Informed consent was obtained from 12 HCV RNA–positive, HIV-infected, IFNα treatment–naive patients enrolled in this study. Patients were either referred for this study by private practitioners in the New York City Metropolitan Area or were recruited from the Liver Clinic at New York–Presbyterian Hospital. The study protocol was approved by the Institutional Review Boards of Weill Medical College of Cornell University and Rockefeller University. Inclusion criteria specified that all patients be either on a stable course of antiretroviral medication or that they not be on any antiretroviral medication for 4 weeks before the initiation of the study. Patients were excluded if they had a history of renal disease, thyroid disease, or diabetes mellitus; evidence of hepatic decompensation or cirrhosis; illicit drug or alcohol abuse; severely elevated α-fetoprotein (≥100 ng/dL); positive antinuclear antibody (to detect autoimmune hepatitis); or hematologic abnormalities, including severe anemia (hemoglobin ≤11 g/dL), neutropenia (absolute neutrophil count ≤1250 cells/mm3), and thrombocytopenia (platelet count ≤70,000 cells/mm3). Study entry required a liver biopsy within the previous 2 years unless medically contraindicated or the patients refused. All biopsies were graded and staged based on the modified Knodell system. 23,24 Demographic, clinical, and laboratory data on the 12 HIV-HCV–coinfected patients stratified by the dose of IFNα are shown in Table 1.
Patients were randomized to receive an induction dose of either IFNα-2a (Hoffman-La Roche Laboratories, Nutley, NJ) at a dose of 9 million units (MU) per day or 3 MU/d for the first 14 days of the study. Thereafter, all patients were treated with 3 MU of IFNα-2a each day for 6 to 12 months. Peripheral blood was obtained for HCV and HIV RNA determinations at 0, 3, 6, 9, 12, 18, 24, 34, 48, 60, and 72 hours and on days 7, 10, 14, 21, and 28 and biweekly thereafter. Blood was also obtained for isolation of peripheral blood mononuclear cells (PBMCs) as previously described. 25
Hepatitis C Virus Genotyping and HIV-1 and Hepatitis C Viral RNA Quantitation
HCV genotypes were determined by sequencing of the NS5B region 26 and classified according to the method of Simmonds et al. 27,28 HCV RNA and HIV RNA were determined by the Roche Amplicor assay (version 2.0; Roche Diagnostics, Branchberg, NJ), with linear ranges from 103 to 107 HCV copies/mL and 400 to 750,000 HIV copies/mL. For HCV RNA between 107 and 108 copies/mL, the samples were diluted at a ratio of 1:10.
The percentages of peripheral blood CD3+, CD4+, CD8+, CD19+, and CD56+16+ cells were determined by 4-color direct flow cytometry using the MultiTEST IMK Kit (Becton Dickinson Immunocytometry Systems, Mountain View, CA). Briefly, 50 μL of heparinized or ETDA-anticoagulated peripheral blood was added to 20 μL of the MultiTEST CD3/CD8/CD45/CD4 (clones SK7, SK1, 2D1 [HLe-1], and SK3, respectively) or CD3/CD16+CD56/CD45/CD19 (clones SK7, B73.1+NCAM 16.2, 2D1 [HLe-1], and SJ25C1, respectively; Becton Dickinson) reagents in test tubes. Samples were analyzed on a FACsCalibur (Becton Dickinson) employing the MultiSET software (Becton Dickinson). Absolute CD3+, CD4+, CD8+, CD19+ and CD56+16+ cell counts were obtained by multiplying the number of lymphocytes by the percentage of positive cells for each antigen.
Vaccinia Virus Expressing Hepatitis C Virus and HIV Antigens
Hepatitis C genes from HCV-H (genotype 1a) and HCV-BK (genotype 1b) were inserted into the L variant of WR, a laboratory strain of vaccinia virus, and poxvirus recombinants were generated as previously described. 29,30 These recombinants express 2 regions of the HCV genome: core to nonstructural region 3 (C-NS3) and nonstructural region 3 to nonstructural region 5 (NS3-NS5). We selected these regions to enable us to detect responses to the entire HCV genome. To measure HIV-specific immune responses, we used the vaccinia recombinant VAbT408, which expresses HIV-1IIIBenv and gag-pol genes. 31
Enzyme-linked Immunospot (ELISPOT) Assay
After overnight incubation with 5 μg/mL of primary anti-IFNγ or 15 μg/mL of anti–interleukin-4 (IL-4) purified monoclonal antibody (clones 1-DIK and I [82.4], respectively; Mabtech, Stockholm, Sweden), 96-well plates (Millipore Multiscreen-HA; Millipore, Bedford, MA) were washed with phosphate-buffered saline and blocked with RPMI–10% fetal bovine serum (FBS) (R-10 media) for 1 hour at 37°C and subsequently washed 3 times with phosphate-buffered saline. Cryopreserved PBMCs were thawed, washed, counted, and resuspended in R-10 media at a concentration of 2 × 106 cells/mL.
To generate antigen-presenting cells, 107 PBMCs were incubated for 1 hour with HCV vaccinia constructs or parental vaccinia at a multiplicity of infection of 5. Effector cells (2 × 105) and antigen-presenting cells (1 × 105) were incubated for 18 hours for IFNγ and for 48 hours for IL-4 at 37°C in 5% CO2. Positive controls consisted of PBMCs stimulated by phytohemagglutinin (PHA) or tetanus toxoid. Negative controls consisted of PBMCs exposed to the parental vaccinia strain without the recombinant HCV proteins or control antigens.
Subsequently, the cells were washed from the wells, and the plates were incubated for 2 hours with 100 μL of 1-μg/mL biotinylated anti-IFNγ (clone 7-B6-1; Mabtech) or biotinylated anti–IL-4 (clone IL-4 II [12.1]). After washing with phosphate-buffered saline–0.05% Tween 20, 100 μL (1:1000 dilution) of avidin peroxidase complex (Vector Stain Elite ABC kit; Vector Laboratories, Burlingame, CA) was added for 1 hour, and 100 μL per well of the chromogenic substrate 3-amino-9-ethylcarbazole (AEC; SIGMA, St. Louis, MO) or diaminobenzidine (DAB; Research Genetics, Carlsbad, CA) for IFNγ and IL-4, respectively, was added. After drying, the spots were counted using an Axioplan 2 Imaging Microscope (Carl Zeiss, Hallbergmoos, Germany) attached to a computer-assisted automatic plate reader (KS ELISPOT; Carl Zeiss).
For matched-pairs analysis, we employed the Wilcoxon matched-pairs signed-rank test; for comparisons between 2 independent groups, we used the Wilcoxon rank sum test either in SAS (version 6.12; SAS Institute, Cary, NC), in STATA (version 5.0; STATA Corporation, College Station, TX), or in S-Plus (version 6.1; Insightful Corporation, Seattle, WA). Correlation was determined using the Spearman test or the Pearson correlation coefficient. Significance was determined by P ≤ 0.05.
Statistical methodology was also used to explore the differences between early viral responders and nonresponders using observations that were collected at irregularly spaced time points. 32–34 To quantify the relationship between log10 HCV RNA and log10 HIV RNA at various time points after initiation of IFNα, we computed the cross-correlation function at different time points (ti, tj). The cross-correlation function is a measure of the predictability of the process xi(t) on the process yi(t) and expresses the relationship between the 2 processes. The cross-correlation function is defined as:EQUATION
Here, N is the number of patients in each category (responders and nonresponders); xk(ti) denotes the log10 HCV RNA for the kth responder, k = 1,2,3, at time ti; and x̄(ti) is the mean function for log10 HCV RNA at time ti. In addition, yk(tj) and ȳ(tj) are, respectively, the value of log10 HIV RNA for the kth patient at time tj and the mean function for log10 HIV RNA at time tj. Moreover, ȳ(tj) is defined analogously as x̄(ti) is.
Where possible, we estimated the dynamic parameters of HCV and HIV RNA decay under IFNα therapy using the model and fitting procedure described by Neumann et al. 21 The model assumes that IFNα blocks production of new virus with an efficacy ϵ but that it has no effect in blocking de novo infections and in modifying immune responses. The solution of the model also assumes that uninfected cells susceptible to infection are present at approximately a constant level during the time of therapy and that free virions are cleared with rate c and infected cells are lost with rate δ.
In most but not all patients, the decay profiles of both HCV and HIV RNA under IFN therapy show a biphasic decline. When c >>δ, the slope of the first phase is characterized by c and the slope of the second phase is characterized by ϵδ. The half-life of free virus is ln(2)/ c, the half-life of infected cells is ln(2)/δ, and ln(2) = 0.693 is the natural logarithm of 2. In some cases, the viral load showed no second phase decline or even a rebound after the initial 2 or 3 days. For these patients, we could not fit the second phase and determine δ. This will be the case if ϵ is very low, or decreases with time, 35 or if a new steady state not predicted by the model is reached. We used a bootstrap method to calculate 95% confidence intervals (CIs) for the parameter estimates whenever possible. In some cases, we had to fix a parameter and could not estimate its CI. In addition, for HIV responders, we observed an early increase in viral load (see below). For these responders, we used the maximum value of the viral load as the baseline viral load; thus, the delay in Table 2 indicates the time at which that viral load was attained. Finally, it is important to note that the mean estimates reported are only for those patients for whom we could calculate them.
Hepatitis C Virus Virologic Responses
Three (25%) patients (P81, P101, and P125) achieved an early HCV viral response, a 2-log10 decrease in HCV RNA by week 12. 36 By week 12, HCV RNA had declined below assay detection in 2 (P81 and P101) of these patients. Subsequently, P81 achieved a sustained virologic response (SVR), P101 had an end-of-treatment response, and P125 continued to have detectable HCV RNA. At baseline, HCV RNA was significantly lower (P = 0.03, 1-sided test) in these early viral responders than in the other study subjects, whom we refer to as nonresponders. The only patient (P81) who achieved an SVR had substantially lower (by 1.4 log10) baseline HCV RNA than the other patients.
Six patients exhibited a decrease in HCV RNA (Fig. 1) that could be analyzed with our previously developed model of HCV treatment dynamics. 21 Using this model, we estimated viral dynamic parameters, which are summarized in Table 2. We found that the mean (± standard deviation [SD]) efficacy of IFNα in blocking HCV production for these 6 patients was 72 ± 14%. The highest efficacy, ϵ = 97%, was observed in P81. We estimated that the half-life, t1/2, of free HCV ranged from 1.2 to 14.7 hours, with a mean of 5.4 ± 5.0 hours (see Table 2), which is slower than that seen previously in HCV-monoinfected patients. 21 Excluding P180, an outlier, the mean t1/2 was 3.5 ± 2.3 hours, however, which is close to the t1/2 in monoinfected patients. 21 Only 2 patients exhibited a second-phase decline (P81 and P101). For these patients, we estimated the t1/2 of HCV-infected cells to be 3 days, but with only 2 patients to analyze, these results should be interpreted cautiously.
HIV Virologic Responses
Six patients (P4, P81, P86, P101, P149, and P166) had HIV RNA above the detection limit (Fig. 2). In these patients, HIV RNA increased transiently during the first 6 to 12 hours, similar to that observed with HIV-1 protease inhibitor use. 37 HIV RNA subsequently decreased to baseline or lower. In 3 patients (P81, P101, and P149), HIV RNA declined between 0.5 and 1.0 log10 in response to IFNα. Modeling the HIV RNA decay in these patients, we estimated the efficacy of IFNα in blocking HIV production (mean: 74 ± 9%; see Table 2) and the clearance rate of HIV, c = 6.2 ± 2.4 day−1, which was similar to that estimated for HCV, c = 5.9 ± 4.8 day−1 (see Table 2).
Hepatitis C Virus and HIV RNA Declines Are Correlated
To evaluate the relationship between log10 HCV RNA and log10 HIV RNA, we computed the cross-correlation function at different time points. We found that IFNα-induced declines in log10 HCV RNA and log10 HIV RNA were more strongly correlated in early viral responders than in nonresponders (Table 3). During the time points before IFNα exerts its antiviral effect, the cross-correlation in the early viral responders is negative, indicating that the log10 HCV RNA and log10 HIV RNA are changing in opposite directions. At time points of 12 and 18 hours, the processes are not correlated. Subsequently, the processes become strongly correlated among the early viral responders. In the nonresponders, the strongest correlation (r = 0.66) occurred at time points of 12 and 18 hours. At the remainder of the time points, the processes were weakly correlated.
Lymphocyte Phenotypes Among Early Viral Responders and Nonresponders
At baseline, the number of CD3+CD56+16+ (natural killer–T or activated CD8+) cells was inversely correlated with HCV RNA (r = −0.89, P = 0.03;Fig. 3). We also evaluated the differences in lymphocyte subsets among early viral responders and nonresponders as well as the changes in subsets after interferon initiation. The mean baseline numbers of total lymphocytes, CD3+, CD4+, CD8+, CD19+, CD3−CD56+16+ (natural killer) and CD3+CD56+16+ cells per microliter of blood were 2-fold higher in early viral responders than in nonresponders. The percentage of cells in each strata was almost identical between the 2 groups, except for CD4+, CD3−CD56+16+ and CD3+CD56+16+ (Table 4). In responders, the percentage of CD4+ cells was below the lower limit of the normal range. During the first 1 to 3 months after IFNα initiation, the mean number of total lymphocytes and the mean number of cells in each lymphocyte subset remained approximately 2-fold higher in early viral responders compared with nonresponders (see Table 4), whereas the percentage of cells remained relatively unchanged. Of note, none of the patients experienced lymphopenia during the study.
Baseline Hepatitis C Virus–Specific Immune Responses in HIV-Hepatitis C Virus–Coinfected Individuals
We used an ex vivo ELISPOT assay to assess HCV- and HIV-specific immune responses in early viral responders and nonresponders against 2 regions of the HCV genome C-NS3 and NS3-NS5 as well as to HIV gag. As shown in Table 5, we found that baseline C-NS3 and NS3-NS5 responses were significantly stronger (P < 0.05) in early viral responders (209.3 and 94.3 interferon-secreting cells [ISCs] per 106 cells for C-NS3 and NS3-NS5, respectively) compared with nonresponders (12 and 2.7 ISCs per 106 cells for C-NS3 and NS3-NS5, respectively). HIV gag responses were substantially stronger than HCV-specific responses, although they were not significantly different in early viral responders compared with nonresponders (see Table 5). HCV-specific IL-4 responses were rarely detected in either early viral responders or nonresponders (data not shown).
We present a kinetic study of HCV treatment with IFNα-2a in HIV-HCV–coinfected patients. The percentage of HIV-HCV–coinfected patients who respond to IFNα therapy tends to be low. Overall, we found that only 3 of 12 patients had an early virologic response, a 2-log reduction in HCV RNA by week 12, and that only 1 had an SVR. Nevertheless, we were able to analyze the kinetics of the HCV response in 6 patients.
To our knowledge, this is the first completed study of HCV kinetics in HIV-HCV–coinfected patients treated with standard IFNα. Three other studies evaluating HCV kinetics in patients treated with pegylated-IFNα have been presented. One study 38 found, as we have, that in coinfected patients, HCV virions have a longer half-life than the 2 to 3 hours 21 reported for HCV-monoinfected patients and that IFNα causes declines in HIV RNA. Only 2 coinfected patients had detectable HIV RNA, however, and in these patients, the effectiveness of therapy in blocking HIV production was 52% and 35%. 38 Another study 39 reported an efficacy for IFNα-ribavirin therapy (65%) similar to that found here for IFNα monotherapy (72%), but the same study found a higher efficacy for pegylated-IFNα-ribavirin therapy (90%). The efficacy of pegylated-IFNα in blocking virion production has been reported to wane between weekly doses, however, making it difficult to ascribe a single constant efficacy parameter to pegylated-IFNα treatment. 35,40 In addition, the mean efficacies reported in this and other studies do not include those patients who did not respond. Consequently, mean population efficacies are probably lower.
By calculating the cross-correlation, we found that HCV RNA and HIV RNA declines were correlated after initiation of IFNα among the early viral responders. Assuming that IFNα is able to inhibit HIV production, we calculated the HIV clearance rate in these patients in a more direct manner than has been previously possible. 37 The HIV clearance rate constant, c, was estimated to be 6.2 day−1, which is similar to the value of 5.9 day−1 obtained for HCV (see Table 2). The similarity between these 2 figures suggests that the clearance mechanisms for HIV and HCV are similar. We note, however, that using plasma apheresis in 2 coinfected patients, Ramratnam et al 41 found faster clearance of HIV than of HCV. In that study, HCV clearance was 7.9 day−1, whereas HIV clearance was 23 day−1. This fast HIV clearance was confirmed in monoinfected patients in the same study and in simian immunodeficiency virus studies using a different technique. 42 The reason for this discrepancy is not clear, but given the small number of patients in each study and the variability and CIs in estimates among patients, one cannot claim that these HIV clearance rate estimates are significantly different.
In the present study, the estimated IFNα efficacy in blocking virus production was also similar for HCV (72%) and HIV (74%) (see Table 2), suggesting that there may be a common mechanism of the action of IFNα. For example, the protein kinase PKR is induced by IFNα and is activated in the presence of double-stranded RNA as well as some single-strand species, such as HIV TAR RNA. 43 Once activated, PKR can phosphorylate the α subunit of eukaryotic protein synthesis initiation factor 2 (eIF-2α), leading to a downregulation of initiation and, hence, of protein synthesis. 43 One can speculate that such mechanisms could affect the ability of hepatocytes to produce HCV and the ability of lymphocytes to produce HIV in similar ways.
Note, however, that interpretation of our results on HIV must be cautious, because there were only 3 patients who had a 0.5- to 1.0-log10 decrease in HIV RNA and the data in these patients were confounded by an early increase in viral load. The increase in HIV RNA within 6 to 12 hours after IFNα initiation was also accompanied by an early increase in HCV RNA and alanine aminotransferase (data not shown).
We found significant differences (P ≤ 0.05) at baseline in the number of C-NS3– and NS3-NS5–specific ISCs between early viral responders and nonresponders, which suggests a role of these cells in the response to therapy. Previous reports suggested that both CD4+44–48 and CD8+49–52 cells play important roles in recovery from HCV during the acute phase of the infection and in response to IFNα53 in HCV-monoinfected individuals. The present study extends these findings to HIV-HCV–coinfected individuals.
In almost all cases, baseline HIV gag responses were stronger than those to HCV-antigens (see Table 5), consistent with previous reports. 54 These findings suggest that suppression of HCV-specific CD8+ T-cell responses may be occurring by means other than general failure of the immune response. The levels of IFNγ-producing cells that we detected in coinfected early viral responders and nonresponders (see Table 5) are similar to the levels recently reported in HCV-monoinfected patients who were treated with standard and pegylated IFNα. 55,56
Quantitative phenotypic evaluation of baseline peripheral blood lymphocyte subsets revealed approximately 2-fold higher numbers of total lymphocytes, CD3+, CD4+, CD8+, CD19+, CD3−CD56+16+ (natural killer) and CD3+CD56+16+ (natural killer–T or activated CD8+) cells in early viral responders compared with nonresponders. In the chimpanzee model of HCV infection, intrahepatic CD8+ immune responses are crucial for the resolution of the infection. 49,57 In addition, lymphocytes from early viral responders may recognize and react to α/β IFNs more efficiently than those from nonresponders. Malaponte et al 58 found that absolute values of CD4+ and CD8+ lymphocytes decreased significantly in early viral responders after a single dose of IFNα.
We found a strong correlation (r = −0.89, P = 0.03) between the baseline number of CD3+CD56+16+ cells and HCV RNA (see Fig. 3). CD3+CD56+16+ cells may be either natural killer–T cells 59,60 or activated CD8+ T cells with natural killer cell markers. 61,62 Strong HCV-specific intrahepatic cytotoxic T lymphocyte responses have been associated with a low viral load in HCV-infected patients. 63 Natural killer–T cells, which account for 20% to 30% of intrahepatic lymphocytes, are important in hepatitis B virus infection, 64,65 parasitic infection, 66 and tumors. 67–69 The importance of these cells in HCV is still controversial, however. 70–72 The inverse correlation between the baseline number of CD3+CD56+16+ cells and HCV RNA (see Fig. 3) and the marked difference in the number of these cells between early viral responders and nonresponders suggest a role for these cells in viral clearance.
In summary, in a small intensive viral kinetic study involving 12 HIV-HCV–coinfected individuals, 3 patients exhibited at least a 2-log10 decrease in HCV RNA by week 12, and 1 ultimately attained an SVR to daily IFNα therapy. We estimated that the mean IFNα efficacy in blocking production of both HIV and HCV RNA was approximately 73%, which was too low to achieve an SVR except in 1 individual in whom the drug efficacy in blocking HCV virion production was unusually large (97%). Our estimate of similar virion clearance rate constants for both HCV and HIV suggests that a common clearance mechanism may exist for both viruses.
Type 1 interferons are natural mediators of host defense. This study of the effects of standard IFN monotherapy indicates that an early viral response is critical but not sufficient for long-term treatment efficacy. The kinetic analysis of the effects of standard IFNα on the host response in the absence of other antiviral agents suggests that modulation of host factors may be required for treatment efficacy. These findings suggest that standard IFNα, even when given daily, is not potent enough for the treatment of coinfected patients, justifying the need for additional studies using more potent anti-HCV regimens. The addition of ribavirin, which is thought to have both antiviral and immunomodulatory effects against HCV, 73 may enhance HCV-specific T helper 1 immune responses in coinfected patients. Further investigation with larger numbers of patients is necessary to elucidate further correlates of protective immunity to HCV in HCV-monoinfected and HIV-HCV–coinfected individuals.
The authors acknowledge the participation of the patients, and the nursing staff of the General Clinical Research Centers of the Rockefeller University Hospital and New York–Presbyterian Hospital, particularly Maria Baston and Chongkol Kasemsawat. They thank Martin Lesser, PhD, for assistance with the data analysis. They also thank Gertrudis Soto for assistance with specimen preparation and Susanna Cunningham-Rundles for critical review of the manuscript. HIV-1 SF2 gp120 was obtained through the AIDS Research and Reference Reagent Program, Division of AIDS, National Institute of Allergy and Infectious Diseases, National Institutes of Health. vP1291 was obtained from the Division of AIDS and from Virogenetics Corporation. HCV recombinant antigens were obtained from Chiron Corporation.
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