risk and poorly differentiated HCC signatures. We showed that ADAMTS12 was expressed in the stromal cells of the tumor and adjacent fibrotic tissues of HCC patients, and more specifically in activated stellate cells. Using a mouse model of carbon tetrachloride-induced liver injury, we showed that Adamts12 was strongly and transiently expressed after a 24 h acute treatment, and that fibrosis was exacerbated in Adamts12-null mice submitted to carbon tetrachloride-induced chronic liver injury. Using the HSC-derived LX-2 cell line, we showed that silencing of ADAMTS12 resulted in profound changes of the gene expression program. In particular, genes previously reported to be induced upon HSC activation, such as PAI-1, were mostly down-regulated following ADAMTS12 knock-down. The phenotype of these cells was changed to a less differentiated state, showing an altered actin network and decreased nuclear spreading. These phenotypic changes, together with the down-regulation of PAI-1, were offset by TGF-ß treatment. The present study thus identifies ADAMTS12 as a modulator of HSC differentiation, and a new player in chronic liver disease.

Phylogenetic inference of the emergence of sequence modules and protein-protein interactions in the ADAMTS-TSL family.

Numerous computational methods based on sequences or structures have been developed for the characterization of protein function, but they are still unsatisfactory to deal with the multiple functions of multi-domain protein families. Here we propose an original approach based on 1) the detection of conserved sequence modules using partial local multiple alignment, 2) the phylogenetic inference of species/genes/modules/functions evolutionary histories, and 3) the identification of co-appearances of modules and functions. Applying our framework to the multidomain ADAMTS-TSL family including ADAMTS (A Disintegrin-like and Metalloproteinase with ThromboSpondin motif) and ADAMTS-like proteins over nine species including human, we identify 45 sequence module signatures that are associated with the occurrence of 278 Protein-Protein Interactions in ancestral genes. Some of these signatures are supported by published experimental data and the others provide new insights (e.g. ADAMTS-5). The module signatures of ADAMTS ancestors notably highlight the dual variability of the propeptide and ancillary regions suggesting the importance of these two regions in the specialization of ADAMTS during evolution. Our analyses further indicate convergent interactions of ADAMTS with COMP and CCN2 proteins. Overall, our study provides 186 sequence module signatures that discriminate distinct subgroups of ADAMTS and ADAMTSL and that may result from selective pressures on novel functions and phenotypes.

Discrete modeling for integration and analysis of large-scale signaling networks.

Most biological processes are orchestrated by large-scale molecular networks which are described in large-scale model repositories and whose dynamics are extremely complex. An observed phenotype is a state of this system that results from control mechanisms whose identification is key to its understanding. The Biological Pathway Exchange (BioPAX) format is widely used to standardize the biological information relative to regulatory processes. However, few modeling approaches developed so far enable for computing the events that control a phenotype in large-scale networks. Here we developed an integrated approach to build large-scale dynamic networks from BioPAX knowledge databases in order to analyse trajectories and to identify sets of biological entities that control a phenotype. The Cadbiom approach relies on the guarded transitions formalism, a discrete modeling approach which models a system dynamics by taking into account competition and cooperation events in chains of reactions. The method can be applied to every BioPAX (large-scale) model thanks to a specific package which automatically generates Cadbiom models from BioPAX files. The Cadbiom framework was applied to the BioPAX version of two resources (PID, KEGG) of the Pathway Commons database and to the Atlas of Cancer Signalling Network (ACSN). As a case-study, it was used to characterize sets of biological entities implicated in the epithelial-mesenchymal transition. Our results highlight the similarities between the PID and ACSN resources in terms of biological content, and underline the heterogeneity of usage of the BioPAX semantics limiting the fusion of models that require curation. Causality analyses demonstrate the smart complementarity of the databases in terms of combinatorics of controllers that explain a phenotype. From a biological perspective, our results show the specificity of controllers for epithelial and mesenchymal phenotypes that are consistent with the literature and identify a novel signature for intermediate states.

Constructing xenobiotic maps of metabolism to predict enzymes catalyzing metabolites capable of binding to DNA.

BACKGROUND: The liver plays a major role in the metabolic activation of xenobiotics (drugs, chemicals such as pollutants, pesticides, food additives...). Among environmental contaminants of concern, heterocyclic aromatic amines (HAA) are xenobiotics classified by IARC as possible or probable carcinogens (2A or 2B). There exist little information about the effect of these HAA in humans. While HAA is a family of more than thirty identified chemicals, the metabolic activation and possible DNA adduct formation have been fully characterized in human liver for only a few of them (MeIQx, PhIP, A[Formula: see text]C). RESULTS: We have developed a modeling approach in order to predict all the possible metabolites of a xenobiotic and enzymatic profiles that are linked to the production of metabolites able to bind DNA. Our prediction of metabolites approach relies on the construction of an enriched and annotated map of metabolites from an input metabolite.The pipeline assembles reaction prediction tools (SyGMa), sites of metabolism prediction tools (Way2Drug, SOMP and Fame 3), a tool to estimate the ability of a xenobotics to form DNA adducts (XenoSite Reactivity V1), and a filtering procedure based on Bayesian framework. This prediction pipeline was evaluated using caffeine and then applied to HAA. The method was applied to determine enzymes profiles associated with the maximization of metabolites derived from each HAA which are able to bind to DNA. The classification of HAA according to enzymatic profiles was consistent with their chemical structures. CONCLUSIONS: Overall, a predictive toxicological model based on an in silico systems biology approach opens perspectives to estimate the genotoxicity of various chemical classes of environmental contaminants. Moreover, our approach based on enzymes profile determination opens the possibility of predicting various xenobiotics metabolites susceptible to bind to DNA in both normal and physiopathological situations.

A pipeline to create predictive functional networks: application to the tumor progression of hepatocellular carcinoma.

BACKGROUND: Integrating genome-wide gene expression patient profiles with regulatory knowledge is a challenging task because of the inherent heterogeneity, noise and incompleteness of biological data. From the computational side, several solvers for logic programs are able to perform extremely well in decision problems for combinatorial search domains. The challenge then is how to process the biological knowledge in order to feed these solvers to gain insights in a biological study. It requires formalizing the biological knowledge to give a precise interpretation of this information; currently, very few pathway databases offer this possibility. RESULTS: The presented work proposes an automatic pipeline to extract automatically regulatory knowledge from pathway databases and generate novel computational predictions related to the state of expression or activity of biological molecules. We applied it in the context of hepatocellular carcinoma (HCC) progression, and evaluate the precision and the stability of these computational predictions. Our working base is a graph of 3383 nodes and 13,771 edges extracted from the KEGG database, in which we integrate 209 differentially expressed genes between low and high aggressive HCC across 294 patients. Our computational model predicts the shifts of expression of 146 initially non-observed biological components. Our predictions were validated at 88% using a larger experimental dataset and cross-validation techniques. In particular, we focus on the protein complexes predictions and show for the first time that NFKB1/BCL-3 complexes are activated in aggressive HCC. In spite of the large dimension of the reconstructed models, our analyses over the computational predictions discover a well constrained region where KEGG regulatory knowledge constrains gene expression of several biomolecules. These regions can offer interesting windows to perturb experimentally such complex systems. CONCLUSION: This new pipeline allows biologists to develop their own predictive models based on a list of genes. It facilitates the identification of new regulatory biomolecules using knowledge graphs and predictive computational methods. Our workflow is implemented in an automatic python pipeline which is publicly available at https://github.com/LokmaneChebouba/key-pipeand contains as testing data all the data used in this paper.

Integration of miRNA-regulatory networks in hepatic stellate cells identifies TIMP3 as a key factor in chronic liver disease.

BACKGROUND & AIMS: Activation of hepatic stellate cells (HSC) is a critical process involved in liver fibrosis. Several miRNAs are implicated in gene regulation during this process but their exact and respective contribution is still incompletely understood. Here we propose an integrative approach of miRNA-regulatory networks to predict new targets. METHODS: miRNA regulatory networks in activated HSCs were built using lists of validated miRNAs and the CyTargetLinker tool. The resulting graphs were filtered according to public transcriptomic data and the reduced graphs were analysed through GO annotation. A miRNA network regulating the expression of TIMP3 was further studied in human liver samples, isolated hepatic cells and mouse model of liver fibrosis. RESULTS: Within the up-regulated miRNAs, we identified a subnetwork of five miRNAs (miR-21-5p, miR-222-3p, miR-221-3p miR-181b-5p and miR-17-5p) that target TIMP3. We demonstrated that TIMP3 expression is inversely associated with inflammatory activity and IL1-ß expression in vivo. We further showed that IL1-ß inhibits TIMP3 expression in HSC-derived LX-2 cells. Using data from The Cancer Genome Atlas (TCGA), we showed that, in hepatocellular carcinoma (HCC), TIMP3 expression is associated with survival (P < .001), while miR-221 (P < .05), miR-222 (P < .01) and miR-181b (P < .01) are markers for a poor prognosis. CONCLUSIONS: Several miRNAs targeting TIMP3 are up-regulated in activated HSCs and down-regulation of TIMP3 expression is associated with inflammatory activity in liver fibrosis and poor prognosis in HCC. The regulatory network including specific miRNAs and TIMP3 is therefore central for the evolution of chronic liver disease.

Increasing 3D Matrix Rigidity Strengthens Proliferation and Spheroid Development of Human Liver Cells in a Constant Growth Factor Environment.

Mechanical forces influence the growth and shape of virtually all tissues and organs. Recent studies show that increased cell contractibility, growth and differentiation might be normalized by modulating cell tensions. Particularly, the role of these tensions applied by the extracellular matrix during liver fibrosis could influence the hepatocarcinogenesis process. The objective of this study is to determine if 3D stiffness could influence growth and phenotype of normal and transformed hepatocytes and to integrate extracellular matrix (ECM) stiffness to tensional homeostasis. We have developed an appropriate 3D culture model: hepatic cells within three-dimensional collagen matrices with varying rigidity. Our results demonstrate that the rigidity influenced the cell phenotype and induced spheroid clusters development whereas in soft matrices, Huh7 transformed cells were less proliferative, well-spread and flattened. We confirmed that ERK1 played a predominant role over ERK2 in cisplatin-induced death, whereas ERK2 mainly controlled proliferation. As compared to 2D culture, 3D cultures are associated with epithelial markers expression. Interestingly, proliferation of normal hepatocytes was also induced in rigid gels. Furthermore, biotransformation activities are increased in 3D gels, where CYP1A2 enzyme can be highly induced/activated in primary culture of human hepatocytes embedded in the matrix. In conclusion, we demonstrated that increasing 3D rigidity could promote proliferation and spheroid developments of liver cells demonstrating that 3D collagen gels are an attractive tool for studying rigidity-dependent homeostasis of the liver cells embedded in the matrix and should be privileged for both chronic toxicological and pharmacological drug screening.

Integrative analysis of high-throughput RNAi screen data identifies the FER and CRKL tyrosine kinases as new regulators of the mitogenic ERK-dependent pathways in transformed cells.

BACKGROUND: Cell proliferation is a hallmark of cancer and depends on complex signaling networks that are chiefly supported by protein kinase activities. Therapeutic strategies have been used to target specific kinases but new methods are required to identify combined targets and improve treatment. Here, we propose a small interfering RNA genetic screen and an integrative approach to identify kinase networks involved in the proliferation of cancer cells. RESULTS: The functional siRNA screen of 714 kinases in HeLa cells identified 91 kinases implicated in the regulation of cell growth, most of them never being reported in previous whole-genome siRNA screens. Based on gene ontology annotations, we have further discriminated between two classes of kinases that, when suppressed, result in alterations of the mitotic index and provoke cell-cycle arrest. Extinguished kinases that lead to a low mitotic index mostly include kinases implicated in cytosolic signaling. In contrast, extinguished kinases that result in a high mitotic index mostly include kinases implicated in cell division. By mapping hit kinases in the PhosphPOINT phosphoprotein database, we generated scale-free networks consisting of 449 and 661 protein-protein interactions for kinases from low MI and high MI groups, respectively. Further analyses of the kinase interactomes revealed specific modules such as FER- and CRKL-containing modules that connect three members of the epidermal growth factor receptor (EGFR) family, suggesting a tight control of the mitogenic EGF-dependent pathway. Based on experimental studies, we confirm the involvement of these two kinases in the regulation of tumor cell growth. CONCLUSION: Based on a combined approach of large kinome-wide siRNA screens and ontology annotations, our study identifies for the first time two kinase groups differentially implicated in the control of cell proliferation. We further demonstrate that integrative analysis of the kinase interactome provides key information which can be used to facilitate or optimize target design for new therapeutic strategies. The complete list of protein-protein interactions from the two functional kinase groups will provide a useful database for future investigations.

MAPK signaling in cisplatin-induced death: predominant role of ERK1 over ERK2 in human hepatocellular carcinoma cells.

Hepatocellular carcinoma treatment by arterial infusion of cis-diamminedichloroplatinum-II (cisplatin) exhibits certain therapeutic efficacy. However, optimizations are required and the mechanisms underlying cisplatin proapoptotic effect remain unclear. The mitogen-activated protein kinase (MAPK) pathway plays a key role in cell response to cisplatin and the functional specificity of the isoform MAPK/ERK kinase 1 and 2 (MEK1/2) and ERK1/2 could influence this response. The individual contribution of each kinase on cisplatin-induced death was thus analyzed after a transient or stable specific inhibition by RNA interference in the human hepatocellular carcinoma cells Huh-7 or in knockout mice. We demonstrated here that ERK1 played a predominant role over ERK2 in cisplatin-induced death, whereas MEK1 and MEK2 acted in a redundant manner. Indeed, at clinically relevant concentrations of cisplatin, ERK1 silencing alone was sufficient to protect cells from cisplatin-induced death both in vitro, in Huh-7 cells and ERK1(-/-) hepatocytes, and in vivo, in ERK1-deficient mice. Moreover, we showed that ERK1 activity correlated with the induction level of the proapoptotic BH3-only protein Noxa, a critical mediator of cisplatin toxicity. On the contrary, ERK2 inhibition upregulated ERK1 activity, favored Noxa induction and sensitized hepatocarcinoma cells to cisplatin. Our results point to a crucial role of ERK1 in cisplatin-induced proapoptotic signal and lead us to propose that ERK2-specific targeting could improve the efficacy of cisplatin therapy by increasing ERK1 prodeath functions.

The complexity of ERK1 and ERK2 MAPKs in multiple hepatocyte fate responses.

Recent reports suggest that extracellular signal-regulated kinase (ERK1) and ERK2 mitogen-activated protein kinases (MAPK) may direct specific biological functions under certain contexts. In this study, we investigated the role of early and sustained epidermal growth factor (EGF) stimulation on long-term hepatocyte differentiation and the possible role of ERK1 and ERK2 in this process. We demonstrate a long-term survival and an elevated level of differentiation up to 3 weeks. The differentiation state of hepatocytes is supported by sustained expression of aldolase B, albumin, and the detoxifying enzymes CYP1A2, 2B2, and 3A23. Similarly to freshly isolated cells, cultured hepatocytes also retain the ability to respond to 3-methylcholanthrene (3MC) and phenobarbital (PB), two known CYP inducers. In addition, we show evidence that continuous MAPK/ERK kinase (MEK) inhibition enhances the level of differentiation. Using RNA interference approaches against ERK1 and ERK2, we demonstrate that this effect requires both ERK1 and ERK2 activity, whereas the specific ERK1 knockdown promotes cell survival and the specific ERK2 knockdown regulates cell proliferation. In conclusion, we demonstrate that early and sustained EGF stimulation greatly extends long-term hepatocyte survival and differentiation, and that inhibition of the ERK1/2 MAPK pathway potentiates these pro-survival/pro-differentiation phenotypes. We clearly attest that specific ERK1 and ERK2 MAPKs determine hepatocyte survival and proliferation, respectively, whereas dual inhibition is required to stabilize a highly differentiated state.

Protease profiling of liver fibrosis reveals the ADAM metallopeptidase with thrombospondin type 1 motif, 1 as a central activator of transforming growth factor beta.

UNLABELLED: During chronic liver disease, tissue remodeling leads to dramatic changes and accumulation of matrix components. Matrix metalloproteases and their inhibitors have been involved in the regulation of matrix degradation. However, the role of other proteases remains incompletely defined. We undertook a gene-expression screen of human liver fibrosis samples using a dedicated gene array selected for relevance to protease activities, identifying the ADAMTS1 (A Disintegrin And Metalloproteinase [ADAM] with thrombospondin type 1 motif, 1) gene as an important node of the protease network. Up-regulation of ADAMTS1 in fibrosis was found to be associated with hepatic stellate cell (HSC) activation. ADAMTS1 is synthesized as 110-kDa latent forms and is processed by HSCs to accumulate as 87-kDa mature forms in fibrotic tissues. Structural evidence has suggested that the thrombospondin motif-containing domain from ADAMTS1 may be involved in interactions with, and activation of, the major fibrogenic cytokine, transforming growth factor beta (TGF-ß). Indeed, we observed direct interactions between ADAMTS1 and latency-associated peptide-TGF-ß (LAP-TGF-ß). ADAMTS1 induces TGF-ß activation through the interaction of the ADAMTS1 KTFR peptide with the LAP-TGF-ß LKSL peptide. Down-regulation of ADAMTS1 in HSCs decreases the release of TGF-ß competent for transcriptional activation, and KTFR competitor peptides directed against ADAMTS1 block the HSC-mediated release of active TGF-ß. Using a mouse liver fibrosis model, we show that carbon tetrachloride treatment induces ADAMTS1 expression in parallel to that of type I collagen. Importantly, concurrent injection of the KTFR peptide prevents liver damage. CONCLUSION: Our results indicate that up-regulation of ADAMTS1 in HSCs constitutes a new mechanism for control of TGF-ß activation in chronic liver disease.

The disintegrin and metalloproteinase ADAM12 contributes to TGF-beta signaling through interaction with the type II receptor.

Transforming growth factor-beta (TGF-beta) regulates a wide variety of biological processes through two types of Ser/Thr transmembrane receptors: the TGF-beta type I receptor and the TGF-beta type II receptor (TbetaRII). Upon ligand binding, TGF-beta type I receptor activated by TbetaRII propagates signals to Smad proteins, which mediate the activation of TGF-beta target genes. In this study, we identify ADAM12 (a disintegrin and metalloproteinase 12) as a component of the TGF-beta signaling pathway that acts through association with TbetaRII. We found that ADAM12 functions by a mechanism independent of its protease activity to facilitate the activation of TGF-beta signaling, including the phosphorylation of Smad2, association of Smad2 with Smad4, and transcriptional activation. Furthermore, ADAM12 induces the accumulation of TbetaRII in early endosomal vesicles and stabilizes the TbetaRII protein presumably by suppressing the association of TbetaRII with Smad7. These results define ADAM12 as a new partner of TbetaRII that facilitates its trafficking to early endosomes in which activation of the Smad pathway is initiated.

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns.

BACKGROUND: Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods. RESULTS: Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values. CONCLUSIONS: Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks.

ADAM and ADAMTS Proteins, New Players in the Regulation of Hepatocellular Carcinoma Microenvironment.

The tumor microenvironment plays a major role in tumor growth, invasion and resistance to chemotherapy, however understanding how all actors from microenvironment interact together remains a complex issue. The tumor microenvironment is classically represented as three closely connected components including the stromal cells such as immune cells, fibroblasts, adipocytes and endothelial cells, the extracellular matrix (ECM) and the cytokine/growth factors. Within this space, proteins of the adamalysin family (ADAM for a disintegrin and metalloproteinase; ADAMTS for ADAM with thrombospondin motifs; ADAMTSL for ADAMTS-like) play critical roles by modulating cell-cell and cell-ECM communication. During last decade, the implication of adamalysins in the development of hepatocellular carcinoma (HCC) has been supported by numerous studies however the functional characterization of most of them remain unsettled. In the present review we propose both an overview of the literature and a meta-analysis of adamalysins expression in HCC using data generated by The Cancer Genome Atlas (TCGA) Research Network.

Integrin-αV-mediated activation of TGF-ß regulates anti-tumour CD8 T cell immunity and response to PD-1 blockade.

TGF-ß is secreted in the tumour microenvironment in a latent, inactive form bound to latency associated protein and activated by the integrin αV subunit. The activation of latent TGF-ß by cancer-cell-expressed αV re-shapes the tumour microenvironment, and this could affect patient responses to PD-1-targeting therapy. Here we show, using multiplex immunofluorescence staining in cohorts of anti-PD-1 and anti-PD-L1-treated lung cancer patients, that decreased expression of cancer cell αV is associated with improved immunotherapy-related, progression-free survival, as well as with an increased density of CD8+CD103+ tumour-infiltrating lymphocytes. Mechanistically, tumour αV regulates CD8 T cell recruitment, induces CD103 expression on activated CD8+ T cells and promotes their differentiation to granzyme B-producing CD103+CD69+ resident memory T cells via autocrine TGF-ß signalling. Thus, our work provides the underlying principle of targeting cancer cell αV for more efficient PD-1 checkpoint blockade therapy.

Interleukin-33 overexpression is associated with liver fibrosis in mice and humans.

Interleukin-33 (IL-33), the most recently identified member of the IL-1 family, induces synthesis of T Helper 2 (Th2)-type cytokines via its heterodimeric ST2/IL-1RAcP receptor. Th2-type cytokines play an important role in fibrosis; thus, we investigated the role of IL-33 in liver fibrosis. IL-33, ST2 and IL-1RAcP gene expression was analysed in mouse and human normal (n= 6) and fibrotic livers (n= 28), and in human hepatocellular carcinoma (HCC; n= 22), using real-time PCR. IL-33 protein was detected in normal and fibrotic liver sections and in isolated liver cells using Western blotting and immunolocalization approaches. Our results showed that IL-33 and ST2 mRNA was overproduced in mouse and human fibrotic livers, but not in human HCC. IL-33 expression correlated with ST2 expression and also with collagen expression in fibrotic livers. The major sources of IL-33 in normal liver from both mice and human beings are the liver sinusoidal endothelial cells and, in fibrotic liver, the activated hepatic stellate cells (HSC). Moreover, IL-33 expression was increased in cultured HSC when stimulated by pro-inflammatory cytokines. In conclusion, IL-33 is strongly associated with fibrosis in chronic liver injury and activated HSC are a source of IL-33.

Fibrillar collagen scoring by second harmonic microscopy: a new tool in the assessment of liver fibrosis.

BACKGROUND & AIMS: Imaging of supramolecular structures by multiphoton microscopy offers significant advantages for studying specific fibrillar compounds in biological tissues. In this study, we aimed to demonstrate the relevance of Second Harmonic Generation (SHG) for assessing and quantifying, without staining, fibrillar collagen in liver fibrosis. METHODS: We first showed the relationship between SHG signal and collagen forms over-produced and accumulated during fibrosis progression. Taking this property into consideration, we developed an innovative method to precisely quantify the fibrosis area in histological slices by scoring of fibrillar collagen deposits (Fibrosis-SHG index). RESULTS: The scoring method was routinely applied to 119 biopsies from patients with chronic liver disease allowing a fast and accurate measurement of fibrosis correlated with the Fibrosis-Metavir score (rho=0.75, p<0.0001). The technique allowed discriminating patients with advanced (moderate to severe) fibrosis (AUROC=0.88, p<0.0001) and cirrhosis (AUROC=0.89, p<0.0001). Taking advantage of its continuous gradation, the Fibrosis-SHG index also allowed the discrimination of several levels of fibrosis within the same F-Metavir stage. The SHG process presented several advantages such as a high reliability and sensitivity that lead to a standardized evaluation of hepatic fibrosis in liver biopsies without staining and pathological examination. CONCLUSIONS: Second harmonic microscopy emerges as an original and powerful tool in the assessment of liver fibrosis and offers new possibilities for the evaluation of experimental protocols. We expect that this technology could easily be applicable in the study of other fibro-proliferative pathologies.

CX3CL1/fractalkine shedding by human hepatic stellate cells: contribution to chronic inflammation in the liver.

Chemokines are the inflammatory mediators that modulate liver fibrosis, a common feature of chronic inflammatory liver diseases. CX3CL1/fractalkine is a membrane-associated chemokine that requires step processing for chemotactic activity and has been recently implicated in liver disease. Here, we investigated the potential shedding activities involved in the release of the soluble chemotactic peptides from CX3CL1 in the injured liver. We showed an increased expression of the sheddases ADAM10 and ADAM17 in patients with chronic liver diseases that was associated with the severity of liver fibrosis. We demonstrated that hepatic stellate cells (HSC) were an important source of ADAM10 and ADAM17 and that treatment with the inflammatory cytokine inter-feron-gamma induced the expression of CX3CL1 and release of soluble peptides. This release was inhibited by the metalloproteinase inhibitor batimastat; however, ADAM10/ADAM17 inhibitor GW280264X only partially affected shedding activity. By using selective tissue metalloprotease inhibitors and overexpression analyses, we showed that CX3CL1 was mainly processed by matrix metalloproteinase (MMP)-2, a metalloprotease highly expressed by HSC. We further demonstrated that the CX3CL1 soluble peptides released from stimulated HSC induced the activation of the CX3CR1-dependent signalling pathway and promoted chemoattraction of monocytes in vitro. We conclude that ADAM10, ADAM17 and MMP-2 synthesized by activated HSC mediate CX3CL1 shedding and release of chemotactic peptides, thereby facilitating recruitment of inflammatory cells and paracrine stimulation of HSC in chronic liver diseases.

In silico prediction of Heterocyclic Aromatic Amines metabolism susceptible to form DNA adducts in humans.

Heterocyclic Aromatic Amines (HAAs) are environmental and food contaminants that are classified as probable or possible carcinogens by the International Agency for Research on Cancer. Thirty different HAAs have been identified. However the metabolism of only three of them have been fully characterized in human hepatocytes: AαC (2-amino-9H-pyrido[2,3-b]indole), MeIQx (2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline) and PhIP (2-amino-1-methyl-6-phenyl-imidazo[4,5-b]pyridine). In this study, we use an integrative approach to accurately predict the biotransformation of 30 HAAs into DNA reactive and non DNA reactive compounds. We first build predicted metabolites networks by iterating a knowledge-based expert system of prediction of metabolic reactions based on fingerprint similarities. Next, we combine several methods for predicting Sites Of Metabolism (SOM) in order to reduce the metabolite reaction graphs and to predict the metabolites reactive with DNA. We validate the method by comparing the experimental versus predicted data for the known AαC, MeIQx and PhIP metabolism. 28 of the 30 experimentally determined metabolites are well predicted and 9 of the 10 metabolites known to form DNA adducts are predicted with a high probability to be reactive with DNA. Applying our approach to the 27 unknown HAAs, we generate maps for the metabolic biotransformation of each HAA, including new metabolites with a high-predicted DNA reactivity, which can be further explored through an user-friendly and interactive web interface.

MiR-146a is over-expressed and controls IL-6 production in cystic fibrosis macrophages.

Cystic fibrosis (CF) is an inherited disease that is characterised by susceptibility to bacterial infections and chronic lung inflammation. Recently, it was suggested that macrophages contribute to impaired host defence and excessive inflammatory responses in CF. Indeed, dysfunction attributed to CF macrophages includes decreased bacterial killing and exaggerated inflammatory responses. However, the mechanisms behind such defects have only been partially defined. MicroRNAs (miRNAs) have emerged as key regulators of several macrophage functions, including their activation, differentiation and polarisation. The goal of this study was to investigate whether miRNA dysregulation underlies the functional abnormalities of CF macrophages. MiRNA profiling of macrophages was performed, with 22 miRNAs identified as differentially expressed between CF and non-CF individuals. Among these, miR-146a was associated with significant enrichment of validated target genes involved in responses to microorganisms and inflammation. As miR-146a dysregulation has been reported in several human inflammatory diseases, we analysed the impact of increased miR-146a expression on inflammatory responses of CF macrophages. These data show that inhibition of miR-146a in lipopolysaccharide-stimulated CF macrophages results in increased interleukin-6 production, which suggests that miR-146a overexpression in CF is functional, to restrict inflammatory responses.