ReviewHIV/AIDS (Auckland, N.Z.)2023
An Evaluation on the Role of Non-Coding RNA in HIV Transcription and Latency: A Review.
Review in HIV/AIDS (Auckland, N.Z.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Targeting NF-κB signaling for HIV latency reversal: Mechanisms, challenges, and therapeutic perspectives.Virus research · 2026Review
- NPM1c⁺-driven lncRNA dysregulation in AML: Mechanisms, Controversies and translational roadblocks.Translational oncology · 2026Review
- Epigenetic mechanisms of retroviral regulation: a comparative review.Epigenetics & chromatin · 2026Review
- Anti-HIV-1 Effect of the Fluoroquinolone Enoxacin and Modulation of Pro-Viral hsa-miR-132 Processing in CEM-SS Cells.Non-coding RNA · 2025Article
- Article
- Direct and indirect effects of CYTOR lncRNA regulate HIV gene expression.PLoS pathogens · 2024Article
- Article
- MicroRNAs and long non-coding RNAs during transcriptional regulation and latency of HIV and HTLV.Retrovirology · 2024Review
- Breaking the Silence: Regulation of HIV Transcription and Latency on the Road to a Cure.Viruses · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
The existence of latent cellular reservoirs is recognized as the major barrier to an HIV cure. Reactivating and eliminating "shock and kill" or permanently silencing "block and lock" the latent HIV reservoir, as well as gene editing, remain promising approaches, but so far have proven to be only partially successful. Moreover, using latency reversing agents or "block and lock" drugs pose additional considerations, including the ability to cause cellular toxicity, a potential lack of specificity for HIV, or low potency when each agent is used alone. RNA molecules, such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are becoming increasingly recognized as important regulators of gene expression. RNA-based approaches for combatting HIV latency represent a promising strategy since both miRNAs and lncRNAs are more cell-type and tissue specific than protein coding genes. Thus, a higher specificity of targeting the latent HIV reservoir with less overall cellular toxicity can likely be achieved. In this review, we summarize current knowledge about HIV gene expression regulation by miRNAs and lncRNAs encoded in the human genome, as well as regulatory molecules encoded in the HIV genome. We discuss both the transcriptional and post-transcriptional regulation of HIV gene expression to align with the current definition of latency, and describe RNA molecules that either promote HIV latency or have anti-latency properties. Finally, we provide perspectives on using each class of RNAs as potential targets for combatting HIV latency, and describe the complexity of the interactions between different RNA molecules, their protein targets, and HIV.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.