Genomics and HCV infection: Progression of fibrosis and treatment response Academic research paper on "Biological sciences"

Review

EUROPEAN ASSOCIATION FOR THE STUDY OF THE LIVER I

JOURNAL OF HEPATOLOGY

Genomics and HCV infection: Progression of fibrosis and

treatment response

Emilie Estrabaud1'23'4'*, Michel Vidaud5, Patrick Marcellin1'2'3'4, Tarik Asselah1'2'3'4'*

1INSERM, UMR773, Team «Viral hepatitis », Centre de Recherche Bichat Beaujon, BP 416, F-75018 Paris, France; 2Université Denis Diderot Paris 7, site Bichat, BP 416, F-750Î8 Paris, France; 3Service d'Hépatologie, PMAD Hôpital Beaujon, 100 Bd du Général Leclerc, Clichy la Garenne, 92110 Clichy Cedex, France; 4Laboratory of Excellence Labex INFLAMEX, PRES Paris Sorbonne Cité, France; 5Service de Biochimie,

Hôpital Beaujon, Clichy, France

Summary

HCV infection is a global health problem that affects 170 million people worldwide. The severity of the disease varies from asymptomatic chronic infection to cirrhosis and hepatocellular carcinoma (HCC). Recently, the standard of care for genotype 1 patients has greatly improved with the addition of protease inhibitors (telaprevir or boceprevir) to pegylated interferon (PegIFN) and ribavirin (RBV). The prediction of fibrosis progression and the response to antiviral treatment are two major issues in the management of patients with chronic hepatitis C. Differential expression of mRNAs was first analyzed for both progression of fibrosis and treatment response. Specific polymorphisms, associated with either fibrosis or viral response, were identified thanks to major improvements in genome scanning technologies. Since 2009, several independent genome wide association studies (GWAS) have reported an association between genetic polymorphisms within the IL-28B promoter and both natural and treatment-induced clearance in genotype 1 infected patients. These different studies showed the strong association and the importance of IL-28B polymorphisms in the treatment response. Combining the different genetic factors could improve their predictive value and help identify patients at a high risk of progression of fibrosis as well as those with a lower chance of responding to treatment. The aim of this review was to discuss the genomic factors (mRNAs, miRNAs, and SNPs) and HCV infection with clinical implications for either progression of fibrosis or treatment response. Recent findings on the IL-28B polymorphism and its application in clinical practice will also be discussed. © 2012 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Introduction

Chronic hepatitis C is the most common cause of cirrhosis and the first indication for liver transplantation in Europe and the United States. The progression from early stage of fibrosis to cirrhosis varies widely among patients with chronic hepatitis C.

Identifying patients in whom fibrosis will progress rapidly as well as non-responders is crucial for disease prognosis. Some defined markers such as male gender, age, alcohol, and obesity may play a role in accelerating fibrosis and treatment failure. The current standard of care for HCV genotype 1 patients is triple therapy with the addition of protease inhibitors (boceprevir and telaprevir) to pegylated interferon (PegIFN) plus ribavirin (RBV). For genotype non-1 patients, treatment is still PegIFN and RBV. The prediction of non-response to treatment is mandatory to avoid side effects and reduce costs.

Since the sequencing of the entire human genome in 2001, major advances have been made in genotyping technologies, in particular, the decrease in the cost of genotyping, the large-scale discovery of single nucleotide polymorphisms (SNPs), the development of massive multiplexed genotyping and the efforts of SNPs consortiums and the HapMap project.

Since 2009, at least 4 different GWAS have investigated genomic markers associated with a response to PegIFN/RBV in patients with chronic HCV (CHC). The same SNPs located in the promoter region of IL-28B were highly associated with natural and treatment-induced viral clearance [1].

The aim of this review was to present and discuss the major genomic markers that have been associated with either fibrosis progression or treatment response in patients with CHC. The

Keywords: Personalized medicine; Genetic; IL-28B; Direct-acting antivirals; Cirrhosis; Biomarkers. Received 13 July 2011; received in revised form 11 May 2012; accepted 14 May 2012

* Corresponding authors. Addresses: Faculté de Medecine Xavier Bichat. INSERM U773.16 rue Henri Huchard. 75018 Paris. France. Tel.: +33 (0) 157277564; fax: +33 (0) 157277531 (E. Estrabaud)' Service d'Hépatologie & INSERM U773' Hôpital Beaujon' 100 Bd du Général Leclerc' 92110 Clichy' France. Tel.: +33 (0) 660957890; fax: +33 (o) 147309440 (t. Asselah).

E-mail addresses: emilie.estrabaud@inserm.fr (E. Estrabaud)' tarik.asselah@bjn.aphp.fr (T. Asselah).

Abbreviations: CHCchronic hepatitis C; CRS' cirrhosis risk score; EVR early virological response; GWAS'genome wide association study; HCV'hepatitis C virus; HSChepatic stellate cells; IFN' Interferon; IL' Interleukin; ISG' interferon stimulated gene; NR' non-response; PegIFN' pegylated-interferon; RVR' rapid virological response; SNP' single nucleotide polymorphism; SVR sustained virological response; IP10' inducible protein 10.

Key Points

• The monitoring of fibrosis is crucial for prognosis of chronic hepatitis C (CHC) and decision to treat. Liver biopsy remains the gold standard to distinguish between moderate and mild fibrosis. Several genetic factors have been identified to help diagnose fibrosis progression

• Genome wide association studies (GWAS) have identified previously unknown markers associated with fibrosis progression and antiviral response. Some polymorphisms have been associated with viral response and fibrosis progression, due to their ability to modulate expression of genes whose products play a role in the antiviral response or fibrosis progression

• The cirrhosis risk score (CRS) including a combination of 7 SNPs may distinguish patients at high risk

of developing cirrhosis. Several SNPs regulating expression of MMP9 and MMP1 have been associated with fibrosis and its progression. IL-28B is not associated with fibrosis stage

• Fibrosis progression is different for each patient; some patients are defined as "rapid fibrosers" and others as "slow fibrosers". The progression likely depends on the intensity of aggressive stimuli (HCV, alcohol, etc.), the duration of exposition to the agent, but also the host genetics and the environment (obesity, etc.)

• Fibrosis regression is different for each patient. The regression is directly associated with the control of the aggressive agent (HCV eradication, control of alcohol consomption, etc.), but also with the host genetics (capacity of fibrosis degradation and repair), and the environment. Some patients are defined as "rapid regressors" and some as "slow regressors"

• By scanning several hundreds of thousands SNPs, 4 independent GWAS reported single nucleotide polymorphisms (SNPs), near the IL-28B (IFNA3) region, that were associated with response to PeglFN/RBV treatment in genotype 1 patients. The association of IL-28B SNPs with viral response is less strong in HCV genotypes 2 and 3 than in genotypes 1 and 4

• The molecular mechanisms of IL-28B SNPs are unknown

• Interferon stimulated genes (ISGs) are highly expressed in the livers of non-responders at baseline compared

to sustained virological responders (SVR). ISG intrahepatic expression remains a better predictive factor of antiviral response in patients with chronic hepatitis C than the IL-28B genotype. However, IL-28B is non-invasive and easier to perform

• The SNP rs12979860 CC is associated with both SVR and RVR. RVR is a strong predictor of SVR whatever the IL-28B genotype. In patients with RVR, rs12979860 CC genotype is not associated with higher SVR rates

• IL-28B polymorphisms may be used in combination with some ISGs, viral genotype and other SNPs to improve prediction of treatment response. IL-28B SNP may be less predictive in triple therapy and future combination

combination of these different markers may help identify a strong predictive genetic signature for fibrosis progression and treatment response.

Genome wide association studies, power and limitations

When the GWAS technology was first described in 1996 [2] (Box 1), its main limitations were due to the lack of technology and the authors suggested geneticists to keep their samples for future experiments. Originally, the HapMap project characterized the pattern of genetic variations in 270 individuals of different ethnicities. The dataset then amounted to a total of 3.1 million SNPs, which is a very important resource for the selection of genetic markers and genotyping assays.

GWAS involves identification of statistical associations between a trait or disease and a genetic polymorphism (SNP), throughout the entire genome.

Linkage disequilibrium can be used to indirectly determine untyped variations around an SNP. The r2 value, which is commonly used to evaluate linkage disequilibriums, measures the correlation between alleles at a nearby genetic variant. If alleles of 2 SNPs are always found on the same chromosome, there is a perfect correlation and r2 = 1. In practice, this means that typing one of these 2 SNPs will provide complete allele information at the 2 sites. If r2 <1 between the 2 alleles, the sample size will need to be proportionally increased to detect a significant association [3].

So far only SNPs with a frequency of more than 5% of the minor allele can be detected effectively by linkage disequilibrium in GWAS. Thus, the HapMAp project does not provide perfect coverage of GWAS so that even in very large GWAS it is impossible to detect rare low frequency genetic variants. However, the technology will probably improve in the future, thus increasing coverage of low frequency variants.

Different methods of correcting the p values of associations have been described to counteract associations due to chance because of the many statistical tests. The most commonly used approach consists in the adjustment of the p value according to Bonferroni. The threshold of 0.05 is divided by the number of SNPs analyzed, which leads to an adjusted threshold of 10~6 to 10~8, for current available assays. However, several real associations may be lost by deleting all associations with a p value above this threshold. Furthermore, to improve the statistical relevance of GWAS, it is extremely important to replicate significant associations in at least one independent cohort of individuals (trait and control).

The GWAS technology has greatly improved in the last decade, however, the detection of rare variants would probably improve this approach even more [3].

Fibrosis

Liver fibrosis is defined as the excess accumulation of extracellular matrix proteins. Fibrogenesis is a complex dynamic process, mediated by necro-inflammation, and activation of stellate cells [4]. Fibrosis progression determines the prognosis and thus the need for treatment. It is therefore crucial to monitor fibrosis in patients with CHC. Several studies have assessed the identification of mRNAs and miRNAs expression during fibrosis (Table 1) and will be discussed in the first part of the review.

The natural history of HCV and factors associated with fibrosis progression are discussed in Box 2.

Principles of GWAS and its clinical and biological application

Patients with the trait . or the disease

Controls

IU FT11 IhFI PI I UHFI PI I S

-3,000,000 SNPs in the genome

Domain significantly associated with the trait

Chr location 22

GWAS uses dense maps of SNPs covering the entire genome to look for allele frequency differences between cases (disease or trait) and controls.

The study of the association between the isolated marker and a disease or trait is based on the selection of genes that are already known to play a role in the trait, while GWAS is based on whole genome scanning. Thus, the main advantage of GWAS is to identify both genes that are expected to play a role and genes that are not, providing new insights into the understanding of the physiopathology of the disease. This technique has revolutionized the identification of genetic markers associated with common disease or traits. Hundreds of thousands of SNPs are tested in a single GWAS for their association with a disease or trait in hundreds or thousands of people. A significant difference in frequency suggests that the corresponding region of the genome encodes for functional DNA variants that may influence the tested disease or trait.

The results obtained with GWAS can be used in two different ways: (i) to help to understand the physiopathology of the disease or trait tested and (ii) to improve personalized medicine. GWAS can identify markers that may be used to develop new therapeutic targets and be tested as new biomarkers to evaluate the risk in patients associated with this variant.

Variation of mRNAs expression and fibrosis

A deregulation of gene expression mainly affecting the IFN ab and y pathways ( STATI, STAT2, ISGF3G/IRF9, IFI27, GIP3, GIP2, OAS2, MXI, CXCL9, CXCLI0, CXCLII, and Viperin) has been reported in patients with CHC and mild fibrosis [5,6].

The transition from mild to moderate fibrosis is crucial in the decision to treat. The expression of 240 liver genes has been compared in 62 patients with mild fibrosis (F1) and moderate fibrosis (F2). Twenty-two genes were upregulated in F2 and mainly involved the cytoskeleton, growth factor cytokines, growth factor receptors, extra-cellular matrix remodeling, and the cell junction [7].

Liver steatosis is frequent in patients with CHC [8]. Three genes involved in the inflammatory pathway (SITPEC, SIGIRR, and TOLLIP) have been described as specifically associated with advanced steatosis in CHC [9].

One study investigated changes in liver mRNAs expression in 13 transplanted patients comparing patients in whom fibrosis progressed with those in whom it did not, before and after transplantation [10]. Fifteen of the 31 upregulated genes encoded for markers of myofibroblasts and myofibroblast-like cells. Liver stress injury and fibrosis development can cause an increase in myofibroblasts due to activation of HSCs and their conversion into the contractile phenotype [10]. It is inter-

esting to note that these data suggest that early fibrosis progression may be associated with a reduction in the pools of quiescent HSCs and with an increase in the number of myofi-broblast-like cells.

Variation in micro-RNAs expression and fibrosis

Micro-RNAs regulate up to 60% of cellular mRNA expression and stability [11-14].

In one study, mir-21 expression was found to be correlated to both HCV viral load and fibrosis [15]. Results are conflicting for mir-122 but it is probably only weakly or not associated with viral load [15,16]. Two studies have reported a correlation between mir-122 expression, liver damage, and stages of fibrosis [15,16] while another did not find any association with mir-122 expression in the serum of patients with CHC [17].

A recent study demonstrated that the different members of the mir-29 family were all downregulated in HCV infected patients. Moreover, freshly isolated HSCs expressed a high rate of mir-29, which was rapidly and markedly reduced after HSC activation [18]. Mir-29 targeted various types of collagen and, interestingly, mir-29 inhibition in mice has been shown to upreg-ulate collagen expression in the liver [19]. Thus, mir-29 downreg-ulation during HSCs activation might play a role in fibrosis by inducing direct accumulation of collagen in the liver.

Liver fibrosis: modification of liver architecture

Normal liver

Hepatocytes

Liver injury

Lymphocyte

Space of Disse

Quiescent stellate cell

Stimuli

Chronic infection, alcohol, etc...

Hepatic sinusoid Normal liver:

The hepatocytes form a parenchymal cell. Quiescent stellate cells are localized between the parenchyma and the sinusoid endothelial cells. Kupffer cells are localized below the endothelial cells in the hepatic sinusoid.

Endothelial cell Activated stellate cell

Deposition of scar matrix

Fibrosis:

Kupffer cell activation

Activation of HSCs to a myofibroblast phenotype.

HSCs activated secrete high amounts of extracelullar

matrix protein.

Activation of Kupffer cells.

Kupffer cells secrete fibrogenic mediators.

Lymphocytes infiltrate the parenchyma.

The accumulation of extracellular matrix proteins and marked modifications in liver architecture define fibrosis progression. In the normal liver, hepatocytes form parenchyma. Hepatic stellate cells (HSCs), that are key cells involved in fibrogenesis, are located between parenchymal cells (hepatocytes) and sinusoidal endothelial cells of the hepatic lobule. HSCs are quiescent and store vitamin A and retinyl palmitate in lipid droplets within the cytoplasm. Under physiological conditions, HSCs regulate vitamin A homeostasis by expressing specific receptors for retinol-binding protein (RBP) at the cell surface. Activation of retinol is regulated by endocytosis of the complex retinol/RBP. HSCs are activated by different stimuli such as chronic viral infection or alcohol intake. Activated HSCs proliferate and undergo a proliferative myofibroblast (MF) phenotype. Under pathological conditions, HSCs produce large amounts of extracellular matrix protein, including collagen, proteoglycan and adhesive glycoproteins, and release vitamin A.

Kupffer cells are the resident liver macrophages in the liver. They remove material from the portal circulation. Kupffer cells direct the destruction of hepatocytes by producing harmful soluble mediators and act as antigen-presenting cells during viral infections. Kupffer cells produce a significant amount of chemoattractant molecules for cytotoxic CD8 and regulatory T cells. They are one of the main sources of transforming growth factor pi production, which induces the transformation of HSCs into myofibroblasts.

When hepatocytes undergo necrosis from different stimuli, infiltrating lymphocytes surround the parenchyma.

Single nucleotide polymorphisms and fibrosis

identification ofSNPs that modulate gene expression associated with fibrosis and fibrosis progression

Several studies have tried to indentify SNPs associated with either fibrosis progression or treatment response (Table 2).

Matrix metalloproteinases (MMPs) play an important role in fibrosis progression. MMP-1, MMP-3, and MMP-9 gene polymorphisms have been shown to influence the transcriptional activity of their respective gene promoters. Interestingly, both MMP-1 2G

homozygote and MMP-9 C allele were more frequent in HCV patients with cirrhosis than in those without cirrhosis [20].

Monocyte chemotactic protein 1 (MCP-1) is upregulated in HSCs during CHC. MCP-1 harbors a functional polymorphism located in its promoter. Interestingly, the 2A homozygote genotype in this specific polymorphism was more frequent in patients with mild fibrosis [21].

Decreased vitamin D levels and genetic variations in the vitamin D receptor (VDR) gene have been described as an important modulator of multiple diseases, including hepatic disorders [22].

Table 1. Variations in mRNAs and miRNAs expression associated with fibrosis progression. (A) Markers identified by candidate gene strategy; (B) markers identified by scanning approach.

A References

Patients (n) Targets (n) Results

Asselah et al., [7]

240 cytoskeleton (KRT19 and SCG10)

growth factors cytokines (CXCL6, IL-8, IL-2, IL-1A and CXCL10)

growth factors receptors (CCR2, CXCR3 and CXCR4) extra-cellular matrix remodelling (TIMP1, MMP7 and MMP9) cell junction (ITGA2 and CLDN4)

miRNAs

Marquez et al., [15] 20 2 mir-122, mir-21

Morita et al., [16| 185 1 mir-122

Bihrer et al., [17] 68 + 19 1 mir-122

B References Patients (n) Targets (n) Results

Smith et al., [10] 13 (0, 3, 6 and 13,026 markers of myofibroblasts (MF) and MF like cells (CARP,

12 months MAGP2, NDRG4, COL12A1, MYOM1, CHRND, FHL1,

after liver MYBPC1, CASQ2, CHRNA1, AMPD1, CACNA1S, MYH2,

transplantation) MYL2 and NEB)

retinoid related proteins (RARRES3, STRA13, RXRB, RXRA,

RDH5, RBP4, RBP5, RODH and RODH-4)

Chiappini et al., [9] 43 22,300 inflammatory pathway (SITPEC, SIGIRR and TOLLIP)

miRNAs

Bandyopadhyay et al., [18] 22 + 4 346 mir-29 family

Table 2. Identification of SNPs associated with fibrosis and the response to antivirals in patients with chronic hepatitis C.

Genes Description of polymorphisms

MMP1 and 9 MMP1 2 G homozygote at position -1607 and MMP9 C allele at position -1562 are more frequent in cir-rhotic patients

CCL2 (MCP1) AA homozygote at position -2518 is more frequent in mild fibrosis

Fibrosis Cirrhosis risk score 7 SNPs (AZIN1: rs62522600; TLR4: rs4986791; TRPM5: rs886277; AP3S2: rs2290351; B008027: rs4290029; STXBP5: rs17740066; AQP2: rs2878771) have been all associated with fibrosis. AZIN1 SNP generates an alternative spliced from of AZIN1 that modifies the fibrogenic potential of HSCs TLR4 SNP have an identified role in fibrosis

PNPLA3 The rs738409 mutant GG is associated with higher risk of steatosis, fibrosis and fibrosis progression

Vitamin D receptor (VDR) Haplotype rs1544410 C, rs7975232 A and rs731236 A with fibrosis progression and cirrhosis

KIR/HLA The combination of KIR2DL3 and HLAC1 is more frequent in patients with high SVR rates

e s IL6 The SNP rs1800795 CC is associated with low IL6 production and high SVR rates

n o p s e IL10 Mutations at positions -819, -1082 and -592 are associated with modulation of IL-10 expression and different viral SVR rates

ral IFNG The mutation C764G is associated with higher SVR rates

> CCR5 CCR5A32 deletion is associated with resistance to HIV-1 and with poor SVR rates in HCV patients

IL28B rs1299860 CC genotype and rs8009917 TT are both associated with high SVR rates

VDR genotyping in 251 patients with chronic hepatitis C showed an association between the haplotype rs1544410 C, rs7975232 A, and rs731236 A with fibrosis progression and cirrhosis. Forty-five percent of the [CCA]-haplotype patients had rapid fibrosis progression and 21.1% had cirrhosis [23].

Cirrhosis risk score

A gene-centric disease association study of 24, 832 putative functional SNPs was performed to assess the association of SNPs with cirrhosis in a cohort of 433 patients with CHC [24]. One SNP located in the DEAD box polypeptide 5 was associated with an

increased risk of advanced fibrosis while the second SNP, located in the gene encoding carnitine palmitoyltransferase 1A (CPTAI), was associated with a decreased risk of advanced fibrosis [24].

In a second study, the authors confirmed all significant SNPs, and selected 361 markers to build a signature predicting cirrhosis, called the cirrhosis risk score (CRS) [25]. Interestingly, DDX5 and CPTIA were not selected for the final 7 SNPs for the CRS. Possible reasons were (i) lower odds ratios and frequencies in the risk group and (ii) decreased robustness and accuracy of these 2 SNPs in multivariate analysis compared to the 7 selected genes. Of the 7 CRS genes, antizyme-inhibitor-1 (AZINI) and Toll-like receptor 4 (TLR4) have been shown to play a role in fibrosis. A recent study has reported that the association of AZINI SNP with the rapid progression of fibrosis, leads to enhanced generation of a novel alternative splice form from AZIN1 that modifies the fibr-ogenic potential of HSCs [26]. All 7 SNPs were associated with the risk of cirrhosis with odds ratios ranging from 1.86 to 3.23. However, the AUC of each SNP was <0.6, showing that predictability was moderate when they were used individually [25]. The addition of clinical factors to the group of SNPs or each of them individually did not significantly improve the AUC.

Two major limitations are associated with the use of CRS to identify patients with rapid progression of fibrosis: (i) CRS cutoff values may only distinguish patients with a very high risk of cirrhosis (ii) CRS was identified in Caucasian patients so it may not be applicable to all ethnic groups [25].

In another study, paired liver biopsies from 271 untreated patients with CHC (F0 = 104, F1 =101, and F2 = 59) were fol-lowed-up for at least 60 months. Mean CRS was significantly higher is patients in whom fibrosis progressed, especially in patients with F0 at the initial biopsy [27].

CRS remained the only variable associated with fibrosis progression in multivariate analysis, including gender and alcohol intake [28].

Genetic studies have reported an association between advanced steatosis and specific SNPs located in genes encoding microsomal triglyceride transfer protein (MTP G493T) [29-31], peroxisome proliferator activated alpha (PPAR L162V) [32], methylenetetrahydrofolate reductase (MTHFR C677T) [33,34], cytokines playing a role in the inflammatory response such as interlekin-10 and -6 (IL-10 and IL-6) [35], transforming growth factor beta-1 (TGFB1) [35], tumor necrosis factor (TNF, -238 position) [36,37] and leptin receptor (LEPR) [35].

PNPLA3 and fibrosis

A non-synonymous sequence variation (rs738409 C/G) encoding an isoleucine to methionine substitution in the adiponutrin/pat-atin-like phospholipase-3 (PNPLA3) has been shown to be strongly associated with increased hepatic fat levels [38]. This SNP was then shown to be associated with disease severity, fibro-sis, and steatosis in non-alcoholic fatty liver disease (NAFLD) [39,40] and in alcoholic liver disease (ALD). Moreover, the same SNP was also associated with elevated liver enzymes in healthy subjects [41]. Interestingly, patients with CHC carrying the rs738409 mutant GG allele had a high risk of steatosis as well as fibrosis and fibrosis progression [42-44]. However, there are conflicting results reporting that PNPLA3 rs738409 GG mutant variant may be a prominent risk factor for HCC in patients with alcoholic cirrhosis, while its effects were negligible in patients with HCV cirrhosis [45].

IL-28B and fibrosis

The analysis of rs8099917 SNPs during liver fibrosis in chronic hepatitis C showed that the G allele, previously shown to be a risk of treatment failure, was associated with lower activity and less fibrosis with a trend towards a lower rate of fibrosis progression. Interestingly, when patients were stratified according to HCV genotype, the association was more significant in HCV genotype non-1 infected patients [46]. However, independent studies have reported that fibrosis progression was not associated with either rs12979860 or with rs8099917 [47,48].

The analysis of a larger cohort showed that PNPLA3 polymorphisms were strongly associated with an increased risk of steatosis in patients with HCV (excluding genotype 3) while the association with IL-28B SNPs was weak [49]. Steatosis was found in 22.5% and 39.6% of two independent cohorts of patients carrying the favorable IL-28B genotype vs. 47.6% and 67.4% of IL-28B non-favorable genotypes, respectively [50].

It has been suggested that levels of LDL cholesterol are significantly higher in CHC subjects carrying the rs12979860 CC genotype compared to CT and TT [51]. However, triglyceride levels were lower in patients carrying the IL-28B CC genotype. IL-28B CC may be associated with less pronounced lipid metabolism disturbances, as shown by serum lipoprotein levels and hepatic steatosis.

Altogether, the different studies have suggested that various SNPs, especially, AZINI and PNLPA3 are associated with fibrosis progression. Moreover, several extra-cellular-matrix and chemo-kine mRNAs are probably upregulated in patients with more advanced fibrosis. However, it is important to bear in mind that some studies have investigated fibrosis progression by analyzing paired biopsies while other studies were cross-sectional. Taking into account the duration of infection could provide useful information to improve the evaluation of fibrosis progression in cross-sectional liver biopsies.

Prediction of treatment response

The current standard of care for chronic hepatitis C and the factors associated with a non-response are shown in Box 3.

Variation in mRNAs expression and treatment response

An 8-gene subset accurately predicted treatment response (GIP2/ IFI15/ISG15, ATF5, IFIT1, MX1, USP18/UBP43, DUSP1, CEB1, and RPS28) using a number of independent classifier analyses [52]. Interestingly, another study evaluated the expression profile of a selection of genes in SVRs and NRs. IFI27 and CXLC9, a two-gene signature, predicted the response to treatment in 79% of the patients with a predictive accuracy of 100% for NRs and 70% for SVRs [53]. One study showed that SVR could be predicted, prior to treatment, by analyzing gene expression of signal transducer and activator of transcription-6 (STAT-6) and suppressor of cytokine signaling-1. Interestingly, even after 24 h of treatment, IFN-dependent gene expression can help predict the probability of achieving an SVR [54]. Many of the genes, found to be upregu-lated in non-responders and responders, encode molecules secreted in the serum (cytokines) [55,56]. Thus, they are a logical approach to the development of serum markers to predict treatment response.

Current treatment in chronic hepatitis C and predictive factors of non-response

Host factors

Viral factors

Treatment

Advanced age

Male gender

Ethnicity

Compliance

Insulin-resistance

Alcohol

Cirrhosis

Genetic

Viral load Genotype Quasispecies

Regimen

Dose and duration Side effects

Treatment for genotype non-1 patients, includes the combination of PeglFN/RBV [140-142]. In patients with genotype 1, the new standard of care includes the addition of a protease inhibitor (boceprevir or telaprevir) to PeglFN/ RBV. The goal of treatment is to obtain a sustained virological response (SVR) defined as undetectable HCV RNA in serum after 24 weeks of post-treatment follow-up. SVR results in the eradication of HCV infection and improvement of the histological outcome [143].

Brief description of factors associated with SVR

Responsiveness to antiviral therapy depends upon viral factors as well as host factors. Viral factors associated with response to treatment are genotype and viral load [144].

Patients who develop a rapid virological response, defined as HCV RNA negative at treatment week 4 have a greater chance to achieve SVR (higher than 85%). Patients who do not have any decrease in viral load will not respond to treatment.

Advanced age, male gender, African American ethnicity, poor adherence, cirrhosis, insulin resistance (and also steatosis, diabetes and alcohol consumption) are all events associated with a poor response to PeglFN/RBV treatment [8, 145]. The chance of achieving an SVR significantly decreases in patients with immune depression, transplantation, or HIV co-infection [146].

Variation of micro-RNAs expression and treatment response

Since cellular miRNAs regulate many cellular pathways, including the immune response, some miRNAs are probably involved in the modulation of antiviral response to PeglFN/RBV in CHC. IFNb has been shown to rapidly modulate the expression of numerous miRNAs, and 8 cellular IFNb-induced miRNAs have sequence-predicted targets within the HCV genome [57].

The level of expression of intra-hepatic mir-122 has been shown to be associated with HCV treatment response. Expression of mir-122 was significantly lower in primary non-responders compared to early responders [58]. Interestingly, the anti mir-122 (SPC3649 or miravirsen) molecules that inhibit HCV replication in chimpanzees [59] have recently been tested in a randomized double-blind study in treatment naive patients with genotype 1 [60].

However, an independent study investigating the expression profile of 470 cellular miRNAs in 99 CHCs, showed no significant

difference in mir-122 expression between responders and non-responders [61]. Eight miRNAs (mir-34b, mir-145, mir-143, mir-652, mir-18a, mir-27b, mir-422b, and mir-378) were differentially expressed in responders and non-responders. Moreover, mir-34b and mir-422 were consistently and significantly high and low in non-responders both 12 and 24 weeks after the end of the treatment [61].

Single nucleotide polymorphisms and treatment response

The main SNPs associated with SVR are summarized in Table 2.

Killer cell immunoglobulin-like receptors (KIR) activating and inhibiting receptors

Natural killer (NKs) cells are a subset of lymphocytes that interact directly with virus-infected cells, activate dentritic cells and secrete Th1-type cytokines to increase antiviral cytotoxic T cell response. NK responses are controlled by multiple activating and inhibitory signals such as the KIR receptors. The ligands for these receptors are human leukocyte antigen (HLA) class I. The wide genetic diversity of the KIR family and the HLA class I generate a large number of combinations between KIR and HLA.

The combination of KIR2DL3 and HLA-C1 was associated with both spontaneous clearance [62] and SVR [63,64] in patients with CHC. This specific combination is supposed to have a weaker inhibitory effect than other combinations leading to a stronger NK cell response.

KIRs are clonally expressed on NKs in a stochastic manner. Interestingly, Khakoo et al. reported a linear trend between the number of KIR2DL3-HLA-C1 interactions and the ORs resolving the infection. In this model, NK cell activity may be mediated through weak inhibitory KIR2DL3-HLA-C1 interactions.

HLA class II alleles have been shown to play a role in spontaneous clearance in patients with HCV infection [65]. Interestingly, a new interaction between KIR2DL3 and HLA class II DRB1*1201 was found to be associated with spontaneous clearance [66].

Prediction of treatment failure improved from 66% with IL-28B to 80% using both IL-28B and HLA-C2/HLA-C2 genes [67]. Moreover, the incorporation of two KIRs in a model including viral load and ethnicity (SVR score) provided complementary results with IL-28B across the CC, CT, and TT genotypes [68].

Genetic variants in the cytokine system and treatment response STAT3 is mainly activated in the liver by IL-6, a cytokine that has been involved in a variety of cell functions including stimulation of hepatocytes to produce acute-phase proteins. The polymorphism rs1800795 within the IL-6 promoter is associated with lower IL-6 levels compared to patients carrying the G allele. Interestingly, higher response rates were reported in patients carrying the rs1800795 G allele compared to C [69]. Yee et al. confirmed the importance of rs1800795 in the viral response and reported that several haplotypes containing rs1800797, rs1800796, rs1800795, and rs2069830 within IL-6, were associated with lower SVR rates [70]. IL-10 is a T-helper type 2 cytokine that plays a major role in T and B cell regulation. Peripheral blood mononuclear cells (PBMCs) from patients with CHC had increased IL-10 mRNA and protein expression. Moreover IL-10 has been shown to inhibit the production of IFNa by stimulation with viral infections [71]. SNPs within

the 11-10 promoter at positions -819 and -592 have been associated with different IL-10 levels. Interestingly, a strong relationship was found between ¡L-10 polymorphisms and response to IFNa treatment [72]. The frequency of -1082 GG genotypes (high IL-10) was higher in patients who did not eliminate the virus compared to controls. The higher level of IL-10 in these patients was associated with a higher risk of ineffective viral clearance and development of chronic infection in female patients [73]. Of all the 8 SNPs identified in the entire ¡FNy gene, the variant C764G was significantly associated with SVR. Functional analyses showed that the G allele conferred higher promoter activity and a stronger binding affinity for HSF1 [74].

¡L-28B and treatment response

Since 2009, several independent GWAS have reported a strong association between SNPs, located in the ¡L-28B promoter region with both natural and treatment-induced viral clearance (summarized in Box 4).

Almost 85% of the patients with East Asian ancestry harbor the C allele while only 40% of the patients with African-American ancestry carry genotype CC (Fig. 1) [75]. Thus, rs12979860 genotype diversity could explain the higher SVR rate in Asian patients.

Interestingly, the rs12979860 CC genotype was also associated with early improved viral kinetics, a higher rate of rapid virological response, and complete early virological response [76]. The association of rs12979860 with viral response has been confirmed in independent cohort studies [77,78]. Interestingly, ¡L-28B genotype was associated with treatment response in patients with CHC but not in those with acute hepatitis C [79]. Moreover, jaundice was more common in CC patients (64%) during acute infection than in CT (24%) or TT (6%). However, jaundice was only associated with an increased chance of spontaneous viral clearance in non-CC patients [80].

It has been suggested that the influence of rs12979860 genotype is a stronger predictive factor of SVR in patients with HCV-G1 than in HCV non-G1 patients [81].

HCV-G-2 and G-3 patients carrying the rs12979860 CC allele had a more rapid reduction in plasma HCV RNA, 3 days after beginning of treatment. However, in accordance with previous results [82], no significant association was found between rs12979860 and SVR in this cohort (98 genotype 2 and 241 genotype 3 patients). Interestingly, the assessment of ¡L-28B SNPs in patients with genotype 2 or 3 might help determine the suitable treatment duration [83].

In a recent study including 164 HCV genotype 4 patients from different ethnic groups, ¡L-28B rs12979860 CC was associated with a better treatment response rate (81.8% vs. 46.5% and 29.4% for CC, CT and TT respectively). No significant relationship was found between rs12979860 and the stage of fibrosis [47].

Interestingly, it has been suggested that ¡L-28B SNP influences HCV re-infection in patients receiving liver transplants. Rs12979860 CC donors were associated with rapid, complete early, and sustained virological response to PegIFN/RBV, compared to CT and TT [84]. While the rs8099917 favorable genotype was associated with a higher SVR rate in both recipients and donors, recipient rs12979860 status will probably have a weaker impact on viral response [84]. The use of both ¡L-28B genotype in

CO £=

¡2 Africa Europe Asia America

n = 428 n = 761 n = 797 n = 358

Fig. 1. Frequency of IL-28B rs12979860 protective allele in worldwide populations. rs12979860 CC is present in up to 80% of patients with Asian ancestry and only 40% of patients with African ancestry. Figure adapted from data reported in Thomas et al. [77].

donors and recipients and HCV core substitution predicted an SVR with 83% sensitivity and 82% specificity [85].

Which specific IL-28B SNPs for the prediction of SVR? Rs8099917 was identified in part by Rauch et al. and Tanaka because rs12979860 was not investigated, since this SNP is not present on either the Illumina Array or the Affymetrix 6.0 genotyping platform. Prediction of SVR with rs12979860 or rs8099917 will probably not matter in Caucasian patients. However, the frequency of these SNPs in other ethnicities may limit its use as predictive factor in the general population. For example, the use of IL-28B in the decision to treat patients with African ancestry, in which the frequency of the rs 12979860 favorable allele is only 40%, would exclude a large number of patients from being eligible for treatment. Therefore, IL-28B may be useful in combination with other predictive factors to avoid excluding patients based on ethnicity.

CCR5 and HCV spontaneous viral clearance

The chemokine receptor CCR5 is activated through the binding of RANTES. CCR5 is also a co-receptor of HIV-1. Interestingly, a common 32-base deletion in the CCR5 gene has been associated with resistance to HIV-1 infection [86-88]. The potential role of CCR5 deletion in resistance to HCV has been studied and suggested to adversely affect outcome of HCV infection [89-94]. However, the different reports are conflicting.

A recent study has investigated the association of both CCR5D32 and rs12979860 with spontaneous HCV clearance

[95]. The authors described an association of response rates with rs12979860 CC only in CCR5 WT homozygous while HCV clearance remained poor in CCR5D32 carriers even in CC patients. Because the frequency of the CCR5D32 homozygous deletion is rare, it is difficult to study the influence of this mutation, either alone or in combination with IL-28B genotype, on the outcome of HCV infection. RANTES is expressed and secreted by HSCs and induces migration, proliferation, and fibrogenic properties

[96]. Different studies have reported the overexpression of CCR5/RANTES in models of liver fibrosis and in patients with CHC [97]. Pharmaceutical companies have developed RANTES inhibitors/CCR5 antagonists which have been successfully tested in phase III studies in patients with HIV infection [98]. Interestingly, the administration of the RANTES inhibitor greatly improved liver fibrosis in mice and accelerated fibrosis regression [99].

IL-28B identification by GWAS

GWAS IL-28B SNP identified Wild type/risk allele Total population % of SVR Population studied % risk allele (within each ethnicity) Viral genotype

Ge et al. rs12979860 C/T 1137 C/C: 79 C/T: 38 T/T: 26 American Caucasian African American Hispanic 30 60 40 1

Tanaka et al. rs8099917 rs12980275 T/G A/G 314 T/T: 64 T/G: 13 G/G: 0 Japanese 15 12 1

Suppiah et al. rs8099917 T/G 848 T/T: 56 T/G: 36 G/G: 31 Australian Caucasian 27 1

Rauch et al. rs8099917 T/G 914 T/T: 76 T/G: 22 G/G: 1 Swiss 17 1, 2, 3 and 4

Since 2009, several independent GWAS have identified the same SNPs located in the promoter region of IL-28B that are associated with HCV clearance [75, 82, 124, 125, 147].

A GWAS reported, for the first time, an association of response to PeglFN/RBV with IL-28B polymorphisms in patients with CHC.1137 patients were included in the cohort. In the different SNPs scanned, rs12979860 was strongly associated with treatment-induced viral clearance in both European-American, African-American and Hispanics. In patients with European-American ancestry, the SVR rate reached almost 80% in patients with genotype CC. However, in African-American patients only 50-55% of patients with the C allele achieve an SVR [75].

Two SNPs (rs12980275 and rs8099917) were found to be significantly associated with viral response to PeglFN/RBV, in an independent GWAS including 154 HCV genotype 1 Japanese patients. It is interesting to note that individuals who are homozygous for the rs8099917 minor allele GG (also called risk allele) were only found in NR [125].

rs8099917 SNP was strongly associated with treatment response in 2 groups of patients. The rs8099917 G allele could predict the response to treatment with 57% sensitivity and 67% sensitivity [124]. The authors showed that IL-28B had a distinct haplotype block and there was no significant association in SNPs outside this block. The haplotype analysis identified a six-allele haplotype (GCCTAG: rs12980275, rs8105790, rs8103142, rs10853727, rs8109886 and rs8099917) associated with viral response. Indeed, this haplotype was present in 31.5% of non-responders compared to 18.8% of responders [124].

In another GWAS, the rs8099917 TT genotype was associated with progression to chronic HCV infection in both mono-infected patients and HIV co-infected patients [82].

Combination of the IL-28B genotype with other factors to predict treatment response

Host factors

High ISGs expression before treatment has been associated with a low SVR rate [52,100]. Since treatment is based on PeglFN intake, patients who already have high ISG expression may not be as stimulated as patients with low ISGs expression. Analysis of post-treatment biopsies in patients with an RVR revealed that PeglFN did not induce ISGs expression above pretreatment levels [100].

Both IFNa and k induce ISGs expression in HCV infected cells, in vitro [101]. However, the kinetics of IFNk-mediated STAT activation and induction of effector genes were different from those of IFNa, suggesting distinct mechanisms of IFNk- and IFNa-induced antiviral states.

Intra-hepatic ISGs expression may be a better predictor of SVR than IL-28B genotype [102,103]. Interestingly, global expression of ISGs is strongly associated with genetic variation of IL-28B [103]. Multivariate analysis of predictors of response showed that a set of 4 ISGs were better predictors than rs12979860 SNP [102]. Despite a small sample size, another study reported an association between rs12979860 SNP and 3 ISGs (ISG!5, IFI27, and IFI6) [104]. Moreover, it has been suggested that IL-28B genotype is associated with a specific cell-type modulation of ISGs expres-

sion ( MxA, PKR, OAS!, and ISG15) in hepatic cells and PBMCs [105].

Several studies have shown that elevated IP10 levels may be a prognostic marker of HCV treatment outcome in HCV genotype 1 infection [55,106-110]. The combination of serum IP-10 and rs12979860 significantly improved the prediction of SVR [111113]. Serum IP-10 was particularly informative in rs12979860 CT carriers, in whom high serum IP-10 levels resulted in a 64% SVR compared to 24% in patients with low IP-10 [112]. Serum IP-10 levels below 150pg/ml significantly predicted a greater reduction of HCV RNA and increased SVR rates in genotype 1 rs12979860 CC patients [111].

It has been suggested that mir-122 expression is associated with treatment outcome [58]. IL-28B genotype and mir-122 hepatic expression have been reported to be independently associated with viral response [102].

Vitamin D deficiency is common in patients with chronic liver disease. A recent study showed that vitamin D serum levels improve prediction of an SVR in association with the IL-28B rs12979860 polymorphism [114]. Vitamin D maybe a key regulator of the innate immune response [115]. However, this study was retrospective. Furthermore, it has not been shown if correcting a vitamin D deficiency before starting treatment may increase SVR rates.

Viral factors and treatment response

Two amino acids substitutions at positions 70 and 91 within the core protein and an accumulation of mutations in the interferon sensitivity determining region (ISDR) located in the NS5A coding region have been associated with viral response [116,117].

Interestingly, two studies [118,119] have shown that ¡L-28B polymorphisms as well as amino acid 70 substitution in the core protein were independently associated with SVR. The SVR rate in patients receiving telaprevir in combination with PegIFN/RBV, was high in those carrying the rs8099917 TT genotype whatever the core 70 substitutions [118].

Of all the host and viral factors achieving an RVR is probably the strongest predictor of SVR [120]. Early viral kinetics were improved and there was a greater probability of achieving an RVR with the rs12979860 CC genotype compared to CT and TT [76,121]. RVR was a strong predictor of SVR whatever the ¡L-28B, suggesting that achieving an RVR may compensate for the negative influence of ¡L-28B genotype. The CC ¡L-28B genotype was associated with high SVR rates in non-RVR patients [76]. However, in patients with an RVR the rate of SVR was high and there were no associations between ¡L-28B genotype and SVR [121]. It is not clear whether the C allele is associated with a higher SVR rate in HCV genotype 2 or 3 patients achieving an RVR [122,123].

¡L-28B polymorphisms may be used in combination with several factors; ISGs, viral genotype and other SNPs before, but also during treatment, to improve prediction of treatment response.

The activity oflFNk and ¡L-28B polymorphisms

The activities of IFNks are summarized in Box 5.

Although multiple SNPs located in the ¡L-28B promoter region have been identified and associated with SVR, none of them were causal variants. The results of studies assessing variations of circulating IFNks in the different ¡L-28B SNPs are contradictory [104,119,124-126].

The putative causal SNP rs8103142 (Lys70Arg) within the ¡L-28B coding region was identified in strong linkage disequilibrium with rs12979860. However, there was no significant difference from the Lys70Arg mutation on either ¡L-28B activity or expression [104].

Detailed genotyping was performed on the ¡L-28B coding region in a cohort of 389 HIV/HCV co-infected patients. Homozygotes for the haplotypes rs4803219, rs28416813, rs8103142, and rs4803217 were strongly linked to the rs12979860 CC genotype (r2 = 0.97). This specific haplotype was especially frequent in individuals with spontaneous clearance compared to those with CHC [127], suggesting a possible effect of these SNPs on viral clearance.

Interestingly, IFNks were highly activated in chimpanzees immediately after HCV infection while IFNaßs were slightly induced [128].

However, it is important to remember that while a common variant associated with a disease in a GWAS is generally linked to a causal effect that is nearby, this is not necessary the case. Thus rs12979860 may be in strong linkage disequilibrium with an unidentified causal SNP located in another gene.

¡L-28B and future therapies ¡FNk-based treatment

The strong association between ¡L-28B genotype and treatment response suggests that IFNk may be an attractive alternative to

IL-28B-CC 90% 71%

IL-28B-nonCC

80% 68%

PR T12PR Telaprevir

PR BOC/PR48 Boceprevir

Fig. 2. SVR in triple therapy according to IL-28B rs12979860. Telaprevir-based therapy improved both RVR and SVR across the different rs12979860 genotypes. In patients with the unfavorable allele, the addition of telaprevir doubled SVR rates. From 87% to 90% of the CC patients achieved an SVR with telaprevir compared to 64% with PegIFN/RBV [135]. Therefore, patients with all different rs12979860 genotypes benefit from telaprevir triple therapy. Among patients carrying the rs12979860 CC allele, 89% of treatment-naïve, and 82% of patients with a treatment-failure had an early response (HCV RNA undetectable at week 8) with boceprevir in addition to PegIFN/RBV. It is interesting to note that these early responder patients were eligible for shorter treatment [139]. Naïve genotype 1 patients with the favorable rs12979860 CC allele do not benefit (SVR) from boceprevir triple therapy compared to PegIFN/RBV.

IFNa. Indeed, IFNk has a limited effect on hematopoietic cells and the central nervous system, promising antiviral activity in the liver and limited receptor expression.

Zymogenetics and Bristol-Myers Squibb have developed PegIFN^ and are assessing its efficacy in the treatment of HCV. A phase 1b study was published in 2010 [129].

The phase IIb study reported a higher early virological response (EVR) following treatment with PegIFNk combined with RBV than with PegIFNa, in patients with genotype 1 and 4. Interestingly, at different weekly doses of PegIFNk (240 to 120 ig), cEVR rates were 55-56.3% compared to 37.9% with 180 ig of PegIFNa in genotype 1 and 4 patients. The tolerability and safety of PegIFNk were better than with PegIFNa, with less anemia and fewer flu-like symptoms [130]. These findings show that PegIFNk has an antiviral effect against HCV. However, further and longer studies on the effect of PegIFNk are needed. Interestingly, rs12979860 CC was associated with an increase in SVR in patients treated with PegIFN (Fig. 2).

IL-28B and triple therapies

In naïve and previously treated genotype 1 patients, the present standard of care is triple therapy with the protease inhibitor boceprevir or telaprevir combined with PegIFN and RBV [131-134]. IL-28B status and response to therapy have been evaluated for telaprevir and boceprevir used in combination with PegIFNa/RBV. In studies of boceprevir triple therapy in both naïve and experienced genotype 1 patients, IL-28B CC genotype was associated with a higher SVR rate [131,134]. Moreover, the favorable genotype was significantly associated with undetectable HCV RNA after 8 weeks of therapy in both naïve (89% for CC vs. 52% for CT and TT) and experienced patients (89-82% for the CC genotype vs. 52% and 51% for CT and TT) [131,134]. Therefore, IL-28B may be used to identify patients who are eligible for shorter therapy. In naïve genotype 1 patients treated with boceprevir, the IL-28B polymorphism was an independent predictor of SVR. SVR rates were higher in CC, CT, and TT patients receiving triple therapy. The differences in SVR rates in patients receiving either PegIFN/ RBV or triple therapy were more marked in CT and TT patients than in CC patients (40% and 30% in CT and TT vs. 3% in CC).

IFNs lambda: signaling and activity

IFN type III or IFNAare genetically distinct from type I IFNs and act through a specific receptor system [148, 149]. However, type I and type III IFN induce the same signal transduction and share identical biological activities. IFNsA belongs to a cytokine type 2 family including IL-10, IL-22 and IL-26. There are three IFNsA encoded by three genes clustered on human Chr19, IFNA1 (IL-29), IFNA2 (.IL-28A) and IFNA3 (IL-28B).

IFNsA expression is induced by LPS or double stranded RNA TLR stimulation [150]. Plasmacytoid dendritic cells are the main producers of IFNsA. Types I and III IFNs are co-produced in response to the same inducers suggesting a common mechanism of regulation. IFNsA binds to a receptor at the cell surface containing two subunits: IFNLR1 specific for IFNsA and IL-10R2 shared among the cytokine 2 family members. While IL-10R2 is ubiquitously expressed, IFNLR1 expression is limited to certain type of cells. A high level of expression of IFNLR1 has been reported in hepatocytes from liver biopsies [151, 152].

IFNsA stimulation results in the activation of IFN-stimulated gene expression (ISGs). IFNsA and type I IFNs binding to their receptors activates the protein kinases Jak1 and Tyk2, leading to activation of downstream STATs. Activated STAT1 and STAT2 heterodimerize with IRF9 and form the ISGF3 complex. The activated complex translocates into the nucleus to activate ISGs transcription by recognition of their IFN-stimulated response element (IRSE) within the promoter region [153, 154]. Moreover, all class II cytokines including IFNsA are able to activate STAT1 ad STAT3. The heterodimer STAT1/STAT3 then translocates into the nucleus and binds IFNA-activated sites (GAS) again resulting in ISGs transcription [155]. Hundreds of ISGs are produced in response to IFNs stimulation. Evidence has shown that even if different IFNs signal through the same pathway each IFN can induce the activation of different ISGs [156, 157]. In the HCV replicon system, Marcello et al. reported that while IFNA induced a steady increase in ISGs levels, type I IFNs peaked early and declined rapidly [101]. These results supported a distinct antiviral state of type I and III IFNs.

The effect of type III IFNs on immune cell function is not fully understood. It has been reported that IFNA decreases the production of Th2-type cytokines, potentially activating a Th1 immune pathway [158-161].

In vitro, the antiviral activity of IFNsA has been described for several viruses including HCV and HBV [101, 153, 162]. Recently, Zhang et al. showed that IL-28B signal through the Jak/STAT pathway in HCV replicating cells [163].

Telaprevir-based therapy improved both RVR and SVR across all different rs12979860 genotypes (Fig. 2) [135]. Although only Caucasians were genotyped for IL-28B SNP, there was an increase

in SVR rates across all IL-28B genotypes in genotype 1 naïve patients treated with telaprevir triple therapy. Patients with the CC genotype were most likely to achieve an RVR and to have

shorter treatment duration. The difference in SVR rates between patients receiving triple therapy and PegIFN/RBV was more marked in patients with the T allele than in those with the CC genotype [135]. There was no significant difference in SVR rates across the different IL-28B genotypes with telaprevir triple therapy in genotype 1 experienced patients [136].

Multivariate analysis identified rs8099917 genotype TT and substitution at aa 70 (Arg70) as significant determinants of SVR after a 12-week or 24-week regimen of triple therapy in patients with HCV genotype 1 [118]. The efficacy of triple therapy was high in patients with the favorable genotype with an SVR rate of 84%, whatever substitution of core aa 70. However, in patients with the unfavorable genotype, the presence of Arg or Gly at position 70 in the core region was associated with a 50% and 12% SVR respectively [118].

The INFORM-1 study reported that a dual combination of the nucleoside polymerase inhibitor mericitabine and the HCV protease inhibitor danoprevir produced a rapid and substantial decrease in viral load that was maintained throughout two weeks of treatment [137]. Finally, the mean reduction in HCV RNA serum levels with the IFN-free regimen was slightly higher in patients with CC polymorphism than in those with CT and TT [138].

Overall, the ability to predict the SVR in patients receiving triple therapy has not been fully evaluated. IL-28B may have limited predictive value in patients with prior failure to PegIFN/RBV. Moreover, in patients with the favorable IL-28B genotype, it may be difficult to not use triple therapy considering the overall increase SVR rates, reported in the different trials, and the possibility of a shorten treatment duration.

For genotype 4, the current treatment remains the combination of PegIFN/RBV, thus the IL-28B polymorphism may be an important factor associated with response. Further studies are needed to determine whether patients with genotype 4 and good predictors of response, including IL-28B CC, can benefit from shorter therapy.

Conclusions

Prediction of both progression of fibrosis and SVR are main issues in chronic hepatitis C. Major advances in genetics during the last decade, allow the identification of specific markers associated with either fibrosis progression or viral response. In particular, SNPs located within genes encoding MMP-I and MMP-9, MCPI, PNLPA3, and vitamin D receptor have been associated with rapid progression of fibrosis. Moreover, CRS comprising 7 different SNPs was able to discriminate patients with high risk of developing a rapid fibrosis progression from those who will remain at low stages of fibrosis. Since the description of IL-28B SNPs association with both natural and treatment-induced HCV clearance, many studies have investigated the use of these factors for the prediction of viral response. IL-28B has been strongly associated with viral response in all reports, including large cohorts of patients.

However, for the single patient, the use of IL-28B as a predictive factor of treatment outcome and decision to treat is not sufficient. IL-28B should probably be combined with other markers to increase baseline prediction of treatment outcome.

During treatment, RVR is the strongest predictor of SVR even compared to IL28 SNPs. For individual patients, RVR may represent global predictors (host and viral) for response. Interestingly, the rs12979860 CC genotype was highly associated with viral

response in patients who did not achieve an RVR [121]. Recent studies have suggested that in triple therapy IL-28B genotyping identifies patients who might be eligible for shorter therapy [135,139]. In genotype 1 experienced patients, previous response (relapse, partial response, non-response) appears to be a stronger predictor than IL-28B status. If strong predictive factors of treatment response are identified for triple therapy for HCV-G1, the duration of treatment may be shortened.

Conflict of interest

The Authors declared that they do not have anything to disclose regarding funding or conflict of interest with respect to this manuscript.

Financial support

EE is supported by a fellowship from the French National Agency for Research on AIDS and Viral Hepatitis (ANRS).

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