Go to The Journal of Clinical Investigation
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Journal stats
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact
  • Physician-Scientist Development
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Immunology
    • Metabolism
    • Nephrology
    • Oncology
    • Pulmonology
    • All ...
  • Videos
  • Collections
    • In-Press Preview
    • Resource and Technical Advances
    • Clinical Research and Public Health
    • Research Letters
    • Editorials
    • Perspectives
    • Physician-Scientist Development
    • Reviews
    • Top read articles

  • Current issue
  • Past issues
  • Specialties
  • In-Press Preview
  • Resource and Technical Advances
  • Clinical Research and Public Health
  • Research Letters
  • Editorials
  • Perspectives
  • Physician-Scientist Development
  • Reviews
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Journal stats
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact
Mechanisms and efficacy of small molecule latency-promoting agents to inhibit HIV reactivation ex vivo
Julie Janssens, Peggy Kim, Sun Jin Kim, Adam Wedrychowski, Gayatri N. Kadiyala, Peter W. Hunt, Steven G. Deeks, Joseph K. Wong, Steven A. Yukl
Julie Janssens, Peggy Kim, Sun Jin Kim, Adam Wedrychowski, Gayatri N. Kadiyala, Peter W. Hunt, Steven G. Deeks, Joseph K. Wong, Steven A. Yukl
View: Text | PDF
Research Article Virology

Mechanisms and efficacy of small molecule latency-promoting agents to inhibit HIV reactivation ex vivo

  • Text
  • PDF
Abstract

Drugs that inhibit HIV transcription and/or reactivation of latent HIV have been proposed as a strategy to reduce HIV-associated immune activation or to achieve a functional cure, yet comparative studies are lacking. We evaluated 26 drugs, including drugs previously reported to inhibit HIV transcription (inhibitors of Tat-dependent HIV transcription, Rev, HSF-1/PTEF-b, HSP90, Jak/Stat, or SIRT1/Tat deacetylation) and other agents that were not tested before (inhibitors of PKC, NF-κB, SP-1, or histone acetyltransferase; NR2F1 agonists), elongation (inhibitors of CDK9/ PTEF-b), completion (inhibitors of PolyA-polymerase), or splicing (inhibitors of human splice factors). To investigate if those drugs would vary in their ability to affect different blocks to HIV transcription, we measured levels of initiated, elongated, midtranscribed, completed, and multiply spliced HIV RNA in PBMCs from antiretroviral therapy–suppressed individuals following ex vivo treatment with each drug and subsequent T cell activation. We identified new drugs that prevent HIV reactivation, including CDK and splicing inhibitors. While some drugs inhibited 1 or 2 steps, other drugs (CDK inhibitors, splicing inhibitors, tanespimycin, and triptolide) inhibited multiple stages of HIV transcription and blocked the production of supernatant viral RNA. These drugs and targets deserve further study in strategies aimed at reducing HIV-associated immune activation or achieving a functional cure.

Authors

Julie Janssens, Peggy Kim, Sun Jin Kim, Adam Wedrychowski, Gayatri N. Kadiyala, Peter W. Hunt, Steven G. Deeks, Joseph K. Wong, Steven A. Yukl

×

Figure 2

Dose-response curves of LPAs.

Options: View larger image (or click on image) Download as PowerPoint
Dose-response curves of LPAs.
Dose-response curves for each drug were ge...
Dose-response curves for each drug were generated in PBMCs from 1 ART-suppressed study participant per drug. PBMCs were aliquoted into wells at 6 × 106 cells/well, activated, and cultured with antiretrovirals in the presence of DMSO alone (no drug) or varying concentrations of individual drugs in DMSO. After 24 hours, the levels of polyadenylated and multiply spliced HIV transcripts were quantified by RT-ddPCR, normalized to 1 μg of total cellular RNA, and expressed as a percentage of the activated DMSO control (% of activated DMSO). The IC50 was determined for ruxolitinib, alvocidib, dinaciclib, AZD4573, quercetin, and pladienolide B using nonlinear regression in Prism.

Copyright © 2026 American Society for Clinical Investigation
ISSN 2379-3708

Sign up for email alerts