Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Combination therapy with anti-HIV-1 antibodies maintains viral suppression

Abstract

Individuals infected with HIV-1 require lifelong antiretroviral therapy, because interruption of treatment leads to rapid rebound viraemia. Here we report on a phase 1b clinical trial in which a combination of 3BNC117 and 10-1074, two potent monoclonal anti-HIV-1 broadly neutralizing antibodies that target independent sites on the HIV-1 envelope spike, was administered during analytical treatment interruption. Participants received three infusions of 30 mg kg−1 of each antibody at 0, 3 and 6 weeks. Infusions of the two antibodies were generally well-tolerated. The nine enrolled individuals with antibody-sensitive latent viral reservoirs maintained suppression for between 15 and more than 30 weeks (median of 21 weeks), and none developed viruses that were resistant to both antibodies. We conclude that the combination of the anti-HIV-1 monoclonal antibodies 3BNC117 and 10-1074 can maintain long-term suppression in the absence of antiretroviral therapy in individuals with antibody-sensitive viral reservoirs.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Delayed viral rebound with 3BNC117 and 10-1074 combination therapy during ATI.
Fig. 2: Amino acid variants at 10-1074 contact sites and bNAb sensitivity of reactivated latent and rebound viruses.
Fig. 3: Comparison of the circulating latent reservoir and rebound viruses.
Fig. 4: Distribution of the circulating latent reservoir and rebound viruses.

Similar content being viewed by others

Data availability

The sequences from all isolated viruses are available in GenBank, accession numbers MH575375MH576416.

References

  1. Doitsh, G. & Greene, W. C. Dissecting how CD4 T cells are lost during HIV infection. Cell Host Microbe 19, 280–291 (2016).

    Article  CAS  Google Scholar 

  2. Churchill, M. J., Deeks, S. G., Margolis, D. M., Siliciano, R. F. & Swanstrom, R. HIV reservoirs: what, where and how to target them. Nat. Rev. Microbiol. 14, 55–60 (2016).

    Article  CAS  Google Scholar 

  3. Nishimura, Y. et al. Early antibody therapy can induce long-lasting immunity to SHIV. Nature 543, 559–563 (2017).

    Article  ADS  CAS  Google Scholar 

  4. Gautam, R. et al. A single injection of crystallizable fragment domain-modified antibodies elicits durable protection from SHIV infection. Nat. Med. 24, 610–616 (2018).

    Article  CAS  Google Scholar 

  5. Schoofs, T. et al. HIV-1 therapy with monoclonal antibody 3BNC117 elicits host immune responses against HIV-1. Science 352, 997–1001 (2016).

    Article  ADS  CAS  Google Scholar 

  6. Caskey, M. et al. Viraemia suppressed in HIV-1-infected humans by broadly neutralizing antibody 3BNC117. Nature 522, 487–491 (2015).

    Article  ADS  CAS  Google Scholar 

  7. Lynch, R. M. et al. Virologic effects of broadly neutralizing antibody VRC01 administration during chronic HIV-1 infection. Sci. Transl. Med. 7, 319ra206 (2015).

    Article  Google Scholar 

  8. Caskey, M. et al. Antibody 10-1074 suppresses viremia in HIV-1-infected individuals. Nat. Med. 23, 185–191 (2017).

    Article  CAS  Google Scholar 

  9. Scheid, J. F. et al. HIV-1 antibody 3BNC117 suppresses viral rebound in humans during treatment interruption. Nature 535, 556–560 (2016).

    Article  ADS  CAS  Google Scholar 

  10. Li, J. Z. et al. The size of the expressed HIV reservoir predicts timing of viral rebound after treatment interruption. AIDS 30, 343–353 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Bar, K. J. et al. Effect of HIV antibody VRC01 on viral rebound after treatment interruption. N. Engl. J. Med. 375, 2037–2050 (2016).

    Article  CAS  Google Scholar 

  12. Shingai, M. et al. Passive transfer of modest titers of potent and broadly neutralizing anti-HIV monoclonal antibodies block SHIV infection in macaques. J. Exp. Med. 211, 2061–2074 (2014).

    Article  CAS  Google Scholar 

  13. Gautam, R. et al. A single injection of anti-HIV-1 antibodies protects against repeated SHIV challenges. Nature 533, 105–109 (2016).

    Article  ADS  CAS  Google Scholar 

  14. Klein, F. et al. HIV therapy by a combination of broadly neutralizing antibodies in humanized mice. Nature 492, 118–122 (2012).

    Article  ADS  CAS  Google Scholar 

  15. Horwitz, J. A. et al. HIV-1 suppression and durable control by combining single broadly neutralizing antibodies and antiretroviral drugs in humanized mice. Proc. Natl Acad. Sci. USA 110, 16538–16543 (2013).

    Article  ADS  CAS  Google Scholar 

  16. Shingai, M. et al. Antibody-mediated immunotherapy of macaques chronically infected with SHIV suppresses viraemia. Nature 503, 277–280 (2013).

    Article  ADS  CAS  Google Scholar 

  17. Trkola, A. et al. Delay of HIV-1 rebound after cessation of antiretroviral therapy through passive transfer of human neutralizing antibodies. Nat. Med. 11, 615–622 (2005).

    Article  CAS  Google Scholar 

  18. Mehandru, S. et al. Adjunctive passive immunotherapy in human immunodeficiency virus type 1-infected individuals treated with antiviral therapy during acute and early infection. J. Virol. 81, 11016–11031 (2007).

    Article  CAS  Google Scholar 

  19. Sarzotti-Kelsoe, M. et al. Optimization and validation of the TZM-bl assay for standardized assessments of neutralizing antibodies against HIV-1. J. Immunol. Methods 409, 131–146 (2014).

    Article  CAS  Google Scholar 

  20. Cohen, Y. Z. et al. Relationship between latent and rebound viruses in a clinical trial of anti–HIV-1 antibody 3BNC117. J. Exp. Med. 215, https://doi.org/10.1084/jem.20180936 (2018).

    Article  Google Scholar 

  21. Robertson, D. L., Sharp, P. M., McCutchan, F. E. & Hahn, B. H. Recombination in HIV-1. Nature 374, 124–126 (1995).

    Article  ADS  CAS  Google Scholar 

  22. Rothenberger, M. K. et al. Large number of rebounding/founder HIV variants emerge from multifocal infection in lymphatic tissues after treatment interruption. Proc. Natl Acad. Sci. USA 112, E1126–E1134 (2015).

    Article  CAS  Google Scholar 

  23. Kearney, M. F. et al. Lack of detectable HIV-1 molecular evolution during suppressive antiretroviral therapy. PLoS Pathog. 10, e1004010 (2014).

    Article  Google Scholar 

  24. Lorenzi, J. C. et al. Paired quantitative and qualitative assessment of the replication-competent HIV-1 reservoir and comparison with integrated proviral DNA. Proc. Natl Acad. Sci. USA 113, E7908–E7916 (2016).

    Article  CAS  Google Scholar 

  25. Wang, Z. et al. Expanded cellular clones carrying replication-competent HIV-1 persist, wax, and wane. Proc. Natl Acad. Sci. USA 115, E2575–E2584 (2018).

    Article  CAS  Google Scholar 

  26. Hosmane, N. N. et al. Proliferation of latently infected CD4+ T cells carrying replication-competent HIV-1: potential role in latent reservoir dynamics. J. Exp. Med. 214, 959–972 (2017).

    Article  CAS  Google Scholar 

  27. Crooks, A. M. et al. Precise quantitation of the latent HIV-1 reservoir: implications for eradication strategies. J. Infect. Dis. 212, 1361–1365 (2015).

    Article  CAS  Google Scholar 

  28. Poignard, P. et al. Neutralizing antibodies have limited effects on the control of established HIV-1 infection in vivo. Immunity 10, 431–438 (1999).

    Article  CAS  Google Scholar 

  29. Scheid, J. F. et al. A method for identification of HIV gp140 binding memory B cells in human blood. J. Immunol. Methods 343, 65–67 (2009).

    Article  CAS  Google Scholar 

  30. Escolano, A., Dosenovic, P. & Nussenzweig, M. C. Progress toward active or passive HIV-1 vaccination. J. Exp. Med. 214, 3–16 (2017).

    Article  CAS  Google Scholar 

  31. Kwong, P. D. & Mascola, J. R. HIV-1 vaccines based on antibody identification, B Cell ontogeny, and epitope structure. Immunity 48, 855–871 (2018).

    Article  CAS  Google Scholar 

  32. Lu, C. L. et al. Enhanced clearance of HIV-1-infected cells by broadly neutralizing antibodies against HIV-1 in vivo. Science 352, 1001–1004 (2016).

    Article  ADS  CAS  Google Scholar 

  33. Walker, B. D. & Yu, X. G. Unravelling the mechanisms of durable control of HIV-1. Nat. Rev. Immunol. 13, 487–498 (2013).

    Article  CAS  Google Scholar 

  34. Colby, D. J. et al. Rapid HIV RNA rebound after antiretroviral treatment interruption in persons durably suppressed in Fiebig I acute HIV infection. Nat. Med. 24, 923–926 (2018).

    Article  CAS  Google Scholar 

  35. Sáez-Cirión, A. et al. Post-treatment HIV-1 controllers with a long-term virological remission after the interruption of early initiated antiretroviral therapy ANRS VISCONTI Study. PLoS Pathog. 9, e1003211 (2013).

    Article  Google Scholar 

  36. Sneller, M. C. et al. A randomized controlled safety/efficacy trial of therapeutic vaccination in HIV-infected individuals who initiated antiretroviral therapy early in infection. Sci. Transl. Med. 9, eaan8848 (2017).

    Article  Google Scholar 

  37. Fidler, S. et al. Virological blips and predictors of post treatment viral control after stopping ART started in primary HIV infection. J. Acquir. Immune Defic. Syndr. 74, 126–133 (2017).

    Article  Google Scholar 

  38. Martin, G. E. et al. Post-treatment control or treated controllers? Viral remission in treated and untreated primary HIV infection. AIDS 31, 477–484 (2017).

    Article  CAS  Google Scholar 

  39. Cohn, L. B. et al. Clonal CD4+ T cells in the HIV-1 latent reservoir display a distinct gene profile upon reactivation. Nat. Med. 24, 604–609 (2018).

    Article  CAS  Google Scholar 

  40. Maldarelli, F. et al. Specific HIV integration sites are linked to clonal expansion and persistence of infected cells. Science 345, 179–183 (2014).

    Article  ADS  CAS  Google Scholar 

  41. Wagner, T. A. et al. Proliferation of cells with HIV integrated into cancer genes contributes to persistent infection. Science 345, 570–573 (2014).

    Article  ADS  CAS  Google Scholar 

  42. Cohn, L. B. et al. HIV-1 integration landscape during latent and active infection. Cell 160, 420–432 (2015).

    Article  CAS  Google Scholar 

  43. Halper-Stromberg, A. et al. Broadly neutralizing antibodies and viral inducers decrease rebound from HIV-1 latent reservoirs in humanized mice. Cell 158, 989–999 (2014).

    Article  CAS  Google Scholar 

  44. Ko, S. Y. et al. Enhanced neonatal Fc receptor function improves protection against primate SHIV infection. Nature 514, 642–645 (2014).

    Article  ADS  CAS  Google Scholar 

  45. Gaudinski, M. R. et al. Safety and pharmacokinetics of the Fc-modified HIV-1 human monoclonal antibody VRC01LS: a phase 1 open-label clinical trial in healthy adults. PLoS Med. 15, e1002493 (2018).

    Article  Google Scholar 

  46. Salazar-Gonzalez, J. F. et al. Deciphering human immunodeficiency virus type 1 transmission and early envelope diversification by single-genome amplification and sequencing. J. Virol. 82, 3952–3970 (2008).

    Article  CAS  Google Scholar 

  47. Kirchherr, J. L. et al. High throughput functional analysis of HIV-1 env genes without cloning. J. Virol. Methods 143, 104–111 (2007).

    Article  CAS  Google Scholar 

  48. Larkin, M. A. et al. Clustal W and Clustal X version 2.0. Bioinformatics 23, 2947–2948 (2007).

    Article  CAS  Google Scholar 

  49. Guindon, S. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst. Biol. 59, 307–321 (2010).

    Article  CAS  Google Scholar 

  50. Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank all study participants who devoted time to our research; members of the Klein and Nussenzweig laboratories for helpful discussions, especially Y. Bar-On, L. Cohn and M. Jankovic; R. Levin for study coordination and the Rockefeller University Hospital Clinical Research Support Office and nursing staff as well as K. Fiddike, C. Golder, S. Margane, M. Platten, E. Voigt and D. Weiland for help with recruitment and study implementation; K. Jain for help with sample processing; S. Kiss for ophthalmologic assessments; T. Keler and the Celldex Therapeutics team for 3BNC117 and 10-1074 manufacturing and regulatory support; C. Conrad for regulatory support; U. Kerkweg, R. Macarthur and A. Johnson for pharmaceutical services; H. Janicki, M. Ercanoglu, P. Schommers and R. Kaiser for help with virus cultures; C. Scheid and U. Holtick for leukaphereses; S. McMillan, S. Mosher, S. Sawant, D. Beaumont, M. Sarzotti-Kelsoe, K. Greene, H. Gao and D. Montefiori for help with PK assay development, validation, reporting, and/or project management; P. Fast and H. Park for clinical monitoring; and S. Schlesinger for input on study design. This work was supported by the Bill and Melinda Gates Foundation Collaboration for AIDS Vaccine Discovery (CAVD) grants OPP1092074, OPP1124068 (M.C.N.), CAVIMC OPP1146996 (G.D.T., M.S.S.); the Heisenberg-Program of the DFG (KL 2389/2-1), the European Research Council (ERC-StG639961), and the German Center for Infection Research (DZIF) (F.K.); the NIH grants 1UM1 AI100663 and R01AI-129795 (M.C.N.); the Einstein-Rockefeller-CUNY Center for AIDS Research (1P30AI124414-01A1); BEAT-HIV Delaney grant UM1 AI126620 (M.C.); and the Robertson fund of the Rockefeller University. M.C.N. is a Howard Hughes Medical Institute Investigator.

Reviewer information

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

Author information

Authors and Affiliations

Authors

Contributions

M.C. is the principal investigator for the work in the United States and F.K. is the principal investigator for Germany; M.C., F.K. and M.C.N. designed the trial; P.M., H.G., F.K., M.C. and M.C.N. analysed the data and wrote the manuscript; P.M., L.N. and T.Ka. performed Q2VOA, rebound cultures and SGA; H.G., M.W.-P., G.K., E.T., J.H., M.C. and F.K. implemented the study; A.L.B., K.M., Y.Z.C., C.L., I.Su., C.W., T.Kü. and C.S. contributed to recruitment and clinical assessments; P.M., H.G. and L.N. performed bulk viral cultures; J.A.P. and T.Y.O. performed bioinformatics processing; K.E.S. and G.D.T. conducted anti-idiotype ELISA; M.S.S. conducted TZM-bl assays; C.U.-O., R.P., C.R., M.S. and I.Sh. coordinated and performed sample processing; L.H., A.P.W., P.J.B. and N.P. contributed to data analysis; J.C.C.L., C-L.L., R.M.G. and G.F. contributed to study design and implementation.

Corresponding authors

Correspondence to Florian Klein, Marina Caskey or Michel C. Nussenzweig.

Ethics declarations

Competing interests

: There are patents on 3BNC117 (PTC/US2012/038400) and 10-1074 (PTC/US2013/065696) that list M.C.N. as an inventor.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Study participant selection and demographics.

a, Flow diagram indicating the selection of study participants. b, Individual participant demographics and baseline clinical characteristics. Grey-shaded rows indicate participants who were found to have detectable viraemia (HIV-1 viral load of >20 copies ml−1) at week −2 or day 0. These participants were not included in the efficacy analyses given the lack of viral suppression at baseline. Amer Indian, American Indian; Hisp, Hispanic. *3TC, lamivudine; ABC, abacavir; cobi, cobicistat; DRV, darunavir; DTG, dolutegravir; EFV, efavirenz; EVG, elvitegravir; FTC, emtricitabine; RPV, rilpivirine; RTV, ritonavir; TAF, tenofovir alafenamide fumarate; TDF, tenofovir disoproxil fumarate. **NNRTI-based regimens were switched four weeks before ART interruption due to longer half-lives of NNRTIs. ***Pre-screening of bulk outgrowth virus obtained from PBMC cultures by TZM-bl assay. #All participants harboured clade B viruses. Viral load <20 D, plasma HIV-1 RNA detected but not quantifiable by clinical assay. d0, day 0; Dx, diagnosis; Scr, screening; Wk −2, week −2.

Extended Data Fig. 2 Demographics, CD4+ T cells during study period in participants and pharmacokinetics of 3BNC117 and 10-1074.

a, Baseline participant demographics. b, Absolute CD4+ T cell counts and percentage of CD4+ T cells among CD3+ T cells at screening (n = 15), day 0 (n = 15), at the time of viral rebound (n = 13) and at the end of the study are shown (n = 15) (see also Supplementary Table 2). The last available time point after resuppression was used as end of the study time point for the participants that reinitiated ART. Red lines indicate mean, error bars indicate standard deviation and individual participants are shown as dots. P values were obtained using a two-tailed paired Student’s t-test comparing CD4+ T cell counts between day 0 and the time of viral rebound. c, d, 3BNC117 (red) and 10-1074 (blue) levels in serum (n = 15) as determined by TZM-bl assay (c) and ELISA (d). In cases in which participants only received 2 infusions due to early viral rebound (9245, 9249 and 9253), only antibody concentrations up to the second infusion were included. Half-life of each bNAb is indicated in days. Curves indicate mean serum antibody concentrations and error bars represent standard deviation. Red and blue triangles indicate 3BNC117 and 10-1074 infusions, respectively. c, In the TZM-bl assay, lower limits of quantification were 0.46 μg ml−1 and 0.10 μg ml−1 for 3BNC117 and 10-1074, respectively. d, In the ELISA, lower limits of detection were 0.78 μg ml−1 and 0.41 μg ml−1, respectively. e, f, Half-lives of both antibodies as measured by TZM-bl assay (e) and ELISA (f). Each dot represents a single participant. The half-lives of both antibodies from the 15 participants enrolled in the study are represented. Black lines indicate the mean value and standard deviation (n = 15). P values were obtained using a two-tailed unpaired Student’s t-test comparing the two antibodies.

Extended Data Fig. 3 Phylogenetic tree of viruses from all enrolled participants.

Maximum likelihood phylogenetic trees of full-length env sequences containing all sequences obtained from Q2VOA cultures and rebound viruses from SGA or rebound outgrowth of the 15 participants enrolled in the study. Participants are indicated by individual colours.

Extended Data Fig. 4 Viral rebound, amino acid variants at 10-1074 contact sites and sensitivities of latent and rebound viruses in the participants with detectable viraemia (>20 copies per ml) two weeks before or at the start of ATI.

a, Plasma HIV-1 RNA levels (black; left y axis) and bNAb serum concentrations (3BNC117, red; 10-1074, blue; right y axis). Red and blue triangles indicate 3BNC117 and 10-1074 infusions, respectively. Serum antibody concentrations were determined by TZM-bl assay. Grey-shaded areas indicate time on ART. Lower limit of detection of HIV-1 RNA was 20 copies per ml. b, Kaplan–Meier plots summarizing time to viral rebound. The y axis shows the percentage of participants that maintained viral suppression. The x axis shows the time in weeks after the start of ATI. Participants receiving the combination of 3BNC117 and 10-1074 are indicated by the blue line (n = 4). The dotted red line indicates a cohort of individuals receiving 3BNC117 alone during ATI9 (n = 13) and the dotted black line indicates a cohort of participants who underwent ATI without any intervention10 (n = 52). c, Colour charts show Env contact sites of 10-1074 at the G(D/N)IR motif (positions 324–327, according to HXB2 numbering) and the glycan at the potential N-linked glycosylation site at position 332 (NxS/T motif at positions 332–334). LR, latent reservoir viruses isolated by Q2VOA (week −2); RB, rebound viruses isolated by SGA (plasma) or viral outgrowth (PBMCs). Each amino acid is represented by a colour and the frequency of each amino acid is indicated by the height of the rectangle. Shaded rectangles indicate the lack of variation between latent reservoir and rebound viruses at the indicated position. Full-colour rectangles represent amino acid residues with changes in distribution between reservoir and rebound viruses. d, Dot plots showing the IC80 (μg ml−1) of 3BNC117 (left) and 10-1074 (right) against latent and rebound viruses determined by TZM-bl neutralization assay. Q2VOA-derived latent viruses from week −2 are shown as black circles. For outgrowth culture-derived rebound viruses, the highest IC80 determined is shown as red circle. For 9250 and 9253, no viruses could be obtained from rebound outgrowth cultures and pseudoviruses were made from env sequences of the latent reservoir (Q2VOA) and rebound viruses (plasma SGA). Note that 9249 and 9253 had pre-existing resistant viruses in the reservoir (IC50 > 2 μg ml−1). 9248 and 9250 had pre-existing viruses that failed to reach an IC100 when tested up to 50 μg ml−1 for 3BNC117 (Extended Data Fig. 5). Rebound viruses of all four participants had an IC80 or IC100 of >50 μg ml−1 for both 3BN117 and 10-1074.

Extended Data Fig. 5 Phylogenetic env trees and TZM-bl neutralization curves for individuals with viral blips.

a, Circulating reservoir and viral rebound in study participants with detectable viraemia at week −2 or day 0. Maximum likelihood phylogenetic trees of full-length env sequences of viruses isolated from week −2 Q2VOA cultures, rebound plasma SGA and rebound outgrowth from the four participants with viral blips. Open black rectangles indicate Q2VOA-derived viruses from week −2. Viruses obtained at the time of rebound are indicated by red rectangles (plasma SGA) and red stars (rebound PBMC outgrowth cultures), respectively. Asterisks indicate nodes with significant bootstrap values (bootstrap support ≥70%). Clones are denoted by coloured lines. Boxes indicate IC80 values (μg ml−1) of 3BNC117 and 10-1074 against individual clones, with asterisks indicating IC100 > 50 μg ml−1. b, Latent reservoir virus TZM-bl neutralization curves for two participants that had a viral load of >20 copies per ml at day 0 (9248 and 9250). Curves show neutralization titres by 3BNC117 (blue), 10-1074 (red) and other bNAbs, when available, for week −2 Q2VOA-derived viruses present in the circulating reservoir. Three representative viruses from 9248 (left) and 9250 (right) are shown. Although these viruses had low 3BNC117 and 10-1074 IC50 or IC80 titres, the IC100 (black dotted line) is reached only at a high concentration or not reached at all. The neutralization titre was measured by TZM-bl neutralization assay using a five-parameter curve fit method.

Extended Data Fig. 6 Amino acid variants at 3BNC117 contact sites of reactivated latent and rebound viruses.

Colour charts show 3BNC117 contact sites in Env according to HXB2 numbering. Diagram shows the 13 participants that experienced viral rebound before week 30. LR, latent reservoir viruses isolated by Q2VOA (on weeks −2 and 12 when available); RB, rebound viruses isolated by SGA (plasma) and viral outgrowth (PBMCs). Each amino acid is represented by a colour and the frequency of each amino acid is indicated by the height of the rectangle. Shaded rectangles indicate the lack of variation and full-colour rectangles represent amino acid residues with changes in the distribution between the reservoir and rebound.

Extended Data Fig. 7 Comparison of the circulating latent reservoir and rebound viruses.

Maximum likelihood phylogenetic trees of full-length env sequences of viruses isolated from Q2VOA, rebound plasma SGA and rebound PBMC outgrowth cultures from participants 9241, 9244, 9246 and 9247, who rebounded before week 30. Open and closed black rectangles indicate Q2VOA-derived viruses from week −2 and week 12, respectively. Viruses obtained at the time of rebound are indicated by red rectangles (plasma SGA) and red stars (rebound PBMC outgrowth cultures). Asterisks indicate nodes with significant bootstrap values (bootstrap support ≥70%). Clones are denoted by coloured lines mirroring the colours of slices in Extended Data Fig. 10a. Boxes indicate IC80 values (μg ml−1) of 3BNC117 and 10-1074 against representative viruses throughout the phylogenetic tree and clones, when possible (Supplementary Table 4). Asterisks in boxes indicate IC100 > 50 μg ml−1.

Extended Data Fig. 8 Recombination events in rebound viruses.

a, Maximum likelihood phylogenetic trees of full-length env sequences of viruses isolated from Q2VOA cultures and rebound SGA in the four participants for whom rebound viruses showed recombination events. Open and closed black rectangles indicate Q2VOA-derived viruses from week −2 and week 12, respectively. Rebound plasma SGA- or outgrowth-derived viruses are indicated by closed red rectangles. Green stars represent parent sequences that underwent recombination to produce the child sequences (red stars). b, Circos plots indicating the relationship between the parent sequences and the recombinants. Open and closed black rectangles indicate Q2VOA-derived sequences from week −2 and week 12, respectively. Rebound virus sequences are indicated by red rectangles. The thickness of the black outer bars represents the number of sequences obtained from that particular clone.

Extended Data Fig. 9 Phylogenetic trees of participants 9245, 9251, 9254 and 9255.

Maximum likelihood phylogenetic trees of full-length env sequences of viruses isolated from Q2VOA cultures and rebound plasma SGA and rebound outgrowth from the two participants (9245 and 9251) with pre-existing resistance to one of the two antibodies and the two sensitive participants (9254 and 9255) who maintained viral suppression for >30 weeks (end of the study). Open and closed black rectangles indicate Q2VOA-derived viruses from week −2 and week 12, respectively. Rebound plasma SGA viruses are indicated by closed red rectangles. Asterisks indicate nodes with significant bootstrap values (bootstrap support ≥ 70%). Clones are denoted by coloured lines beside the phylogenetic tree. Numbers correspond to 3BNC117 and 10-1074 IC80 neutralization titres.

Extended Data Fig. 10 Clonal distribution of the circulating latent reservoir and IUPM changes.

a, Pie charts depicting the distribution of Q2VOA-derived env sequences obtained at weeks −2 (W−2) and week 12 (W12). Number in the inner circle indicates the total number of analysed env sequences. White represents sequences isolated only once across both time points and coloured slices represent identical sequences that appear more than once (clones). The size of each pie slice is proportional to the size of the clone. Red arrows denote clones that significantly change in size (P ≤ 0.05 (two-sided Fisher’s exact test)) between the two time points. b, Summary of clonal env sequences and IUPM in the nine individuals with an antibody-sensitive reservoir. c, IUPM versus time of viral rebound in the antibody-sensitive individuals (n = 7) who rebounded within the study observation period (30 weeks). P values were obtained using a two-tailed Pearson correlation test comparing the two variables.

Supplementary information

Supplementary Tables

This file contains Supplementary Tables 1–5.

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mendoza, P., Gruell, H., Nogueira, L. et al. Combination therapy with anti-HIV-1 antibodies maintains viral suppression. Nature 561, 479–484 (2018). https://doi.org/10.1038/s41586-018-0531-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41586-018-0531-2

Keywords

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing