Background: Nonalcoholic fatty liver disease (NAFLD) with resulting nonalcoholic steatohepatitis (NASH) are increasingly a cause of cirrhosis and hepatocellular carcinoma (HCC) globally. This burden is expected to increase as epidemics of obesity, diabetes and metabolic syndrome continue to grow. The goal of this analysis was to use a Markov model to forecast NAFLD disease burden using currently available data. Methods:A model was used to estimate NAFLD and NASH disease progression in 8 countries based on data for adult prevalence of obesity and type 2 diabetes mellitus (DM). Published estimates and expert consensus were used to build and validate the model projections. Results:If obesity and DM level off in the future, we project a modest growth in total NAFLD cases (0-30%), between 2016-2030, with the highest growth in China as result of urbanization and the lowest growth in Japan as result of a shrinking population.However, at the same time, NASH prevalence will increase 15-56%, while liver mortality and advanced liver disease will more than double as result of an aging/increasing population.Conclusions: NAFLD and NASH represent a large and growing public health problem and efforts to understand this epidemic and to mitigate the disease burden are needed.If obesity and DM continue to increase at current and historical rates, both NAFLD and 4 NASH prevalence are expected to increase. Since both are reversible, public health campaigns to increase awareness and diagnosis, and to promote diet and exercise can help manage the growth in future disease burden.Lay summary: Nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) can lead to advanced liver disease, and are occurring in increasing numbers in tandem with epidemics of obesity and diabetes. A mathematical model was built to understand how the disease burden associated with NAFLD and NASH will change over time. Results suggest increasing numbers of cases of advanced liver disease and liver-related mortality in the coming years. 5 BACKGROUNDNonalcoholic fatty liver disease (NAFLD) is a leading cause of liver disease globally [1][2][3]. This condition is characterized by excess liver fat in the absence of other causes such as alcohol consumption [4,5]. Obesity, type 2 diabetes mellitus (DM) and metabolic syndrome (MetS) are consistently identified as the most important risk factors for NAFLD [4,6].In order to classify the population, NAFLD may be divided into two groups: NAFL (steatosis only) or NASH (nonalcoholic steatohepatitis), where steatosis is accompanied by inflammation and ballooning. NASH frequently progresses to liver fibrosis [7] that is the main risk factor for liver-related mortality [8]. Odds of progression to advanced liver disease, including hepatic decompensation and hepatocellular carcinoma (HCC), are higher among those with NASH compared to those with NAFL [7]. Increasing age, obesity, DM and the presence of NASH have been consistently identified as risk factors for progression to cirrhosis [6,9].There is a...

BackgroundPD-L1 expression on neutrophils contributes to the impaired immune response in infectious disease, but the detailed role of PD-L1 expression on neutrophils in HCC remains unclear.MethodsWe investigated the phenotype and morphology of neutrophils infiltrated in tumour tissues from both patients with HCC and hepatoma-bearing mice.ResultsWe found that neutrophils dominantly infiltrated in the peritumoural region. The neutrophil-to-T cell ratio (NLR) was higher in peritumoural tissue than that in the intratumoural tissue and was negatively correlated with the overall survival of patients with HCC. Infiltrating neutrophils displayed a phenotype of higher frequency of programmed cell death ligand 1 (PD-L1) positive neutrophils. The ratio of PD-L1+ neutrophils-to-PD-1+ T cells was higher in peritumoural tissue and better predicted the disease-free survival of patients with HCC. We further confirmed a higher frequency of PD-L1+ neutrophils and PD-1+ T cells in hepatoma-bearing mice. Functionally, the PD-L1+ neutrophils from patients with HCC effectively suppressed the proliferation and activation of T cells, which could be partially reversed by the blockade of PD-L1.ConclusionsOur results indicate that the tumour microenvironment induces impaired antitumour immunity via the modulation of PD-L1 expression on tumour infiltrating neutrophils.Electronic supplementary materialThe online version of this article (doi:10.1186/s13046-015-0256-0) contains supplementary material, which is available to authorized users.

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Background and Aims Nonalcoholic steatohepatitis (NASH) is a common cause of chronic liver disease. Clinical trials use the NASH Clinical Research Network (CRN) system for semiquantitative histological assessment of disease severity. Interobserver variability may hamper histological assessment, and diagnostic consensus is not always achieved. We evaluate a second harmonic generation/two‐photon excitation fluorescence (SHG/TPEF) imaging‐based tool to provide an automated quantitative assessment of histological features pertinent to NASH. Approach and Results Images were acquired by SHG/TPEF from 219 nonalcoholic fatty liver disease (NAFLD)/NASH liver biopsy samples from seven centers in Asia and Europe. These were used to develop and validate qFIBS, a computational algorithm that quantifies key histological features of NASH. qFIBS was developed based on in silico analysis of selected signature parameters for four cardinal histopathological features, that is, fibrosis (qFibrosis), inflammation (qInflammation), hepatocyte ballooning (qBallooning), and steatosis (qSteatosis), treating each as a continuous rather than categorical variable. Automated qFIBS analysis outputs showed strong correlation with each respective component of the NASH CRN scoring (P < 0.001; qFibrosis [r = 0.776], qInflammation [r = 0.557], qBallooning [r = 0.533], and qSteatosis [r = 0.802]) and high area under the receiver operating characteristic curve values (qFibrosis [0.870‐0.951; 95% confidence interval {CI}, 0.787‐1.000; P < 0.001], qInflammation [0.820‐0.838; 95% CI, 0.726‐0.933; P < 0.001), qBallooning [0.813‐0.844; 95% CI, 0.708‐0.957; P < 0.001], and qSteatosis [0.939‐0.986; 95% CI, 0.867‐1.000; P < 0.001]) and was able to distinguish differing grades/stages of histological disease. Performance of qFIBS was best when assessing degree of steatosis and fibrosis, but performed less well when distinguishing severe inflammation and higher ballooning grades. Conclusions qFIBS is an automated tool that accurately quantifies the critical components of NASH histological assessment. It offers a tool that could potentially aid reproducibility and standardization of liver biopsy assessments required for NASH therapeutic clinical trials.