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Journal of Virology, March 2005, p. 3071-3083, Vol. 79, No. 5
0022-538X/05/$08.00+0 doi:10.1128/JVI.79.5.3071-3083.2005
Copyright © 2005, American Society for Microbiology. All Rights Reserved.
Department of Molecular Microbiology and Immunology, St. Louis University School of Medicine,1 Department of Medicine, Division of Gastroenterology and Hepatology, St. Louis University Health Sciences Center, St. Louis, Missouri,2 Center for the Study of Hepatitis C, The Rockefeller University, New York, New York3
Received 7 July 2004/ Accepted 18 October 2004
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In the present study, we addressed the question of whether the extent of genetic heterogeneity of HCV genotype 1 isolates among patients with chronic infection bears any relationship to the response to antiviral therapy with the pegylated alpha-2a interferon. Although many studies have analyzed this question in the context of standard interferon therapy, there are not abundant data on the effects of the long-acting forms of alpha interferon. A total of 29 patients undergoing a 48-week treatment period with a combination of pegylated alpha-2a interferon and ribavirin were studied for their patterns of response based on viral RNA levels in serum. To determine whether viral factors affect the treatment response, we analyzed the pretreatment viral genetic heterogeneity using a segment of ca. 1,400 nucleotides from the E1/E2 region. We also followed up on a selected subset of patients in the responder and nonresponder groups to investigate whether the pattern of quasispecies evolution differed between these two groups while on therapy.
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Molecular cloning of E1/E2 and HVR-1. Total RNA was extracted from 100 µl of serum as previously described (7). Reverse transcription-PCR (RT-PCR) was performed to amplify a 1.37-kb fragment encompassing E1 and most of the E2 region. The contamination-prevention measures suggested by Kwok and Higuchi were adopted in all procedures (24). Briefly, 5 µl of extracted serum RNA was mixed with 1 µl of 50 mmol of MgCl2/liter, 2 µl of 10x PCR buffer, 1 µl of 100 mmol of dithiothreitol/liter, 0.3 µl of 100 µmol of deoxynucleoside triphosphates/liter, 0.2 µl of 100 µmol of reverse primer DPR1 (Table 1) /liter, 16 U of RNasin, and 80 U of SuperScript II (Gibco-BRL) in a total 20-µl reaction volume, followed by incubation at 42°C for 60 min in a thermal cycler DNA 480 (Perkin-Elmer-Cetus, Norwalk, Conn.). First-round PCR was performed by mixing 20 µl of RT reaction mixture with 30 µl of matrix containing 3 µl of 10x PCR buffer, 0.2 µl of 100 µmol of deoxynucleoside triphosphates/liter, 0.2 µl of 100 µmol of the indicated primers (Table 1)/liter, and 1.25 U of Taq DNA polymerase (Perkin-Elmer-Cetus). Files were programmed for 95°C for 4 min, followed by 5 cycles of 95°C for 1 min, 55°C for 1 min, and 72°C for 2 min, followed by 30 cycles of 95°C for 30 s, 55°C for 1 min, and 72°C for 2 min, with a final 7-min extension at 72°C. Then, 5 µl of product from the first round was used as the template for second-round amplification as described above, except the concentration of MgCl2 was adjusted to 2.5 µmol/liter, and the primers were replaced by different inner sets for HCV genotype 1a or HCV genotype 1b (Table 1). Primer positions were according to HCV J4 strain (GenBank accession no. D10750), with degenerate bases matched to the standard International Union of Pure and Applied Chemistry (IUPAC) codes. For generation of short PCR fragments (494 bp) encompassing hypervariable region 1 (HVR-1), a second set of nested primers was used in conjunction with RT-PCR conditions similar to those described above for the 1,400-bp fragments, except that elongation times were restricted to 30 s. The primer sequences for the short product are shown in Table 1, with numbering according to HCV J4 strain (GenBank accession no. D10750).
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TABLE 1. Nested RT-PCR primers used for the amplification of HCV domains E1/E2, HVR-1, and NS5aa
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Molecular cloning and nucleotide sequencing of PCR fragments. PCR fragments were isolated by electrophoresis on agarose gels and purified by using Qiagen DNA purification kits. The fragments were ligated into the pTOPO-TA cloning vector (Invitrogen) and Escherichia coli TOP-10 cells were used for transformation and recovery of plasmid clones. Miniprep DNAs were screened for inserts, and clones containing appropriate size inserts were used for nucleotide sequence analysis. Nucleotide sequencing reactions were done by using DTCS Quick Start Reagents (Beckman Coulter) and run on an Applied Biosystems DNA Sequenator.
GenBank accession numbers. The GenBank accession numbers of nucleotide sequences analyzed in the present study are AY746598 to AY746942.
Analysis of genetic parameters.
The sequences were aligned with CLUSTAL W (version 1.74) (16). Sequence editing, multiple sequence comparisons were performed with matched programs in the Wisconsin GCG package (Oxford Molecular Group, Inc., version 10.0). The mean genetic distance (d), the number of synonymous substitutions per synonymous site (dS), and the number of nonsynonymous substitutions per nonsynonymous site (dN) were calculated with the Kimura two-parameter method (all sites) (21) in the Molecular Evolutionary Genetics Analysis software package (MEGA; version 1.02) (22). Phylogenetic trees were constructed by using the neighbor-joining method (35) with a bootstrap test implanted in MEGA. The genetic complexity at both nucleotide and amino acid level was evaluated for each patient by calculating normalized entropy (Sn) as follows: Sn = S/lnN, where N is the total number of clones, and S =
i(pilnpi), where pi is the frequency of each clone in the viral quasispecies population.
Statistical tests. Statistical analyses were performed with SPSS Base 10.0 (SPSS, Inc., Chicago, Ill.). Independent means t tests were used to analyze differences between the genetic parameters of responders and nonresponders at various time points. To determine the relationships between patient characteristics and treatment response, t tests were used to compare age, weight, height, body mass index, inflammation, and fibrosis while Fisher exact tests were used for evaluating gender and race. The Pearson correlation coefficient (r) was calculated to determine the relationship between genetic heterogeneity and patient age, weight, height, body mass index, inflammation, and fibrosis. Independent means t tests were used to analyze differences between genetic parameters and patient gender and race.
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TABLE 2. Treatment outcomes based on virologic responsesa
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For other patient variables examined in relationship to treatment response, patient age was significantly lower for early viral responders versus nonresponders (42.9 years versus 51.4 years, respectively; P < 0.05) but not significantly different for sustained viral responders versus nonresponders (45 versus 46.8 years, respectively). For pretreatment liver fibrosis scores, the mean scores were lower for early viral responders versus nonresponders (1.78 versus 2.50, respectively; P < 0.05). The mean scores were also lower for sustained viral responders versus nonresponders (1.73 versus 2.24, respectively), even though this difference was not significant. There was no relationship between treatment responses and either race or genotype (1a versus 1b), respectively.
Phylogeny of pretreatment viral quasispecies. To begin characterization of the genetic variation within and between patient groups as a pretreatment variable, serum RNA was used for RT-PCR to generate 1.36-kb amplicons that encompassed the region from the beginning of E1 to nucleotide position 2280 in the E2 region. Between 10 and 15 individual clones for each patient were sequenced. Evaluation of evolutionary relationships of quasispecies variants within pretreatment serum RNA specimens and analysis for clustering of the evolutionary patterns with respect to treatment outcome were done by constructing a phylogenetic tree for the sequences of the E1-E2 region, as shown in Fig. 1. Each collection of patient-specific quasispecies showed limited genetic evolution at the pretreatment time point. The extent of evolution of the viral populations among different patient samples was also limited. In particular, there was no evidence for a significant difference in evolution between populations from those patients with a complete response to antiviral therapy and those with a nonresponse at the EVR time point. To further screen the E1-E2 region for existence of possible genetic differences that might discriminate responders from nonresponders, a series of trees was constructed based on consensus sequences for each quasispecies population, with consecutive lengths of ca. 150 nucleotides. HVR-1 showed the greatest extent of evolution within a given sample. However, there was no obvious correlation of either HVR-1 or of any region outside of HVR-1 with treatment response (data not shown). This is consistent with the phylogenetic tree shown in Fig. 1. We did not include the putative interferon sensitivity region of E2 (38, 41) in our study for technical reasons which precluded PCR amplification of this portion of E2. Thus, the possible effects of this determinant in influencing treatment responses or in contributing to genetic heterogeneity cannot be evaluated at this time.
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FIG. 1. Phylogenetic analysis of pretreatment viral clones. A neighbor-joining tree was constructed as described in Materials and Methods. The tree depicts evolutionary relationships for responders (blue) and nonresponders (red) or partial responders (black) based on the 12-week endpoint.
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TABLE 3. Comparison of genetic parameters between two groups: early viral response
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TABLE 4. Comparison of genetic parameters between two groups: sustained viral response
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Pretreatment viral genetic parameters were also compared to determine whether the subgroup of seven patients who exhibited an EVR and ETR but later relapsed and failed to achieve an SVR (EVR "escapers") could be distinguished from the other EVRs. As shown in Table 5, there were no significant differences in the nucleotide and amino acid complexities of HVR-1 or in the diversity of the E1 and non-HVR-1 regions of E2 between these two groups of early viral responders.
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TABLE 5. Comparison of genetic parameters between EVR escape and nonescape groups
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Genetic parameters during treatment in patients with different therapeutic responses. To determine whether differences evolved in quasispecies complexity and diversity between early viral responders and nonresponders while they received antiviral therapy, several patients from these two respective groups were selected for further analysis. Quasispecies characterization was done on serial RNA samples for three nonresponders and four responders (based on the 12-week time point). A region of 494 nucleotides encompassing the HVR-1, part of E1 and part of E2 outside of HVR-1 was chosen for analysis, because the baseline genetic distance parameters were greatest for HVR-1 in both treatment groups, and this region was therefore expected to be most sensitive to evolutionary changes in response to antiviral therapy. The results of this analysis are shown in Table 6. For the nonresponder group (patients 14, 15, and 16), there was no significant change in the viral RNA load in serum from baseline to the time that the subsequent samples were collected between 90 and 270 days after initiation of therapy. The mean nucleotide complexities for this group at baseline versus the final follow-up sample were 0.737 and 0.604, respectively. The mean amino acid complexities for these same samples were 0.692 and 0.331, respectively. The mean diversities at baseline and follow-up ranged from 0.063 to 0.114 and 0.01 to 0.131, respectively. Comparison of the diversities of baseline and follow-up samples for these patients showed either no marked change (patient 14) or a decrease (patients 15 and 16) with similar trends for both synonymous and nonsynonymous nucleotide substitutions. Comparison of the genetic diversity of the baseline samples alone versus the composite of baseline plus follow-up samples revealed either no change (patient 15 [0.063 versus 0.063]) or a slight increase in genetic distance (patients 14 [0.110 versus 138] and 16 [0.114 versus 0.177]). Quasispecies evolution was analyzed for one patient (patient 15 [see below and Fig. 2 ]), which revealed a monophyletic pattern of variants, a finding consistent with the lack of significant genetic diversity in this interferon-resistant population. In each of the individual nonresponders, several quasispecies variants were present at baseline and showed different patterns of change (data not shown). In one case these were replaced by several new quasispecies, none of which was dominant (patient 14); in another case, one subdominant clone present at baseline became dominant at follow-up (patient 15); in the third case, a dominant quasispecies was present at follow-up but was not present at baseline or day 90 (patient 16). Genetic diversity increased in one of the three cases (patient 14) between baseline and follow-up, and the dN/dS ratio increased in only this case as well.
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TABLE 6. HVR-1 genetic parameters on treatment in patients with different therapeutic responses
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FIG. 2. Phylogenetic trees for baseline and follow-up sequences of the HVR-1 for representative patients within the early viral responder and nonresponder subgroups. Trees were constructed with the neighbor-joining method, and the reliability of tree topology confirmed with 100 bootstrap replicates at the major branch points. The left panel shows the tree for responder patient 12 (baseline samples are indicated by 12-3, 12-6, 12-9, etc.; follow-up samples are indicated by 12-1-4, 12-1-9, etc., and 12-2-6, 12-2-10f, etc. [see Table 5]). The right panel shows the tree for nonresponder patient 15 (baseline and follow-up samples are indicated as described for patient 12).
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Phylogenetic trees for representative patients in the responder and nonresponder groups are shown in Fig. 2. Responding patient 12 exhibited two distinct evolutionary clusters when baseline and follow-up samples were compared. One was composed of baseline variants, and the other was composed of variants appearing on days 1 and 7, which showed intermingling of variants (Fig. 2, left). This patient went on to achieve a sustained viral response. Nonresponding patient 15 showed little evolution among quasispecies variants when baseline and follow-up samples were compared (Fig. 2, right), with intermingling of viruses from the baseline and subsequent time points. This suggests a relative evolutionary stasis of the quasispecies population in response to interferon compared to the pattern observed for patient 12.
Analysis of NS5A sequence heterogeneity. To determine whether there was a relationship between early viral response and genetic determinants within the NS5A region, pretreatment serum RNAs were used for derivation of a 251-bp PCR product that encompassed the ISDR, and nucleotides 6892 to 7098 were then used for comparison of the population sequences among patients. A phylogenetic tree constructed for these consensus sequences showed a very similar amount of evolutionary drift for this region when responders and nonresponders were compared based on the 12-week time point (Fig. 3A), suggesting there was no overall dramatic difference in sequence heterogeneity between these two groups. To further analyze the relationship of these two groups, the sequences from the responders and nonresponders were compared for differences in nucleotide and amino acid substitutions. Within the ISDR, the mean and range of amino acid substitutions for nonresponders were 2 and 0 to 5, respectively, whereas among responders quasispecies diversity was greater (mean of 2.1 substitutions, [range, 0 to 8]). Responders also exhibited substitutions at more codon positions than nonresponders (16 versus 6, respectively). Both groups exhibited some common substitutions (alanine to threonine at codon 2217, asparagine to arginine at codon 2218, and glutamic acid to aspartic acid at codon 2225). Comparison of each collection of NS5A sequences was made relative to a reference consensus sequence, derived from a set of available genotype 1a isolates as described in Materials and Methods. The number of amino acid differences between the ISDR regions of responders and the reference sequence, as well as the number of amino acid differences between the nonresponders and the reference sequence, showed no significant differences (Fig. 3B). These data suggest that the pretreatment sequences of the NS5A ISDR do not correlate with the response to pegylated interferon.
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FIG. 3. Analysis of NS5A sequences and relationship to treatment response. (A) Phylogenetic relationship of population sequences for the 206 nucleotide sequence from baseline serum samples of all 29 patients in the study, together with HCV01 (HCV genotype 1a prototype [M62321]). (B) Genetic comparison of NS5A sequences for nonresponders (top) and responders (bottom) with respect to the 1a prototype sequence. The reference sequence is indicated on the top line. The P value refers to the comparison of genetic distances of responders and HCV01 versus nonresponders and HCV01.
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RNA loads in response to treatment showed differences in the kinetics of decline among both responders and nonresponders, indicating heterogeneity in the pattern of response to this form of antiviral therapy, although pretreatment RNA levels in serum were not predictive of treatment responses. Age and liver fibrosis were related to early viral response, since responders were significantly younger and exhibited significantly lower fibrosis scores than nonresponders. Age was not a distinguishing factor for sustained viral responders versus nonresponders, although liver fibrosis scores were again lower among the responders. Taken together, these data indicate a more favorable treatment response in the context of less severe pretreatment liver fibrosis. The relationship of fibrosis to viral genetic parameters is discussed further below.
In terms of the hypothesis that the degree of genetic variation of HCV is a factor which affects the response to treatment, we observed a relationship between genetic complexity at both the nucleotide and the amino acid level of HVR-1 and the virologic outcome after 12 weeks of antiviral therapy. The nucleotide complexity was lower in the responder group, and the amino acid complexity for this region was significantly lower. Analysis of the genetic diversity with respect to the 12-week treatment outcome also showed differences between responders and nonresponders. For the E1 region, a lower nucleotide diversity was apparent among the responders and was associated with a lower rate of synonymous but not nonsynonymous substitutions. For E2, the genetic diversity and number of synonymous and nonsynonymous substitutions were all lower among responders than nonresponders, but the differences were significant for the non-HVR-1 region of E2 but not that of HVR-1. These differences were associated with a lower rate of both synonymous and nonsynonymous substitutions. The data for the E1 region suggest that although there is greater evolution of this region among nonresponders than responders, this does not seem to be driven by immune pressure, since the amino acid diversity was not greater in conjunction with this differences in nucleotide complexity. This may reflect that the E1 protein is less involved in immune selection than E2. For the HVR-1, the greater genetic distances among nonresponders also suggest greater evolution of viruses in the latter group. The lack of a significant difference compared to responders suggests that in the cohort of patients studied here, the HVR-1 is highly evolved as a result of chronic infection and immune pressure and is not a particularly sensitive indicator of whether a response will occur at the 12-week time point. The region of E2 outside of HVR-1 exhibited the greatest differences in genetic distances between responders and nonresponders. This suggests that, like HVR-1, the non-HVR-1 region of the E2 protein may also be subject to immune pressure, with a greater degree of baseline genetic distance in it being a factor involved in poor treatment outcome at the 12-week time point. At the present time, we cannot distinguish whether the differences in non-HVR-1 regions of E2 are simply markers for viral variation that are related to poor treatment response through other mechanisms unrelated to the E2 region. Specific regions of E2 might be involved in the genetic diversity differences between responders and nonresponders and reflect differences in amino acid complexity between these two groups, resulting from immune selection on E2 outside of the HVR-1. This could, for instance, involve HVR-2, where sequence heterogeneity has been observed (34). It is also not known whether the putative interferon-sensitive region of E2 (38, 41) could also contribute any effect, since that region was not included in our analysis.
Pretreatment fibrosis score appeared to be a predictor of antiviral response, at least for early viral responders, although its relationship to viral genetic parameters needs to be further investigated, since higher fibrosis scores and increased genetic heterogeneity of the E1-E2 region were related as trends, but no significant correlations could actually be shown. Although subjects with an early viral response were younger and exhibited lower fibrosis scores than those without a response, these characteristics did not therefore clearly explain the predictive value of the viral genetic complexity of the HVR-1 for this response. A possible relationship could have been obscured by the relatively small numbers of subjects examined in the present study or, alternatively, the lack of a large enough range in the fibrosis scores to demonstrate such an effect. Thus, our data do not allow a conclusion that lesser fibrosis, as might be observed in younger patients with a shorter duration of infection, was necessarily driven by a lower degree of viral genetic heterogeneity.
In contrast to these findings for the early viral response, there was no significant correlation between sustained viral response and genetic complexity and diversity for the E1-E2 region, although the HVR-1 showed substantial differences for these two groups in genetic distance parameters compared to either E1 or the non-HVR-1 region of E2. This phenomenon is likely explained by the fact that there was crossover of some patients who had an early viral response into the group that did not have a sustained viral response (7 of the 18 early viral responders, Table 2). We interpret this to mean that viral parameters are determinants of the early response to pegylated interferon-ribavirin therapy, with less viral quasispecies complexity and diversity favoring a treatment response. However, these parameters appear to be less important as determinants of response over the remaining treatment period. Presumably, host factors such as T-cell effector functions and virus-specific antibodies presumably operate to control and eliminate HCV variants that are becoming resistant to interferon over time. Failure of these adaptive defenses may be related to mutations that render viral variants able to escape from cytotoxic T cells and neutralizing antibodies. This could contribute to the inability to maintain a virologic response between 12 and 72 weeks and may be involved in the nonresponding patients studied here, since the crossovers into the nonresponse group occurred after the end-of-treatment time point. We must, however, acknowledge that there are other interpretations of these data as well.
Our data are generally consistent with some other studies that have examined genetic parameters as predictors of response to antiviral therapy. Among patients with genotype 1b infection treated with either peginterferon or alpha interferon in combination with ribavirin, pretreatment viral genetic heterogeneity, as indicated by nucleotide complexity of the HVR-1, was lower in those exhibiting a short-term response to therapy (6 months of treatment), but this was not predictive of a sustained viral response (1, 2). In a group of patients of genotypes 1, 2, or 3 for whom genetic complexity and diversity were analyzed in relationship to interferon monotherapy, the pretreatment genetic complexity and diversity of a 558-nucleotide region encompassing the HVR-1 did not correlate with achieving a sustained response (9). However, decreases in these parameters during the initial few weeks of therapy occurred in the group of patients who ultimately achieved a sustained response. The rate of early viral responses were not reported in that study, and only a small number of responding patients were in the genotype 1 category. Similar conclusions about the relationship of pretreatment genetic parameters to sustained viral response were observed in another study (36), where immune pressure, reflected by a high ratio of nonsynonymous to synonymous substitutions in HVR-1, was observed in the context of virus eradication. This suggests that host rather than viral factors are more important in this process. Other studies have also reported changes in viral quasispecies complexity and diversity in response to interferon therapy, and it is apparent that some patients appear to exhibit viral evolution, whereas others do not, when HVR-1 is used as an indicator (32). The factors responsible for this variation are not known, and these may be responsible in part for conflicting data obtained in small studies of HCV genetic variation and treatment outcomes, where nucleotide sequence analysis and/or SSCP have been used for analysis of genetic diversity (13, 15, 17, 19, 31, 42, 44).
We also conducted analysis of genetic parameters on a subset of responders and nonresponders using serum samples obtained while on treatment. This included patients who exhibited virus reduction on the order of 3 logs over a period of 7 to 60 days. The HVR-1 region was selected for this analysis because this region is presumed to undergo immune selection during the course of chronic infection, and published data support the hypothesis that this region exhibits a decrease in the genetic complexity and diversity in response to interferon therapy (9). There was no significant decrease in the viral RNA load among the nonresponders chosen in our analysis. The overall trend among nonresponders was a slight decrease in quasispecies complexity and diversity with time, which is consistent with the preservation of interferon-resistant virus clones, although there is no formal proof of this based on our available data. Among responders there was either a slight increase or decrease in quasispecies complexity over time, accompanied by increases or decreases in genetic distance parameters, respectively. This contrasts with the finding that quasispecies diversity uniformly decreases among interferon-responsive patients (9) and suggests that genotype 1 infections may in fact exhibit more varied patterns of quasispecies evolution during successful short-term eradication of viral infection, although it is conceivable that this difference is also related to an effect of long-acting interferon in driving viral evolution. Although another study of quasispecies viral evolution during peginterferon plus ribavirin therapy has shown a decline in genetic complexity and diversity of HVR-1 among responding patients (2), some of the subjects in that study exhibited an increase in these parameters despite a decline in viral RNA levels in serum, a result similar to the phenomenon we observed. Further evaluation of larger numbers of treatment responders is needed to ascertain the basis for the variable response in quasispecies evolution while on antiviral therapy.
The NS5A region contains a putative interferon sensitivity determinant that has been the subject of numerous investigations which have generated conflicting data on the relationship of genetic variations in this region to responsiveness to interferon (5, 6, 12, 20, 25, 26, 30, 33, 37, 40, 48). We did not observe that the NS5A ISDR region contained any genetic markers that allowed a distinction of responders from nonresponders. This issue has remained controversial since the original report of sequence heterogeneity within the ISDR correlating with response to interferon and subsequent studies that failed to substantiate this observation. We also did not examine regions flanking the ISDR that have been implicated in binding to PKR (11) and thus cannot exclude the possibility that determinants in such regions could play a role in modulating the response to pegylated interferon in the patient population studied here.
We are grateful to Janice Strinko for managing the clinical protocol.
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