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Viral sequence evolution in Chinese genotype 1b chronic hepatitis C patients experiencing unsuccessful interferon treatment
Infection, Genetics and Evolution 11 (2011) 382–390
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Viral sequence evolution in Chinese genotype 1b chronic hepatitis C patients experiencing unsuccessful interferon treatment Xiaogang Xiang a,b, Jie Lu b, Zhixia Dong a, Huijuan Zhou a, Wanyin Tao b, Qing Guo a, Xiaqiu Zhou a, Shisan Bao c, Qing Xie a,b,**, Jin Zhong b,* a
Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin Er Road, Shanghai 20005, China Key Laboratory of Molecular Virology and Immunology, Institut Pasteur of Shanghai, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 225 South Chongqing Road, Shanghai 200025, China c Discipline of Pathology (D06), Bosch Institute and School of Medical Sciences, The University of Sydney, New South Wales 2006, Australia b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 6 July 2010 Received in revised form 12 November 2010 Accepted 24 November 2010 Available online 13 December 2010
The efficiencies of IFN-a based therapy in chronic genotype 1b HCV patients are still unsatisfied to date. The mechanisms underlining treatment failure remain unclear and controversial. To investigate HCV sequence evolution in unsuccessfully treated genotype 1b patients before, during and after the therapy, full-length open-reading-frame of HCV genomes at week 0, week 48 and year 5 in one breakthrough and one nonresponse patients were amplified by reverse transcription (RT)-nested-PCR and sequenced. Mutations were scored and analyzed according to their locations in the HCV genome. HCV sequences in the breakthrough patient displayed significantly more mutations during the one-year therapy than that in the nonresponse patient, with p7 and NS2 encoding regions having the highest mutation rates. Most of the mutations selected during the therapy phase in the breakthrough patient were maintained and few new mutations arose in the four-year post-therapy phase, suggesting these mutations might not compromise viral fitness. Altogether our data suggest that mutations occurred during the therapy phase in the breakthrough patient are likely driven by the action of interferon and ribavirin, and these mutations may have important effects on the responses to interferon based therapy in genotype 1b HCV patients. ß 2010 Elsevier B.V. All rights reserved.
Keywords: Hepatitis C virus Interferon therapy Sustained virological response Breakthrough Nonresponse Sequence evolution
1. Introduction Chronic hepatitis C virus (HCV) infection is a major public health burden and a leading cause of chronic liver disease including chronic hepatitis, liver cirrhosis, end-stage liver disease and hepatocellular carcinoma (HCC), and it is one of the most common indications for liver transplantation worldwide (Ghany et al., 2009). The World Health Organization reports that over 3% of the global population with approximately 180 million individuals is estimated to be infected with HCV. The prevalence was estimated to be 1.6% in the United States (Armstrong et al.,
Abbreviations: HCV, hepatitis C virus; CHC, chronic hepatitis C; SVR, sustained virological response; IFN-a, interferon alpha; ORF, open reading frame; HCC, hepatocellular carcinoma. * Corresponding author at: Institut Pasteur of Shanghai, Chinese Academy of Sciences, 225 South Chongqing Road, Shanghai, 200025, China. Tel.: +86 21 63858685; fax: +86 21 63859365. ** Corresponding author at: Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin Er Road, Shanghai 20005, China. Tel.: +86 21 64370045x360403; fax: +86 21 64454930. E-mail addresses: [email protected] (J. Zhong), [email protected] (Q. Xie). 1567-1348/$ – see front matter ß 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.meegid.2010.11.011
2006), and about 1% in Europe (Sy and Jamal, 2006), but over 3.2% with more than 41 million people infected in China (Xia et al., 1996). In nearly 85% of the cases, the disease progresses into chronicity (Ghany et al., 2009). Currently, there is no vaccine to prevent HCV infection, and the only available treatment regimens based on interferon alpha (IFNa) or pegylated (peg)-IFN-a plus ribavirin for 24–48 weeks lead to a sustained virological response (SVR) in about 39.8–40.9% of patients infected by genotype 1 HCV (McHutchison et al., 2009), which is the prevalent HCV genotype in the United States, Europe, and China (Ghany et al., 2009; Lu et al., 2005), while 75–80% for genotypes 2 and 3 (Feld and Hoofnagle, 2005). Treatment failure occurs in the following forms: nonresponse (serum HCV RNA level declines less than 2 log between baseline and week 12, and remains above the detection limit throughout treatment), breakthrough (serum HCV RNA level drops below the detection limit, but rebounds while on therapy), and relapse (serum HCV RNA level drops below the detection limit, but rebounds after the therapy is discontinued) (Dieterich et al., 2009). Unfortunately, molecular mechanisms underlying the failure of the interferon based therapy for chronic hepatitis C (CHC) patients are still unclear. Host factors have been suggested to contribute to the resistance to the
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interferon based therapy (Gao et al., 2004; Ge et al., 2009; SarasinFilipowicz et al., 2008; Suppiah et al., 2009; Tanaka et al., 2009). Recent studies showed that single nucleotide polymorphisms (SNPs) (rs12979860, rs12980275, and rs8099917) near the IL28B gene encoding IFN-l-3 on chromosome 19 are strongly associated with the clinical outcome of the interferon based therapy, although the molecular mechanisms behind these observations remain elusive (Ge et al., 2009; Suppiah et al., 2009; Tanaka et al., 2009). On the other hand, the strong correlation of SVR rate with HCV genotypes suggests that HCV genomes (viral factors) must also be critical determinants for the outcome of the interferon therapy. Although it has been suggested that multiple HCV proteins are associated with interferon resistance (Wohnsland et al., 2007), including NS5A (ISDR; PKR-BD; V3; V4 (Jain et al., 2009); IRRDR (ElShamy et al., 2008)), E2 (PePHD; HVR1; HVR2; HVR3 (Troesch et al., 2006)), NS3/NS4A, and Core (Wohnsland et al., 2007), none of these studies reached a definitive consensus, and there are lots of contradictions between in vivo and in vitro results (Aus dem Siepen et al., 2005; Brillet et al., 2007; Gale et al., 1998; Gaudy et al., 2005; Jardim et al., 2009; Tsai et al., 2008). Moreover, most of these results were derived from the comparison of the HCV genomic sequences between the SVR patients and the patients who did not achieve SVR, therefore, it is difficult to rule out the contributions of genetic background and host factors of different patients to the outcome of the therapy. Breakthrough patients who initially respond to the interferon based therapy well and the HCV RNA level decreases to the undetectable level, but have reappearance of HCV RNA in serum during the therapy may represent a more unbiased subject to investigate whether the evolution of viral genomic sequences within a single patient play any roles in interferon resistance. Since interferon resistant HCV quasispecies might be selected during the therapy (Cuevas et al., 2008; Enomoto et al., 1995; Kuntzen et al., 2007; Xu et al., 2008), the analysis of the viral genomic sequences before, during and after the therapy may help understand the roles of viral determinants of interferon resistance. The present study aimed to investigate the evolution of HCV genomic sequences in CHC patients with genotype 1b during the interferon therapy. We compared the full-length HCV ORF sequences before, during and after the therapy, as well as the mutation types, in one breakthrough patient and one nonresponse patient. We found that the HCV genomic sequences in the breakthrough patient displayed significantly more mutations during the 1-year therapy than that in the nonresponse patient, with p7 and NS2 encoding regions having the highest mutation rates. The HCV sequence analysis of a 4-year post-therapy followup revealed that a vast majority of mutations selected during the therapy phase in the breakthrough patient were maintained while very few new mutations arose during the 4-year post-therapy span, suggesting the selection of the mutations during the therapy phase may be driven by the action of interferon and ribavirin and these mutations likely did not compromise viral fitness. Our data provide additional evidence to demonstrate that viral determinants may contribute to interferon resistance during interferon therapy of CHC patients. 2. Methods 2.1. Patients and clinical treatment A total of 19 CHC patients (11 males and 8 females) with genotype 1b who received the treatment of conventional IFN-a plus Ribavirin from August 2003 to July 2004 at the Department of Infectious Diseases of Ruijin Hospital, Shanghai Jiaotong University School of Medicine, were included in this study. The patients, all Chinese Han ethnicity, were treatment-naı¨ve prior to IFN-a and Ribavirin, and were free of human immunodeficiency virus (HIV)
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infection and other concomitant liver diseases, such as hepatitis B virus (HBV) or other hepatotropic virus infections, alcohol abuse, autoimmune hepatitis and hereditary liver diseases. The study had been approved by the Ethics Committee of Shanghai Ruijin Hospital in accordance with the Helsinki Declaration, and written informed consents were obtained from all patients. They received conventional IFN-a three times a week at a dose of 6 million units subcutaneously, and ribavirin was administered orally twice a day to a total dose of 1000 mg (body weight <75 kg) or 1200 mg (body weight 75 kg) for 48 weeks and were followed up at least 6 months after completion of one-year therapy. Two cases (body weight <75 kg) were selected retrospectively for another four-year follow-up after termination of therapy: one was a breakthrough patient (patient 002), and the other was a nonresponse patient (patient 007). No dose modification was performed in the two patients during anti-viral treatment. Serum samples were collected at multiple time points during and after therapy, and were stored at 80 8C. Samples, collected at week 0 (baseline), week 12, week 48 and year 5, were used for HCV sequences analyzing in this study. 2.2. HCV RNA quantification and genotyping of CHC patients HCV RNA quantification was performed using a one-step quantitative HCV RT-PCR kit (PG Biotech, Shenzhen, China) with the standard-curve of Taqman probe method, and the detection limit was 1000 copies/ml. HCV genotyping was performed using the HCV genotyping gene chip kit (Realchip Biotech, Ningbo, China) according to the manufacturer’s instructions. 2.3. HCV RNA extraction, RT-PCR, full-length HCV ORF amplification and sequencing Total RNA was extracted from 140 ml of serum samples, using QIAamp Viral RNA mini kit (QIAGEN, Hilden, Germany), and dissolved in 60 ml of elution buffer and stored at 80 8C until use. The sequencing of HCV genomes was performed following a previously published protocol with some modification (Yao and Tavis, 2005). In brief, HCV RNA was reverse-transcribed (RT) into cDNA using TaKaRa RNA LA PCRTM Kit (AMV) Ver.1.1 (TaKaRa, Dalian, China) with HCV specific primers. Nested-PCR primers spanning the full-length HCV ORF sequences used in this study were listed in Supplementary Table S1. All PCR fragments were purified using the AxyPrep DNA Gel Extraction Kit (Axygen, Hangzhou, China) and then sequenced. Consensus sequences for the full-length HCV ORF were obtained by aligning overlapping sequences of PCR products as described previously (Yao and Tavis, 2005). A total of 7 full-length HCV genotype 1b sequences generated in this study had been deposited in GenBank under the accession numbers from GU451218 to GU451224. 2.4. Sequence analysis Vector NTI Advance Version 10.3 (Invitrogen, Carlsbad, CA, USA) and BioEdit Sequence Alignment Editor Version 7.0.9.9 (Ibis Biosciences, Carlsbad, CA, USA) (Hall, 1999) were used to edit, assemble and align sequences. To insure integrity of the sequence data, appropriate precautions were taken as recommended (Learn et al., 1996; Yao and Tavis, 2005). Amino acid sequences were deduced from nucleotide sequences. Mutations were rechecked through the chromatogram. If there were two peaks at the same residue, HCV RNA would be PCR amplified again and resequenced. By evaluation of numerous overlapping sequence fragments, only clear changes were identified as mutations. Mutation rates at different time points were calculated at nucleotide and amino acid levels in the 10 viral protein encoding regions, respectively. The
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Table 1 Clinical data of chronic hepatitis C patients treated with IFN-a plus ribavirin. Characteristic
Breakthrough (n = 5)
Nonresponse (n = 2)
Relapse (n = 3)
SVR (n = 9)
P value
Age (years) Gender (M/F) Body weight (kg) Baseline HCV RNA (log10 copies/ml) ALT (IU/l) AST (IU/l) Total bilirubin (mmol/l) Albumin (g/l) Platelet count (1E9/l) AFP (ng/ml) Histological activity index (pre-treatment) Fibrosis stage (pre-treatment) Histological activity index (post-treatment) Fibrosis stage (post-treatment)
49.6 16.6 3/2 67.2 9.7 6.88 0.30 140.4 52.4 95.8 47.8 15.0 4.7 46.6 4.8 168.6 86.7 7.6 7.1 5.6 0.5 3.4 1.5 5.0 0.8 3.0 1.4
46.5 14.8 1/1 57.5 7.8 6.7 0.24 208.5 133.6 107.5 40.3 18.0 4.2 46.0 5.7 119.0 49.5 7.5 3.5 6.0 1.4 2.5 0.7 5.5 2.1 2.5 0.7
46.7 4.2 1/2 66.0 5.3 6.55 0.39 111.3 10.7 80.7 26.7 16.7 9.3 47.0 3.6 139.7 9.5 3.3 1.2 8.0 2.0 3.7 1.2 6.0 1.4 3.5 0.7
41. 9.7 6/3 69.1 7.7 6.43 0.53 126.8 57.1 85.0 46.9 13.9 2.7 48.2 1.2 183.7 41.1 4.4 2.1 5.3 2.1 2.7 1.7 2.9 1.6 2.6 2.1
0.677 0.823 0.362 0.327 0.345 0.887 0.651 0.738 0.415 0.391 0.184 0.688 0.039 0.902
Note: All measurement data here were expressed as means with standard deviations, and differences between different groups were determined by one-way ANOVA, where P < 0.05 was considered to be statistically significant.
rates of synonymous substitution per synonymous site (dS) and non-synonymous substitution per non-synonymous site (dN), as well as the dN/dS ratio, were obtained at SNAP-(Synonymous Nonsynonymous Analysis Program)-http://www.hiv.lanl.gov (Korber, 2000). 2.5. Statistical analysis All analyses were carried out using SPSS statistical software version 17.0 (SPSS Inc. Chicago, IL, USA). The differences among different groups were determined by one-way ANOVA, where P < 0.05 was considered to be statistically significant.
liver alanine aminotransferase (ALT) showed that the liver damage was temporally controlled during the therapy (ALT 50 IU/l at week 12), but became deleterious again when serum HCV RNA rebounded. Eventually, this patient developed liver cirrhosis 4 years later and had experienced three times of massive upper gastrointestinal hemorrhage during the fifth year. On the contrary, patient 007 (Fig. 1F), a 56-year-old female with a 13-year-history of HCV infection at the onset of treatment, did not respond to the interferon treatment very well as serum HCV RNA level did not dropped significantly, but the liver ALT level did restore to normal and maintained at a very low level throughout the therapy and post-therapy phases. This patient did not develop liver cirrhosis in our study time frame.
3. Results 3.1. Patient characteristics and antiviral therapeutic efficiency
3.2. Sequence analysis of full-length HCV ORF in the breakthrough and nonresponse patients before, during and after therapy
Nineteen genotype 1b chronic hepatitis C patients were recruited for receiving the treatment of IFN-a plus ribavirin. The treatment regime was described in Methods, and the patients’ characteristics were summarized in Table 1. Serum HCV RNA kinetics of all the patients during therapy was shown in Fig. 1. Nine of the nineteen patients achieved SVR (47.4%), as the serum HCV RNA levels in these patients became non-detectable at the termination of the therapy (week 48) and thereafter (week 60 and week 72). In those who failed to achieve SVR, five were breakthrough (26.3%), two were nonresponse (10.5%) and three relapsed after the cessation of the therapy (15.8%). There were no significant differences among breakthrough, nonresponse, relapse and SVR patients in the age, gender, body weight, pre-treatment HCV RNA levels, ALT, AST, total bilirubin, albumin, platelet count, AFP, pre-treatment liver histological activity index (HAI) and fibrosis stage and post-treatment liver fibrosis stage except for the post-treatment liver HAI (an indicator of liver inflammation), which was much better in patients achieved SVR (P = 0.039). One breakthrough patient (patient 002) and one nonresponse patient (patient 007) were selected retrospectively for a long-term follow-up at the end of treatment. The clinical courses of the two patients were shown in Fig. 1E and F. Patient 002 (Fig. 1E), a 66 years old male with a 21-year-history of HCV infection at the onset of treatment, initially responded to the therapy very well and serum HCV RNA level quickly decreased from 107 copies/ml at baseline to below the detection limit (103 copies/ml) at week 12. However, serum HCV RNA reappeared at week 24 and reached above 107 copies/ml at week 48 when the therapy was terminated. Serum HCV RNA remained positive in the 4-year post-therapy period and was 1.4 105 copies/ml at year 5. The measurement of
The sequences of full-length HCV ORF from patient 002 (breakthrough) and patient 007 (nonresponse) at week 0 (pretreatment baseline), week 48 and year 5 were analyzed respectively. Four overlapping fragments spanning the full-length HCV ORF were PCR amplified and bulk sequenced (Fig. 2A). The nucleotide sequence at each position was verified by at least 6 independent sequencing reactions from forward and reverse directions. The consensus sequences, either single peaks or predominant nucleotide peaks, were constructed to represent the major quasispecies in each sample. The week 0 baseline HCV sequences were used as references to score mutations in HCV genomes of week 48 and year 5. Notably, there were much fewer mutations in the HCV genomes of nonresponse patient than that of the breakthrough patient at week 48 and year 5. As shown in Fig. 2B, there were 67 nucleotide changes and 12 amino acid changes from week 0 to week 48, and 140 nucleotide changes and 28 amino acid changes from week 0 to year 5 in the nonresponse patient, while there were 180 nucleotide changes and 41 amino acid changes from week 0 to week 48, and 302 nucleotide changes and 62 amino acid changes from week 0 to year 5 in the breakthrough patient. Furthermore, we calculated the ratio of nonsynonymous mutation to synonymous mutation (dN/dS) during the therapy (Korber, 2000). The dN/dS values were 0.1270 and 0.0826 during the therapy phase (weeks 0–48), or 0.9453 and 0.0953 in the periods from week 0 to year 5, for the breakthrough and nonresponse patients, respectively. We then analyzed the distribution of mutations of the week 48 HCV genomes in each of 10 viral protein-encoding regions. Mutation rates were calculated as the number of mutations divided by the length of each viral protein-encoding region (Fig. 3A
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Fig. 1. Serum HCV RNA kinetics of CHC patients during the course of interferon therapy. The treatment of interferon plus ribavirin started at week 0 and ended at week 48. HCV RNA levels at the indicated time point were shown as the Log10(levels [copies/ml]). The detection limit is 1000 copies/ml. (A) Nine SVR patients (defined as HCV RNA negative 24 weeks after cessation of treatment). (B) Three relapse patients (defined as reappearance of HCV RNA in serum after therapy is discontinued). (C) Five virological breakthrough patients (defined as reappearance of HCV RNA in serum while still on therapy). (D) Two nonresponse patients (defined as serum HCV RNA level declines less than 2 log between baseline and week 12, and remains above the detection limit throughout treatment). (E) The clinical course of the breakthrough patient (patient 002, male, 66, with a 21-year-history of HCV infection). (F) The clinical course of the nonresponse patient (patient 007, female, 56, with a 13-year-history of HCV infection). Serum samples were collected at week 0, 1, 12, 24, 48 and year 5 after therapy.
and B). The overall mutation rates of the week 48 HCV genome in the breakthrough patient were 1.97% and 1.43% at the nucleotide and amino acid levels, respectively, much higher than those in the nonresponse patient (0.74% and 0.40%, respectively). Interestingly, p7 and NS2 regions of the week 48 HCV genome in the breakthrough patient had the highest mutation rates (p7: 5.82% and 4.76%, NS2: 4.45% and 3.69% at nucleotide and amino acid levels, respectively), while E2 had the lowest mutation rates (0.64% and 0.28% at nucleotide and amino acid levels, respectively) (Fig. 3A). Only one mutation site was detected in the E2 region at position 397 (in HVR1 region) in the breakthrough patient, and both patients had one mutation in IRRDR of NS5A. There was no
mutation in ISDR and PePHD regions in the two patients (supplementary Tables S2 and S3). Subsequently, we analyzed how HCV genomic sequences evolved during the 4-year post-therapy period. The year 5 HCV sequences were compared with the week 48 sequences, and the mutations that occurred during the 4-year span were scored. To measure how fast the viral sequences evolved, we calculated the yearly mutation rate (defined as mutation rate per year). As shown in Fig. 3C and D, the overall yearly mutation rates between week 48 and year 5 in the breakthrough patient were 0.41% and 0.39% at nucleotide and amino acid levels, respectively, much lower than those between baseline and week 48 (1.97% and 1.43%; Fig. 3A),
[()TD$FIG]
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Fig. 2. Sequencing analysis of HCV ORF at week 0, week 48 and year 5 in the breakthrough and nonresponse patients. (A) The schematic representation of RT-PCR amplification of HCV ORF for sequencing. The full-length HCV ORF was divided into four overlapping amplicons. (B) Geographic location of mutations identified in week 48 and year 5 HCV ORF in the breakthrough and nonresponse patients. The week 0 baseline HCV sequences were used as references for the comparison. Nonsynonymous sequence changes (amino acid mutations) were indicated as vertical dashes according to their locations in the HCV genome. Schematic diagram of HCV ORF structure was drawn on the top. The numbers of mutations at the nucleotide (Nu) and amino acid (AA) levels were indicated on the right.
while the yearly mutation rates between week 48 and year 5 in the nonresponse patient were 0.52% and 0.28% at nucleotide and amino acid levels respectively, similar to those between baseline and week 48 (0.74% and 0.40%; Fig. 3B). In addition, we calculated the yearly mutation rates between the baseline and year 5 for the both patients. As shown in Fig. 3E and F, the overall yearly mutation rates were 0.66% (nucleotide) and 0.41% (amino acid) in the breakthrough patient, and 0.31% (nucleotide) and 0.23% (amino acid) in the nonresponse patient.
accounting for 67.57% (Fig. 4C), indicating most mutations were developed after the termination of interferon based therapy. Meanwhile, the A-B-A type accounted for 24.32% while the A-B-B type only accounted for 8.11%, demonstrating that the majority of week 48 mutations in the nonresponse patients were reverted to the baseline sequences.
3.3. Analysis of mutation types of the HCV genomes in the breakthrough and nonresponse patients before, during and after therapy
The IL28B gene polymorphism (rs12979860, rs12980275, and rs8099917) in the breakthrough and nonresponse patients was determined. It has been illustrated that all of the three SNPs were heterozygous genotypes, with C/T, A/G, and G/T, respectively (Table 2).
To better illustrate how HCV sequences evolved before, during and after the interferon therapy, we classified all amino acid changes among week 0, week 48 and year 5 into the following four categories: a week 48 mutation was maintained at year 5 (denoted A-B-B type); a week 48 mutation was reverted to the original baseline sequence at year 5 (denoted A-B-A); a week 48 mutation was changed to a non-baseline sequence at year 5 (denoted A-B-C); a year 5 mutation while not appear at week 48 (A-A-B). In the case of breakthrough patient, A-B-B and A-A-B types were the leading mutation types, accounting for 47.14% and 40.0%, respectively, while A-B-C type was the least frequent one (1.43%) (Fig. 4A). In addition, majority of week 48 mutations were maintained at year 5 (A-B-B) and very few of them were reverted to the baseline sequences (A-B-A) or changed to non-baseline sequences (A-B-C) at year 5. The analysis of mutation distributions showed that mutations in p7 and NS2 encoding regions, the most frequently varying regions, were all A-B-B types except for one A-B-C mutation in NS2 (Fig. 4B). In the case of the nonresponse patient, we found that A-A-B mutations were the most common type,
3.4. Analysis of the host genetic variations near the IL28B gene in the breakthrough and nonresponse patients
4. Discussion Almost 85% of patients infected with HCV are not able to clear the virus (Marcellin, 1999) and are at high risk for progressive liver fibrosis, cirrhosis, and HCC (Leone and Rizzetto, 2005). Although great progresses have been made in the field of clinical treatment, the efficiency of therapy is not satisfied enough to date (Feld and Hoofnagle, 2005; McHutchison et al., 2009), especially in CHC patients with genotype 1 which are classed as the ‘‘difficult-totreat’’ patients (Pawlotsky, 2004). In general, treatment failure can be defined as the nonresponse, breakthrough, and relapse (Dieterich et al., 2009; Ghany et al., 2009). Accumulating evidence suggest that viral factors play an important role in interferon resistance (Gao et al., 2004; Sarasin-Filipowicz et al., 2008; Suppiah et al., 2009; Tanaka et al., 2009), but the underlining mechanisms remain poorly understood and controversial. It has been shown that the variability of HCV genome sequence prior to the interferon
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Fig. 3. The mutation rates per year of each viral protein encoding region during the periods of therapy and post-therapy. Mutation rates per year from week 0 to week 48 HCV ORF in the breakthrough and nonresponse patients were shown in (A) and (B), respectively, and mutation rates per year from week 48 to year 5 of HCV ORF in the breakthrough and nonresponse patients were shown in (C) and (D), respectively. The mutation rates per year from week 0 to year 5 of HCV ORF in the breakthrough and nonresponse patients were shown in (E) and (F), respectively. The white and black bars represent the mutation rates per year at the nucleotide and amino acid levels, respectively.
based therapy may influence the outcome of the therapy (Cannon et al., 2008). It would be worth analyzing and comparing the pretherapy HCV sequences in the breakthrough and nonresponse patients with those in the responders. Our current study, however, focuses on the HCV genome sequence evolution before, during and long after interferon based therapy in the same patients who experienced unsuccessful antiviral treatment. This kind of analyses have been extremely rare, especially analysis of the HCV genome from breakthrough patients in which the interferon resistant HCV variants might be selected under the pressure of the interferon based therapy. In the present study, we found that the HCV genome in the breakthrough patient was more prone to change during the interferon based therapy than the nonresponse patient during the same period (Fig. 3). More importantly, we found that mutation rates per year during the anti-viral therapy were much higher than those during the post-therapy period in the breakthrough patient, suggesting that HCV sequence evolution had important effects on therapeutic outcomes. It is likely that the interferon resistant HCV variants might be selected during the interferon based therapy in
the breakthrough patient since the viremia decreased in the early phase of the therapy, but rebounded in the late phase of the therapy. In contrast, the HCV mutation rate during the therapy phase in the nonresponse patient was very low. This could be due to the pre-existence of interferon resistant HCV variants at the onset of therapy in the patient. Alternatively, host factors may contribute to interferon/ribavirin resistance, so that there was a less selection pressure for HCV to mutate in the nonresponse patient. Furthermore, we analyzed how HCV sequences evolved in the post-therapy phase. We found that the majority of mutations occurring during the one-year therapy phase in the breakthrough patient were maintained after the termination of antiviral treatment for four years (A-B-B type in Fig. 4), while the majority of mutations occurring during the therapy phase in the nonresponse patient were reverted to the original baseline sequences four years after the termination of treatment (A-B-A type in Fig. 4). Our results suggested that mutations accumulated during the therapy phase in the breakthrough patient might not affect virus fitness, while the mutations accumulated during the therapy phase
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Fig. 4. Four types of mutations in the course of the interferon therapy of the breakthrough and nonresponse patients. All amino acid changes among week 0, week 48 and year 5 were classified into the four types: A-B-B type represents a week 48 mutation that was maintained at year 5, A-B-A type represents a week 48 mutation that was reverted to the original baseline sequence at year 5, A-B-C type represents a week 48 mutation that was changed to a non-baseline sequence at year 5, and A-A-B type represents a mutation that appeared at year 5 but not at week 48. (A) and (C) The percentage of the four mutation types in the breakthrough and nonresponse patients, respectively. (B) and (D) Geographic distribution of the four mutation types in the 10 viral protein encoding regions in the breakthrough and nonresponse patients, respectively.
in the nonresponse patient likely reduced virus fitness so that they could not be maintained when the interferon and ribavirin had been withdrawn. Of course, we cannot exclude a possibility that mutations in different regions of the HCV genome may have different potentials to revert to the wild type. Since the ISDR region in NS5A was proposed to be associated with the interferon resistance (Enomoto et al., 1995), many studies have been done to analyze viral factors that contribute to the outcome of the interferon based therapy. It was shown that the number of mutations in IRRDR region (6) can be served as a marker for predicting SVR (El-Shamy et al., 2008). Our results showed that both of the breakthrough and nonresponse patients had only one mutation in the IRRDR region (Supplemental Tables S2 and S3), which was in line with their hypothesis that a less diverse (5) IRRDR sequence predicts non-SVR (El-Shamy et al., 2008). Surprisingly, in the present study, we found no mutation in the ISDR (NS5A), PKR-BD (NS5A) and PePHD (E2) regions (Supplemental Tables S2 and S3), previously known for their potential roles in the interferon resistance (El-Shamy et al., 2008; Troesch et al., 2006; Wohnsland et al., 2007). Moreover, we found Table 2 Host IL28B gene polymorphisms in the breakthrough and nonresponse patients. SNPs
Breakthrough
Nonresponse
rs12979860 rs12980275 rs8099917
C/T A/G G/T
C/T A/G G/T
that the E2 encoding region had the lowest mutation rate (Fig. 3). Because E2 is a primary target of humoral immune responses (Burioni et al., 1998), the lowest mutation rate might indicate the low levels of humoral immune pressure in these two unsuccessfully treated patients. Interestingly, we found that p7 and NS2 encoding regions had the highest mutation rates during the therapy phase in the breakthrough patient (Fig. 3). Cannon et al. found that the mutations in NS2 of relapsers were less conservative than that in nonresponders, suggesting NS2 variation contributes to the different therapeutic outcomes (Cannon et al., 2008). Consistent with their findings, in the current study similar results in NS2 were observed by comparing the HCV full-length ORF sequences in the breakthrough patient during interferon based therapy. Moreover, the mutations in p7 and NS2 encoding regions of the breakthrough patient were all A-B-B types except for one A-B-C site in NS2 (Fig. 4B). P7 and NS2 are dispensable for HCV RNA replication (Blight et al., 2002; Lohmann et al., 1999), but essential for in vivo infectivity and virus assembly and packaging (Jones et al., 2007; Phan et al., 2009; Sakai et al., 2003; Steinmann et al., 2007; StGelais et al., 2009). It is tempting to speculate that mutations in these regions may confer to the interferon/ribavirin resistance, although it is difficult to exclude the possible involvement of mutations in other regions including NS5A in interferon/ribavirin resistance as reported by other groups (El-Shamy et al., 2008; Wohnsland et al., 2007). It would be helpful to test the effects of the mutations in various regions on interferon/ribavirin resistance using an in vitro HCV cell culture model (Zhong et al., 2005). In addition, clinical
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trials combining interferon and ribavirin with a p7 inhibitor have demonstrated improved response rates in genotype-1-infected individuals (Steinmann et al., 2007; StGelais et al., 2009). Therefore, it would be interesting to investigate whether p7 and NS2 proteins play any roles in interferon/ribavirin resistance and whether p7 and NS2 sequences can be used to predict the outcomes of interferon treatment in CHC patients. Recent studies showed that single nucleotide polymorphisms (SNPs) (rs12979860, rs12980275, and rs8099917) near the IL28B gene encoding IFN-l-3 on chromosome 19 are strongly associated with the clinical outcome of the interferon based therapy (Ge et al., 2009; Suppiah et al., 2009; Tanaka et al., 2009). Therefore we determined these three IL28B SNPs in the breakthrough and nonresponse patients. Our results indicated that all of the three SNPs were heterozygous, with C/T, A/G, and G/T (Table 2), respectively. However, because of the limited numbers of patients we analyzed, no explicit conclusion could be drawn from this analysis. It would be interesting to analyze the IL28 SNPs of all recruited patients. In conclusion, our study presented additional evidence that viral factors may have important effects on the outcome of ‘‘difficult-to-treat’’ CHC patients, and the action of interferon and ribavirin may be the major force to drive the evolution of HCV genomic sequences and to select the resistant HCV variants in the breakthrough patients. The results presented herein provide a new insight into the mechanisms of interferon resistance. However, because of the limited numbers of patients investigated in this study, we were unable to absolutely rule out other factors affecting interferon response. Therefore it is important to monitor more breakthrough and nonresponse patients to verify our findings. Acknowledgements The authors thank the patients who participated in this study, especially the two patients selected for the 5-year follow-up. The study was supported by grants of the Key Basic Research Foundation of Science and Technology Commission of Shanghai Municipality (No. 08JC1415300), the National Natural Science Foundation of China (NSFC30872252), the National Key Programs on Infectious Disease (2008ZX10002-013) to Q. Xie, grants of Shanghai Municipal Health Bureau (No. AB83070002009018-51) to H. Zhou, and grants of Chinese Academy of Science (KSCX1-YW10), the National Key Programs on Infectious Disease (2008ZX10002-014), the 973 Program (2009CB522501), Shanghai Pasteur Health Research Foundation (SPHRF2009001) and Chinese Ministry of Personnel (the excellent Chinese oversea returnee scholarship) to J. Zhong. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.meegid.2010.11.011. References Armstrong, G.L., Wasley, A., Simard, E.P., McQuillan, G.M., Kuhnert, W.L., Alter, M.J., 2006. The prevalence of hepatitis C virus infection in the United States, 1999 through 2002. Ann. Intern. Med. 144, 705–714. Aus dem Siepen, M., Lohmann, V., Wiese, M., Ross, S., Roggendorf, M., Viazov, S., 2005. Nonstructural protein 5A does not contribute to the resistance of hepatitis C virus replication to interferon alpha in cell culture. Virology 336, 131–136. Blight, K.J., McKeating, J.A., Rice, C.M., 2002. Highly permissive cell lines for subgenomic and genomic hepatitis C virus RNA replication. J. Virol. 76, 13001– 13014. Brillet, R., Penin, F., Hezode, C., Chouteau, P., Dhumeaux, D., Pawlotsky, J.M., 2007. The nonstructural 5A protein of hepatitis C virus genotype 1b does not contain an interferon sensitivity-determining region. J. Infect. Dis. 195, 432–441.
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Infection, Genetics and Evolution journal homepage: www.elsevier.com/locate/meegid
Viral sequence evolution in Chinese genotype 1b chronic hepatitis C patients experiencing unsuccessful interferon treatment Xiaogang Xiang a,b, Jie Lu b, Zhixia Dong a, Huijuan Zhou a, Wanyin Tao b, Qing Guo a, Xiaqiu Zhou a, Shisan Bao c, Qing Xie a,b,**, Jin Zhong b,* a
Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin Er Road, Shanghai 20005, China Key Laboratory of Molecular Virology and Immunology, Institut Pasteur of Shanghai, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 225 South Chongqing Road, Shanghai 200025, China c Discipline of Pathology (D06), Bosch Institute and School of Medical Sciences, The University of Sydney, New South Wales 2006, Australia b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 6 July 2010 Received in revised form 12 November 2010 Accepted 24 November 2010 Available online 13 December 2010
The efficiencies of IFN-a based therapy in chronic genotype 1b HCV patients are still unsatisfied to date. The mechanisms underlining treatment failure remain unclear and controversial. To investigate HCV sequence evolution in unsuccessfully treated genotype 1b patients before, during and after the therapy, full-length open-reading-frame of HCV genomes at week 0, week 48 and year 5 in one breakthrough and one nonresponse patients were amplified by reverse transcription (RT)-nested-PCR and sequenced. Mutations were scored and analyzed according to their locations in the HCV genome. HCV sequences in the breakthrough patient displayed significantly more mutations during the one-year therapy than that in the nonresponse patient, with p7 and NS2 encoding regions having the highest mutation rates. Most of the mutations selected during the therapy phase in the breakthrough patient were maintained and few new mutations arose in the four-year post-therapy phase, suggesting these mutations might not compromise viral fitness. Altogether our data suggest that mutations occurred during the therapy phase in the breakthrough patient are likely driven by the action of interferon and ribavirin, and these mutations may have important effects on the responses to interferon based therapy in genotype 1b HCV patients. ß 2010 Elsevier B.V. All rights reserved.
Keywords: Hepatitis C virus Interferon therapy Sustained virological response Breakthrough Nonresponse Sequence evolution
1. Introduction Chronic hepatitis C virus (HCV) infection is a major public health burden and a leading cause of chronic liver disease including chronic hepatitis, liver cirrhosis, end-stage liver disease and hepatocellular carcinoma (HCC), and it is one of the most common indications for liver transplantation worldwide (Ghany et al., 2009). The World Health Organization reports that over 3% of the global population with approximately 180 million individuals is estimated to be infected with HCV. The prevalence was estimated to be 1.6% in the United States (Armstrong et al.,
Abbreviations: HCV, hepatitis C virus; CHC, chronic hepatitis C; SVR, sustained virological response; IFN-a, interferon alpha; ORF, open reading frame; HCC, hepatocellular carcinoma. * Corresponding author at: Institut Pasteur of Shanghai, Chinese Academy of Sciences, 225 South Chongqing Road, Shanghai, 200025, China. Tel.: +86 21 63858685; fax: +86 21 63859365. ** Corresponding author at: Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin Er Road, Shanghai 20005, China. Tel.: +86 21 64370045x360403; fax: +86 21 64454930. E-mail addresses: [email protected] (J. Zhong), [email protected] (Q. Xie). 1567-1348/$ – see front matter ß 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.meegid.2010.11.011
2006), and about 1% in Europe (Sy and Jamal, 2006), but over 3.2% with more than 41 million people infected in China (Xia et al., 1996). In nearly 85% of the cases, the disease progresses into chronicity (Ghany et al., 2009). Currently, there is no vaccine to prevent HCV infection, and the only available treatment regimens based on interferon alpha (IFNa) or pegylated (peg)-IFN-a plus ribavirin for 24–48 weeks lead to a sustained virological response (SVR) in about 39.8–40.9% of patients infected by genotype 1 HCV (McHutchison et al., 2009), which is the prevalent HCV genotype in the United States, Europe, and China (Ghany et al., 2009; Lu et al., 2005), while 75–80% for genotypes 2 and 3 (Feld and Hoofnagle, 2005). Treatment failure occurs in the following forms: nonresponse (serum HCV RNA level declines less than 2 log between baseline and week 12, and remains above the detection limit throughout treatment), breakthrough (serum HCV RNA level drops below the detection limit, but rebounds while on therapy), and relapse (serum HCV RNA level drops below the detection limit, but rebounds after the therapy is discontinued) (Dieterich et al., 2009). Unfortunately, molecular mechanisms underlying the failure of the interferon based therapy for chronic hepatitis C (CHC) patients are still unclear. Host factors have been suggested to contribute to the resistance to the
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interferon based therapy (Gao et al., 2004; Ge et al., 2009; SarasinFilipowicz et al., 2008; Suppiah et al., 2009; Tanaka et al., 2009). Recent studies showed that single nucleotide polymorphisms (SNPs) (rs12979860, rs12980275, and rs8099917) near the IL28B gene encoding IFN-l-3 on chromosome 19 are strongly associated with the clinical outcome of the interferon based therapy, although the molecular mechanisms behind these observations remain elusive (Ge et al., 2009; Suppiah et al., 2009; Tanaka et al., 2009). On the other hand, the strong correlation of SVR rate with HCV genotypes suggests that HCV genomes (viral factors) must also be critical determinants for the outcome of the interferon therapy. Although it has been suggested that multiple HCV proteins are associated with interferon resistance (Wohnsland et al., 2007), including NS5A (ISDR; PKR-BD; V3; V4 (Jain et al., 2009); IRRDR (ElShamy et al., 2008)), E2 (PePHD; HVR1; HVR2; HVR3 (Troesch et al., 2006)), NS3/NS4A, and Core (Wohnsland et al., 2007), none of these studies reached a definitive consensus, and there are lots of contradictions between in vivo and in vitro results (Aus dem Siepen et al., 2005; Brillet et al., 2007; Gale et al., 1998; Gaudy et al., 2005; Jardim et al., 2009; Tsai et al., 2008). Moreover, most of these results were derived from the comparison of the HCV genomic sequences between the SVR patients and the patients who did not achieve SVR, therefore, it is difficult to rule out the contributions of genetic background and host factors of different patients to the outcome of the therapy. Breakthrough patients who initially respond to the interferon based therapy well and the HCV RNA level decreases to the undetectable level, but have reappearance of HCV RNA in serum during the therapy may represent a more unbiased subject to investigate whether the evolution of viral genomic sequences within a single patient play any roles in interferon resistance. Since interferon resistant HCV quasispecies might be selected during the therapy (Cuevas et al., 2008; Enomoto et al., 1995; Kuntzen et al., 2007; Xu et al., 2008), the analysis of the viral genomic sequences before, during and after the therapy may help understand the roles of viral determinants of interferon resistance. The present study aimed to investigate the evolution of HCV genomic sequences in CHC patients with genotype 1b during the interferon therapy. We compared the full-length HCV ORF sequences before, during and after the therapy, as well as the mutation types, in one breakthrough patient and one nonresponse patient. We found that the HCV genomic sequences in the breakthrough patient displayed significantly more mutations during the 1-year therapy than that in the nonresponse patient, with p7 and NS2 encoding regions having the highest mutation rates. The HCV sequence analysis of a 4-year post-therapy followup revealed that a vast majority of mutations selected during the therapy phase in the breakthrough patient were maintained while very few new mutations arose during the 4-year post-therapy span, suggesting the selection of the mutations during the therapy phase may be driven by the action of interferon and ribavirin and these mutations likely did not compromise viral fitness. Our data provide additional evidence to demonstrate that viral determinants may contribute to interferon resistance during interferon therapy of CHC patients. 2. Methods 2.1. Patients and clinical treatment A total of 19 CHC patients (11 males and 8 females) with genotype 1b who received the treatment of conventional IFN-a plus Ribavirin from August 2003 to July 2004 at the Department of Infectious Diseases of Ruijin Hospital, Shanghai Jiaotong University School of Medicine, were included in this study. The patients, all Chinese Han ethnicity, were treatment-naı¨ve prior to IFN-a and Ribavirin, and were free of human immunodeficiency virus (HIV)
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infection and other concomitant liver diseases, such as hepatitis B virus (HBV) or other hepatotropic virus infections, alcohol abuse, autoimmune hepatitis and hereditary liver diseases. The study had been approved by the Ethics Committee of Shanghai Ruijin Hospital in accordance with the Helsinki Declaration, and written informed consents were obtained from all patients. They received conventional IFN-a three times a week at a dose of 6 million units subcutaneously, and ribavirin was administered orally twice a day to a total dose of 1000 mg (body weight <75 kg) or 1200 mg (body weight 75 kg) for 48 weeks and were followed up at least 6 months after completion of one-year therapy. Two cases (body weight <75 kg) were selected retrospectively for another four-year follow-up after termination of therapy: one was a breakthrough patient (patient 002), and the other was a nonresponse patient (patient 007). No dose modification was performed in the two patients during anti-viral treatment. Serum samples were collected at multiple time points during and after therapy, and were stored at 80 8C. Samples, collected at week 0 (baseline), week 12, week 48 and year 5, were used for HCV sequences analyzing in this study. 2.2. HCV RNA quantification and genotyping of CHC patients HCV RNA quantification was performed using a one-step quantitative HCV RT-PCR kit (PG Biotech, Shenzhen, China) with the standard-curve of Taqman probe method, and the detection limit was 1000 copies/ml. HCV genotyping was performed using the HCV genotyping gene chip kit (Realchip Biotech, Ningbo, China) according to the manufacturer’s instructions. 2.3. HCV RNA extraction, RT-PCR, full-length HCV ORF amplification and sequencing Total RNA was extracted from 140 ml of serum samples, using QIAamp Viral RNA mini kit (QIAGEN, Hilden, Germany), and dissolved in 60 ml of elution buffer and stored at 80 8C until use. The sequencing of HCV genomes was performed following a previously published protocol with some modification (Yao and Tavis, 2005). In brief, HCV RNA was reverse-transcribed (RT) into cDNA using TaKaRa RNA LA PCRTM Kit (AMV) Ver.1.1 (TaKaRa, Dalian, China) with HCV specific primers. Nested-PCR primers spanning the full-length HCV ORF sequences used in this study were listed in Supplementary Table S1. All PCR fragments were purified using the AxyPrep DNA Gel Extraction Kit (Axygen, Hangzhou, China) and then sequenced. Consensus sequences for the full-length HCV ORF were obtained by aligning overlapping sequences of PCR products as described previously (Yao and Tavis, 2005). A total of 7 full-length HCV genotype 1b sequences generated in this study had been deposited in GenBank under the accession numbers from GU451218 to GU451224. 2.4. Sequence analysis Vector NTI Advance Version 10.3 (Invitrogen, Carlsbad, CA, USA) and BioEdit Sequence Alignment Editor Version 7.0.9.9 (Ibis Biosciences, Carlsbad, CA, USA) (Hall, 1999) were used to edit, assemble and align sequences. To insure integrity of the sequence data, appropriate precautions were taken as recommended (Learn et al., 1996; Yao and Tavis, 2005). Amino acid sequences were deduced from nucleotide sequences. Mutations were rechecked through the chromatogram. If there were two peaks at the same residue, HCV RNA would be PCR amplified again and resequenced. By evaluation of numerous overlapping sequence fragments, only clear changes were identified as mutations. Mutation rates at different time points were calculated at nucleotide and amino acid levels in the 10 viral protein encoding regions, respectively. The
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Table 1 Clinical data of chronic hepatitis C patients treated with IFN-a plus ribavirin. Characteristic
Breakthrough (n = 5)
Nonresponse (n = 2)
Relapse (n = 3)
SVR (n = 9)
P value
Age (years) Gender (M/F) Body weight (kg) Baseline HCV RNA (log10 copies/ml) ALT (IU/l) AST (IU/l) Total bilirubin (mmol/l) Albumin (g/l) Platelet count (1E9/l) AFP (ng/ml) Histological activity index (pre-treatment) Fibrosis stage (pre-treatment) Histological activity index (post-treatment) Fibrosis stage (post-treatment)
49.6 16.6 3/2 67.2 9.7 6.88 0.30 140.4 52.4 95.8 47.8 15.0 4.7 46.6 4.8 168.6 86.7 7.6 7.1 5.6 0.5 3.4 1.5 5.0 0.8 3.0 1.4
46.5 14.8 1/1 57.5 7.8 6.7 0.24 208.5 133.6 107.5 40.3 18.0 4.2 46.0 5.7 119.0 49.5 7.5 3.5 6.0 1.4 2.5 0.7 5.5 2.1 2.5 0.7
46.7 4.2 1/2 66.0 5.3 6.55 0.39 111.3 10.7 80.7 26.7 16.7 9.3 47.0 3.6 139.7 9.5 3.3 1.2 8.0 2.0 3.7 1.2 6.0 1.4 3.5 0.7
41. 9.7 6/3 69.1 7.7 6.43 0.53 126.8 57.1 85.0 46.9 13.9 2.7 48.2 1.2 183.7 41.1 4.4 2.1 5.3 2.1 2.7 1.7 2.9 1.6 2.6 2.1
0.677 0.823 0.362 0.327 0.345 0.887 0.651 0.738 0.415 0.391 0.184 0.688 0.039 0.902
Note: All measurement data here were expressed as means with standard deviations, and differences between different groups were determined by one-way ANOVA, where P < 0.05 was considered to be statistically significant.
rates of synonymous substitution per synonymous site (dS) and non-synonymous substitution per non-synonymous site (dN), as well as the dN/dS ratio, were obtained at SNAP-(Synonymous Nonsynonymous Analysis Program)-http://www.hiv.lanl.gov (Korber, 2000). 2.5. Statistical analysis All analyses were carried out using SPSS statistical software version 17.0 (SPSS Inc. Chicago, IL, USA). The differences among different groups were determined by one-way ANOVA, where P < 0.05 was considered to be statistically significant.
liver alanine aminotransferase (ALT) showed that the liver damage was temporally controlled during the therapy (ALT 50 IU/l at week 12), but became deleterious again when serum HCV RNA rebounded. Eventually, this patient developed liver cirrhosis 4 years later and had experienced three times of massive upper gastrointestinal hemorrhage during the fifth year. On the contrary, patient 007 (Fig. 1F), a 56-year-old female with a 13-year-history of HCV infection at the onset of treatment, did not respond to the interferon treatment very well as serum HCV RNA level did not dropped significantly, but the liver ALT level did restore to normal and maintained at a very low level throughout the therapy and post-therapy phases. This patient did not develop liver cirrhosis in our study time frame.
3. Results 3.1. Patient characteristics and antiviral therapeutic efficiency
3.2. Sequence analysis of full-length HCV ORF in the breakthrough and nonresponse patients before, during and after therapy
Nineteen genotype 1b chronic hepatitis C patients were recruited for receiving the treatment of IFN-a plus ribavirin. The treatment regime was described in Methods, and the patients’ characteristics were summarized in Table 1. Serum HCV RNA kinetics of all the patients during therapy was shown in Fig. 1. Nine of the nineteen patients achieved SVR (47.4%), as the serum HCV RNA levels in these patients became non-detectable at the termination of the therapy (week 48) and thereafter (week 60 and week 72). In those who failed to achieve SVR, five were breakthrough (26.3%), two were nonresponse (10.5%) and three relapsed after the cessation of the therapy (15.8%). There were no significant differences among breakthrough, nonresponse, relapse and SVR patients in the age, gender, body weight, pre-treatment HCV RNA levels, ALT, AST, total bilirubin, albumin, platelet count, AFP, pre-treatment liver histological activity index (HAI) and fibrosis stage and post-treatment liver fibrosis stage except for the post-treatment liver HAI (an indicator of liver inflammation), which was much better in patients achieved SVR (P = 0.039). One breakthrough patient (patient 002) and one nonresponse patient (patient 007) were selected retrospectively for a long-term follow-up at the end of treatment. The clinical courses of the two patients were shown in Fig. 1E and F. Patient 002 (Fig. 1E), a 66 years old male with a 21-year-history of HCV infection at the onset of treatment, initially responded to the therapy very well and serum HCV RNA level quickly decreased from 107 copies/ml at baseline to below the detection limit (103 copies/ml) at week 12. However, serum HCV RNA reappeared at week 24 and reached above 107 copies/ml at week 48 when the therapy was terminated. Serum HCV RNA remained positive in the 4-year post-therapy period and was 1.4 105 copies/ml at year 5. The measurement of
The sequences of full-length HCV ORF from patient 002 (breakthrough) and patient 007 (nonresponse) at week 0 (pretreatment baseline), week 48 and year 5 were analyzed respectively. Four overlapping fragments spanning the full-length HCV ORF were PCR amplified and bulk sequenced (Fig. 2A). The nucleotide sequence at each position was verified by at least 6 independent sequencing reactions from forward and reverse directions. The consensus sequences, either single peaks or predominant nucleotide peaks, were constructed to represent the major quasispecies in each sample. The week 0 baseline HCV sequences were used as references to score mutations in HCV genomes of week 48 and year 5. Notably, there were much fewer mutations in the HCV genomes of nonresponse patient than that of the breakthrough patient at week 48 and year 5. As shown in Fig. 2B, there were 67 nucleotide changes and 12 amino acid changes from week 0 to week 48, and 140 nucleotide changes and 28 amino acid changes from week 0 to year 5 in the nonresponse patient, while there were 180 nucleotide changes and 41 amino acid changes from week 0 to week 48, and 302 nucleotide changes and 62 amino acid changes from week 0 to year 5 in the breakthrough patient. Furthermore, we calculated the ratio of nonsynonymous mutation to synonymous mutation (dN/dS) during the therapy (Korber, 2000). The dN/dS values were 0.1270 and 0.0826 during the therapy phase (weeks 0–48), or 0.9453 and 0.0953 in the periods from week 0 to year 5, for the breakthrough and nonresponse patients, respectively. We then analyzed the distribution of mutations of the week 48 HCV genomes in each of 10 viral protein-encoding regions. Mutation rates were calculated as the number of mutations divided by the length of each viral protein-encoding region (Fig. 3A
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Fig. 1. Serum HCV RNA kinetics of CHC patients during the course of interferon therapy. The treatment of interferon plus ribavirin started at week 0 and ended at week 48. HCV RNA levels at the indicated time point were shown as the Log10(levels [copies/ml]). The detection limit is 1000 copies/ml. (A) Nine SVR patients (defined as HCV RNA negative 24 weeks after cessation of treatment). (B) Three relapse patients (defined as reappearance of HCV RNA in serum after therapy is discontinued). (C) Five virological breakthrough patients (defined as reappearance of HCV RNA in serum while still on therapy). (D) Two nonresponse patients (defined as serum HCV RNA level declines less than 2 log between baseline and week 12, and remains above the detection limit throughout treatment). (E) The clinical course of the breakthrough patient (patient 002, male, 66, with a 21-year-history of HCV infection). (F) The clinical course of the nonresponse patient (patient 007, female, 56, with a 13-year-history of HCV infection). Serum samples were collected at week 0, 1, 12, 24, 48 and year 5 after therapy.
and B). The overall mutation rates of the week 48 HCV genome in the breakthrough patient were 1.97% and 1.43% at the nucleotide and amino acid levels, respectively, much higher than those in the nonresponse patient (0.74% and 0.40%, respectively). Interestingly, p7 and NS2 regions of the week 48 HCV genome in the breakthrough patient had the highest mutation rates (p7: 5.82% and 4.76%, NS2: 4.45% and 3.69% at nucleotide and amino acid levels, respectively), while E2 had the lowest mutation rates (0.64% and 0.28% at nucleotide and amino acid levels, respectively) (Fig. 3A). Only one mutation site was detected in the E2 region at position 397 (in HVR1 region) in the breakthrough patient, and both patients had one mutation in IRRDR of NS5A. There was no
mutation in ISDR and PePHD regions in the two patients (supplementary Tables S2 and S3). Subsequently, we analyzed how HCV genomic sequences evolved during the 4-year post-therapy period. The year 5 HCV sequences were compared with the week 48 sequences, and the mutations that occurred during the 4-year span were scored. To measure how fast the viral sequences evolved, we calculated the yearly mutation rate (defined as mutation rate per year). As shown in Fig. 3C and D, the overall yearly mutation rates between week 48 and year 5 in the breakthrough patient were 0.41% and 0.39% at nucleotide and amino acid levels, respectively, much lower than those between baseline and week 48 (1.97% and 1.43%; Fig. 3A),
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Fig. 2. Sequencing analysis of HCV ORF at week 0, week 48 and year 5 in the breakthrough and nonresponse patients. (A) The schematic representation of RT-PCR amplification of HCV ORF for sequencing. The full-length HCV ORF was divided into four overlapping amplicons. (B) Geographic location of mutations identified in week 48 and year 5 HCV ORF in the breakthrough and nonresponse patients. The week 0 baseline HCV sequences were used as references for the comparison. Nonsynonymous sequence changes (amino acid mutations) were indicated as vertical dashes according to their locations in the HCV genome. Schematic diagram of HCV ORF structure was drawn on the top. The numbers of mutations at the nucleotide (Nu) and amino acid (AA) levels were indicated on the right.
while the yearly mutation rates between week 48 and year 5 in the nonresponse patient were 0.52% and 0.28% at nucleotide and amino acid levels respectively, similar to those between baseline and week 48 (0.74% and 0.40%; Fig. 3B). In addition, we calculated the yearly mutation rates between the baseline and year 5 for the both patients. As shown in Fig. 3E and F, the overall yearly mutation rates were 0.66% (nucleotide) and 0.41% (amino acid) in the breakthrough patient, and 0.31% (nucleotide) and 0.23% (amino acid) in the nonresponse patient.
accounting for 67.57% (Fig. 4C), indicating most mutations were developed after the termination of interferon based therapy. Meanwhile, the A-B-A type accounted for 24.32% while the A-B-B type only accounted for 8.11%, demonstrating that the majority of week 48 mutations in the nonresponse patients were reverted to the baseline sequences.
3.3. Analysis of mutation types of the HCV genomes in the breakthrough and nonresponse patients before, during and after therapy
The IL28B gene polymorphism (rs12979860, rs12980275, and rs8099917) in the breakthrough and nonresponse patients was determined. It has been illustrated that all of the three SNPs were heterozygous genotypes, with C/T, A/G, and G/T, respectively (Table 2).
To better illustrate how HCV sequences evolved before, during and after the interferon therapy, we classified all amino acid changes among week 0, week 48 and year 5 into the following four categories: a week 48 mutation was maintained at year 5 (denoted A-B-B type); a week 48 mutation was reverted to the original baseline sequence at year 5 (denoted A-B-A); a week 48 mutation was changed to a non-baseline sequence at year 5 (denoted A-B-C); a year 5 mutation while not appear at week 48 (A-A-B). In the case of breakthrough patient, A-B-B and A-A-B types were the leading mutation types, accounting for 47.14% and 40.0%, respectively, while A-B-C type was the least frequent one (1.43%) (Fig. 4A). In addition, majority of week 48 mutations were maintained at year 5 (A-B-B) and very few of them were reverted to the baseline sequences (A-B-A) or changed to non-baseline sequences (A-B-C) at year 5. The analysis of mutation distributions showed that mutations in p7 and NS2 encoding regions, the most frequently varying regions, were all A-B-B types except for one A-B-C mutation in NS2 (Fig. 4B). In the case of the nonresponse patient, we found that A-A-B mutations were the most common type,
3.4. Analysis of the host genetic variations near the IL28B gene in the breakthrough and nonresponse patients
4. Discussion Almost 85% of patients infected with HCV are not able to clear the virus (Marcellin, 1999) and are at high risk for progressive liver fibrosis, cirrhosis, and HCC (Leone and Rizzetto, 2005). Although great progresses have been made in the field of clinical treatment, the efficiency of therapy is not satisfied enough to date (Feld and Hoofnagle, 2005; McHutchison et al., 2009), especially in CHC patients with genotype 1 which are classed as the ‘‘difficult-totreat’’ patients (Pawlotsky, 2004). In general, treatment failure can be defined as the nonresponse, breakthrough, and relapse (Dieterich et al., 2009; Ghany et al., 2009). Accumulating evidence suggest that viral factors play an important role in interferon resistance (Gao et al., 2004; Sarasin-Filipowicz et al., 2008; Suppiah et al., 2009; Tanaka et al., 2009), but the underlining mechanisms remain poorly understood and controversial. It has been shown that the variability of HCV genome sequence prior to the interferon
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Fig. 3. The mutation rates per year of each viral protein encoding region during the periods of therapy and post-therapy. Mutation rates per year from week 0 to week 48 HCV ORF in the breakthrough and nonresponse patients were shown in (A) and (B), respectively, and mutation rates per year from week 48 to year 5 of HCV ORF in the breakthrough and nonresponse patients were shown in (C) and (D), respectively. The mutation rates per year from week 0 to year 5 of HCV ORF in the breakthrough and nonresponse patients were shown in (E) and (F), respectively. The white and black bars represent the mutation rates per year at the nucleotide and amino acid levels, respectively.
based therapy may influence the outcome of the therapy (Cannon et al., 2008). It would be worth analyzing and comparing the pretherapy HCV sequences in the breakthrough and nonresponse patients with those in the responders. Our current study, however, focuses on the HCV genome sequence evolution before, during and long after interferon based therapy in the same patients who experienced unsuccessful antiviral treatment. This kind of analyses have been extremely rare, especially analysis of the HCV genome from breakthrough patients in which the interferon resistant HCV variants might be selected under the pressure of the interferon based therapy. In the present study, we found that the HCV genome in the breakthrough patient was more prone to change during the interferon based therapy than the nonresponse patient during the same period (Fig. 3). More importantly, we found that mutation rates per year during the anti-viral therapy were much higher than those during the post-therapy period in the breakthrough patient, suggesting that HCV sequence evolution had important effects on therapeutic outcomes. It is likely that the interferon resistant HCV variants might be selected during the interferon based therapy in
the breakthrough patient since the viremia decreased in the early phase of the therapy, but rebounded in the late phase of the therapy. In contrast, the HCV mutation rate during the therapy phase in the nonresponse patient was very low. This could be due to the pre-existence of interferon resistant HCV variants at the onset of therapy in the patient. Alternatively, host factors may contribute to interferon/ribavirin resistance, so that there was a less selection pressure for HCV to mutate in the nonresponse patient. Furthermore, we analyzed how HCV sequences evolved in the post-therapy phase. We found that the majority of mutations occurring during the one-year therapy phase in the breakthrough patient were maintained after the termination of antiviral treatment for four years (A-B-B type in Fig. 4), while the majority of mutations occurring during the therapy phase in the nonresponse patient were reverted to the original baseline sequences four years after the termination of treatment (A-B-A type in Fig. 4). Our results suggested that mutations accumulated during the therapy phase in the breakthrough patient might not affect virus fitness, while the mutations accumulated during the therapy phase
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Fig. 4. Four types of mutations in the course of the interferon therapy of the breakthrough and nonresponse patients. All amino acid changes among week 0, week 48 and year 5 were classified into the four types: A-B-B type represents a week 48 mutation that was maintained at year 5, A-B-A type represents a week 48 mutation that was reverted to the original baseline sequence at year 5, A-B-C type represents a week 48 mutation that was changed to a non-baseline sequence at year 5, and A-A-B type represents a mutation that appeared at year 5 but not at week 48. (A) and (C) The percentage of the four mutation types in the breakthrough and nonresponse patients, respectively. (B) and (D) Geographic distribution of the four mutation types in the 10 viral protein encoding regions in the breakthrough and nonresponse patients, respectively.
in the nonresponse patient likely reduced virus fitness so that they could not be maintained when the interferon and ribavirin had been withdrawn. Of course, we cannot exclude a possibility that mutations in different regions of the HCV genome may have different potentials to revert to the wild type. Since the ISDR region in NS5A was proposed to be associated with the interferon resistance (Enomoto et al., 1995), many studies have been done to analyze viral factors that contribute to the outcome of the interferon based therapy. It was shown that the number of mutations in IRRDR region (6) can be served as a marker for predicting SVR (El-Shamy et al., 2008). Our results showed that both of the breakthrough and nonresponse patients had only one mutation in the IRRDR region (Supplemental Tables S2 and S3), which was in line with their hypothesis that a less diverse (5) IRRDR sequence predicts non-SVR (El-Shamy et al., 2008). Surprisingly, in the present study, we found no mutation in the ISDR (NS5A), PKR-BD (NS5A) and PePHD (E2) regions (Supplemental Tables S2 and S3), previously known for their potential roles in the interferon resistance (El-Shamy et al., 2008; Troesch et al., 2006; Wohnsland et al., 2007). Moreover, we found Table 2 Host IL28B gene polymorphisms in the breakthrough and nonresponse patients. SNPs
Breakthrough
Nonresponse
rs12979860 rs12980275 rs8099917
C/T A/G G/T
C/T A/G G/T
that the E2 encoding region had the lowest mutation rate (Fig. 3). Because E2 is a primary target of humoral immune responses (Burioni et al., 1998), the lowest mutation rate might indicate the low levels of humoral immune pressure in these two unsuccessfully treated patients. Interestingly, we found that p7 and NS2 encoding regions had the highest mutation rates during the therapy phase in the breakthrough patient (Fig. 3). Cannon et al. found that the mutations in NS2 of relapsers were less conservative than that in nonresponders, suggesting NS2 variation contributes to the different therapeutic outcomes (Cannon et al., 2008). Consistent with their findings, in the current study similar results in NS2 were observed by comparing the HCV full-length ORF sequences in the breakthrough patient during interferon based therapy. Moreover, the mutations in p7 and NS2 encoding regions of the breakthrough patient were all A-B-B types except for one A-B-C site in NS2 (Fig. 4B). P7 and NS2 are dispensable for HCV RNA replication (Blight et al., 2002; Lohmann et al., 1999), but essential for in vivo infectivity and virus assembly and packaging (Jones et al., 2007; Phan et al., 2009; Sakai et al., 2003; Steinmann et al., 2007; StGelais et al., 2009). It is tempting to speculate that mutations in these regions may confer to the interferon/ribavirin resistance, although it is difficult to exclude the possible involvement of mutations in other regions including NS5A in interferon/ribavirin resistance as reported by other groups (El-Shamy et al., 2008; Wohnsland et al., 2007). It would be helpful to test the effects of the mutations in various regions on interferon/ribavirin resistance using an in vitro HCV cell culture model (Zhong et al., 2005). In addition, clinical
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trials combining interferon and ribavirin with a p7 inhibitor have demonstrated improved response rates in genotype-1-infected individuals (Steinmann et al., 2007; StGelais et al., 2009). Therefore, it would be interesting to investigate whether p7 and NS2 proteins play any roles in interferon/ribavirin resistance and whether p7 and NS2 sequences can be used to predict the outcomes of interferon treatment in CHC patients. Recent studies showed that single nucleotide polymorphisms (SNPs) (rs12979860, rs12980275, and rs8099917) near the IL28B gene encoding IFN-l-3 on chromosome 19 are strongly associated with the clinical outcome of the interferon based therapy (Ge et al., 2009; Suppiah et al., 2009; Tanaka et al., 2009). Therefore we determined these three IL28B SNPs in the breakthrough and nonresponse patients. Our results indicated that all of the three SNPs were heterozygous, with C/T, A/G, and G/T (Table 2), respectively. However, because of the limited numbers of patients we analyzed, no explicit conclusion could be drawn from this analysis. It would be interesting to analyze the IL28 SNPs of all recruited patients. In conclusion, our study presented additional evidence that viral factors may have important effects on the outcome of ‘‘difficult-to-treat’’ CHC patients, and the action of interferon and ribavirin may be the major force to drive the evolution of HCV genomic sequences and to select the resistant HCV variants in the breakthrough patients. The results presented herein provide a new insight into the mechanisms of interferon resistance. However, because of the limited numbers of patients investigated in this study, we were unable to absolutely rule out other factors affecting interferon response. Therefore it is important to monitor more breakthrough and nonresponse patients to verify our findings. Acknowledgements The authors thank the patients who participated in this study, especially the two patients selected for the 5-year follow-up. The study was supported by grants of the Key Basic Research Foundation of Science and Technology Commission of Shanghai Municipality (No. 08JC1415300), the National Natural Science Foundation of China (NSFC30872252), the National Key Programs on Infectious Disease (2008ZX10002-013) to Q. Xie, grants of Shanghai Municipal Health Bureau (No. AB83070002009018-51) to H. Zhou, and grants of Chinese Academy of Science (KSCX1-YW10), the National Key Programs on Infectious Disease (2008ZX10002-014), the 973 Program (2009CB522501), Shanghai Pasteur Health Research Foundation (SPHRF2009001) and Chinese Ministry of Personnel (the excellent Chinese oversea returnee scholarship) to J. Zhong. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.meegid.2010.11.011. References Armstrong, G.L., Wasley, A., Simard, E.P., McQuillan, G.M., Kuhnert, W.L., Alter, M.J., 2006. The prevalence of hepatitis C virus infection in the United States, 1999 through 2002. Ann. Intern. Med. 144, 705–714. Aus dem Siepen, M., Lohmann, V., Wiese, M., Ross, S., Roggendorf, M., Viazov, S., 2005. Nonstructural protein 5A does not contribute to the resistance of hepatitis C virus replication to interferon alpha in cell culture. Virology 336, 131–136. Blight, K.J., McKeating, J.A., Rice, C.M., 2002. Highly permissive cell lines for subgenomic and genomic hepatitis C virus RNA replication. J. Virol. 76, 13001– 13014. Brillet, R., Penin, F., Hezode, C., Chouteau, P., Dhumeaux, D., Pawlotsky, J.M., 2007. The nonstructural 5A protein of hepatitis C virus genotype 1b does not contain an interferon sensitivity-determining region. J. Infect. Dis. 195, 432–441.
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