Estrogen receptor-1 is a key regulator of HIV-1 latency that imparts gender-specific restrictions on the latent reservoir
Bibliographic record
Abstract
Unbiased shRNA library screens revealed that the estrogen receptor-1 (ESR-1) is a key factor regulating HIV-1 latency. In both Jurkat T cells and a Th17 primary cell model for HIV-1 latency, selective estrogen receptor modulators (SERMs, i.e., fulvestrant, raloxifene, and tamoxifen) are weak proviral activators and sensitize cells to latency-reversing agents (LRAs) including low doses of TNF-α (an NF-κB inducer), the histone deacetylase inhibitor vorinostat (soruberoylanilide hydroxamic acid, SAHA), and IL-15. To probe the physiologic relevance of these observations, leukapheresis samples from a cohort of 12 well-matched reproductive-age women and men on fully suppressive antiretroviral therapy were evaluated by an assay measuring the production of spliced envelope (env) mRNA (the EDITS assay) by next-generation sequencing. The cells were activated by T cell receptor (TCR) stimulation, IL-15, or SAHA in the presence of either β-estradiol or an SERM. β-Estradiol potently inhibited TCR activation of HIV-1 transcription, while SERMs enhanced the activity of most LRAs. Although both sexes responded to SERMs and β-estradiol, females showed much higher levels of inhibition in response to the hormone and higher reactivity in response to ESR-1 modulators than males. Importantly, the total inducible RNA reservoir, as measured by the EDITS assay, was significantly smaller in the women than in the men. We conclude that concurrent exposure to estrogen is likely to limit the efficacy of viral emergence from latency and that ESR-1 is a pharmacologically attractive target that can be exploited in the design of therapeutic strategies for latency reversal.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".