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Combination anti-HIV antibodies provide sustained virological suppression

Nature volume 606, pages 375–381 (2022)Cite this article

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Abstract

Antiretroviral therapy is highly effective in suppressing human immunodeficiency virus (HIV)1. However, eradication of the virus in individuals with HIV has not been possible to date2. Given that HIV suppression requires life-long antiretroviral therapy, predominantly on a daily basis, there is a need to develop clinically effective alternatives that use long-acting antiviral agents to inhibit viral replication3. Here we report the results of a two-component clinical trial involving the passive transfer of two HIV-specific broadly neutralizing monoclonal antibodies, 3BNC117 and 10-1074. The first component was a randomized, double-blind, placebo-controlled trial that enrolled participants who initiated antiretroviral therapy during the acute/early phase of HIV infection. The second component was an open-label single-arm trial that enrolled individuals with viraemic control who were naive to antiretroviral therapy. Up to 8 infusions of 3BNC117 and 10-1074, administered over a period of 24 weeks, were well tolerated without any serious adverse events related to the infusions. Compared with the placebo, the combination broadly neutralizing monoclonal antibodies maintained complete suppression of plasma viraemia (for up to 43 weeks) after analytical treatment interruption, provided that no antibody-resistant HIV was detected at the baseline in the study participants. Similarly, potent HIV suppression was seen in the antiretroviral-therapy-naive study participants with viraemia carrying sensitive virus at the baseline. Our data demonstrate that combination therapy with broadly neutralizing monoclonal antibodies can provide long-term virological suppression without antiretroviral therapy in individuals with HIV, and our experience offers guidance for future clinical trials involving next-generation antibodies with long half-lives.

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Fig. 1: The study design and the effect of treatment with a combination of 3BNC117 and 10-1074 on plasma viraemia in the study participants.
Fig. 2: Sensitivity of replication-competent HIV to 3BNC117 and 10-1074 and pharmacokinetics.
Fig. 3: Dynamics of HIV reservoirs.

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Data availability

TCR sequencing data are available online (https://clients.adaptivebiotech.com/login; login: chun-review@adaptivebiotech.com, password: chun2021review). The HIV-specific CDR3 sequences were downloaded from the following four databases: the immune epitope database (IEDB; http://www.iedb.org/), VDJdb (https://vdjdb.cdr3.net), McPAS-TCR (http://friedmanlab.weizmann.ac.il/McPAS-TCR/) and the Pan Immune Repertoire Database (PIRD; https://db.cngb.org/pird/).

Code availability

The R scripts that were used in the data analysis have been deposited at GitHub (https://github.com/cihangenome/combination-antibodies-HIV). The following R packages were used: factoextra (v.1.0.7), FactoMineR (v.2.4), reshape (v.0.8.8), reshape2 (v.1.4.4), writexl (v.1.4.0), gdata (v.2.18.0), psych (v.2.1.9), car (v.3.0-11), carData (v.3.0-4), corrr (v.0.4.3), lubridate (v.1.8.0), readxl (v.1.3.1), forcats (v.0.5.1), stringr (v.1.4.0), purrr (v.0.3.4), readr (v.2.0.2), tidyr (v.1.1.4), tibble (v.3.1.5), tidyverse (v.1.3.1), ggpubr (v.0.4.0), immunarch (v.0.6.6), patchwork (v.1.1.1), data.table (v.1.14.2), dtplyr (v.1.1.0), dplyr (v.1.0.7) and ggplot2 (v.3.3.5).

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Acknowledgements

We thank the study volunteers for their participation in this study; D. Asmuth, J. Mascola and S. Read for their guidance; and the NIAID HIV Outpatient Clinic staff for their assistance in the execution of this study. This work was supported by the Intramural Research Program of the National Institute of Allergy and Infectious Diseases, National Institutes of Health.

Author information

Author notes

  1. These authors contributed equally: Michael C. Sneller, Jana Blazkova, Susan Moir, Tae-Wook Chun

Authors and Affiliations

  1. Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA

    Michael C. Sneller, Jana Blazkova, J. Shawn Justement, Victoria Shi, Brooke D. Kennedy, Jekaterina Tolstenko, Genevieve McCormack, Emily J. Whitehead, Rachel F. Schneck, Anthony S. Fauci, Susan Moir & Tae-Wook Chun

  2. Critical Care Medicine Department, Clinical Center, NIH, Bethesda, MD, USA

    Kathleen Gittens

  3. Biostatistics Research Branch, NIAID, NIH, Bethesda, MD, USA

    Michael A. Proschan

  4. Maple Leaf Medical Clinic, Toronto, Ontario, Canada

    Erika Benko & Colin Kovacs

  5. NIAID Collaborative Bioinformatics Resource, NIAID, NIH, Bethesda, MD, USA

    Cihan Oguz

  6. Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research, Frederick, MD, USA

    Cihan Oguz

  7. Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA

    Michael S. Seaman

  8. Laboratory of Molecular Immunology, The Rockefeller University, New York, NY, USA

    Marina Caskey & Michel C. Nussenzweig

  9. Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA

    Michel C. Nussenzweig

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Contributions

M.C.S. and T.-W.C. designed the clinical trial and research. J.B., J.S.J., V.S., B.D.K., E.J.W., R.F.S. M.S.S., S.M. and T.-W.C. performed experiments. J.B. and C.O. performed bioinformatic analysis. M.C.S., K.G., J.T., G.M., E.B., C.K. and T.-W.C. contributed to recruitment of study participants. M.C. and M.C.N. provided study drugs. M.C.S., J.B., M.A.P., C.O., M.S.S, S.M. and T.-W.C. analysed data. M.C.S., A.S.F., S.M. and T.-W.C. wrote the manuscript.

Corresponding author

Correspondence to Tae-Wook Chun.

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Competing interests

M.C.N. is listed as an inventor for patents on 3BNC117 (PTC/US2012/038400) and 10-1074 (PTC/US2013/065696); 3BNC117 and 10-1074 are licensed to Gilead Sciences by Rockefeller University from which M.C.N. has received payments. M.C.N. is a member of the Scientific Advisory Boards of Celldex Therapeutics, Walking Fish Therapeutics and Frontier Biotechnologies. M.C.N. had no control over the direction and ultimately the reporting of the clinical portion of the research while holding their financial interests. The other authors declare no competing interests.

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Nature thanks Lu Zheng and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Consolidated Standards of Reporting Trials (CONSORT) flow diagram for the trial.

CONSORT diagram shows the study enrolment of 14 participants who underwent randomization to the bNAb or placebo groups.

Extended Data Fig. 2 Dynamics of HIV reservoirs.

a. Frequencies of CD4+ T cells carrying total HIV DNA in study participants in the placebo arm of Group 1. b. Frequencies of CD4+ T cells carrying total HIV DNA in study participants in the Group 2 in whom plasma viraemia was suppressed by the combination bNAbs.

Extended Data Fig. 3 Longitudinal measurements of CD4+ T cell counts and phenotypic analyses of CD8+ T cells.

a. Levels of CD4+ T cell counts of the bNAb (n = 7) and placebo (n = 7) arms of Group 1 and Group 2 (n = 5) study participants are shown. b. Frequencies of the activation/exhaustion markers TIGIT, PD-1, CD38 and HLA-DR (left) and T cell subsets (TN, naive; TCM, central memory; TTM, transitional memory; TEM, effector memory; TTD, terminally differentiated) on CD8+ T cells of the bNAb (n = 5) and placebo (n = 7) arms of Group 1 and Group 2 (n = 5) study participants are shown. The grey lines indicate median values. P values were determined using the two-sided Wilcoxon matched-pairs signed rank test and were adjusted for multiple testing. ns, not significant.

Extended Data Fig. 4 Phenotypic analysis of T cells.

Longitudinal high-dimensional flow cytometric analyses of PBMCs of study participants. a. Global opt-SNE plots of CD3+ T cells of combined data from each group of study participants. b. Opt-SNE visualization of expression of the indicated markers are shown. c. Opt-SNE map of T cell clusters identified by FlowSOM clustering. Each number indicates a distinct cluster. Heatmap shows the level of expression (MFI) within individual clusters. d. Comparison of frequencies of T cells expressing markers associated with indicated clusters in the bNAb (n = 5) and placebo (n = 7) arms of Group 1 and Group 2 (n = 5) study participants are shown. P values were determined using the two-sided Wilcoxon matched-pairs signed rank test and were adjusted for multiple testing. ns, not significant.

Extended Data Fig. 5 Levels of biomarkers in the plasma of the bNAb (n = 5) and placebo (n = 7) arms of Group 1 and Group 2 (n = 5) study participants over time.

The grey lines indicate median values. P values were determined using the two-sided Wilcoxon matched-pairs signed rank test and were adjusted for multiple testing. ns, not significant.

Extended Data Fig. 6 Analysis of HIV-specific CD8+ T cells.

Frequencies of HIV Gag-specific CD8+ T cells and dynamics of CD8+ T cell receptor (TCR) repertoire. a. Frequencies of polyfunctional (IFN-γ+TNF-α+MIP-1β+) HIV Gag-specific CD8+ T cells in the bNAb (n = 5) and placebo (n = 7) arms of Group 1 and Group 2 (n = 5) study participants are shown. The grey lines indicate median values. P values were determined using the two-sided Wilcoxon matched-pairs signed rank test. b. Changes in the HIV-specific breadth and depth of CD8+ T cells of study participants are shown (upper panels). Highly enriched CD8+ T cells were obtained using a bead-based purification method. The analysis includes 35 CD8+ T cell-derived genomic DNA samples from 12 study participants (15 samples from 5 participants in the bNAb arm of Group 1, 5 samples from 2 participants in the placebo arm of Group 1, and 15 samples from 5 participants in Group 2). Violin plots show the Gaussian kernel probability density of the breadth/depth values over time. The median values and interquartile ranges of the time point-specific distribution are shown as circles and vertical lines, respectively. Principal component analysis (PCA) of the changes in the TCR repertoire characteristics is shown (lower panels). Each ellipse shows the 95% confidence interval in the PCA space and the center of each ellipse is indicated by larger sized symbols that represent specific time points. Lower left panels depict PCA results with the frequencies of the HIV-specific clonotypes ranked among the top 25 with respect to their P values associated with the pairwise comparisons between the three time points. Lower right panels depict PCA results with the gene usage profiles derived from the TRBV-TRBJ gene pairs in the above clonotypes. Principal component (PC) 1 and PC2 represent a lower-dimensional representation of the input data consisting of the frequencies of the HIV-specific clonotypes (lower left panel) and the usage levels of the TRBV-TRBJ gene pairs (lower right panel) for each patient group. P values were determined using the two-sided Wilcoxon signed-rank test.

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Supplementary Information

Supplementary Tables 1–5 and Supplementary Fig.1, containing the gating strategy for flow cytometry analysis.

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Sneller, M.C., Blazkova, J., Justement, J.S. et al. Combination anti-HIV antibodies provide sustained virological suppression. Nature 606, 375–381 (2022). https://doi.org/10.1038/s41586-022-04797-9

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