Nicolas Goossens

IL28B alleles associated with poor hepatitis C virus (HCV) clearance protect against inflammation and fibrosis in patients infected with non-1 HCV genotypes.

Genetic polymorphisms near IL28B are associated with spontaneous and treatment‐induced clearance of hepatitis C virus (HCV), two processes that require the appropriate activation of the host immune responses. Intrahepatic inflammation is believed to mirror such activation, but its relationship with IL28B polymorphisms has yet to be fully appreciated. We analyzed the association of IL28B polymorphisms with histological and follow‐up features in 2335 chronically HCV‐infected Caucasian patients. Assessable phenotypes before any antiviral treatment included necroinflammatory activity (n = 1,098), fibrosis (n = 1,527), fibrosis progression rate (n = 1,312), and hepatocellular carcinoma development (n = 1,915). Associations of alleles with the phenotypes were evaluated by univariate analysis and multivariate logistic regression, accounting for all relevant covariates. The rare G allele at IL28B marker rs8099917—previously shown to be at risk of treatment failure—was associated with lower activity (P = 0.04), lower fibrosis (P = 0.02) with a trend toward lower fibrosis progression rate (P = 0.06). When stratified according to HCV genotype, most significant associations were observed in patients infected with non‐1 genotypes (P = 0.003 for activity, P = 0.001 for fibrosis, and P = 0.02 for fibrosis progression rate), where the odds ratio of having necroinflammation or rapid fibrosis progression for patients with IL28B genotypes TG or GG versus TT were 0.48 (95% confidence intervals 0.30‐0.78) and 0.56 (0.35‐0.92), respectively. IL28B polymorphisms were not predictive of the development of hepatocellular carcinoma. Conclusion: In chronic hepatitis C, IL28B variants associated with poor response to interferon therapy may predict slower fibrosis progression, especially in patients infected with non‐1 HCV genotypes. (HEPATOLOGY 2012)

Is genotype 3 of the hepatitis C virus the new villain

Genotype 3 of the hepatitis C virus (HCV) has been long considered an easy‐to‐treat infection, with higher cure rates (∼70%) than other viral genotypes with the standard combination of pegylated interferon‐α and ribavirin. However, the relative insensitivity of this genotype to most protease inhibitors and the recent unexpected data on decreased effectiveness of sofosbuvir have raised questions on how to achieve universal cure, a goal that seems reasonable for other genotypes. In addition, increasing clinical and experimental data show that HCV genotype 3 may be associated not only with severe steatosis, but also with accelerated fibrosis progression rate and increased oncogenesis. Conclusion: Currently available data suggest that we should increase our efforts to understand the virology and pathogenesis of HCV genotype 3, aiming at better and more potent, genotype‐targeted treatments. (Hepatology 2014;59:2403–2412)

Ectopic lymphoid structures function as microniches for tumor progenitor cells in hepatocellular carcinoma

Ectopic lymphoid-like structures (ELSs) are often observed in cancer, yet their function is obscure. Although ELSs signify good prognosis in certain malignancies, we found that hepatic ELSs indicated poor prognosis for hepatocellular carcinoma (HCC). We studied an HCC mouse model that displayed abundant ELSs and found that they constituted immunopathological microniches wherein malignant hepatocyte progenitor cells appeared and thrived in a complex cellular and cytokine milieu until gaining self-sufficiency. The egress of progenitor cells and tumor formation were associated with the autocrine production of cytokines previously provided by the niche. ELSs developed via cooperation between the innate immune system and adaptive immune system, an event facilitated by activation of the transcription factor NF-κB and abolished by depletion of T cells. Such aberrant immunological foci might represent new targets for cancer therapy.

Hepatitis C virus-induced hepatocellular carcinoma

Hepatitis C virus (HCV) is a leading etiology of hepatocellular carcinoma (HCC). The interaction of HCV with its human host is complex and multilayered; stemming in part from the fact that HCV is a RNA virus with no ability to integrate in the hosts genome. Direct and indirect mechanisms of HCV-induced HCC include activation of multiple host pathways such as liver fibrogenic pathways, cellular and survival pathways, interaction with the immune and metabolic systems. Host factors also play a major role in HCV-induced HCC as evidenced by genomic studies identifying polymorphisms in immune, metabolic, and growth signaling systems associated with increased risk of HCC. Despite highly effective direct-acting antiviral agents, the morbidity and incidence of liver-related complications of HCV, including HCC, is likely to persist in the near future. Clinical markers to selectively identify HCV subjects at higher risk of developing HCC have been reported however they require further validation, especially in subjects who have experienced sustained virological response. Molecular biomarkers allowing further refinement of HCC risk are starting to be implemented in clinical platforms, allowing objective stratification of risk and leading to individualized therapy and surveillance for HCV individuals. Another role for molecular biomarker-based stratification could be enrichment of HCC chemoprevention clinical trials leading to smaller sample size, shorter trial duration, and reduced costs.

A hepatic stellate cell gene expression signature associated with outcomes in hepatitis C cirrhosis and hepatocellular carcinoma after curative resection

Objective We used an informatics approach to identify and validate genes whose expression is unique to hepatic stellate cells and assessed the prognostic capability of their expression in cirrhosis. Design We defined a hepatic stellate cell gene signature by comparing stellate, immune and hepatic transcriptome profiles. We then created a prognostic index using a combination of hepatic stellate cell signature expression and clinical variables. This signature was derived in a retrospective–prospective cohort of hepatitis C-related early-stage cirrhosis (prognostic index derivation set) and validated in an independent retrospective cohort of patients with postresection hepatocellular carcinoma (HCC). We then examined the association between hepatic stellate cell signature expression and decompensation, HCC development, progression of Child–Pugh class and survival. Results The 122-gene hepatic stellate cell signature consists of genes encoding extracellular matrix proteins and developmental factors and correlates with the extent of fibrosis in human, mouse and rat datasets. Importantly, association of clinical prognostic variables with overall survival was improved by adding the signature; we used these results to define a prognostic index in the derivation set. In the validation set, the same prognostic index was associated with overall survival. The prognostic index was associated with decompensation, HCC and progression of Child–Pugh class in the derivation set, and HCC recurrence in the validation set. Conclusions This work highlights the unique transcriptional niche of stellate cells, and identifies potential stellate cell targets for tracking, targeting and isolation. Hepatic stellate cell signature expression may identify patients with HCV cirrhosis or postresection HCC with poor prognosis.

Clinicopathological indices to predict hepatocellular carcinoma molecular classification.

Hepatocellular carcinoma (HCC) is the second most lethal cancer caused by lack of effective therapies. Although promising, HCC molecular classification, which enriches potential responders to specific therapies, has not yet been assessed in clinical trials of anti‐HCC drugs. We aimed to overcome these challenges by developing clinicopathological surrogate indices of HCC molecular classification.

The Impact of Obesity and Metabolic Syndrome on Chronic Hepatitis C

The metabolic syndrome and the hepatitis C virus (HCV) infection are 2 global health care challenges with a complex interaction. Insulin resistance, a central component of the metabolic syndrome, is epidemiologically and pathophysiologically intrinsically linked to HCV infection. Insulin resistance and diabetes affect clinical outcomes in patients with liver disease related to HCV, namely, incidence of hepatocellular carcinoma, liver-related mortality, fibrosis progression rate, response to antiviral therapy, and possibly the incidence of cardiovascular events. Viral and metabolic steatosis and its interactions with HCV and the metabolic syndrome are discussed. Management and the need for further research conclude the article.

The XBP1 Arm of the Unfolded Protein Response Induces Fibrogenic Activity in Hepatic Stellate Cells Through Autophagy

Autophagy and the unfolded protein response (UPR) both promote activation of hepatic stellate cells (HSC), however the link between the two stimuli remains unclear. Here we have explored the role of X-box binding protein 1 (XBP1), one of three UPR effector pathways and sought to establish the interdependence between autophagy and the UPR during HSC activation. XBP1 induction accompanied both culture-based HSC activation and ER stress induced by tunicamycin. Ectopic overexpression of XBP1 induced collagen 1-alpha expression in HSCs, which was inhibited by knockdown of ATG7, a critical autophagy mediator. Genome-wide transcriptomic profiling indicated an upregulation of collagen synthesis pathways, but not of the transforming growth factor (TGF)-b pathway, a canonical fibrogenic driver, suggesting that XBP1 activates a specific subset of fibrogenesis pathways independent of TGF-β1. XBP1 target gene signatures were significantly induced in rodent liver fibrosis models (n = 3–5) and in human samples of non-alcoholic fatty liver disease (NAFLD) (n = 72–135). Thus, XBP1-mediated UPR contributes to fibrogenic HSC activation and is functionally linked to cellular autophagy.

Current level of evidence on causal association between hepatitis C virus and type 2 diabetes: A review

Graphical abstract

Using Big Data to Discover Diagnostics and Therapeutics for Gastrointestinal and Liver Diseases

Technologies such as genome sequencing, gene expression profiling, proteomic and metabolomic analyses, electronic medical records, and patient-reported health information have produced large amounts of data from various populations, cell types, and disorders (big data). However, these data must be integrated and analyzed if they are to produce models or concepts about physiological function or mechanisms of pathogenesis. Many of these data are available to the public, allowing researchers anywhere to search for markers of specific biological processes or therapeutic targets for specific diseases or patient types. We review recent advances in the fields of computational and systems biology and highlight opportunities for researchers to use big data sets in the fields of gastroenterology and hepatology to complement traditional means of diagnostic and therapeutic discovery.