Including osteoprotegerin and collagen IV in a score-based blood test for liver fibrosis increases diagnostic accuracy

BACKGROUND: Noninvasive methods for liver fibrosis evaluation in chronic liver diseases have been recently developed, i.e. transient elastography (Fibroscan™) and blood tests (Fibrometer®, Fibrotest®, and Hepascore®). In this study, we aimed to design a new score in chronic hepatitis C (CHC) by selecting blood markers in a large panel and we compared its diagnostic performance with those of other noninvasive methods. METHODS: Sixteen blood tests were performed in 306 untreated CHC patients included in a multicenter prospective study (ANRS HC EP 23 Fibrostar) using METAVIR histological fibrosis stage as reference. The new score was constructed by non linear regression using the most accurate biomarkers. RESULTS: Five markers (alpha-2-macroglobulin, apolipoprotein-A1, AST, collagen IV and osteoprotegerin) were included in the new function called Coopscore©. Using the Obuchowski Index, Coopscore© shows higher diagnostic performances than for Fibrometer®, Fibrotest®, Hepascore® and Fibroscan™ in CHC. Association between Fibroscan™ and Coopscore© might avoid 68% of liver biopsies for the diagnosis of significant fibrosis. CONCLUSION: Coopscore© provides higher accuracy than other noninvasive methods for the diagnosis of liver fibrosis in CHC. The association of Coopscore© with Fibroscan™ increases its predictive value

Endothelin-1 enhances fibrogenic gene expression, but does not promote DNA synthesis or apoptosis in hepatic stellate cells

BACKGROUND: In liver injury, the pool of hepatic stellate cell (HSC) increases and produces extracellular matrix proteins, decreasing during the resolution of fibrosis. The profibrogenic role of endothelin-1 (ET-1) in liver fibrosis remains disputed. We therefore studied the effect of ET-1 on proliferation, apoptosis and profibrogenic gene expression of HSCs. RESULTS: First passage HSC predominantly expressed endothelin A receptor (ETAR) mRNA and 4th passage HSC predominantly expressed the endothelin B receptor (ETBR) mRNA. ET-1 had no effect on DNA synthesis in 1st passage HSC, but reduced DNA synthesis in 4th passage HSC by more than 50%. Inhibition of proliferation by endothelin-1 was abrogated by ETBR specific antagonist BQ788, indicating a prominent role of ETBR in growth inhibition. ET-1 did not prevent apoptosis induced by serum deprivation or Fas ligand in 1st or 4th passage HSC. However, ET-1 increased procollagen α1(I), transforming growth factor β-1 and matrix metalloproteinase (MMP)-2 mRNA transcripts in a concentration-dependent manner in 1st, but not in 4th passage HSC. Profibrogenic gene expression was abrogated by ETAR antagonist BQ123. Both BQ123 and BQ788 attenuated the increase of MMP-2 expression by ET-1. CONCLUSION: We show that ET-1 stimulates fibrogenic gene expression for 1st passage HSC and it inhibits HSC proliferation for 4th passage HSC. These data indicate the profibrogenic and antifibrogenic action of ET-1 for HSC are involved in the process of liver fibrosis

Clinical decision modeling system

<p>Abstract</p> <p>Background</p> <p>Decision analysis techniques can be applied in complex situations involving uncertainty and the consideration of multiple objectives. Classical decision modeling techniques require elicitation of too many parameter estimates and their conditional (joint) probabilities, and have not therefore been applied to the problem of identifying high-performance, cost-effective combinations of clinical options for diagnosis or treatments where many of the objectives are unknown or even unspecified.</p> <p>Methods</p> <p>We designed a Java-based software resource, the Clinical Decision Modeling System (CDMS), to implement Naïve Decision Modeling, and provide a use case based on published performance evaluation measures of various strategies for breast and lung cancer detection. Because cost estimates for many of the newer methods are not yet available, we assume equal cost. Our use case reveals numerous potentially high-performance combinations of clinical options for the detection of breast and lung cancer.</p> <p>Results</p> <p>Naïve Decision Modeling is a highly practical applied strategy which guides investigators through the process of establishing evidence-based integrative translational clinical research priorities. CDMS is not designed for clinical decision support. Inputs include performance evaluation measures and costs of various clinical options. The software finds trees with expected emergent performance characteristics and average cost per patient that meet stated filtering criteria. Key to the utility of the software is sophisticated graphical elements, including a tree browser, a receiver-operator characteristic surface plot, and a histogram of expected average cost per patient. The analysis pinpoints the potentially most relevant pairs of clinical options ('critical pairs') for which empirical estimates of conditional dependence may be critical. The assumption of independence can be tested with retrospective studies prior to the initiation of clinical trials designed to estimate clinical impact. High-performance combinations of clinical options may exist for breast and lung cancer detection.</p> <p>Conclusion</p> <p>The software could be found useful in simplifying the objective-driven planning of complex integrative clinical studies without requiring a multi-attribute utility function, and it could lead to efficient integrative translational clinical study designs that move beyond simple pair wise competitive studies. Collaborators, who traditionally might compete to prioritize their own individual clinical options, can use the software as a common framework and guide to work together to produce increased understanding on the benefits of using alternative clinical combinations to affect strategic and cost-effective clinical workflows.</p

TCRep 3D: An Automated In Silico Approach to Study the Structural Properties of TCR Repertoires

TCRep 3D is an automated systematic approach for TCR-peptide-MHC class I structure prediction, based on homology and ab initio modeling. It has been considerably generalized from former studies to be applicable to large repertoires of TCR. First, the location of the complementary determining regions of the target sequences are automatically identified by a sequence alignment strategy against a database of TCR Vα and Vβ chains. A structure-based alignment ensures automated identification of CDR3 loops. The CDR are then modeled in the environment of the complex, in an ab initio approach based on a simulated annealing protocol. During this step, dihedral restraints are applied to drive the CDR1 and CDR2 loops towards their canonical conformations, described by Al-Lazikani et. al. We developed a new automated algorithm that determines additional restraints to iteratively converge towards TCR conformations making frequent hydrogen bonds with the pMHC. We demonstrated that our approach outperforms popular scoring methods (Anolea, Dope and Modeller) in predicting relevant CDR conformations. Finally, this modeling approach has been successfully applied to experimentally determined sequences of TCR that recognize the NY-ESO-1 cancer testis antigen. This analysis revealed a mechanism of selection of TCR through the presence of a single conserved amino acid in all CDR3β sequences. The important structural modifications predicted in silico and the associated dramatic loss of experimental binding affinity upon mutation of this amino acid show the good correspondence between the predicted structures and their biological activities. To our knowledge, this is the first systematic approach that was developed for large TCR repertoire structural modeling

X4 Human Immunodeficiency Virus Type 1 gp120 Promotes Human Hepatic Stellate Cell Activation and Collagen I Expression through Interactions with CXCR4

<div><h3>Background & Aims</h3><p>Patients coinfected with HIV-1 and HCV develop more rapid liver fibrosis than patients monoinfected with HCV. HIV RNA levels correlate with fibrosis progression implicating HIV directly in the fibrotic process. While activated hepatic stellate cells (HSCs) express the 2 major HIV chemokine coreceptors, CXCR4 and CCR5, little is known about the pro-fibrogenic effects of the HIV-1 envelope protein, gp120, on HSCs. We therefore examined the <em>in vitro</em> impact of X4 gp120 on HSC activation, collagen I expression, and underlying signaling pathways and examined the <em>in vivo</em> expression of gp120 in HIV/HCV coinfected livers.</p> <h3>Methods</h3><p>Primary human HSCs and LX-2 cells, a human HSC line, were challenged with X4 gp120 and expression of fibrogenic markers assessed by qRT-PCR and Western blot +/− either CXCR4-targeted shRNA or anti-CXCR4 neutralizing antibody. Downstream intracellular signaling pathways were evaluated with Western blot and pre-treatment with specific pathway inhibitors. Gp120 immunostaining was performed on HIV/HCV coinfected liver biopsies.</p> <h3>Results</h3><p>X4 gp 120 significantly increased expression of alpha-smooth muscle actin (a-SMA) and collagen I in HSCs which was blocked by pre-incubation with either CXCR4-targeted shRNA or anti-CXCR4 neutralizing antibody. Furthermore, X4 gp120 promoted Extracellular signal-regulated kinase (ERK) 1/2 phosphorylation and pretreatment with an ERK inhibitor attenuated HSC activation and collagen I expression. Sinusoidal staining for gp120 was evident in HIV/HCV coinfected livers.</p> <h3>Conclusions</h3><p>X4 HIV-1 gp120 is pro-fibrogenic through its interactions with CXCR4 on activated HSCs. The availability of small molecule inhibitors to CXCR4 make this a potential anti-fibrotic target in HIV/HCV coinfected patients.</p> </div