Myeloid-derived Suppressor Cells Are Correlated With The Prognosis Of Antiviral Therapy In Patients With Chronic Hepatitis C Infection

Background and AimsChronic hepatitis C virus infection(CHC) is a serious health problem worldwide. There are estimated to be more than 185 million individuals infected with hepatitis C virus(HCV) worldwide. 74-86% of newly infected persons will develop chronic infection characterized by liver fibrosis, with some cases developing into cirrhosis and hepatocellular carcinoma. Several large-scale seroprevalence studies had reported estimates in large samples of asymptomatic Chinese ranging from 0.39 to 3.2%. As of 2012, HCV infection was the fourth most commonly reported infectious disease in China after hepatitis B virus infection, pulmonary tuberculosis and dysentery. Particularly among those over 35 ages, reporting incidence for those tested passively has increased steadily over time. HCV infection in China is an increasingly large burden for families and society.Currently, antiviral therapy still is only one way to control the progression of hepatitis C. In the last four years, the treatment of HCV infection has improved dramatically. The launch of the first direct acting antiviral(DAA) agents in 2011, boceprevir and telaprevir, first generation protease inhibitors(PIs), in combination with PEG-IFN/RBV was a major step forward in improving HCV treatment. In 2014, three new DAAs including Sofosbuvir, Simeprevir and Daclatasvir were approved by FDA and EMA and launched in a number of Western countries. Those DAA regimens with a shortened duration of treatment are able to improve SVR rate to over 90%, thus raising the possibility of curing HCV. Although the new era of antiviral therapy for HCV holds great promise to finally rein, the cost of a 12-week course therapy has been estimated in excess of $84,000. However, the average cost of 48-week antiviral therapy based on the PEG-IFN/RBV is only $10,564 for each patient in China. The cost is far lower than that in Western countries. Thus, the combination of PEG-IFN/RBV is still as a standard treatment for hepatitis C in China. However, approximately one-half of patients with chronic hepatitis C virus infection(CHC) fail to achieve viral clearance. Thus, it is important to identify the factors that may be valuable in improving antiviral strategy and treatment response.Myeloid-derived suppressor cells(MDSCs) are a heterogeneous subset consisting of immature monocytes/macrophages, dendritic cells and granulocytes. MDSCs mainly locate in peripheral cycling blood and inhibit T-cell responses. Many studies have demonstrated that MDSCs significantly increase in malignancies, autoimmune disease and virus infectious disease. Moreover, the accumulation of MDSCs is frequently associated with negative prognosis of diseases. Many factors, such as infections of bacterium, microorganism, parasites or virus, chemotherapy, autoimmune diseases, stress reaction, induce the increase of MDSCs. Recent reports showed that HCV can promote the accumulation of MDSCs, and the MDSCs can inhibit the proliferation and IFN-γ secretion of CD+ and CD8+ T cells. Thus, the accumulation of MDSCs might facilitate and maintain HCV persistent infection. Recent studies reported that the same downtrends locate in the changes of serum HCV RNA and MDSCs in patients with pegylated interferon combined with ribavirin. The phenomenon may indicate that the levels of HCV RNA are associated with the increase of MDSCs.Many studies have demonstrated that the significantly increase of MDSCs is frequently associated with negative prognosis of diseases. However, to date, few studies demonstrated that the correlation between the accumulation of MDSCs and the antiviral responses with pegylated interferon plus ribavirin(PEG-IFN/RBV) in CHC patients. Moreover, whether the MDSCs can predict the sustained virological response(SVR) of CHC patients during early stages of therapy is unclear. Materials and Methods 1 MaterialsA total of 206 treatment-na?ve CHC patients were enrolled in the Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University(Zhengzhou, China) between June 2011 and June 2013 and diagnosed positive for serum HCV RNA and anti-HCV antibody. The exclusion criteria of patients included co-infection with human immunodeficiency virus(HIV), hepatitis B virus(HBV) or mycobacterium tuberculosis, alcohol intake averaging greater than 50 g per day, active drug abuse, chronic systemic disease, psychiatric disorders, autoimmune disease, pregnancy or lactation. The group of healthy controls(n = 20) consisted of local volunteers, who were seronegative for HCV and had normal aminotransferase levels. Each CHC patient received antiviral therapy with PEG-IFN/RBV for 24 weeks(HCV genotype 2a) or 48 weeks(HCV genotype 1b), and blood samples were obtained at pre-determined time points throughout the treatment period. 2 MethodsThe nested case-control study was used in this study. The patients were follow up untill 24 weeks after antivirus therapy. Base on the outcome of treatment, the patients were divided into SVR group and Non-SVR. The data of patients such as demography, clinicopathological parameters and the related results of antivirus therapy were collected and analyzed. The peripheral cycling bloods(10ml) were acquired in various time points during research. Peripheral blood mononuclear cells(PBMCs) were isolated from whole blood samples(heparinized blood) by Ficoll-Hypaque(Amersham, Freiburg, Germany) density gradient centrifugation and analyzed immediately. Cell phenotype was analyzed on a flow cytometer(BD LSR II)(BD Biosciences). Data were acquired as the fraction of labeled cells within a live-cell gate set for 10000 events. For the flow cytometric sorting, BD Influx TM machine(BD Biosciences) was used to test G-MDSCs(HLA-DR-/low CD33+CD14-CD11b+), M-MDSCs(HLA-DR-/low CD33+ CD14+CD11b+), STAT3, p-STAT3, ARG-1, the proliferation and secretion of IFN-γ and phenotypes of CD4+T and CD8+T cells. G-MDSCs and M-MDSCs were isolated by FACS. The inhibitory genes of MDSCs were tested by q RT-PCR. CD4+T and CD8+T cells were isolated with magic beads. 3 Statistic and analysisStatistical analysis was performed using the SPSS software(version 16.0; SPSS Inc, Chicago, IL, USA) and Graph Pad Prism software(version 5.0; San Diego, CA, USA). Categorical data were expressed as numbers or proportions of subjects with the specific features. The Chi-square test or the Fisher’s exact probability test was used to compare categorical data. Continuous variables normally distributed were summarized as mean ± standard deviation(SD), and the One-Way ANOVA test was used to compare the difference between two groups. Continuous variables not normally distributed were summarized as medians and ranges, and the nonparametric Mann-Whitney U test was used to compare the difference between two groups. The Kruskal-Wallis H test was used for comparison of differences among three or more groups and further comparisons between any two groups within these multiple groups were conducted using the Nemenyi method. The Correlations between variables were calculated using the Spearman rank order correlations. The single variable binary logistic regression model was used to analyze the possible predictors for SVR in CHC patients. The multivariate binary logistic regression analysis was used to explore the independent predictive factors of SVR. The receiver operating characteristic curve(ROC) was adopted to analyze the MDSCs for predicting the likelihood of achieving SVR. All P values were two-sided. P value of less than 0.05 was considered as statistically significant in all cases.Results Part1 The analysis of predictive factors of the prognosis of antiviral therapy in patients with chronic hepatitis C infection 1 In 206 CHC patients, 180 finished antiviral therapy and follow up, the SVR was 70.6%. 2 MDSCs were divided into G-MDSCs(HLA-DR-/lowCD33+CD14-CD11b+) and M-MDSCs(HLA-DR-/lowCD33+CD14+CD11b+). The G-MDSCs of Non-SVR patients were significantly higher than that of SVR patients and healthy donors(P < 0.05), but there were no statistic differences of M-MDSCs among three groups(P > 0.05). 3 G-MDSCs were positively associated with HCV RNA, ALT, AST and LSM(P < 0.05), and were negatively associated with CD4+T and CD8+T cells(P < 0.05). M-MDSCs were not associated with above indexes(P > 0.05).4 The results of ROC analysis indicated that the variable of G-MDSCs was optimal predictor of SVR for its biggest AUC area and the cutoff was 5.38%. 5 The results of single and multiple variable logistic regression analysis showed that HCV genotypes(CI.95%:3.75-12.33; P<0.01), G-MDSCs(CI.95%:1.62-5.47; P=0.01) and RVR(CI.95%:1.34-8.48; P=0.03) were independent predictor of SVR. Part2 The MDSCs in CHC patients influence the phenotypes and functions of T cells. 1 The core protein of HCV induced the increase of the G-MDSCs(P < 0.05), but not the M-MDSCs(P > 0.05). Through deleting the HCV RNA, PEG-IFN/RBV decreased the G-MDSCs. 2 The G-MDSCs could inhibit the proliferations and IFN-γ increases of CD4+T and CD8+T cells through the way of cells touch(P < 0.05), the inhibitory ability of G-MDSCs from Non-SVR patients was stronger than that from SVR patients and healthy donors(P < 0.05). 3 The G-MDSCs, but not M-MDSCs could promote T cells apoptosis(P < 0.05), the G-MDSCs from Non-SVR patients had stronger ability to promote T cells apoptosis than that of SVR patients(P < 0.05). 4 The G-MDSCs could enhance the percentages of T cells in G0-G1 phase of cell cycle(P < 0.05). 5 The G-MDSCs were negatively associated with the percentages of center memory CD4+T cells(r=-0.46, P<0.01) and CD8+T cells(r=-0.28, P = 0.02), the M-MDSCs were not associated with memory subsets of T cells. 6 The G-MDSCs were positively associated with the percentages o Treg cells(r=0.42, P < 0.05), furthermore, G-MDSCs could induce the increase of Treg cells. The M-MDSCs had no correlations with Treg cells in CHC patients(r=0.23, P = 0.08). 7 The MDSCs could induce the changes of phenotypes of T cells, enhance the expressions of PD-1, CTLA-4 and Tim-3, and down regulation of the expression of OX40 on the surfaces of T cells.. Part3 The mechanism of MDSCs inhibition on response of T cells 1 The expressions of inhibitory cytokines and genes such as ARG-1, COX-2, TGF-β, IL-6 and IL-10 in Non-SVR patients were significantly higher than that of SVR patients and healthy donors(P < 0.05). 2 The expressions of STAT3 and p-STAT3 in Non-SVR patients were significantly higher than that of SVR patients and healthy donors(P < 0.05). 3 The S31-201 could down regulation of the expressions of STAT3, p-STAT3 and ARG-1 by inhibiting STAT3 signaling(P < 0.05). 4 Compared to wild STAT3, the G-MDSCs with blocked STAT3 only had mild ability to inhibit the proliferation and IFN-γ secretion of CD4+T cells and CD8+T cells. 5 The IL-10 could activate STAT3 of G-MDSCs to promote the expressions of ARG-1, COX-2, i NOS, TGF-β, IL-6(P < 0.05), but it could not activate blocked STAT3 by S31-201. to promote the expressions of ARG-1, COX-2, i NOS, TGF-β, IL-6(P < 0.05). 6 The IL-10 could activate STAT3 of G-MDSCs by promoting the phosphorylation of STAT3(P < 0.05), however, IL-10 could not activate STAT3 of M-MDSCs(P < 0.05). 7 The IL-10 could enhance the expressions of ARG-1, COX-2, i NOS, TGF-β, IL-6 m RNA( P < 0.05), but S31-201 could block the function of IL-10( P < 0.05). Conclusion1 The G-MDSCs are positively associated with HCV RNA, ALT, AST and LSM and are negatively associated with CD4+ and CD8+T cells; moreover, G-MDSCs is the independent predictor of SVR in CHC patients treated with PEG-IFN/RBV. 2 The core protein of HCV can enhance G-MDSCs, but not M-MDSCs; through decreasing the HCV RNA, PEG-IFN/RBV inhibit G-MDSCs. 3 The G-MDSCs can inhibit the proliferations and IFN-γ increases of CD4+T and CD8+T cells, promote T cells apoptosis, promote the increase of the center memory T cells and Treg cells. Furthermore, the G-MDSCs can enhance the expressions of PD-1, CTLA-4 and Tim-3, and down regulation of the expression of OX40 on the surfaces of T cells.4 The IL-10 could activate STAT3 of G-MDSCs to promote the expressions of ARG-1, COX-2, i NOS, TGF-β, IL-6, and enhance the inhibitory function of G-MDSCs.