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Relationship of HIV reservoir characteristics with immune status and viral rebound kinetics in an HIV therapeutic vaccine study

Li, Jonathan Z.a; Heisey, Andreaa; Ahmed, Hayata; Wang, Hongyingb; Zheng, Lub; Carrington, Maryc,d; Wrin, Terrie; Schooley, Robert T.f; Lederman, Michael M.g; Kuritzkes, Daniel R.athe ACTG A5197 Study Team

doi: 10.1097/QAD.0000000000000478
Basic Science

Objectives: The objective of this study is to evaluate the impact of therapeutic HIV vaccination on the HIV reservoir and assess the relationship of the viral reservoir with HIV-specific immune status and viral rebound kinetics.

Design: A retrospective analysis of ACTG A5197, a randomized, placebo-controlled trial of a therapeutic rAd5 HIV-1 gag vaccine.

Methods: Participants received vaccine/placebo at weeks 0, 4 and 26 prior to a 16-week analytic treatment interruption (ATI) at week 38. Cell-associated HIV-1 RNA and DNA (CA-RNA and CA-DNA) and HIV-1 residual viremia were quantified at weeks 0, 8 and 38. HIV-specific CD4+/CD8+ activity was assessed by an intracellular cytokine staining assay.

Results: At study entry, CA-RNA and CA-DNA levels were correlated inversely with the numbers of HIV-specific CD4+ interferon-γ producing cells (CA-RNA: r = −0.23, P = 0.03 and CA-DNA: r = −0.28, P < 0.01, N = 93). Therapeutic HIV vaccination induced HIV-specific CD4+ activity, but did not significantly affect levels of CA-RNA or CA-DNA. Vaccine recipients with undetectable residual viremia at week 8 had higher frequencies of HIV-specific CD4+ and CD8+ interferon-γ producing cells (undetectable versus detectable residual viremia: 277 versus 161 CD4+ cells/106 lymphocytes, P = 0.03 and 1326 versus 669 CD8+ cells/106 lymphocytes, P = 0.04). Pre-ATI CA-RNA and CA-DNA were associated with post-ATI plasma HIV set point (CA-RNA: r = 0.51, P < 0.01 and CA-DNA: r = 0.47, P < 0.01).

Conclusion: Vaccine-induced T-cell responses were associated with a modest transient effect on residual viremia, but more potent immune responses and/or combination treatment with latency-reversing agents are needed to reduce the HIV reservoir. HIV reservoir measures may act as biomarkers of post-ATI viral rebound kinetics.

Clinical Trials Registration: NCT00080106.

Supplemental Digital Content is available in the text

aBrigham and Women's Hospital, Harvard Med School

bHarvard School of Public Health, Boston, Massachusetts

cCancer and Inflammation Program, Laboratory of Experimental Immunology, Leidos Biomedical Research Institute, Frederick National Laboratory for Cancer Research, Frederick, Maryland

dRagon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology, and Harvard University, Cambridge, Massachusetts

eMonogram Biosciences

fUniversity of California, San Diego, La Jolla, California

gCase Western Reserve University, Cleveland, Ohio, USA.

Correspondence to Jonathan Z. Li, MD, Division of Infectious Diseases, Brigham and Women's Hospital, 65 Landsdowne Street, Rm 421, Cambridge, MA 02139, USA. E-mail:

Received 30 May, 2014

Revised 29 August, 2014

Accepted 29 August, 2014

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Website (

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The persistence of HIV within long-lived reservoirs results in the need for life-long antiretroviral therapy (ART). Although ART has saved millions of lives, its use is associated with a number of drawbacks that include side effects, drug–drug interactions, pill fatigue, drug resistance and high cost. Therefore, developing novel strategies that can reverse HIV latency and boost HIV-specific immune responses to achieve sustained ART-free HIV remission is a priority for HIV research [1]. Spontaneous control of HIV in the absence of ART has been described in HIV controllers. Such control may be mediated, at least in part, by strong HIV-specific CD8+ T-cell effector activity [2–5]. One strategy that seeks to induce such responses is therapeutic HIV vaccination, which aims to further boost HIV-specific immune activity [6].

Despite the hope that therapeutic HIV vaccination could play a central role in HIV curative strategies, little is known about the effect of vaccination and vaccine-induced T-cell responses on the HIV reservoir. Although it is proposed that activating HIV-specific T cells during suppressive ART may reduce the latent reservoir [5], this approach could increase viremia and expand the HIV reservoir due to higher levels of HIV production and target cell availability [7]. ACTG A5197 was a randomized, placebo-controlled trial of a therapeutic rAd5 HIV-1 gag vaccine in participants on suppressive ART. The vaccine induced HIV-specific CD4+ and CD8+ interferon-gamma (IFN-γ) producing T cells [8]. Factors associated with lower viral rebound set point during the analytic treatment interruption (ATI) included randomization to the vaccine arm, lower pre-ART viral load and a greater number of HIV-specific CD4+ T cells [8,9]. In the current study, we explored the impact of therapeutic vaccination and immune status on the HIV reservoir among participants of A5197. In addition, we evaluated whether quantitative measures of the HIV reservoir can serve as useful biomarkers to predict the kinetics of HIV rebound during an ATI.

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Patients and methods

Study population

Study design and patient inclusion criteria for ACTG A5197 have been described in detail [8]. Eligible individuals were on ART with CD4+ cell counts at least 500 cells/μl, plasma HIV-1 RNA levels of 50 copies/ml or less with a history of HIV-1 RNA of 500 copies/ml or less for 24 months prior to enrollment and screening serum Ad5 antibody titres of 200 units/ml or less. Participants were randomized 2 : 1 to receipt of either a replication-defective rAd5 vaccine containing an HIV-1 gag insert or placebo at weeks 0, 4 and 26. Starting at week 38, participants underwent a 16-week ATI. Plasma and peripheral blood mononuclear cells (PBMCs) were collected at weeks 0, 8 and 38. Plasma HIV-1 RNA levels were measured at weeks 1, 2, 3, 4, 6, 8, 10, 12 and 16 of the ATI.

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Human leukocyte antigen typing

Human leukocyte antigen (HLA) class I typing was performed following the PCR-SSOP (sequence-specific oligonucleotide probing) and the PCR-SBT (sequence based typing) protocols recommended by the 13th International Histocompatibility Workshop ( Participants were grouped into protective, neutral or unfavourable HLA groups based on race-specific definitions. Protective HLA alleles were defined a priori as HLA B*27, B*57 for both white and black participants, and B*81 for black participants only. Unfavourable HLA alleles were defined as the HLA-B*35-Px variants (B*3502, 3503, 3504 or 5301) for both white and black participants; B*0702 and B*0801 for white participants only; and B*4501 and B*5802 for black participants only. Participants with one protective and one unfavourable allele or those with neither protective nor unfavourable HLA alleles were categorized in the neutral HLA group.

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HIV-1 reservoir assays

Cell-associated HIV-1 RNA and DNA (CA-RNA and CA-DNA) and residual viremia by a single-copy assay (SCA) were quantified at weeks 0, 8 and 38. Cellular RNA and DNA were isolated from cryopreserved PBMCs using the AllPrep DNA/RNA Mini Kit (Qiagen, Valencia, California, USA). CA-RNA and CA-DNA were quantified using a real-time PCR approach with primers/probes targeting conserved regions of the HIV long terminal repeat (LTR)/gag as previously described [10].

Low-level HIV-1 viral loads were measured using the SCA as previously described [11]. The efficiency of HIV amplification by the SCA primers and probes was evaluated by sequencing of the HIV-1 gag region to assess potential sequence mismatches between the SCA primer/probe and patient sequence. For those samples with any sequence mismatches, SCA was performed on plasma samples with detectable viremia by a commercial assay to confirm concordance of values by the two assays. The limit of detection of the SCA was determined by the amount of available plasma for the assay and standardized to the highest limit for any individual (0.7 copies/ml). The limit of detection was used in the analysis for undetectable SCA results.

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HIV-specific CD4+ and CD8+ activity by intracellular cytokine staining assay for interferon-gamma

Blood samples obtained at protocol-defined intervals were sent to Merck Research Laboratories by overnight courier. HIV-specific CD4+ and CD8+ responses were evaluated by an intracellular cytokine staining assay as previously described [8,12,13]. Lymphocytes were exposed to HIV-1 Gag, Nef, Pol or mock peptide pools for 18 h. IFN-γ producing CD4+ and CD8+ T cells were detected by multiparameter flow cytometry.

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Neutralizing antibody assay

HIV-1 neutralizing antibody (NAb) levels were measured at pre-ATI (week 38) for a subset of participants using a recombinant-virus assay (Monogram Biosciences, South San Francisco, California, USA) [14]. The neutralizing capacity of pre-ATI plasma was assessed using pseudotyped virus containing participant env amplified from plasma HIV-1 RNA obtained at the first post-ATI time point when the viral load was more than 1000 HIV-1 RNA copies/ml. The NAb titre was calculated as the reciprocal of the plasma dilution conferring 50% inhibition (IC50). The association between NAb titre and viral rebound endpoints were adjusted for baseline CD4+ cell count, nadir CD4+ cell count, age, treatment arm assignment and HIV-specific CD4+ IFN-γ production.

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Statistical analysis

Associations between HIV reservoir levels and either immune status or viral rebound kinetics were assessed by Spearman correlation, Wilcoxon rank sum test and Fisher's exact test for two group comparisons. No adjustments were made for multiple comparisons. For HIV rebound kinetics, the two coprimary endpoints of the study [ATI viral load set point and viral load time-averaged area-under-the-curve (TA-AUC)] and time to viral rebound at least 200 HIV RNA copies/ml were assessed. The ATI viral load set point was defined as the mean of the week 12 and 16 plasma HIV-1 RNA levels. For the viral load TA-AUC endpoint, viral rebound kinetics for each study participant were estimated by the linear trapezoidal method, with the use of the first, last and intervening plasma log10 HIV-1 RNA levels observed during the ATI to calculate the AUC, and by dividing the AUC by the number of days between the first and the last observation.

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HIV reservoir levels and HIV-specific T-cell activity at study entry

At study entry, there were no significant differences between treatment arms in levels of CA-RNA [vaccine (N = 64) versus placebo (N = 32) arms: median 152 copies/106 PBMCs versus 179 copies/106 PBMCs, P = 0.78], CA-DNA (76 copies/106 PBMCs versus 93 copies/106 PBMCs, P = 0.41] or residual viremia [vaccine (N = 64) versus placebo (N = 30): median 0.7 versus 0.7 copies/ml, P = 0.63]. Levels of CA-RNA were correlated with levels of CA-DNA (Spearman r = 0.55, P < 0.01, N = 92) and residual viremia (Spearman r = 0.23, P = 0.04, N = 77).

Baseline (week 0) CA-RNA and CA-DNA levels in PBMCs were correlated negatively with the frequency of HIV-specific CD4+ IFN-γ producing cells (Fig. 1, CA-RNA: Spearman r = −0.23, P = 0.03, N = 93 and CA-DNA: r = −0.28, P < 0.01, N = 93), but not with the frequency of CD8+ IFN-γ producing cells. The level of residual viremia at study entry did not correlate with either HIV-specific CD4+ or CD8+ activity.

Fig. 1

Fig. 1

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Effect of vaccination on cell-associated HIV RNA, cell-associated HIV DNA and residual plasma viremia

Despite increasing HIV-specific CD4+ IFN-γ activity [8], vaccination did not result in significant changes in CA-RNA or CA-DNA prior to the ATI (Fig. 2). By week 8, after two doses of the vaccine/placebo, modest differences between study arms were noted in the levels of residual viremia [vaccine (N = 65) versus placebo (N = 30): median 0.7 versus 1.1 copies/ml, P = 0.08] and proportions of individuals with detectable residual viremia (37 versus 57%, P = 0.08). The within-arm comparison of residual viremia changes between baseline and week 8 did not show a significant change either in the vaccine or placebo arm [Wilcoxon signed rank test P = 0.25 (vaccine) and P = 0.43 (placebo)]. Vaccine recipients with undetectable residual viremia at week 8 had significantly higher frequencies of HIV-specific CD4+ IFN-γ producing cells [undetectable residual viremia (N = 39) versus detectable residual viremia (N = 24): 277 versus 161 cells/106 lymphocytes, P = 0.03] and CD8+ IFN-γ producing cells [undetectable residual viremia (N = 39) versus detectable residual viremia (N = 24): 1326 versus 669 cells/106 lymphocytes, P = 0.04]. At week 38, however, the associations between residual viremia and HIV-specific CD4+ and CD8+ activity had weakened and were no longer statistically significant [undetectable residual viremia (N = 35) versus detectable residual viremia (N = 25): 249 versus 153 CD4+ IFN-γ producing cells/106 lymphocytes, P = 0.08; and 1007 versus 838 CD8+ IFN-γ producing cells/106 lymphocytes, P = 0.51].

Fig. 2

Fig. 2

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Association of HIV reservoir levels with T-cell activation and human leukocyte antigen haplotype

At baseline, CA-RNA and CA-DNA levels were significantly associated with the frequency of activated CD8+CD38+ cells (CA-RNA: Spearman r = −0.26, P = 0.01, N = 90; CA-DNA: r = −0.22, P = 0.04, N = 90), but not with frequency of activated CD4+CD38+ T cells. The frequencies of activated CD4+ and CD8+ cells at baseline were not associated with CA-RNA:DNA ratio, residual viremia levels, post-ATI set point or TA-AUC.

Individuals with unfavourable HLA alleles were found to have significantly higher levels of CA-RNA and residual viremia than the participants with neutral HLA alleles (Fig. 3). Those with unfavourable HLA alleles were also found to have the highest levels of CA-DNA, but the difference between HLA types was not statistically significant.

Fig. 3

Fig. 3

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Relationship of neutralizing antibody titres with HIV reservoir levels and postanalytic treatment interruption rebound kinetics

The median (Q1, Q3) NAb titre on the log10 scale was 1.86 (1.79, 2.04). At the pre-ATI (week 38) time point, NAb titres were positively correlated with residual viremia levels (Supplemental Fig. 1,, Spearman r = 0.42, P < 0.01, N = 37) and less so with levels of CA-RNA (r = 0.31, P = 0.06), CA-DNA (r = 0.22, P = 0.18) and CA-RNA : DNA ratio (r = 0.21, P = 0.21). NAb titre was significantly associated with post-ATI TA-AUC endpoint (P = 0.03) after adjusting for potential confounders (HIV-specific CD4+ IFN-γ producing cells, nadir CD4+ T-cell count and treatment arm), but was not significantly associated with the post-ATI viral load set point.

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Association of preanalytic treatment interruption cell-associated HIV RNA and cell-associated HIV DNA levels with HIV rebound kinetics

The plasma HIV-1 RNA set point reached during the ATI was positively correlated with pre-ATI (week 38) CA-RNA and CA-DNA (Fig. 4, CA-RNA: Spearman r = 0.51, P < 0.01, N = 90; CA-DNA: r = 0.47, P < 0.01, N = 93). Pre-ATI CA-RNA and CA-DNA levels were also significantly associated with ATI TA-AUC (CA-RNA: r = 0.38, P < 0.01; CA-DNA: r = 0.36, P < 0.01). Pre-ATI CA-RNA:DNA ratio and levels of residual viremia were not significantly associated with either the ATI viral load set point or TA-AUC.

Fig. 4

Fig. 4

The associations between these HIV reservoir measures and confirmed time to viral rebound at least 200 HIV RNA copies/ml were weaker and not statistically significant (CA-RNA: r = −0.17, P = 0.16, N = 72; CA-DNA: r = −0.15, P = 0.2, N = 75; residual viremia: r = −0.15, P = 0.17, N = 88). The results were largely unchanged when the analysis was stratified by treatment arm (Table S1,

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ACTG study A5197 represents one of the largest therapeutic HIV vaccine studies performed during the modern combination ART era and offers a valuable opportunity to assess vaccine-associated changes in the HIV reservoir, the relationship of the reservoir with immune status and whether HIV reservoir measures predict viral rebound kinetics. Early in the vaccination course, higher frequencies of HIV-specific CD4+ and CD8+ cells were associated with lower levels of residual viremia, but this effect waned over time. Despite a higher level of vaccine-induced HIV-specific CD4+ activity, CA-RNA and CA-DNA levels were not significantly altered by vaccination. In addition, we found significant associations between HIV reservoir levels and both T-cell activation and HLA type. Finally, higher pre-ATI CA-RNA and CA-DNA levels were associated with higher post-ATI viral load set point.

Vaccination with rAd5-HIV gag induced at least two-fold increase in HIV-specific CD4+ IFN-γ activity in approximately 40% of recipients [8]. Levels of HIV-specific CD4+ activity peaked at week 8 (after two doses of vaccination) and were predictive of post-ATI viral load set point. Only the week 8 HIV-specific CD4+ activity was associated with lower residual viremia. This finding is consistent with the concept of a stronger initial vaccine-induced immune response that waned over time. In aggregate, these results suggest that the longer vaccination schedule may not have increased vaccine response and that an earlier treatment interruption might have demonstrated a more robust vaccine effect.

Although the use of therapeutic HIV vaccines is being explored as part of a strategy to induce posttreatment HIV control, little is known about how the stimulation of HIV-specific T cells may affect the latent HIV reservoir. Although it is hoped that a vaccine-induced immune response may help clear the HIV reservoir [5], a recent study of an autologous dendritic cell based therapeutic HIV vaccine demonstrated an increased T-cell activation as well as residual viremia and cell-associated RNA after vaccination despite continuous ART [7]. In contrast, the vaccines used in A5197 increased HIV-specific CD4+ and CD8+ T-cell activity without inducing higher levels of cell-associated HIV RNA or plasma residual viremia. Several factors could explain the differences seen in the level of postvaccination HIV expression in these studies. These include the vaccine strategy (adenoviral vector versus autologous dendritic cells), differences in the length of time on ART and participant characteristics. In the dendritic cell study, participants had a median CD4+ count of 486 cells/μl and were only treated with approximately 12 weeks of ART prior to vaccine administration [7]. In contrast, A5197 participants had higher CD4+ cell counts at baseline (853 cells/μl in the vaccine arm) and all participants were on suppressive ART for at least 2 years prior to study entry. In addition, a small study of a DNA prime, rAd5 boost strategy in 12 vaccine recipients demonstrated an increase in HIV-specific T-cell response without significant changes in residual viremia or size of the latent reservoir by viral outgrowth assay [15]. It is also interesting to note that a study of a modified Vaccinia Ankara and Fowlpox-based therapeutic HIV vaccine in young adults showed a transient decrease in the size of the HIV reservoir by viral outgrowth assay and that the latent reservoir size was correlated with postvaccination HIV-specific CD4+ IFN-γ+ cells [16]. Evaluation of the HIV reservoir effects of other therapeutic HIV vaccine strategies is needed to further explore these findings.

Certain HLA alleles (e.g. B*27 and B*57) are associated with strong HIV-specific immune responses and are overrepresented in HIV controllers [3]. Such protective HLA alleles have also been associated with lower plasma viral loads and HIV CA-DNA levels [17,18]. In contrast, unfavourable HLA alleles have been identified (e.g. B*35-Px) that are associated with more rapid HIV disease progression [19]. In this study, we found an increased baseline level of residual viremia and CA-RNA in participants with unfavourable HLA alleles. This association occurred in the setting of suppressive ART and could signify a larger transcriptionally active HIV reservoir in those with unfavourable HLA alleles. It is possible that a greater distinction in HIV reservoir size may have been detected within certain CD4+ cell subsets, as a previous report showed lower HIV DNA levels within the central memory T-cell compartment of long-term nonprogressors harbouring either HLA B*27 or B*57 [18]. No significant differences in HIV reservoir were observed between individuals with protective HLA alleles and those harbouring either unfavourable or neutral HLA alleles. However, there were a limited number of participants with protective HLA alleles and studies in larger cohorts are needed to explore the finding that those with protective HLA alleles had the lowest levels of CA-DNA.

The induction of NAbs may be an important strategy for delaying the timing of viral rebound after treatment interruption [20]. In an analysis of the ACTG study A5170, McLinden et al. [21] found that higher NAb titres were significantly associated with lower viral load during treatment interruption. In contrast, our results showed that higher pre-ATI NAb titres were associated with both higher levels of pre-ATI residual viremia and post-ATI viral load. These results suggest that the extent of pre-ATI NAb titres detected in this study was primarily a reflection of circulating antigen levels and not apparently protective against post-ATI viral rebound. One potential explanation for the disparate results may be assay differences, as the A5170 analysis evaluated the extent of heterologous NAb titres against four subtype B isolates, whereas the current study measured levels of autologous NAb titres. It is possible that the measurement of heterologous NAbs may be more indicative of broadly neutralizing antibodies specific to more conserved aspects of the viral envelope. In addition, the relationship between NAb titres and extent or timing of viral rebound may be nonlinear [21]. Other studies evaluating the protective ability of either heterologous and/or autologous NAbs during treatment interruption have also shown mixed results [22–27]. More comprehensive studies are needed to fully characterize the impact of both heterologous and autologous NAbs, as well as antibody diversity and effector functions (e.g. antibody-dependent cellular cytotoxicity) on viral rebound kinetics during treatment interruption.

Clinical trials of therapeutic vaccines and interventions targeting the HIV reservoir would ideally include an ATI component, as was performed in A5197, to demonstrate an effect on viral rebound kinetics. However, such studies are time-consuming, costly and not without clinical risks [28]. Therefore, many recent studies have focused their outcome measurements on surrogate endpoints, such as the effects on the viral reservoir. Residual plasma viremia and cell-associated HIV-1 RNA and DNA are commonly used measures of the HIV reservoir size [11,29–32]. However, few studies have evaluated the ability of these measures to predict the timing and extent of viral rebound, which are the ultimate markers of success. In this study, we show that pre-ATI cell-associated HIV RNA and DNA measured in PBMCs are significantly correlated with plasma viral load set point and TA-AUC after the treatment interruption. These results are supported by several published reports. One study found a correlation between pre-ATI proviral DNA levels and viral set point, but study participants underwent four short (2 weeks) ATI cycles prior to a longer ATI, a study design that significantly complicates interpretation of the results [33]. A second study also found an association between pre-ATI proviral DNA levels and viral control during the ATI, but study participants were on suboptimal regimens (including nucleoside reverse transcriptase inhibitor only regimens) and many had multiple short ATI cycles [34]. Overall, these results suggest that HIV reservoir measurements while on suppressive ART could be used to predict some aspects of post-ATI viral rebound dynamics and could have potential as biomarker endpoints of future interventional HIV reservoir studies.

This study has a few notable limitations. Our analyses of the association between pre-ATI CA-RNA and CA-DNA with post-ATI viral kinetics were complicated by the fact that two-thirds of participants received the therapeutic vaccination. A sensitivity analysis showed that the results were largely unchanged when the analysis was restricted to placebo recipients only. Although measuring HIV reservoir levels in total PBMCs is more cost-effective and surveys a broader range of cells, it is possible that the association between HIV reservoir measures and viral rebound dynamics may be even stronger if only CD4+ T cells were included or if viral outgrowth assays were performed. The viral outgrowth assay avoids the measurement of replication-defective HIV proviruses, but has other limitations. Viral outgrowth assays may underestimate the presence of replication-competent provirus [35,36] and the use of viral outgrowth assays has limited scalability for larger studies as it is costly, and time and labour-intensive [37].

In this study, therapeutic HIV vaccination-induced T-cell response was associated with a modest, transient effect on residual viremia, but no significant changes in CA-RNA or CA-DNA levels. More potent immune responses and/or combination treatment with latency-reversing agents are needed to significantly reduce the latent HIV reservoir. Although HIV reservoir measures were found to predict post-ATI viral load set point, additional studies are needed to confirm this association and to determine which HIV reservoir characteristic may best predict HIV rebound kinetics. Finding early markers of efficacy for viral eradication strategies could be a key step in streamlining the development of next-generation therapeutics with a goal of sustained ART-free HIV remission.

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We wish to thank the participants of ACTG A5197 for their participation. We thank John Mellors and Annie Bedison for their technical support with the SCA and thank Zixin Hu, Francoise Giguel, FSTRF and ACTG staff for their assistance. We also acknowledge Elizabeth Anton and the Clinical Reference Laboratory at Monogram Biosciences for performing the NAb assays.

J.Z.L., A.H., H.A. and D.R.K. provided scientific input into the study design. J.Z.L., H.W. and L.Z. performed the statistical analysis. All authors were involved in data collection, data analysis and the editing of the manuscript.

This work was supported in part by a grant from the Harvard University Center for AIDS Research (to Dr Li, NIAID 5P30AI060354-08), National Institutes of Health (NIH) grants UM1 AI068634 (Statistical and Data Management Center of the AIDS Clinical Trials Group), UM1 AI068636 (AIDS Clinical Trials Group) and a subcontract from UM1 AI068636 to the Harvard Virology Support Laboratory (to Dr Kuritzkes). Merck provided the A5197 study vaccine and performed the assays characterizing HIV-specific T-cell activity. The NAb assays were performed by Monogram Biosciences. This project has been funded in whole or in part with federal funds from the Frederick National Laboratory for Cancer Research, under Contract No. HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government. This Research was supported in part by the Intramural Research Program of the NIH, Frederick National Lab, Center for Cancer Research.

J.Z.L. has served as a consultant for Therapy Edge, Quest Diagnostics and SeraCare Life Sciences. D.R.K. has served as a consultant to and/or has received research grant support from Abbott, Avexa, Bristol-Myers Squibb, Gilead, GlaxoSmithKline, Merck and ViiV Healthcare; he has also received speaking honoraria from Gilead and ViiV.

This study was presented in part at the Conference on Retroviruses and Opportunistic Infections; 3–6 March 2014; Boston, Massachusetts, USA.

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Conflicts of interest

There are no conflicts of interest.

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1. Archin NM, Liberty AL, Kashuba AD, Choudhary SK, Kuruc JD, Crooks AM, et al. Administration of vorinostat disrupts HIV-1 latency in patients on antiretroviral therapy. Nature 2012; 487:482–485.
2. Betts MR, Nason MC, West SM, De Rosa SC, Migueles SA, Abraham J, et al. HIV nonprogressors preferentially maintain highly functional HIV-specific CD8+ T cells. Blood 2006; 107:4781–4789.
3. Pereyra F, Jia X, McLaren PJ, Telenti A, de Bakker PI, Walker BD, et al. The major genetic determinants of HIV-1 control affect HLA class I peptide presentation. Science 2010; 330:1551–1557.
4. Saez-Cirion A, Sinet M, Shin SY, Urrutia A, Versmisse P, Lacabaratz C, et al. Heterogeneity in HIV suppression by CD8 T cells from HIV controllers: association with Gag-specific CD8 T cell responses. J Immunol 2009; 182:7828–7837.
5. Graf EH, Pace MJ, Peterson BA, Lynch LJ, Chukwulebe SB, Mexas AM, et al. Gag-positive reservoir cells are susceptible to HIV-specific cytotoxic T lymphocyte mediated clearance. PLoS One 2013; 8:e71879.
6. Garcia F, Leon A, Gatell JM, Plana M, Gallart T. Therapeutic vaccines against HIV infection. Hum Vaccin Immunother 2012; 8:569–581.
7. Macatangay BJ, Lawani MB, Riddler S, Wheeler ND, Bedison MA, Rinaldo CR, Mellors J. Dendritic cell-based HIV therapeutic vaccine increases residual viremia in individuals on ART [Abstract 143]. Conference on Retroviruses and Opportunistic Infections; 3–6 March 2014; Boston, MA.
8. Schooley RT, Spritzler J, Wang H, Lederman MM, Havlir D, Kuritzkes DR, et al. AIDS clinical trials group 5197: a placebo-controlled trial of immunization of HIV-1-infected persons with a replication-deficient adenovirus type 5 vaccine expressing the HIV-1 core protein. J Infect Dis 2010; 202:705–716.
9. Li JZ, Brumme ZL, Brumme CJ, Wang H, Spritzler J, Robertson MN, et al. Factors associated with viral rebound in HIV-1-infected individuals enrolled in a therapeutic HIV-1 gag vaccine trial. J Infect Dis 2011; 203:976–983.
10. Malnati MS, Scarlatti G, Gatto F, Salvatori F, Cassina G, Rutigliano T, et al. A universal real-time PCR assay for the quantification of group-M HIV-1 proviral load. Nat Protoc 2008; 3:1240–1248.
11. Palmer S, Wiegand AP, Maldarelli F, Bazmi H, Mican JM, Polis M, et al. New real-time reverse transcriptase-initiated PCR assay with single-copy sensitivity for human immunodeficiency virus type 1 RNA in plasma. J Clin Microbiol 2003; 41:4531–4536.
12. Tobery TW, Dubey SA, Anderson K, Freed DC, Cox KS, Lin J, et al. A comparison of standard immunogenicity assays for monitoring HIV type 1 gag-specific T cell responses in Ad5 HIV Type 1 gag vaccinated human subjects. AIDS Res Hum Retroviruses 2006; 22:1081–1090.
13. Trigona WL, Clair JH, Persaud N, Punt K, Bachinsky M, Sadasivan-Nair U, et al. Intracellular staining for HIV-specific IFN-gamma production: statistical analyses establish reproducibility and criteria for distinguishing positive responses. J Interferon Cytokine Res 2003; 23:369–377.
14. Richman DD, Wrin T, Little SJ, Petropoulos CJ. Rapid evolution of the neutralizing antibody response to HIV type 1 infection. Proc Natl Acad Sci U S A 2003; 100:4144–4149.
15. Casazza JP, Bowman KA, Adzaku S, Smith EC, Enama ME, Bailer RT, et al. Therapeutic vaccination expands and improves the function of the HIV-specific memory T-cell repertoire. J Infect Dis 2013; 207:1829–1840.
16. Persaud D, Luzuriaga K, Ziemniak C, Muresan P, Greenough T, Fenton T, et al. Effect of therapeutic HIV recombinant poxvirus vaccines on the size of the resting CD4+ T-cell latent HIV reservoir. AIDS 2011; 25:2227–2234.
17. Dalmasso C, Carpentier W, Meyer L, Rouzioux C, Goujard C, Chaix ML, et al. Distinct genetic loci control plasma HIV-RNA and cellular HIV-DNA levels in HIV-1 infection: the ANRS Genome Wide Association 01 study. PLoS One 2008; 3:e3907.
18. Descours B, Avettand-Fenoel V, Blanc C, Samri A, Melard A, Supervie V, et al. Immune responses driven by protective human leukocyte antigen alleles from long-term nonprogressors are associated with low HIV reservoir in central memory CD4 T cells. Clin Infect Dis 2012; 54:1495–1503.
19. Gao X, Nelson GW, Karacki P, Martin MP, Phair J, Kaslow R, et al. Effect of a single amino acid change in MHC class I molecules on the rate of progression to AIDS. N Engl J Med 2001; 344:1668–1675.
20. Trkola A, Kuster H, Rusert P, Joos B, Fischer M, Leemann C, et al. Delay of HIV-1 rebound after cessation of antiretroviral therapy through passive transfer of human neutralizing antibodies. Nat Med 2005; 11:615–622.
21. McLinden RJ, Paris RM, Polonis VR, Close NC, Su Z, Shikuma CM, et al. Association of HIV neutralizing antibody with lower viral load after treatment interruption in a prospective trial (A5170). AIDS 2010; 26:1–9.
22. Montefiori DC, Hill TS, Vo HT, Walker BD, Rosenberg ES. Neutralizing antibodies associated with viremia control in a subset of individuals after treatment of acute human immunodeficiency virus type 1 infection. J Virol 2001; 75:10200–10207.
23. Ortiz GM, Wellons M, Brancato J, Vo HT, Zinn RL, Clarkson DE, et al. Structured antiretroviral treatment interruptions in chronically HIV-1-infected subjects. Proc Natl Acad Sci U S A 2001; 98:13288–13293.
24. Schweighardt B, Wrin T, Meiklejohn DA, Spotts G, Petropoulos CJ, Nixon DF, Hecht FM. Immune escape mutations detected within HIV-1 epitopes associated with viral control during treatment interruption. J Acquir Immune Defic Syndr 2010; 53:36–46.
25. Salgado M, Rabi SA, O’Connell KA, Buckheit RW 3rd, Bailey JR, Chaudhry AA, et al. Prolonged control of replication-competent dual- tropic human immunodeficiency virus-1 following cessation of highly active antiretroviral therapy. Retrovirology 2011; 8:97.
26. Van Gulck E, Bracke L, Heyndrickx L, Coppens S, Atkinson D, Merlin C, et al. Immune and viral correlates of ‘secondary viral control’ after treatment interruption in chronically HIV-1 infected patients. PLoS One 2012; 7:e37792.
27. Nicastri E, Dori L, Buonomini AR, Tommasi C, De Nardo P, Bellagamba R, et al. HIV neutralizing antibody titer during structured treatment interruption of highly active antiretroviral therapy. AIDS 2012; 26:1451–1452.
28. El-Sadr WM, Lundgren JD, Neaton JD, Gordin F, Abrams D, Arduino RC, et al. CD4+ count-guided interruption of antiretroviral treatment. N Engl J Med 2006; 355:2283–2296.
29. Chun TW, Fauci AS. Latent reservoirs of HIV: obstacles to the eradication of virus. Proc Natl Acad Sci U S A 1999; 96:10958–10961.
30. Palmer S, Maldarelli F, Wiegand A, Bernstein B, Hanna GJ, Brun SC, et al. Low-level viremia persists for at least 7 years in patients on suppressive antiretroviral therapy. Proc Natl Acad Sci U S A 2008; 105:3879–3884.
31. Henrich TJ, Gallien S, Li JZ, Pereyra F, Kuritzkes DR. Low-level detection and quantitation of cellular HIV-1 DNA and 2-LTR circles using droplet digital PCR. J Virol Methods 2012; 186:68–72.
32. Eriksson S, Graf EH, Dahl V, Strain MC, Yukl SA, Lysenko ES, et al. Comparative analysis of measures of viral reservoirs in HIV-1 eradication studies. PLoS Pathog 2013; 9:e1003174.
33. Yerly S, Gunthard HF, Fagard C, Joos B, Perneger TV, Hirschel B, Perrin L. Proviral HIV-DNA predicts viral rebound and viral setpoint after structured treatment interruptions. AIDS 2004; 18:1951–1953.
34. Lafeuillade A, Poggi C, Hittinger G, Counillon E, Emilie D. Predictors of plasma human immunodeficiency virus type 1 RNA control after discontinuation of highly active antiretroviral therapy initiated at acute infection combined with structured treatment interruptions and immune-based therapies. J Infect Dis 2003; 188:1426–1432.
35. Ho Y, Shan L, Wang J, Hosmane N, Blankson JN, Siliciano RF. Characterization of noninduced HIV-1 proviruses dampens the hope for HIV-1 eradication [abstract 43]. 20th Conference on Retroviruses and Opportunistic Infections; 3–6 March 2013; Atlanta, GA.
36. Sobolewski M, Cillo A, Lalama CM, Bosch RJ, Mellors J. A rapid virion recovery assay reveals a larger population of inducible proviruses in resting CD4+ T cells than previously recognized [abstract 174LB]. 20th Conference on Retroviruses and Opportunistic Infections; 3–6 March 2013; Atlanta, GA.
37. Siliciano JD, Siliciano RF. Enhanced culture assay for detection and quantitation of latently infected, resting CD4+ T-cells carrying replication-competent virus in HIV-1-infected individuals. Methods Mol Biol 2005; 304:3–15.

analytic treatment interruption; HIV; reservoir; therapeutic vaccine

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