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Ex vivo analysis identifies effective HIV-1 latency–reversing drug combinations
Gregory M. Laird, … , Janet D. Siliciano, Robert F. Siliciano
Gregory M. Laird, … , Janet D. Siliciano, Robert F. Siliciano
Published March 30, 2015
Citation Information: J Clin Invest. 2015;125(5):1901-1912. https://doi.org/10.1172/JCI80142.
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Research Article AIDS/HIV

Ex vivo analysis identifies effective HIV-1 latency–reversing drug combinations

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Abstract

Reversal of HIV-1 latency by small molecules is a potential cure strategy. This approach will likely require effective drug combinations to achieve high levels of latency reversal. Using resting CD4+ T cells (rCD4s) from infected individuals, we developed an experimental and theoretical framework to identify effective latency-reversing agent (LRA) combinations. Utilizing ex vivo assays for intracellular HIV-1 mRNA and virion production, we compared 2-drug combinations of leading candidate LRAs and identified multiple combinations that effectively reverse latency. We showed that protein kinase C agonists in combination with bromodomain inhibitor JQ1 or histone deacetylase inhibitors robustly induce HIV-1 transcription and virus production when directly compared with maximum reactivation by T cell activation. Using the Bliss independence model to quantitate combined drug effects, we demonstrated that these combinations synergize to induce HIV-1 transcription. This robust latency reversal occurred without release of proinflammatory cytokines by rCD4s. To extend the clinical utility of our findings, we applied a mathematical model that estimates in vivo changes in plasma HIV-1 RNA from ex vivo measurements of virus production. Our study reconciles diverse findings from previous studies, establishes a quantitative experimental approach to evaluate combinatorial LRA efficacy, and presents a model to predict in vivo responses to LRAs.

Authors

Gregory M. Laird, C. Korin Bullen, Daniel I.S. Rosenbloom, Alyssa R. Martin, Alison L. Hill, Christine M. Durand, Janet D. Siliciano, Robert F. Siliciano

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Figure 8

Mathematical model relating ex vivo virus release to predicted increases in plasma HIV-1 RNA levels in vivo.

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Mathematical model relating ex vivo virus release to predicted increases...
A viral dynamic model (A, detailed in Supplemental Materials) was used to estimate changes in plasma HIV-1 RNA levels in response to the LRA treatments for which ex vivo data on virus release was available. Arrows depict routes from latently infected cells to productively infected cells after exposure to antigen or LRAs. Crosses indicate elimination/death. (B) Predicted peak plasma HIV-1 RNA levels during LRA treatment. For each LRA treatment, median fold change in supernatant HIV-1 versus the DMSO control (x axis) was used to estimate LRA-driven activation rate a′; this parameter estimate was used to predict peak plasma viral load following continuous administration of the LRA (y axis). (C) Predicted time course of viral load (y axis, log scale) following administration of single-dose LRA treatment that remains active for 1 day. (D) Predicted time course of viral load (y axis, log scale) following administration of single-dose romidepsin that remains active for 1 day (solid lines) or that continues indefinitely (dotted lines). Gray shading in C and D indicates duration of LRA activity. Parameters: dy = 1/day; d′y = 1 day-1 (blue curves in B and D, all curves in C) or one-third day-1 (red curves in B and D); a + dz = 5.2 × 10–4 day–1 (reservoir half-life of 44 months), initial viral load = 2 copies/ml. For other parameters, see Supplemental Materials.

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ISSN: 0021-9738 (print), 1558-8238 (online)

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