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Host factors determining the efficacy of hepatitis C treatment.

ABSTRACT: Combination therapy with pegylated interferon and ribavirin is the standard of care (SOC) for the treatment of chronic hepatitis C (CHC). Treating CHC with SOC may show a sustained virological response (SVR) in approximately 50-70 % of genotype 1 CHC patients and an SVR in 70-90 % of genotype 2 CHC patients. The genotype, baseline viral load, and viral kinetics (i.e., rapid virologic response and early virologic response) can be used as predictors of response-guided therapy. Nonetheless, host factors, e.g. age, ethnicity, insulin resistance, and genetic variations, may also play important roles in the SVR in CHC patients treated with SOC. Recent genome-wide association studies have demonstrated that single-nucleotide polymorphisms near the interleukin 28B gene (IL28B) were associated with SVR to treatment with SOC in CHC patients. The IL28B polymorphisms may contribute to the viral kinetics during treatment. Asian people have favorable IL28B polymorphisms. This factor may at least partly explain the high eradication rate of hepatitis C by SOC in Asia. Combination therapy with direct-acting antivirals (DAAs) and SOC can increase the SVR rates both in treatment-naïve and treatment-experienced patients. Although the IL28B polymorphisms also affect the SVR of triple therapy with SOC and first-generation protease inhibitors, pilot studies have demonstrated that potent DAAs might overcome the influence of IL28B polymorphisms. Thus, the treatment of hepatitis C virus infection could be simplified in the near future.

SUBMITTER: Chuang WL

PROVIDER: S-EPMC3698435 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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Host factors determining the efficacy of hepatitis C treatment.

Chuang Wan-Long WL Yu Ming-Lung ML

Journal of gastroenterology 20121027 1

Combination therapy with pegylated interferon and ribavirin is the standard of care (SOC) for the treatment of chronic hepatitis C (CHC). Treating CHC with SOC may show a sustained virological response (SVR) in approximately 50-70 % of genotype 1 CHC patients and an SVR in 70-90 % of genotype 2 CHC patients. The genotype, baseline viral load, and viral kinetics (i.e., rapid virologic response and early virologic response) can be used as predictors of response-guided therapy. Nonetheless, host fa ...[more]

PMID: 23104468

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Project description:Recent development of proteomic array technology, including protein profiling coupling ProteinChip array with surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF/MS), provides a potentially powerful tool for discovery of new biomarkers by comparison of its profiles according to patient phenotypes. We used this approach to identify the host factors associated with treatment response in patients with chronic hepatitis C (CHC) receiving a 48-wk course of pegylated interferon (PEG-IFN) alpha 2b plus ribavirin (RBV). Protein profiles of pretreatment serum samples from 32 patients with genotype 1b and high viral load were conducted by SELDI-TOF/MS by using the three different ProteinChip arrays (CM10, Q10, IMAC30). Proteins showed significantly different peak intensities between sustained virological responders (SVRs), and non-SVRs were identified by chromatography, SDS-PAGE, TOF/MS and tandem mass spectrometry (MS/MS) assay. Eleven peak intensities were significantly different between SVRs and non-SVRs. The three SVR-increased peaks could be identified as two apolipoprotein (Apo) fragments and albumin and, among the eight non-SVR-increased proteins, four peaks identified as two iron-related and two fibrogenesis-related protein fragments, respectively. Multivariate analysis showed that the serum ferritin and three peak intensity values (Apo A1, hemopexin and transferrin) were independent variables associated with SVRs, and the area under the receiver operating characteristic (ROC) curves for SVR prediction by using the Apo A1/hemopexin and hemopexin/transferrin were 0.964 and 0.936. In conclusion, pretreatment serum protein profiling by SELDI-TOF/MS is variable for identification of response-related host factors, which are useful for treatment efficacy prediction in CHC receiving PEG-IFN plus RBV. Our data also may help us understand the mechanism for treatment resistance and development of more effective antiviral therapy targeted toward the modulation of lipogenesis or iron homeostasis in CHC patients.

Project description:Hepatitis B virus (HBV) RNA in serum is a novel biomarker for intrahepatic HBV replication and treatment response. For its proper use, it is essential to identify factors influencing serum HBV RNA level. Using a rapid amplification of complimentary DNA (cDNA) ends (RACE) PCR technique (lower limit of detection [LLD], 800 copies/mL [c/mL]), serum HBV RNA levels were measured in samples of 488 untreated individuals with chronic HBV infection who were eligible to treatment according to currently used recommendations. We explored the association of serum levels of HBV RNA with patient- and virus-associated factors. HBV genotype distribution was 21/10/20/46/3% for A/B/C/D/other. Mean HBV RNA serum level was 5.9 (1.6) log10 c/mL (hepatitis B e antigen [HBeAg]-positive chronic hepatitis B [CHB], 6.5 [1.2] log c/mL; HBeAg-negative CHB, 4.1 [1.2] log c/mL; P < 0.001). By multivariable linear regression, factors associated with lower HBV RNA level were HBeAg negativity (β = -0.69; P < 0.001), HBV genotypes A (β = -0.13; P = 0.002), B (β = -0.07; P = 0.049), and C (β = -0.61; P < 0.001) in comparison to D, and presence of HBV basal core promoter mutation either alone (β = -0.14; P = 0.001) or in combination with precore mutation (β = -0.22; P < 0.001). Higher serum alanine aminotransferase (ALT) was associated with higher HBV RNA (β = 0.23; P < 0.001). HBV RNA correlated strongly with HBV DNA (HBeAg-pos, r = 0.72; P < 0.001; HBeAg-neg, r = 0.78; P < 0.001) and moderately with quantitative hepatitis B surface antigen (qHBsAg; HBeAg-pos, r = 0.54; P < 0.001; HBeAg-neg, r = 0.19; P = 0.04) and quantitative hepatitis B surface antigen (qHBeAg; r = 0.41; P < 0.001).ConclusionIn this multiethnic cohort of 488 untreated individuals with CHB, factors associated with serum HBV RNA level were HBeAg status, serum ALT, HBV genotype, and presence of basal core promotor mutations. For the future use of serum HBV RNA as a clinical marker, it seems mandatory to take these factors into consideration. (Hepatology 2018).

Project description:BackgroundOnly about 50% of patients chronically infected with HCV genotype 1 (HCV-1) respond to treatment with pegylated interferon-alfa and ribavirin (dual therapy), and protease inhibitors have to be administered together with these drugs increasing costs and side-effects. We aimed to develop a predictive model of treatment response based on a combination of baseline clinical and viral parameters.MethodologySeventy-four patients chronically infected with HCV-1b and treated with dual therapy were studied (53 retrospectively -training group-, and 21 prospectively -validation group-). Host and viral-related factors (viral load, and genetic variability in the E1-E2, core and Interferon Sensitivity Determining Region) were assessed. Multivariate discriminant analysis and decision tree analysis were used to develop predictive models on the training group, which were then validated in the validation group.Principal findingsA multivariate discriminant predictive model was generated including the following variables in decreasing order of significance: the number of viral variants in the E1-E2 region, an amino acid substitution pattern in the viral core region, the IL28B polymorphism, serum GGT and ALT levels, and viral load. Using this model treatment outcome was accurately predicted in the training group (AUROC = 0.9444; 96.3% specificity, 94.7% PPV, 75% sensitivity, 81% NPV), and the accuracy remained high in the validation group (AUROC = 0.8148, 88.9% specificity, 90.0% PPV, 75.0% sensitivity, 72.7% NPV). A second model was obtained by a decision tree analysis and showed a similarly high accuracy in the training group but a worse reproducibility in the validation group (AUROC = 0.9072 vs. 0.7361, respectively).Conclusions and significanceThe baseline predictive models obtained including both host and viral variables had a high positive predictive value in our population of Spanish HCV-1b treatment naïve patients. Accurately identifying those patients that would respond to the dual therapy could help reducing implementation costs and additional side effects of new treatment regimens.

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Host factors determining the efficacy of hepatitis C treatment.

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Host factors determining the efficacy of hepatitis C treatment.

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